From e7295202e42f523d21c9f8ba0c4d3472789d500b Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Fri, 31 Jan 2025 09:53:14 +0100
Subject: [PATCH 01/31] doc: update readme/doc with conda install

---
 .github/workflows/build.yml             |    4 +-
 .gitlab-ci.yml                          |  139 ---
 LICENSE                                 | 1251 ++++++++++++-----------
 README.md                               |   17 +-
 docs/source/getting_started/install.rst |   15 +-
 pyproject.toml                          |   12 +-
 6 files changed, 694 insertions(+), 744 deletions(-)
 delete mode 100644 .gitlab-ci.yml

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index aba330a..69054f9 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -162,7 +162,7 @@ jobs:
       - name: Publish distribution to TestPyPI
         uses: pypa/gh-action-pypi-publish@release/v1
         with:
-          repository-url: https://pypi.org/legacy/
           verbose: true
           skip-existing: true
-          
+          # fix error 404 with default https://pypi.org/legacy/
+          repository-url: https://upload.pypi.org/legacy/
diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
deleted file mode 100644
index d7c81ff..0000000
--- a/.gitlab-ci.yml
+++ /dev/null
@@ -1,139 +0,0 @@
-# Gitlab CI config - Courtesy of T. Janvier (BRGM)
-default: # linux image on linux runnner
-  image: nexus-docker.brgm.fr/brgm/miniconda3:latest
-  tags:
-    - brgm
-
-.windows: # windows image on windows runnner
-  image: nexus-docker.brgm.fr/brgm/miniconda3:windows
-  tags:
-    - windows-2022-docker
-
-
-stages:
-  - build
-  - test
-  - deploy
-
-
-.version_tag:
-  only: # see https://peps.python.org/pep-0440/
-    variables:
-      - $CI_COMMIT_TAG =~ /^(?P<epoch>\D+)?(?P<version>(?P<release>\d+(?:\.\d+)*)(?P<pre>(?:a|b|rc)\d+?)?((?P<post>\.post\d+))?(?P<dev>\.dev\d+)?(?P<build>\+\S+)?)$/
-  except:
-    - branches
-
-
-# ----- Build ----- #
-
-.build:
-  stage: build
-  extends: .version_tag
-  when: manual
-  script:
-    # build multiple versions using cibuildwheel
-    # - python -m cibuildwheel --output-dir ./dist 
-    # build standalone environment for testing (current package + all dependencies)
-    # - python -m pip wheel -w ./dist/wheelhouse .[test]
-    - python -m pip wheel -w ./dist/ .
-  artifacts:
-    paths:
-    - dist/
-    expose_as: wheel
-    expire_in: 12 hours
-    
-
-build-linux:
-  when: manual
-  extends: .build
-  before_script:
-    - echo "gridmarthe ci/cd pipeline"
-    - python --version
-    - mamba install gfortran
-    - gfortran --version
-    - python -m pip install --upgrade pip setuptools wheel
-    - python -m pip install cibuildwheel build
-    # uncomment next line if you need internal dependencies
-    # - python -m pip config set global.index-url ${REGISTRY_NEXUS}/pypi-all/simple
-
-build-windows:
-  when: manual
-  extends: 
-    - .windows
-    - .build
-  before_script:
-    - echo "gridmarthe ci/cd pipeline"
-    - python --version
-    - gfortran --version
-    - pip install --upgrade pip setuptools wheel
-    - pip install cibuildwheel build
-
-
-# ----- Test config ----- #
-
-.test:
-  stage: test
-  extends: .version_tag
-  when: manual
-  script:
-    - python -c 'import gridmarthe'
-  # allow_failure: true
-
-
-test-linux:
-  needs: ["build-linux"]
-  extends: .test
-  before_script:
-    - echo "gridmarthe ci/cd pipeline"
-    - python --version
-    - mamba install gfortran
-    - gfortran --version
-    - python -m pip install --no-index --no-deps dist/*none*.whl # no-index: avoid search pypi index ; no-deps, wheels already build
-    - python -m pip install --no-index --no-deps dist/*linux*.whl
-
-
-test-windows:
-  needs: ["build-windows"]
-  extends: 
-    - .windows
-    - .test
-  before_script:
-    - echo "gridmarthe ci/cd pipeline"
-    - python --version
-    - gfortran --version
-    - pip install --no-index --no-deps dist/*none*.whl
-    - pip install --no-index --no-deps dist/*win*.whl
-
-
-
-# ----- Publish ----- #
-
-.deploy:
-  extends: .version_tag
-  stage: deploy
-  except:
-    - branches
-
-
-deploy-nexus_snapshot:
-  needs: ["build-linux", "build-windows"]
-  extends: .deploy
-  before_script:
-    - echo ${NEXUS_URL}
-    - echo ${REGISTRY_NEXUS_USER}
-    - echo ${REGISTRY_NEXUS}
-    - pip install twine
-  script:
-    - twine upload -u ${REGISTRY_NEXUS_USER} -p ${REGISTRY_NEXUS_PASSWORD} --repository-url ${REGISTRY_NEXUS}/pypi-snapshots/ dist/*.whl
-  when: manual
-
-
-deploy-pip:
-  needs: ["build-linux", "build-windows"]
-  extends: .deploy
-  before_script:
-    - pip install twine
-  script:
-    - twine upload --skip-existing --verbose dist/*.whl
-  when: manual
-
diff --git a/LICENSE b/LICENSE
index 23f589c..f288702 100644
--- a/LICENSE
+++ b/LICENSE
@@ -1,619 +1,674 @@
-GNU General Public License
+                    GNU GENERAL PUBLIC LICENSE
+                       Version 3, 29 June 2007
 
-Version 3, 29 June 2007
-Copyright © 2007 Free Software Foundation, Inc. <https://fsf.org/>
+ Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
+ Everyone is permitted to copy and distribute verbatim copies
+ of this license document, but changing it is not allowed.
 
-Everyone is permitted to copy and distribute verbatim copies of this license
-document, but changing it is not allowed.
+                            Preamble
 
-Preamble
---------
+  The GNU General Public License is a free, copyleft license for
+software and other kinds of works.
 
-The GNU General Public License is a free, copyleft license for software and other
-kinds of works.
-
-The licenses for most software and other practical works are designed to take away
-your freedom to share and change the works. By contrast, the GNU General Public
-License is intended to guarantee your freedom to share and change all versions of a
-program--to make sure it remains free software for all its users. We, the Free
-Software Foundation, use the GNU General Public License for most of our software; it
-applies also to any other work released this way by its authors. You can apply it to
+  The licenses for most software and other practical works are designed
+to take away your freedom to share and change the works.  By contrast,
+the GNU General Public License is intended to guarantee your freedom to
+share and change all versions of a program--to make sure it remains free
+software for all its users.  We, the Free Software Foundation, use the
+GNU General Public License for most of our software; it applies also to
+any other work released this way by its authors.  You can apply it to
 your programs, too.
 
-When we speak of free software, we are referring to freedom, not price. Our General
-Public Licenses are designed to make sure that you have the freedom to distribute
-copies of free software (and charge for them if you wish), that you receive source
-code or can get it if you want it, that you can change the software or use pieces of
-it in new free programs, and that you know you can do these things.
-
-To protect your rights, we need to prevent others from denying you these rights or
-asking you to surrender the rights. Therefore, you have certain responsibilities if
-you distribute copies of the software, or if you modify it: responsibilities to
-respect the freedom of others.
-
-For example, if you distribute copies of such a program, whether gratis or for a fee,
-you must pass on to the recipients the same freedoms that you received. You must make
-sure that they, too, receive or can get the source code. And you must show them these
-terms so they know their rights.
-
-Developers that use the GNU GPL protect your rights with two steps: (1) assert
-copyright on the software, and (2) offer you this License giving you legal permission
-to copy, distribute and/or modify it.
-
-For the developers' and authors' protection, the GPL clearly explains that there is
-no warranty for this free software. For both users' and authors' sake, the GPL
-requires that modified versions be marked as changed, so that their problems will not
-be attributed erroneously to authors of previous versions.
-
-Some devices are designed to deny users access to install or run modified versions of
-the software inside them, although the manufacturer can do so. This is fundamentally
-incompatible with the aim of protecting users' freedom to change the software. The
-systematic pattern of such abuse occurs in the area of products for individuals to
-use, which is precisely where it is most unacceptable. Therefore, we have designed
-this version of the GPL to prohibit the practice for those products. If such problems
-arise substantially in other domains, we stand ready to extend this provision to
-those domains in future versions of the GPL, as needed to protect the freedom of
-users.
-
-Finally, every program is threatened constantly by software patents. States should
-not allow patents to restrict development and use of software on general-purpose
-computers, but in those that do, we wish to avoid the special danger that patents
-applied to a free program could make it effectively proprietary. To prevent this, the
-GPL assures that patents cannot be used to render the program non-free.
-
-The precise terms and conditions for copying, distribution and modification follow.
-
-Terms and Conditions
---------------------
-
-0. Definitions
-^^^^^^^^^^^^^^
-
-“This License” refers to version 3 of the GNU General Public License.
-
-“Copyright” also means copyright-like laws that apply to other kinds of
+  When we speak of free software, we are referring to freedom, not
+price.  Our General Public Licenses are designed to make sure that you
+have the freedom to distribute copies of free software (and charge for
+them if you wish), that you receive source code or can get it if you
+want it, that you can change the software or use pieces of it in new
+free programs, and that you know you can do these things.
+
+  To protect your rights, we need to prevent others from denying you
+these rights or asking you to surrender the rights.  Therefore, you have
+certain responsibilities if you distribute copies of the software, or if
+you modify it: responsibilities to respect the freedom of others.
+
+  For example, if you distribute copies of such a program, whether
+gratis or for a fee, you must pass on to the recipients the same
+freedoms that you received.  You must make sure that they, too, receive
+or can get the source code.  And you must show them these terms so they
+know their rights.
+
+  Developers that use the GNU GPL protect your rights with two steps:
+(1) assert copyright on the software, and (2) offer you this License
+giving you legal permission to copy, distribute and/or modify it.
+
+  For the developers' and authors' protection, the GPL clearly explains
+that there is no warranty for this free software.  For both users' and
+authors' sake, the GPL requires that modified versions be marked as
+changed, so that their problems will not be attributed erroneously to
+authors of previous versions.
+
+  Some devices are designed to deny users access to install or run
+modified versions of the software inside them, although the manufacturer
+can do so.  This is fundamentally incompatible with the aim of
+protecting users' freedom to change the software.  The systematic
+pattern of such abuse occurs in the area of products for individuals to
+use, which is precisely where it is most unacceptable.  Therefore, we
+have designed this version of the GPL to prohibit the practice for those
+products.  If such problems arise substantially in other domains, we
+stand ready to extend this provision to those domains in future versions
+of the GPL, as needed to protect the freedom of users.
+
+  Finally, every program is threatened constantly by software patents.
+States should not allow patents to restrict development and use of
+software on general-purpose computers, but in those that do, we wish to
+avoid the special danger that patents applied to a free program could
+make it effectively proprietary.  To prevent this, the GPL assures that
+patents cannot be used to render the program non-free.
+
+  The precise terms and conditions for copying, distribution and
+modification follow.
+
+                       TERMS AND CONDITIONS
+
+  0. Definitions.
+
+  "This License" refers to version 3 of the GNU General Public License.
+
+  "Copyright" also means copyright-like laws that apply to other kinds of
 works, such as semiconductor masks.
 
-“The Program” refers to any copyrightable work licensed under this
-License. Each licensee is addressed as “you”. “Licensees” and
-“recipients” may be individuals or organizations.
-
-To “modify” a work means to copy from or adapt all or part of the work in
-a fashion requiring copyright permission, other than the making of an exact copy. The
-resulting work is called a “modified version” of the earlier work or a
-work “based on” the earlier work.
-
-A “covered work” means either the unmodified Program or a work based on
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-
-To “propagate” a work means to do anything with it that, without
-permission, would make you directly or secondarily liable for infringement under
-applicable copyright law, except executing it on a computer or modifying a private
-copy. Propagation includes copying, distribution (with or without modification),
-making available to the public, and in some countries other activities as well.
-
-To “convey” a work means any kind of propagation that enables other
-parties to make or receive copies. Mere interaction with a user through a computer
-network, with no transfer of a copy, is not conveying.
-
-An interactive user interface displays “Appropriate Legal Notices” to the
-extent that it includes a convenient and prominently visible feature that (1)
-displays an appropriate copyright notice, and (2) tells the user that there is no
-warranty for the work (except to the extent that warranties are provided), that
-licensees may convey the work under this License, and how to view a copy of this
-License. If the interface presents a list of user commands or options, such as a
+  "The Program" refers to any copyrightable work licensed under this
+License.  Each licensee is addressed as "you".  "Licensees" and
+"recipients" may be individuals or organizations.
+
+  To "modify" a work means to copy from or adapt all or part of the work
+in a fashion requiring copyright permission, other than the making of an
+exact copy.  The resulting work is called a "modified version" of the
+earlier work or a work "based on" the earlier work.
+
+  A "covered work" means either the unmodified Program or a work based
+on the Program.
+
+  To "propagate" a work means to do anything with it that, without
+permission, would make you directly or secondarily liable for
+infringement under applicable copyright law, except executing it on a
+computer or modifying a private copy.  Propagation includes copying,
+distribution (with or without modification), making available to the
+public, and in some countries other activities as well.
+
+  To "convey" a work means any kind of propagation that enables other
+parties to make or receive copies.  Mere interaction with a user through
+a computer network, with no transfer of a copy, is not conveying.
+
+  An interactive user interface displays "Appropriate Legal Notices"
+to the extent that it includes a convenient and prominently visible
+feature that (1) displays an appropriate copyright notice, and (2)
+tells the user that there is no warranty for the work (except to the
+extent that warranties are provided), that licensees may convey the
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+the interface presents a list of user commands or options, such as a
 menu, a prominent item in the list meets this criterion.
 
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-^^^^^^^^^^^^^^
-
-The “source code” for a work means the preferred form of the work for
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+
+  The "source code" for a work means the preferred form of the work
+for making modifications to it.  "Object code" means any non-source
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+interfaces specified for a particular programming language, one that
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+
+  The "System Libraries" of an executable work include anything, other
+than the work as a whole, that (a) is included in the normal form of
+packaging a Major Component, but which is not part of that Major
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+produce the work, or an object code interpreter used to run it.
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+the source code needed to generate, install, and (for an executable
+work) run the object code and to modify the work, including scripts to
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+System Libraries, or general-purpose tools or generally available free
+programs which are used unmodified in performing those activities but
+which are not part of the work.  For example, Corresponding Source
+includes interface definition files associated with source files for
+the work, and the source code for shared libraries and dynamically
+linked subprograms that the work is specifically designed to require,
+such as by intimate data communication or control flow between those
+subprograms and other parts of the work.
+
+  The Corresponding Source need not include anything that users
+can regenerate automatically from other parts of the Corresponding
+Source.
+
+  The Corresponding Source for a work in source code form is that
+same work.
+
+  2. Basic Permissions.
+
+  All rights granted under this License are granted for the term of
+copyright on the Program, and are irrevocable provided the stated
+conditions are met.  This License explicitly affirms your unlimited
+permission to run the unmodified Program.  The output from running a
+covered work is covered by this License only if the output, given its
+content, constitutes a covered work.  This License acknowledges your
+rights of fair use or other equivalent, as provided by copyright law.
+
+  You may make, run and propagate covered works that you do not
+convey, without conditions so long as your license otherwise remains
+in force.  You may convey covered works to others for the sole purpose
+of having them make modifications exclusively for you, or provide you
+with facilities for running those works, provided that you comply with
+the terms of this License in conveying all material for which you do
+not control copyright.  Those thus making or running the covered works
+for you must do so exclusively on your behalf, under your direction
+and control, on terms that prohibit them from making any copies of
+your copyrighted material outside their relationship with you.
+
+  Conveying under any other circumstances is permitted solely under
+the conditions stated below.  Sublicensing is not allowed; section 10
+makes it unnecessary.
+
+  3. Protecting Users' Legal Rights From Anti-Circumvention Law.
+
+  No covered work shall be deemed part of an effective technological
+measure under any applicable law fulfilling obligations under article
+11 of the WIPO copyright treaty adopted on 20 December 1996, or
+similar laws prohibiting or restricting circumvention of such
+measures.
+
+  When you convey a covered work, you waive any legal power to forbid
+circumvention of technological measures to the extent such circumvention
+is effected by exercising rights under this License with respect to
+the covered work, and you disclaim any intention to limit operation or
+modification of the work as a means of enforcing, against the work's
+users, your or third parties' legal rights to forbid circumvention of
+technological measures.
+
+  4. Conveying Verbatim Copies.
+
+  You may convey verbatim copies of the Program's source code as you
+receive it, in any medium, provided that you conspicuously and
+appropriately publish on each copy an appropriate copyright notice;
+keep intact all notices stating that this License and any
+non-permissive terms added in accord with section 7 apply to the code;
+keep intact all notices of the absence of any warranty; and give all
+recipients a copy of this License along with the Program.
+
+  You may charge any price or no price for each copy that you convey,
+and you may offer support or warranty protection for a fee.
+
+  5. Conveying Modified Source Versions.
+
+  You may convey a work based on the Program, or the modifications to
+produce it from the Program, in the form of source code under the
+terms of section 4, provided that you also meet all of these conditions:
+
+    a) The work must carry prominent notices stating that you modified
+    it, and giving a relevant date.
+
+    b) The work must carry prominent notices stating that it is
+    released under this License and any conditions added under section
+    7.  This requirement modifies the requirement in section 4 to
+    "keep intact all notices".
+
+    c) You must license the entire work, as a whole, under this
+    License to anyone who comes into possession of a copy.  This
+    License will therefore apply, along with any applicable section 7
+    additional terms, to the whole of the work, and all its parts,
+    regardless of how they are packaged.  This License gives no
+    permission to license the work in any other way, but it does not
+    invalidate such permission if you have separately received it.
+
+    d) If the work has interactive user interfaces, each must display
+    Appropriate Legal Notices; however, if the Program has interactive
+    interfaces that do not display Appropriate Legal Notices, your
+    work need not make them do so.
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+  A compilation of a covered work with other separate and independent
+works, which are not by their nature extensions of the covered work,
+and which are not combined with it such as to form a larger program,
+in or on a volume of a storage or distribution medium, is called an
+"aggregate" if the compilation and its resulting copyright are not
+used to limit the access or legal rights of the compilation's users
+beyond what the individual works permit.  Inclusion of a covered work
+in an aggregate does not cause this License to apply to the other
+parts of the aggregate.
+
+  6. Conveying Non-Source Forms.
+
+  You may convey a covered work in object code form under the terms
+of sections 4 and 5, provided that you also convey the
+machine-readable Corresponding Source under the terms of this License,
+in one of these ways:
+
+    a) Convey the object code in, or embodied in, a physical product
+    (including a physical distribution medium), accompanied by the
+    Corresponding Source fixed on a durable physical medium
+    customarily used for software interchange.
+
+    b) Convey the object code in, or embodied in, a physical product
+    (including a physical distribution medium), accompanied by a
+    written offer, valid for at least three years and valid for as
+    long as you offer spare parts or customer support for that product
+    model, to give anyone who possesses the object code either (1) a
+    copy of the Corresponding Source for all the software in the
+    product that is covered by this License, on a durable physical
+    medium customarily used for software interchange, for a price no
+    more than your reasonable cost of physically performing this
+    conveying of source, or (2) access to copy the
+    Corresponding Source from a network server at no charge.
+
+    c) Convey individual copies of the object code with a copy of the
+    written offer to provide the Corresponding Source.  This
+    alternative is allowed only occasionally and noncommercially, and
+    only if you received the object code with such an offer, in accord
+    with subsection 6b.
+
+    d) Convey the object code by offering access from a designated
+    place (gratis or for a charge), and offer equivalent access to the
+    Corresponding Source in the same way through the same place at no
+    further charge.  You need not require recipients to copy the
+    Corresponding Source along with the object code.  If the place to
+    copy the object code is a network server, the Corresponding Source
+    may be on a different server (operated by you or a third party)
+    that supports equivalent copying facilities, provided you maintain
+    clear directions next to the object code saying where to find the
+    Corresponding Source.  Regardless of what server hosts the
+    Corresponding Source, you remain obligated to ensure that it is
+    available for as long as needed to satisfy these requirements.
+
+    e) Convey the object code using peer-to-peer transmission, provided
+    you inform other peers where the object code and Corresponding
+    Source of the work are being offered to the general public at no
+    charge under subsection 6d.
+
+  A separable portion of the object code, whose source code is excluded
+from the Corresponding Source as a System Library, need not be
+included in conveying the object code work.
+
+  A "User Product" is either (1) a "consumer product", which means any
+tangible personal property which is normally used for personal, family,
+or household purposes, or (2) anything designed or sold for incorporation
+into a dwelling.  In determining whether a product is a consumer product,
+doubtful cases shall be resolved in favor of coverage.  For a particular
+product received by a particular user, "normally used" refers to a
+typical or common use of that class of product, regardless of the status
+of the particular user or of the way in which the particular user
+actually uses, or expects or is expected to use, the product.  A product
+is a consumer product regardless of whether the product has substantial
+commercial, industrial or non-consumer uses, unless such uses represent
 the only significant mode of use of the product.
 
-“Installation Information” for a User Product means any methods,
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-modified versions of a covered work in that User Product from a modified version of
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-functioning of the modified object code is in no case prevented or interfered with
-solely because modification has been made.
-
-If you convey an object code work under this section in, or with, or specifically for
-use in, a User Product, and the conveying occurs as part of a transaction in which
-the right of possession and use of the User Product is transferred to the recipient
-in perpetuity or for a fixed term (regardless of how the transaction is
-characterized), the Corresponding Source conveyed under this section must be
-accompanied by the Installation Information. But this requirement does not apply if
-neither you nor any third party retains the ability to install modified object code
-on the User Product (for example, the work has been installed in ROM).
-
-The requirement to provide Installation Information does not include a requirement to
-continue to provide support service, warranty, or updates for a work that has been
-modified or installed by the recipient, or for the User Product in which it has been
-modified or installed. Access to a network may be denied when the modification itself
-materially and adversely affects the operation of the network or violates the rules
-and protocols for communication across the network.
-
-Corresponding Source conveyed, and Installation Information provided, in accord with
-this section must be in a format that is publicly documented (and with an
-implementation available to the public in source code form), and must require no
-special password or key for unpacking, reading or copying.
-
-7. Additional Terms
-^^^^^^^^^^^^^^^^^^^
-
-“Additional permissions” are terms that supplement the terms of this
-License by making exceptions from one or more of its conditions. Additional
-permissions that are applicable to the entire Program shall be treated as though they
-were included in this License, to the extent that they are valid under applicable
-law. If additional permissions apply only to part of the Program, that part may be
-used separately under those permissions, but the entire Program remains governed by
+  "Installation Information" for a User Product means any methods,
+procedures, authorization keys, or other information required to install
+and execute modified versions of a covered work in that User Product from
+a modified version of its Corresponding Source.  The information must
+suffice to ensure that the continued functioning of the modified object
+code is in no case prevented or interfered with solely because
+modification has been made.
+
+  If you convey an object code work under this section in, or with, or
+specifically for use in, a User Product, and the conveying occurs as
+part of a transaction in which the right of possession and use of the
+User Product is transferred to the recipient in perpetuity or for a
+fixed term (regardless of how the transaction is characterized), the
+Corresponding Source conveyed under this section must be accompanied
+by the Installation Information.  But this requirement does not apply
+if neither you nor any third party retains the ability to install
+modified object code on the User Product (for example, the work has
+been installed in ROM).
+
+  The requirement to provide Installation Information does not include a
+requirement to continue to provide support service, warranty, or updates
+for a work that has been modified or installed by the recipient, or for
+the User Product in which it has been modified or installed.  Access to a
+network may be denied when the modification itself materially and
+adversely affects the operation of the network or violates the rules and
+protocols for communication across the network.
+
+  Corresponding Source conveyed, and Installation Information provided,
+in accord with this section must be in a format that is publicly
+documented (and with an implementation available to the public in
+source code form), and must require no special password or key for
+unpacking, reading or copying.
+
+  7. Additional Terms.
+
+  "Additional permissions" are terms that supplement the terms of this
+License by making exceptions from one or more of its conditions.
+Additional permissions that are applicable to the entire Program shall
+be treated as though they were included in this License, to the extent
+that they are valid under applicable law.  If additional permissions
+apply only to part of the Program, that part may be used separately
+under those permissions, but the entire Program remains governed by
 this License without regard to the additional permissions.
 
-When you convey a copy of a covered work, you may at your option remove any
-additional permissions from that copy, or from any part of it. (Additional
-permissions may be written to require their own removal in certain cases when you
-modify the work.) You may place additional permissions on material, added by you to a
-covered work, for which you have or can give appropriate copyright permission.
-
-Notwithstanding any other provision of this License, for material you add to a
-covered work, you may (if authorized by the copyright holders of that material)
-supplement the terms of this License with terms:
-
-   a) Disclaiming warranty or limiting liability differently from the terms of
-      sections 15 and 16 of this License; or
-   b) Requiring preservation of specified reasonable legal notices or author
-      attributions in that material or in the Appropriate Legal Notices displayed by works
-      containing it; or
-   c) Prohibiting misrepresentation of the origin of that material, or requiring that
-      modified versions of such material be marked in reasonable ways as different from the
-      original version; or
-   d) Limiting the use for publicity purposes of names of licensors or authors of the
-      material; or
-   e) Declining to grant rights under trademark law for use of some trade names,
-      trademarks, or service marks; or
-   f) Requiring indemnification of licensors and authors of that material by anyone
-      who conveys the material (or modified versions of it) with contractual assumptions of
-      liability to the recipient, for any liability that these contractual assumptions
-      directly impose on those licensors and authors.
-
-All other non-permissive additional terms are considered “further
-restrictions” within the meaning of section 10. If the Program as you received
-it, or any part of it, contains a notice stating that it is governed by this License
-along with a term that is a further restriction, you may remove that term. If a
-license document contains a further restriction but permits relicensing or conveying
-under this License, you may add to a covered work material governed by the terms of
-that license document, provided that the further restriction does not survive such
-relicensing or conveying.
-
-If you add terms to a covered work in accord with this section, you must place, in
-the relevant source files, a statement of the additional terms that apply to those
-files, or a notice indicating where to find the applicable terms.
-
-Additional terms, permissive or non-permissive, may be stated in the form of a
-separately written license, or stated as exceptions; the above requirements apply
-either way.
-
-8. Termination
-^^^^^^^^^^^^^^
-
-You may not propagate or modify a covered work except as expressly provided under
-this License. Any attempt otherwise to propagate or modify it is void, and will
-automatically terminate your rights under this License (including any patent licenses
-granted under the third paragraph of section 11).
-
-However, if you cease all violation of this License, then your license from a
-particular copyright holder is reinstated (a) provisionally, unless and until the
-copyright holder explicitly and finally terminates your license, and (b) permanently,
-if the copyright holder fails to notify you of the violation by some reasonable means
+  When you convey a copy of a covered work, you may at your option
+remove any additional permissions from that copy, or from any part of
+it.  (Additional permissions may be written to require their own
+removal in certain cases when you modify the work.)  You may place
+additional permissions on material, added by you to a covered work,
+for which you have or can give appropriate copyright permission.
+
+  Notwithstanding any other provision of this License, for material you
+add to a covered work, you may (if authorized by the copyright holders of
+that material) supplement the terms of this License with terms:
+
+    a) Disclaiming warranty or limiting liability differently from the
+    terms of sections 15 and 16 of this License; or
+
+    b) Requiring preservation of specified reasonable legal notices or
+    author attributions in that material or in the Appropriate Legal
+    Notices displayed by works containing it; or
+
+    c) Prohibiting misrepresentation of the origin of that material, or
+    requiring that modified versions of such material be marked in
+    reasonable ways as different from the original version; or
+
+    d) Limiting the use for publicity purposes of names of licensors or
+    authors of the material; or
+
+    e) Declining to grant rights under trademark law for use of some
+    trade names, trademarks, or service marks; or
+
+    f) Requiring indemnification of licensors and authors of that
+    material by anyone who conveys the material (or modified versions of
+    it) with contractual assumptions of liability to the recipient, for
+    any liability that these contractual assumptions directly impose on
+    those licensors and authors.
+
+  All other non-permissive additional terms are considered "further
+restrictions" within the meaning of section 10.  If the Program as you
+received it, or any part of it, contains a notice stating that it is
+governed by this License along with a term that is a further
+restriction, you may remove that term.  If a license document contains
+a further restriction but permits relicensing or conveying under this
+License, you may add to a covered work material governed by the terms
+of that license document, provided that the further restriction does
+not survive such relicensing or conveying.
+
+  If you add terms to a covered work in accord with this section, you
+must place, in the relevant source files, a statement of the
+additional terms that apply to those files, or a notice indicating
+where to find the applicable terms.
+
+  Additional terms, permissive or non-permissive, may be stated in the
+form of a separately written license, or stated as exceptions;
+the above requirements apply either way.
+
+  8. Termination.
+
+  You may not propagate or modify a covered work except as expressly
+provided under this License.  Any attempt otherwise to propagate or
+modify it is void, and will automatically terminate your rights under
+this License (including any patent licenses granted under the third
+paragraph of section 11).
+
+  However, if you cease all violation of this License, then your
+license from a particular copyright holder is reinstated (a)
+provisionally, unless and until the copyright holder explicitly and
+finally terminates your license, and (b) permanently, if the copyright
+holder fails to notify you of the violation by some reasonable means
 prior to 60 days after the cessation.
 
-Moreover, your license from a particular copyright holder is reinstated permanently
-if the copyright holder notifies you of the violation by some reasonable means, this
-is the first time you have received notice of violation of this License (for any
-work) from that copyright holder, and you cure the violation prior to 30 days after
+  Moreover, your license from a particular copyright holder is
+reinstated permanently if the copyright holder notifies you of the
+violation by some reasonable means, this is the first time you have
+received notice of violation of this License (for any work) from that
+copyright holder, and you cure the violation prior to 30 days after
 your receipt of the notice.
 
-Termination of your rights under this section does not terminate the licenses of
-parties who have received copies or rights from you under this License. If your
-rights have been terminated and not permanently reinstated, you do not qualify to
-receive new licenses for the same material under section 10.
-
-9. Acceptance Not Required for Having Copies
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-You are not required to accept this License in order to receive or run a copy of the
-Program. Ancillary propagation of a covered work occurring solely as a consequence of
-using peer-to-peer transmission to receive a copy likewise does not require
-acceptance. However, nothing other than this License grants you permission to
-propagate or modify any covered work. These actions infringe copyright if you do not
-accept this License. Therefore, by modifying or propagating a covered work, you
-indicate your acceptance of this License to do so.
-
-10. Automatic Licensing of Downstream Recipients
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-Each time you convey a covered work, the recipient automatically receives a license
-from the original licensors, to run, modify and propagate that work, subject to this
-License. You are not responsible for enforcing compliance by third parties with this
-License.
-
-An “entity transaction” is a transaction transferring control of an
-organization, or substantially all assets of one, or subdividing an organization, or
-merging organizations. If propagation of a covered work results from an entity
-transaction, each party to that transaction who receives a copy of the work also
-receives whatever licenses to the work the party's predecessor in interest had or
-could give under the previous paragraph, plus a right to possession of the
-Corresponding Source of the work from the predecessor in interest, if the predecessor
-has it or can get it with reasonable efforts.
-
-You may not impose any further restrictions on the exercise of the rights granted or
-affirmed under this License. For example, you may not impose a license fee, royalty,
-or other charge for exercise of rights granted under this License, and you may not
-initiate litigation (including a cross-claim or counterclaim in a lawsuit) alleging
-that any patent claim is infringed by making, using, selling, offering for sale, or
-importing the Program or any portion of it.
-
-11. Patents
-^^^^^^^^^^^
-
-A “contributor” is a copyright holder who authorizes use under this
-License of the Program or a work on which the Program is based. The work thus
-licensed is called the contributor's “contributor version”.
-
-A contributor's “essential patent claims” are all patent claims owned or
-controlled by the contributor, whether already acquired or hereafter acquired, that
-would be infringed by some manner, permitted by this License, of making, using, or
-selling its contributor version, but do not include claims that would be infringed
-only as a consequence of further modification of the contributor version. For
-purposes of this definition, “control” includes the right to grant patent
-sublicenses in a manner consistent with the requirements of this License.
-
-Each contributor grants you a non-exclusive, worldwide, royalty-free patent license
-under the contributor's essential patent claims, to make, use, sell, offer for sale,
-import and otherwise run, modify and propagate the contents of its contributor
-version.
-
-In the following three paragraphs, a “patent license” is any express
-agreement or commitment, however denominated, not to enforce a patent (such as an
-express permission to practice a patent or covenant not to sue for patent
-infringement). To “grant” such a patent license to a party means to make
-such an agreement or commitment not to enforce a patent against the party.
-
-If you convey a covered work, knowingly relying on a patent license, and the
-Corresponding Source of the work is not available for anyone to copy, free of charge
-and under the terms of this License, through a publicly available network server or
-other readily accessible means, then you must either (1) cause the Corresponding
-Source to be so available, or (2) arrange to deprive yourself of the benefit of the
-patent license for this particular work, or (3) arrange, in a manner consistent with
-the requirements of this License, to extend the patent license to downstream
-recipients. “Knowingly relying” means you have actual knowledge that, but
-for the patent license, your conveying the covered work in a country, or your
-recipient's use of the covered work in a country, would infringe one or more
-identifiable patents in that country that you have reason to believe are valid.
-
-If, pursuant to or in connection with a single transaction or arrangement, you
-convey, or propagate by procuring conveyance of, a covered work, and grant a patent
-license to some of the parties receiving the covered work authorizing them to use,
-propagate, modify or convey a specific copy of the covered work, then the patent
-license you grant is automatically extended to all recipients of the covered work and
-works based on it.
-
-A patent license is “discriminatory” if it does not include within the
-scope of its coverage, prohibits the exercise of, or is conditioned on the
-non-exercise of one or more of the rights that are specifically granted under this
-License. You may not convey a covered work if you are a party to an arrangement with
-a third party that is in the business of distributing software, under which you make
-payment to the third party based on the extent of your activity of conveying the
-work, and under which the third party grants, to any of the parties who would receive
-the covered work from you, a discriminatory patent license (a) in connection with
-copies of the covered work conveyed by you (or copies made from those copies), or (b)
-primarily for and in connection with specific products or compilations that contain
-the covered work, unless you entered into that arrangement, or that patent license
-was granted, prior to 28 March 2007.
-
-Nothing in this License shall be construed as excluding or limiting any implied
-license or other defenses to infringement that may otherwise be available to you
-under applicable patent law.
-
-12. No Surrender of Others' Freedom
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-If conditions are imposed on you (whether by court order, agreement or otherwise)
-that contradict the conditions of this License, they do not excuse you from the
-conditions of this License. If you cannot convey a covered work so as to satisfy
-simultaneously your obligations under this License and any other pertinent
-obligations, then as a consequence you may not convey it at all. For example, if you
-agree to terms that obligate you to collect a royalty for further conveying from
-those to whom you convey the Program, the only way you could satisfy both those terms
-and this License would be to refrain entirely from conveying the Program.
-
-13. Use with the GNU Affero General Public License
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-Notwithstanding any other provision of this License, you have permission to link or
-combine any covered work with a work licensed under version 3 of the GNU Affero
-General Public License into a single combined work, and to convey the resulting work.
-The terms of this License will continue to apply to the part which is the covered
-work, but the special requirements of the GNU Affero General Public License, section
-13, concerning interaction through a network will apply to the combination as such.
-
-14. Revised Versions of this License
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-The Free Software Foundation may publish revised and/or new versions of the GNU
-General Public License from time to time. Such new versions will be similar in spirit
-to the present version, but may differ in detail to address new problems or concerns.
-
-Each version is given a distinguishing version number. If the Program specifies that
-a certain numbered version of the GNU General Public License “or any later
-version” applies to it, you have the option of following the terms and
-conditions either of that numbered version or of any later version published by the
-Free Software Foundation. If the Program does not specify a version number of the GNU
-General Public License, you may choose any version ever published by the Free
-Software Foundation.
-
-If the Program specifies that a proxy can decide which future versions of the GNU
-General Public License can be used, that proxy's public statement of acceptance of a
-version permanently authorizes you to choose that version for the Program.
-
-Later license versions may give you additional or different permissions. However, no
-additional obligations are imposed on any author or copyright holder as a result of
-your choosing to follow a later version.
-
-15. Disclaimer of Warranty
-^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW.
-EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES
-PROVIDE THE PROGRAM “AS IS” WITHOUT WARRANTY OF ANY KIND, EITHER
-EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
-MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE
-QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE
-DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
-
-16. Limitation of Liability
-^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING WILL ANY
-COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS THE PROGRAM AS
-PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL,
-INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE
-PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE
-OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE
-WITH ANY OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE
-POSSIBILITY OF SUCH DAMAGES.
-
-17. Interpretation of Sections 15 and 16
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-If the disclaimer of warranty and limitation of liability provided above cannot be
-given local legal effect according to their terms, reviewing courts shall apply local
-law that most closely approximates an absolute waiver of all civil liability in
-connection with the Program, unless a warranty or assumption of liability accompanies
-a copy of the Program in return for a fee.
-
-END OF TERMS AND CONDITIONS
-
-How to Apply These Terms to Your New Programs
----------------------------------------------
-
-If you develop a new program, and you want it to be of the greatest possible use to
-the public, the best way to achieve this is to make it free software which everyone
-can redistribute and change under these terms.
-
-To do so, attach the following notices to the program. It is safest to attach them
-to the start of each source file to most effectively state the exclusion of warranty;
-and each file should have at least the “copyright” line and a pointer to
-where the full notice is found.
-
-.. pull-quote::
-
-   <one line to give the program's name and a brief idea of what it does.>
-   Copyright (C) <year>  <name of author>
-
-   This program is free software: you can redistribute it and/or modify
-   it under the terms of the GNU General Public License as published by
-   the Free Software Foundation, either version 3 of the License, or
-   (at your option) any later version.
-
-   This program is distributed in the hope that it will be useful,
-   but WITHOUT ANY WARRANTY; without even the implied warranty of
-   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-   GNU General Public License for more details.
-
-   You should have received a copy of the GNU General Public License
-   along with this program.  If not, see <http://www.gnu.org/licenses/>.
+  Termination of your rights under this section does not terminate the
+licenses of parties who have received copies or rights from you under
+this License.  If your rights have been terminated and not permanently
+reinstated, you do not qualify to receive new licenses for the same
+material under section 10.
+
+  9. Acceptance Not Required for Having Copies.
+
+  You are not required to accept this License in order to receive or
+run a copy of the Program.  Ancillary propagation of a covered work
+occurring solely as a consequence of using peer-to-peer transmission
+to receive a copy likewise does not require acceptance.  However,
+nothing other than this License grants you permission to propagate or
+modify any covered work.  These actions infringe copyright if you do
+not accept this License.  Therefore, by modifying or propagating a
+covered work, you indicate your acceptance of this License to do so.
+
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+
+  Nothing in this License shall be construed as excluding or limiting
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+otherwise be available to you under applicable patent law.
+
+  12. No Surrender of Others' Freedom.
+
+  If conditions are imposed on you (whether by court order, agreement or
+otherwise) that contradict the conditions of this License, they do not
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+not convey it at all.  For example, if you agree to terms that obligate you
+to collect a royalty for further conveying from those to whom you convey
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+
+  13. Use with the GNU Affero General Public License.
+
+  Notwithstanding any other provision of this License, you have
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+
+  14. Revised Versions of this License.
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+  The Free Software Foundation may publish revised and/or new versions of
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+be similar in spirit to the present version, but may differ in detail to
+address new problems or concerns.
+
+  Each version is given a distinguishing version number.  If the
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+option of following the terms and conditions either of that numbered
+version or of any later version published by the Free Software
+Foundation.  If the Program does not specify a version number of the
+GNU General Public License, you may choose any version ever published
+by the Free Software Foundation.
+
+  If the Program specifies that a proxy can decide which future
+versions of the GNU General Public License can be used, that proxy's
+public statement of acceptance of a version permanently authorizes you
+to choose that version for the Program.
+
+  Later license versions may give you additional or different
+permissions.  However, no additional obligations are imposed on any
+author or copyright holder as a result of your choosing to follow a
+later version.
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+  15. Disclaimer of Warranty.
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+APPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
+HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
+OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
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+  16. Limitation of Liability.
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+DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
+PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
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+  17. Interpretation of Sections 15 and 16.
+
+  If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+                     END OF TERMS AND CONDITIONS
+
+            How to Apply These Terms to Your New Programs
+
+  If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+  To do so, attach the following notices to the program.  It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+    <one line to give the program's name and a brief idea of what it does.>
+    Copyright (C) <year>  <name of author>
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU General Public License as published by
+    the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU General Public License for more details.
+
+    You should have received a copy of the GNU General Public License
+    along with this program.  If not, see <https://www.gnu.org/licenses/>.
 
 Also add information on how to contact you by electronic and paper mail.
 
-If the program does terminal interaction, make it output a short notice like this
-when it starts in an interactive mode:
-
-.. pull-quote::
-
-   <program>  Copyright (C) <year>  <name of author>
-   This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'.
-   This is free software, and you are welcome to redistribute it
-   under certain conditions; type 'show c' for details.
-
-The hypothetical commands `show w` and `show c` should show the appropriate parts of
-the General Public License. Of course, your program's commands might be different;
-for a GUI interface, you would use an “about box”.
-
-You should also get your employer (if you work as a programmer) or school, if any, to
-sign a “copyright disclaimer” for the program, if necessary. For more
-information on this, and how to apply and follow the GNU GPL, see
-<http://www.gnu.org/licenses/>.
-
-The GNU General Public License does not permit incorporating your program into
-proprietary programs. If your program is a subroutine library, you may consider it
-more useful to permit linking proprietary applications with the library. If this is
-what you want to do, use the GNU Lesser General Public License instead of this
-License. But first, please read
-<http://www.gnu.org/philosophy/why-not-lgpl.html>.
\ No newline at end of file
+  If the program does terminal interaction, make it output a short
+notice like this when it starts in an interactive mode:
+
+    <program>  Copyright (C) <year>  <name of author>
+    This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+    This is free software, and you are welcome to redistribute it
+    under certain conditions; type `show c' for details.
+
+The hypothetical commands `show w' and `show c' should show the appropriate
+parts of the General Public License.  Of course, your program's commands
+might be different; for a GUI interface, you would use an "about box".
+
+  You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU GPL, see
+<https://www.gnu.org/licenses/>.
+
+  The GNU General Public License does not permit incorporating your program
+into proprietary programs.  If your program is a subroutine library, you
+may consider it more useful to permit linking proprietary applications with
+the library.  If this is what you want to do, use the GNU Lesser General
+Public License instead of this License.  But first, please read
+<https://www.gnu.org/licenses/why-not-lgpl.html>.
diff --git a/README.md b/README.md
index 7c21c1f..88d0e85 100644
--- a/README.md
+++ b/README.md
@@ -1,3 +1,7 @@
+[![PyPI - Version](https://img.shields.io/pypi/v/gridmarthe)](https://pypi.org/project/gridmarthe/)
+[![Conda Version](https://img.shields.io/conda/vn/conda-forge/gridmarthe.svg)](https://anaconda.org/conda-forge/gridmarthe)
+[![GitLab License](https://img.shields.io/gitlab/license/brgm%2Fhydrogeological-modelling%2Fmarthe-tools%2Fgridmarthe)](https://gitlab.com/brgm/hydrogeological-modelling/marthe-tools/gridmarthe/-/blob/dev/LICENSE?ref_type=heads)
+
 # Gridmarthe
 
 Python project for (fast) Marthe grid operations.
@@ -36,6 +40,7 @@ pip install gridmarthe
 For GNU/Linux and MacOS, the package needs gfotran/gcc to run.
 
 Linux, example with debian/ubuntu:
+
 ```bash
 sudo apt install gcc gfortran
 ```
@@ -47,6 +52,16 @@ MacOS:
 brew install gcc gfortran
 ```
 
+### From conda-forge
+
+`gridmarthe` is also available in the `conda-forge` channel. Conda users can install it with:
+
+```bash
+conda install gridmarthe
+# or, with mamba
+mamba install gridmarthe
+```
+
 
 ### From sources
 
@@ -112,7 +127,7 @@ Simple examples can be found in the
 
 ## License
 
-This software is open-source and released under the GNU General Public License (v3+) [GNU/GPL-V3 Licensed](LICENSE).
+This software is open-source and released under the [GNU General Public License (v3+)](LICENSE).
 
 
 ## Authors and acknowledgment
diff --git a/docs/source/getting_started/install.rst b/docs/source/getting_started/install.rst
index 141c637..d3f92d7 100644
--- a/docs/source/getting_started/install.rst
+++ b/docs/source/getting_started/install.rst
@@ -14,7 +14,20 @@ From pip
 From conda-forge (with conda or mamba)
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-Not yet available.
+`gridmarthe` is also available in the `conda-forge` channel. Conda users can install it with:
+
+.. code-block:: bash
+    
+    conda install gridmarthe
+    # or, with mamba
+    mamba install gridmarthe
+
+It is also possible to search for available versions:
+
+.. code-block:: bash
+
+    mamba search gridmarthe --channel conda-forge
+
 
 
 From the source
diff --git a/pyproject.toml b/pyproject.toml
index e1d1b0b..ac6fb6f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -32,11 +32,16 @@ classifiers = [
     "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)",
     "Programming Language :: Python :: 3",
     "Programming Language :: Python :: 3 :: Only",
+    "Programming Language :: Python :: Implementation :: CPython",
     "Programming Language :: Fortran",
     "Operating System :: POSIX :: Linux",
     "Operating System :: MacOS",
     "Operating System :: Microsoft :: Windows",
+    "Topic :: Scientific/Engineering",
     "Topic :: Scientific/Engineering :: Hydrology",
+    "Topic :: Software Development",
+    "Intended Audience :: Science/Research",
+    "Intended Audience :: Developers",
     "Development Status :: 4 - Beta",
 ]
 
@@ -87,13 +92,14 @@ include-package-data = true
 # https://mesonbuild.com/meson-python/reference/pyproject-settings.html
 # https://mesonbuild.com/meson-python/how-to-guides/meson-args.html
 # setup = ['--default-library=static']
-# setup = ['--build-dir=src']
+# setup = ['--build-dir=build']
 
 
 [tool.cibuildwheel]
-# skip = "cp36-* cp37-* cp-38* pp37-* *-manylinux_i686 *_ppc64le *_s390x *_universal2"
 skip = "cp36-* cp37-* cp-38* pp* *musl* *_i686 *_ppc64le *_s390x *_universal2"
 # skip = ["pp*", "*musl*"]
+# test-requires = "pytest"
+# test-command = "pytest {project}/tests"
 
 [tool.cibuildwheel.linux]
 archs = ["x86_64"]
@@ -112,5 +118,5 @@ archs = ["arm64"]
 package = 'gridmarthe'
 [tool.spin.commands]
 Build = [
-    'spin.cmds.meson.build',
+    'spin.cmds.pip.install',
 ]

From c33e6f8210064601d4e43f65b8a955d7e3cdfd59 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Tue, 4 Feb 2025 11:35:54 +0100
Subject: [PATCH 02/31] fix: color in license badge... :)

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 88d0e85..937f015 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
 [![PyPI - Version](https://img.shields.io/pypi/v/gridmarthe)](https://pypi.org/project/gridmarthe/)
 [![Conda Version](https://img.shields.io/conda/vn/conda-forge/gridmarthe.svg)](https://anaconda.org/conda-forge/gridmarthe)
-[![GitLab License](https://img.shields.io/gitlab/license/brgm%2Fhydrogeological-modelling%2Fmarthe-tools%2Fgridmarthe)](https://gitlab.com/brgm/hydrogeological-modelling/marthe-tools/gridmarthe/-/blob/dev/LICENSE?ref_type=heads)
+[![GitLab License](https://img.shields.io/gitlab/license/brgm%2Fhydrogeological-modelling%2Fmarthe-tools%2Fgridmarthe?color=blue)](https://gitlab.com/brgm/hydrogeological-modelling/marthe-tools/gridmarthe/-/blob/dev/LICENSE?ref_type=heads)
 
 # Gridmarthe
 

From 90c703fcd00f58e2ca96f2a679c984bcea018ee0 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Fri, 14 Feb 2025 10:40:57 +0100
Subject: [PATCH 03/31] dev: add title in read_shallow to harmonize intent(out)

---
 src/gridmarthe/lecsem/edsemigl.f90  | 37 ++++++++++++++++++++++++++++-
 src/gridmarthe/lecsem/scan_grid.f90 |  6 +++--
 2 files changed, 40 insertions(+), 3 deletions(-)

diff --git a/src/gridmarthe/lecsem/edsemigl.f90 b/src/gridmarthe/lecsem/edsemigl.f90
index d798511..b2d56c1 100644
--- a/src/gridmarthe/lecsem/edsemigl.f90
+++ b/src/gridmarthe/lecsem/edsemigl.f90
@@ -1,4 +1,39 @@
-! (Provenance MARTHE, Fichier : edsemi.f90, convert utf-8 )
+! Copyright 2024, BRGM
+! 
+! This file is part of Gridmarthe.
+! 
+! Gridmarthe is free software: you can redistribute it and/or modify it under the
+! terms of the GNU General Public License as published by the Free Software
+! Foundation, either version 3 of the License, or (at your option) any later
+! version.
+! 
+! Gridmarthe is distributed in the hope that it will be useful, but WITHOUT ANY
+! WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
+! PARTICULAR PURPOSE. See the GNU General Public License for more details.
+! 
+! You should have received a copy of the GNU General Public License along with
+! Gridmarthe. If not, see <https://www.gnu.org/licenses/>.
+!
+!
+! (Provenance MARTHE, file : edsemi.f90, convert utf-8 )
+!
+! MARTHE License:
+!Copyright © 2002-2024 BRGM
+!
+! Permission is granted under the following conditions :
+! The User undertakes:
+! 1.  To use the software only at his own premises.
+! 2.  Not to use the software simultaneously on several computers or through a network or server.
+! 3.  To ensure that the Marthe software is not passed to any third party (subcontractor, client, etc.) and to take every precaution necessary to prevent illegal copying of the software.
+!
+! The User is nevertheless permitted:
+! 1.  To make one or more backup copies of the software for his own use.
+! 2.  To install the software on several workstations at his premises (for instance a desktop and a lap top computer) provided that the software will be never used simultaneously on several computers.
+
+! Limitation of liability:
+! The greatest care was taken to the realization of this software, however BRGM will not be held liable for any direct or indirect damage (including lost profits, lost savings, costs, fees, or expenses of any kind) rising from the use or impossibility of using the software.
+!
+!
       SUBROUTINE EDSEMI7_0(FONC, NKOL, NLIG, XCOL, YLIG, X0, Y0, INVY &
        ,TITSEM, IEREDI, IOUMAI, DXLU, DYLU)
 !=================================================================================
diff --git a/src/gridmarthe/lecsem/scan_grid.f90 b/src/gridmarthe/lecsem/scan_grid.f90
index 95b4bcc..5400ed6 100644
--- a/src/gridmarthe/lecsem/scan_grid.f90
+++ b/src/gridmarthe/lecsem/scan_grid.f90
@@ -141,7 +141,8 @@ END SUBROUTINE SCAN_DIM
     !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
     ! =============================================================================!
     !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
-    SUBROUTINE READ_GRID(XFILE, XTYP_DON, KNBSTEP, KNBTOT, KNU_ZOOMX, PVAR, PDATES, KSTEPS, PXCOL, PYLIG, PDXLU, PDYLU, TITSEM)
+    SUBROUTINE READ_GRID(XFILE, XTYP_DON, KNBSTEP, KNBTOT, KNU_ZOOMX, PVAR, PDATES, &
+        KSTEPS, PXCOL, PYLIG, PDXLU, PDYLU, TITSEM)
         !
         IMPLICIT NONE
         !
@@ -221,7 +222,7 @@ END SUBROUTINE READ_GRID
     ! =============================================================================!
     !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
     SUBROUTINE READ_GRID_SHALLOW(XFILE, XTYP_DON, KNBSTEP, KN_COUCHMX, KNBTOT, &
-        KNU_ZOOMX, PVAR, PDATES, KSTEPS, PXCOL, PYLIG, PDXLU, PDYLU)
+        KNU_ZOOMX, PVAR, PDATES, KSTEPS, PXCOL, PYLIG, PDXLU, PDYLU, TITSEM)
         !
         IMPLICIT NONE
         !
@@ -234,6 +235,7 @@ SUBROUTINE READ_GRID_SHALLOW(XFILE, XTYP_DON, KNBSTEP, KN_COUCHMX, KNBTOT, &
         REAL(KIND=4), DIMENSION(KNBSTEP), INTENT(OUT) :: PDATES
         REAL(KIND=4), DIMENSION(KNBSTEP, KNU_ZOOMX + 1, KNBTOT), INTENT(OUT) :: PVAR
         REAL(KIND=4), DIMENSION(KNU_ZOOMX + 1, 999), INTENT(OUT) :: PXCOL, PYLIG, PDXLU, PDYLU
+        CHARACTER (LEN=132), INTENT(OUT)              :: TITSEM
         !
         !
         INTEGER    :: ISTEPINC, ISTEP_TEMP, INTOT_TEMP, N_COUCH2

From 1ca7503b325623556bd5540c9d4a245098814003 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Fri, 14 Feb 2025 10:48:06 +0100
Subject: [PATCH 04/31] change: code restructuration

---
 src/gridmarthe/__init__.py                 |  36 +-
 src/gridmarthe/__version__.py              |  18 +-
 src/gridmarthe/gridmarthe.py               | 460 +++++----------------
 src/gridmarthe/lecsem/__init__.py          |  15 +-
 src/gridmarthe/lecsem/_parse_gridmarthe.py | 200 +++++++++
 src/gridmarthe/operasem.py                 | 261 ------------
 src/gridmarthe/operasem/gis.py             | 117 ++++++
 src/gridmarthe/operasem/interp.py          |  76 ++++
 src/gridmarthe/plot.py                     |   1 +
 src/gridmarthe/scripts/cleanmgrid.py       | 136 ++++--
 src/gridmarthe/scripts/ncmart.py           |  38 +-
 src/gridmarthe/utils.py                    | 147 +++++++
 12 files changed, 845 insertions(+), 660 deletions(-)
 create mode 100644 src/gridmarthe/lecsem/_parse_gridmarthe.py
 delete mode 100644 src/gridmarthe/operasem.py
 create mode 100644 src/gridmarthe/operasem/gis.py
 create mode 100644 src/gridmarthe/operasem/interp.py

diff --git a/src/gridmarthe/__init__.py b/src/gridmarthe/__init__.py
index 16b1d96..2fd6e9c 100644
--- a/src/gridmarthe/__init__.py
+++ b/src/gridmarthe/__init__.py
@@ -1,15 +1,35 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
+#
+#    This file is part of gridmarthe.
+#
+#    gridmarthe is a python library to manage grid files for 
+#    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
+#    Copyright (C) 2024  BRGM
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+#
+
+import xarray as xr
+from typing import Union
 
 
+from .__version__ import __version__
 from .gridmarthe import *
 from .operasem import *
 from .plot import plot_nested_grid, plot_outcrop
 
-from typing import Union
-
-from .__version__ import __version__
-
 
 @xr.register_dataset_accessor('mart')
 class MartheGrid(object):
@@ -63,10 +83,4 @@ def subset_coords(self, dims=['x', 'y'], gdf=None, xmin=None, ymin=None, xmax=No
     def dropna(self, varname='charge', nanval=9999.):
         ds = self.obj.copy()
         masque = ds[varname].where(ds[varname] != nanval).dropna(dim='zone') # drop nanval
-        return ds.sel(zone=masque['zone'])
-    
-    # def write(self, fmt='mart'):
-        # if fmt.lower() in ['mart', 'marthe']
-            # write_marthe_grid()
-        # else:
-            # self.obj.to_netcdf()
+        return ds.sel(zone=masque['zone'])
\ No newline at end of file
diff --git a/src/gridmarthe/__version__.py b/src/gridmarthe/__version__.py
index 58bdced..16accd6 100644
--- a/src/gridmarthe/__version__.py
+++ b/src/gridmarthe/__version__.py
@@ -1,4 +1,20 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-__version__ = '0.1.2'
+__version__ = '0.1.3'
+
+_copyleft = """
+    {program}  Copyright (C) {year}  {name_of_author}.
+    This program comes with ABSOLUTELY NO WARRANTY.
+    This is free software, see GNU General Public Lisence v3 for copying.
+""".format(program='gridmarthe', year=2024, name_of_author='BRGM') #(A. Manlay, J.P. Vergnes)
+
+
+# def _show_c():
+    # print('c')
+    # return
+
+
+# def _show_w():
+    # print('w')
+    # return
\ No newline at end of file
diff --git a/src/gridmarthe/gridmarthe.py b/src/gridmarthe/gridmarthe.py
index 07276d9..baaad02 100644
--- a/src/gridmarthe/gridmarthe.py
+++ b/src/gridmarthe/gridmarthe.py
@@ -1,15 +1,35 @@
 #! /usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-import os, re
+import os
 from datetime import datetime
 
 import pandas as pd
 import numpy as np
 import xarray as xr #needs netcdf4
 
-from . import lecsem
-from .utils import _datetime64_to_float, _is_sorted
+from .lecsem import (
+    _lecsem,
+    _read_marthe_grid,
+    _transform_xcoords,
+    _transform_ycoords,
+    _set_layers,
+    _get_id_grid,
+    _get_col_and_lig,
+    _decode_title,
+    _parse_dims_from_xr_attrs,
+    _extract_zvar_from_ds,
+    scan_var,
+)
+
+
+from .utils import (
+    read_dates_from_pastp,
+    assign_coords,
+    stack_coords,
+    dropna,
+    fillna
+)
 
 from typing import Union
 
@@ -65,198 +85,69 @@
 }
 
 
-def read_dates_from_pastp(fpastp, encoding='ISO-8859-1'):
-    """Read simulation timesteps from a .pastp file
+
+def _parse_attrs(
+    title=None,
+    dims=None,
+    xyfactor=1.,
+    dates=None,
+    is_nested=False,
+    dxlus=None,
+    dylus=None,
+    xcols=None,
+    yligs=None
+):
+    """ Parse attributes for xarray.Dataset
+    nb: attrs must be string, int, float
     """
-    # reading file as raw df - not str ; faster with pandas func
-    pastp = pd.read_csv(
-        fpastp,
-        header=None,
-        encoding=encoding
-    ).squeeze('columns')
-
-    # First, get steady state time
-    idx_0  = pastp.loc[pastp.str.contains(r' \*\*\* D.*but de la simulation.*', regex=True)].index.values[0]
-    date_0 = re.findall(r'[0-9]+', pastp.iloc[idx_0] )
-    
-    # convert as DF
-    timesteps = pd.DataFrame([{
-        'timestep': 0, 
-        'date': datetime(int(date_0[2]), int(date_0[1]), int(date_0[0]) ) 
-    }])
-
-    # Then, get all ending times for transient state
-    idx  = pastp.loc[pastp.str.contains(r'^ \*\*\* Le pas.*\d+: se termine.*', regex=True)]
-    # extract dates from strings
-    dates= pd.DataFrame(
-        idx.str.findall(r'[0-9]+').to_list(),
-        columns=['timestep', 'day', 'month', 'year'],
-        #dtype={'timestep':int, 'day':int, 'month':int, 'year':int}
-    )
-    
-    # assign dtype
-    dates['timestep'] = pd.to_numeric(dates['timestep'])
+    prologue = {
+        'conventions'         :'CF-1.10', # check https://cfconventions.org/
+        'title'               : title if title is not None else '',
+        'marthe_grid_version' : 9.0,
+        'original_dimensions' : 'x,y,z [grids]: ' + '; '.join(
+            [ ' '.join(map(str, x)) for x in dims]
+        ),
+    }
 
-    # convert data as datetime object
-    dates['date'] = pd.to_datetime(dates[['day', 'month', 'year']])
-    dates = dates.drop(['month','year', 'day'], axis=1)
+    grid_attrs = {
+        'lon_resolution': ', '.join(map(str, np.unique(dxlus))),
+        'lat_resolution': ', '.join(map(str, np.unique(dylus))),
+        'scale_factor'  : xyfactor,
+        'nested_grid'   : str(is_nested),
+        'extend'        : "xymin : {} {}; xymax: {} {}".format(
+            np.min(xcols), np.min(yligs), np.max(xcols), np.max(yligs)
+        ),
+    }
+    dates_attrs = {}
+    if isinstance(dates, pd.DatetimeIndex):
+        dates_attrs = {
+            'period'    : '{}-{}'.format(
+                pd.to_datetime(dates.min()).year, pd.to_datetime(dates.max()).year
+            ), # force pd.date_time, case of pastp => numpydatetime64 / # np.datetime_as_string(i, unit='M')
+            'frequency' : '{} day(s)'.format(str(dates.to_series().diff().mean().days)),
+        }
     
-    return pd.concat([timesteps, dates], axis=0)
-
-
-def scan_var(xfile):
-    """ List all variables stored in a Marthe grid file """
-    var = lecsem.modgridmarthe.scan_typevar(xfile) # get a list of unique type_var that are in xfile
-    var = np.char.strip(np.char.decode(var, 'ISO-8859-1')) # decode byte array provided by f2py
-    var = var[var != ''] # get rid of empty element provided by fortran code
-    return var
+    epilogue = {
+        'creation_date' : 'Created on {}'.format(datetime.utcnow().strftime('%Y-%m-%dT%H:%M:%SZ UTC')),
+        'institution'   : 'BRGM, French Geological Survey, Orléans, France',
+        'comment'       : 'Hydrogeological model created with MARTHE code '\
+                          '(Thiery, D. 2020. Guidelines for MARTHE v7.8 computer code'\
+                          'for hydro-systems modelling. report BRGM/RP-69660-FR).'
+    }
 
-def _read_marthe_grid(xfile, varname='CHARGE', shallow_only=False):
-    """ Read a Marthe grid file
-    using fortran wrapper, for a specific variable
-    
-    Parameters
-    ----------
-    xfile: str
-        Filename to read
-    varname : str
-        string of variable in xfile to get values.
-        Default is CHARGE (groundwater head)
-    
-    Returns
-    -------
-    zvar  : np.array
-        variable read from marthe grid file as numpy ndarray (one vector)
-    zdates: np.array
-        array of dates (from start))
-    isteps: np.array
-        array of indexes of timesteps
-    zxcol : np.array
-        array of x coordinates
-    zylig : np.array
-        array of y coordinates
-    zdxlu : np.array
-        array of dx (equals np.diff(x))
-    zdylu : np.array
-        array of dy (equals np.diff(y))
-    ztitle: np.array
-        title of marthe grid file read
-    dims  : np.array
-        list of dimensions of grid [maingrid[x, y, z], nestedgrid1[...], ...]
-    """
-    nu_zoomx = lecsem.modgridmarthe.scan_nu_zoomx(xfile) # scan nb of nested grids (gig)
-    dims, nbsteps = lecsem.modgridmarthe.scan_dim(xfile, varname, nu_zoomx)
-    nbtot = np.prod(dims, axis=1).sum() # product deprecated => prod // DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead.
-    if nbtot == 0:
-        raise ValueError(f'Varname ({varname}) not found in xfile. No data to parse.')
-    
-    if shallow_only:
-        res = list(lecsem.modgridmarthe.read_grid_shallow( xfile, varname, nbsteps, dims[0][-1] ,nbtot, nu_zoomx ))
-    else:
-        res = list(lecsem.modgridmarthe.read_grid( xfile, varname, nbsteps, nbtot, nu_zoomx))
-    
-    res.append(dims)
-    return res
-
-
-def _transform_xcoords(zxcol, zylig, zdxlu, nlayer=1, factor=1):
-    xcols, dxlus = [], []
-    for igig in range(zxcol.shape[0]):
-        nb = np.extract(zylig[igig] != 1e+20, zylig[igig]).shape[0]
-        xcols2 = np.tile(zxcol[igig], nb)
-        xcols2 = np.extract(xcols2 != 1e+20, xcols2)
-        dxlus2 = np.tile(zdxlu[igig], nb)
-        dxlus2 = np.extract(dxlus2 != 1e+20, dxlus2)
-        if nlayer > 1:
-            # need to paste coords for multilayer to match dims of zvar
-            xcols2 = np.tile(xcols2, nlayer)
-            dxlus2 = np.tile(dxlus2, nlayer)
-        xcols.append(xcols2)
-        dxlus.append(dxlus2)
-    xcols = np.hstack(xcols)*factor
-    dxlus = np.hstack(dxlus)*factor
-    return xcols, dxlus
-
-def _transform_ycoords(zxcol, zylig, zdylu, nlayer=1, factor=1):
-    yligs, dylus = [], []
-    for igig in range(zylig.shape[0]):
-        yligs2, dylus2 = [], []
-        for i in range(len(zxcol[igig][zxcol[igig] != 1e+20])):
-            tmp1 = zylig[igig][zylig[igig] != 1e+20]
-            tmp2 = zdylu[igig][zdylu[igig] != 1e+20]
-            if nlayer > 1:
-                # need to paste coords for multilayer to match dims of zvar
-                tmp1 = np.tile(tmp1, nlayer)
-                tmp2 = np.tile(tmp2, nlayer)
-            yligs2.append(tmp1)
-            dylus2.append(tmp2)
-        yligs2 = np.vstack(yligs2).transpose().flatten()
-        dylus2 = np.vstack(dylus2).transpose().flatten()
-        yligs.append(yligs2)
-        dylus.append(dylus2)
-    yligs = np.hstack(yligs)*factor
-    dylus = np.hstack(dylus)*factor
-    return yligs, dylus
-
-def _set_layers(dims):
-    # add layer to match dim of zvar
-    zlay = []
-    for igig in range(len(dims)):
-        for z in range(dims[igig][-1]):
-            zlay.append(np.tile(z+1, dims[igig][0] * dims[igig][1]))
-    zlay = np.hstack(zlay)
-    return zlay
-
-def _decode_title(title, encoding='ISO-8859-1'):
-    title = title.decode(encoding)
-    title = re.search('(\D+)\s+Pas\s+\d+;', title)
-    if title is not None:
-        return title.group(1).strip()
-    else:
-        return None
-
-def _get_col_and_lig(dims):
-    """ Add col/lig indexes (i,j) """
-    # cols are xcoords index (x are sorted asc)
-    # ligs are ycoords index (y are sorted dsc)
-    # dims = [maingrid[x, y, z], gig[x, y, z], ...]
-    # cols and lig indexes are a range from 1 to len(x), for each grid. Same index col/lig, for every layer (z dim).
-    cols, ligs = [], []
-    for grid in dims:
-        zcols = np.arange(1, grid[0]+1)
-        zligs = np.arange(1, grid[1]+1) # lig 0 is max y ; max lig is min y.
-        # add res tiled on y and z dims, for xcols
-        cols = np.append(cols, np.tile(zcols, grid[-1] * grid[1]))
-        # for ylig, it's a bit different, we need to map ylig on shape of xcol for each ylig, then tile on z dim
-        # e.g. we need:
-        # [xcol] 1, 2, 3, 4, 5
-        # [ylig]   [ value ]
-        # 1,     1  1  1  1  1
-        # 2,     2  2  2  2  2
-        # 3,     ...
-        # but flattened, so: repeat ylig value on xcol size, then tile on z_dim size
-        ligs = np.append( ligs, np.tile( np.repeat(zligs, zcols.shape[0]), grid[-1] ) )
-    return cols.astype(np.int32), ligs.astype(np.int32)
-
-def _get_id_grid(dims):
-    # add id grid : 0 = main grid, >0 = nested grid(s)
-    id_grids = []
-    for igig in range(len(dims)):
-        id_grids.append(np.tile(igig, np.prod(dims[igig])))
-    id_grids = np.hstack(id_grids)
-    return id_grids
+    return {**prologue, **grid_attrs, **dates_attrs, **epilogue}
 
 
 
 def load_marthe_grid(
     filename: str,
     varname: Union[str, None] = None,
-    dates=None,
     fpastp: Union[str, None] = None,
+    dates=None,
     nanval: Union[int, float, None] = None,
     drop_nan: bool = False,
     xyfactor: Union[int, float] = 1.,
-    # shallow_only=False,
+    shallow_only=False,
     keepligcol: bool = False,
     add_id_grid: bool = False,
     title: Union[str, None] = None,
@@ -266,6 +157,7 @@ def load_marthe_grid(
         'projection'      : 'epsg:27572',
         'domain'          : 'FR-France',
     },
+    engine: str = 'xarray',
     verbose: bool=False,
 ):
     """ Read Marthe Grid File as xarray.Dataset 
@@ -293,14 +185,14 @@ def load_marthe_grid(
             All datavars are added to dataset, using recursive call to func
             if wrong variable name is passed, empty data will be returned.
         
+        fpastp: str, Optionnal
+            A pastp file to read for dates
+        
         dates: sequence, Optionnal
             Can be a pd.date_range, pd.Series, pd.DatetimeIndex, np.array or list of datetime/np.datetime objects.
             If no dates (or no fpastp) is provided, a fake sequence of dates from 1850 to 1900 will
             be used for xarray object
         
-        fpastp: str, Optionnal
-            A pastp file to read for dates
-        
         nanval: float, Optionnal
             A code value for nan values. Default is 9999.
         
@@ -312,6 +204,9 @@ def load_marthe_grid(
             factor to transform X and Y values. e.g.: 1000 to convert km XY to meters.
             Default is 1.
         
+        shallow_only: bool, Optionnal
+            Boolean to read only the first layer. Default is False.
+        
         keepligcol: bool, Optionnal
             Add columns (col) and rows (lig) index (from 1 to n), Default is False.
         
@@ -328,10 +223,18 @@ def load_marthe_grid(
         model_attrs: dict, Optionnal
             Dictionnary of attributes to add to Dataset.
             by default, gis attrs are added and can be modified
+            >>> {
             >>>    'resolution_units': 'm',
             >>>    'projection'      : 'epsg:27572',
-            >>>    'domain'          : 'FR-France',
+            >>>    'domain'          : 'FR-France'
+            >>> }
         
+        engine: str, Optionnal
+            Engine to use for returned object. Default is 'xarray', which return xarray.Dataset object.
+            Another option is 'numpy', which return a list of numpy arrays :
+            [zvar, zdates, isteps, zxcol, zylig, zdxlu, zdylu, ztitle, dims]
+
+
         verbose: bool, Optionnal
             Print some information about execution in stdout.
             Default is False.
@@ -359,14 +262,14 @@ def load_marthe_grid(
             # if no varname read from scan, it can be a bug (some version of marthe did not write field name in metadata)
             raise ValueError('No variable founded in file, please consider check file or clean it (cleanmgrid util or winmarthe)')
 
-    elif varname == 'all':
+    elif varname.lower() == 'all':
         varname  = scan_var(filename)
         # -- recursive call
         arrays = []
         for var in varname:
             arrays.append( load_marthe_grid(
-                filename, var, dates, fpastp, nanval, dropna, xyfactor,
-                keepligcol, add_id_grid, title, var_attrs, model_attrs, verbose
+                filename, var, fpastp, dates, nanval, drop_nan, xyfactor, shallow_only,
+                keepligcol, add_id_grid, title, var_attrs, model_attrs, engine, verbose
             ) )
         return xr.merge(arrays)
         
@@ -377,9 +280,16 @@ def load_marthe_grid(
     (
         zvar, zdates, isteps, zxcol,
         zylig, zdxlu, zdylu, ztitle, dims
-    ) = _read_marthe_grid(filename, varname) #, shallow_only=shallow_only)
+    ) = _read_marthe_grid(filename, varname, shallow_only=shallow_only)
+
+    if engine == 'numpy':
+        return [zvar, zdates, isteps, zxcol, zylig, zdxlu, zdylu, ztitle, dims]
     
     # --- transform data and parse into xarray.Dataset
+    if shallow_only:
+        print('NOT YET AVAILABLE')
+        # TODO shape (time, gig, values) -> (time, values)
+    
     if title is None:
         title = _decode_title(ztitle)
     
@@ -419,7 +329,7 @@ def load_marthe_grid(
     if dims[0][-1] > 1:
         zlus = _set_layers(dims)
         zattrs = {'units': '-', 'axis': 'Z', 'positive': 'down', 'standard_name': 'depth', 'long_name': 'aquifer_layer'} # not if full 3D ! TODO better
-        dic_data['z'] = ("zone", zlus, zattrs) # ajout lay
+        dic_data['z'] = ("zone", zlus, zattrs) # add lay
         
     if fpastp is not None:
         # add dates from a pastp file, case of non-uniform timesteps or edition not set every timestep
@@ -430,35 +340,22 @@ def load_marthe_grid(
         if verbose:
             print('Warning: No dates or fpastp provided, using default (fake) dates to constructed xarray object.')
         dates = pd.date_range('1850', '1900', len(isteps))
-    
-    
+        # dates = np.arange(1, len(isteps)+1) # TODO use integers for time is no dates provided ?
+
+    # --- Create xarray.Dataset object
     ds = xr.Dataset(
         data_vars=dic_data,
         coords={
             'time': dates,
             'zone': range(1, zvar.shape[1] + 1),
-            # 'x': (['zone'], xcols),
-            # 'y': (['zone'], yligs),
+            # 'xc': (['zone'], xcols), # TODO coordinates directly as coords depending on dims ?
+            # 'yc': (['zone'], yligs),
             # 'domain_size': dims, # add non dimension coordinate for info
             # 'domain_origin': [(x0, y0) for igig in grids], # add non dimension coordinate for info
         },
         attrs={
-            # attrs must be string, int, float
-            'conventions'         :'CF-1.10', # check https://cfconventions.org/
-            'title'               : title if title is not None else '',
-            'marthe_grid_version' : 9.0,
-            'original_dimensions' : 'x,y,z [grids]: ' + '; '.join([ ' '.join(map(str, x)) for x in dims]),
-            'lon_resolution'      : ', '.join(map(str, np.unique(dxlus))),
-            'lat_resolution'      : ', '.join(map(str, np.unique(dylus))),
-            'scale_factor'        : xyfactor,
-            'nested_grid'         : str(is_nested),
-            'extend'              : "xymin : {} {}; xymax: {} {}".format(np.min(xcols), np.min(yligs), np.max(xcols), np.max(yligs)),
-            'frequency'           : '{} day(s)'.format(str(dates.to_series().diff().mean().days)),
-            'period'              : '{}-{}'.format(pd.to_datetime(dates.min()).year, pd.to_datetime(dates.max()).year), # force pd.date_time, case of pastp => numpydatetime64 / # np.datetime_as_string(i, unit='M')
-            'creation_date'       : 'Created on {}'.format(datetime.utcnow().strftime('%Y-%m-%dT%H:%M:%SZ UTC')),
-            'institution'         : 'BRGM, French Geological Survey, Orléans, France',
-            'comment'             : 'Hydrogeological model created with MARTHE code (Thiery, D. 2020. Guidelines for MARTHE v7.8 computer code for hydro-systems modelling. report BRGM/RP-69660-FR).',
-            **model_attrs,
+            **_parse_attrs(title, dims, xyfactor, dates, is_nested, dxlus, dylus, xcols, yligs),
+            **model_attrs
         }
     )
     
@@ -474,103 +371,6 @@ def load_marthe_grid(
     return ds
 
 
-def dropna(ds, varname: str, nanval: Union[list, float]):
-    """ Drop values corrresponding to NaN (marthe convention, eg. code 9999.) 
-    for 1D (or 2D (time, zone)) array
-    zone must me a coordinate dimension.
-    
-    Returns
-    -------
-    dataset where variable != nanval
-    """
-    if isinstance(nanval, (float, int, str)):
-        nanval = [nanval]
-    # mask = ds[varname.lower()].where(ds[varname.lower()] != nanval).dropna(dim='zone') # drop nanval
-    mask = ds[varname.lower()].where(~ds[varname.lower()].isin(nanval)).dropna(dim='zone') # drop nanval
-    ds_no_nan = ds.sel(zone=mask['zone'])
-    return ds_no_nan
-
-def subset(ds, varname: str, value: Union[list, float]):
-    """ Subset dataset based on variable name and value.
-    --> inverse of :py:func:`dropna`
-    
-    Returns
-    -------
-    dataset where variable = value
-    """
-    if isinstance(value, (float, int, str)):
-        value = [value]
-    mask = ds[varname.lower()].where(ds[varname.lower()].isin(value)).dropna(dim='zone')
-    ds_filter = ds.sel(zone=mask['zone'])
-    return ds_filter
-
-def replace(ds, varname: str, value: float, replace: float):
-    """ Replace a value in xr.Dataset for a variable
-    """
-    ds[varname].data = np.where(ds[varname].data == value, replace, ds[varname].data)
-    return ds
-    
-def fillna(ds, varname, value):
-    """ Replace real nan (np.nan) value in dataset[varname], edge case of :py:func:`replace()`
-    """
-    ds[varname].data = np.where(np.isnan(ds[varname].data), value, ds[varname].data)
-    return ds
-
-
-def assign_coords(da_in, add_lay=True, coords=['x', 'y', 'z'], keep_zone=False, zone_label='zone'):
-    """ assign coords to transform a 1D or 2D (time, zone) array to 3D or 4D
-    """
-    if len(coords) == 3:
-        z_coords = da_in.get(coords[2], None) # assert z is here, or bypass
-    else:
-        z_coords = None
-    
-    if add_lay is False:
-        # in some case, even if z is included it should not be treated as coord (ex. plot outcrop)
-        z_coords = None
-    
-    da = da_in.assign_coords(
-        #x=(zone_label, np.around(da_in[coords[0]].data, 1) ),
-        x=(zone_label, da_in[coords[0]].data ),
-        y=(zone_label, da_in[coords[1]].data ),
-    )
-    dims = ['y', 'x']
-    
-    if z_coords is not None:
-        da = da.assign_coords(z=(zone_label, da_in[coords[2]].data))
-        dims.insert(0, 'z')
-    
-    da = da.set_index(zone=dims)
-    if not keep_zone:
-        da = da.drop_duplicates(zone_label).unstack(zone_label) # drop duplicates is a security for nested grids, if dropnan was not performed
-    return da.sortby(dims)
-
-
-def stack_coords(ds, coords=['z', 'y', 'x'], dropna=False):
-    """ Transform a 3 or 4D aray into 1 or 2D array 
-    inverse of  :py:func:`assign_coords`
-    """
-    # create zone index
-    coords = [d for d in coords if d in ds.coords.keys()] # make sure to drop coords that are not present
-    dims = np.prod( [len(ds[d]) for d in coords] ) # create new zone dim
-    zone = np.arange(dims)
-    
-    # stack coords
-    ds2 = ds.copy().stack(zone=coords) # multiindex zone grouping coords key
-    
-    # keep only zone as dim
-    ds3 = ds2.drop_vars(['zone'] + coords).assign_coords(zone=('zone', zone))
-    
-    # get back xy[z] as var
-    for c in coords:
-        ds3[c] = ('zone', ds2[c].data)
-    
-    if dropna:
-        ds3 = ds3.dropna(dim='zone')
-    return ds3
-
-
-
 def reset_geometry(ds, path_to_permh: str, variable='permeab', fillna=False):
     """ Reset a Marthe grid geometry based on permh dataset
     All values (nan, nested grid margins) should be included in
@@ -633,39 +433,6 @@ def reset_geometry(ds, path_to_permh: str, variable='permeab', fillna=False):
 
 
 
-def _parse_dims(str_dims):
-    if str_dims is None:
-        return None
-    else:
-        return [list(map(int, x.split(' '))) for x in str_dims.strip('x, y, z [grids]: ').split('; ')]
-
-
-# def sort_data(ds):
-    # TODO:
-    # s'assurer de l'ordre si ds a été retravaillé :
-        # order by z, y, x, dx
-    # extraire les x, y, dx, dy selon dims = pas de doublons
-    # print('not yet available')
-
-def _extract_zvar(ds, varname):
-    
-    zvar    = ds[varname].data
-    zdates  = ds.time.data
-    zxcol   = ds.x.data
-    zylig   = ds.y.data
-    zdxlu   = ds.dx.data
-    zdylu   = ds.dy.data
-    # from pymarthe : dx, dy = map(abs, map(np.gradient, [xcc,ycc])) # Using the absolute gradient TODO
-    ztitle  = ds.attrs.get('title')
-    izdates = _datetime64_to_float(zdates)
-
-    return (
-        zvar, zdates,
-        zxcol, zylig, zdxlu, zdylu,
-        ztitle, izdates
-    )
-
-
 def write_marthe_grid(ds, fileout='grid.out', varname='charge', file_permh: str = None, title=None, dims=None, debug=False):
     """ Write Dataset as MartheGrid v9 file
     
@@ -725,7 +492,7 @@ def write_marthe_grid(ds, fileout='grid.out', varname='charge', file_permh: str
     ds2 = ds.copy()
     
     if dims is None:
-        dims = _parse_dims(ds2.attrs.get('original_dimensions'))
+        dims = _parse_dims_from_xr_attrs(ds2.attrs.get('original_dimensions'))
     
     if dims is None:
         raise ValueError("""Original dimensions cannot be None.\
@@ -753,13 +520,13 @@ def write_marthe_grid(ds, fileout='grid.out', varname='charge', file_permh: str
         zvar, zdates,
         zxcol, zylig, zdxlu, zdylu,
         ztitle, izdates
-    ) = _extract_zvar(ds2, varname)
+    ) = _extract_zvar_from_ds(ds2, varname)
     
     if title is None and ztitle == '':
         title = 'Marthe Grid ' # dummy arg to set type as string
     
     # call fortran module to write marthe grid
-    status = lecsem.modgridmarthe.write_grid(
+    status = _lecsem.modgridmarthe.write_grid(
         xvar=zvar,
         xcol=zxcol,
         ylig=zylig,
@@ -784,10 +551,3 @@ def write_marthe_grid(ds, fileout='grid.out', varname='charge', file_permh: str
     
     return status 
 
-
-
-if __name__ == '__main__':
-    
-    print(lecsem.__doc__)
-    print(lecsem.modgridmarthe.__doc__)
-    
diff --git a/src/gridmarthe/lecsem/__init__.py b/src/gridmarthe/lecsem/__init__.py
index 5712458..95ff588 100644
--- a/src/gridmarthe/lecsem/__init__.py
+++ b/src/gridmarthe/lecsem/__init__.py
@@ -1 +1,14 @@
-from .lecsem import *
+from ._parse_gridmarthe import (
+    _lecsem,
+    _read_marthe_grid,
+    _transform_xcoords,
+    _transform_ycoords,
+    _set_layers,
+    _get_id_grid,
+    _get_col_and_lig,
+    _decode_title,
+    _extract_zvar_from_ds,
+    _parse_dims_from_xr_attrs,
+    scan_var,
+)
+
diff --git a/src/gridmarthe/lecsem/_parse_gridmarthe.py b/src/gridmarthe/lecsem/_parse_gridmarthe.py
new file mode 100644
index 0000000..15c7a43
--- /dev/null
+++ b/src/gridmarthe/lecsem/_parse_gridmarthe.py
@@ -0,0 +1,200 @@
+#! /usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import re
+import numpy as np
+
+from . import lecsem as _lecsem
+
+from ..utils import _datetime64_to_float
+
+
+
+def scan_var(xfile):
+    """ List all variables stored in a Marthe grid file """
+    var = _lecsem.modgridmarthe.scan_typevar(xfile) # get a list of unique type_var that are in xfile
+    var = np.char.strip(np.char.decode(var, 'ISO-8859-1')) # decode byte array provided by f2py
+    var = var[var != ''] # get rid of empty element provided by fortran code
+    return var
+
+
+def _read_marthe_grid(xfile, varname='CHARGE', shallow_only=False):
+    """ Read a Marthe grid file
+    using fortran wrapper, for a specific variable
+    
+    Parameters
+    ----------
+    xfile: str
+        Filename to read
+    varname : str
+        string of variable in xfile to get values.
+        Default is CHARGE (groundwater head)
+    
+    Returns
+    -------
+    zvar  : np.array
+        variable read from marthe grid file as numpy ndarray (one vector)
+    zdates: np.array
+        array of dates (from start))
+    isteps: np.array
+        array of indexes of timesteps
+    zxcol : np.array
+        array of x coordinates
+    zylig : np.array
+        array of y coordinates
+    zdxlu : np.array
+        array of dx (equals np.diff(x))
+    zdylu : np.array
+        array of dy (equals np.diff(y))
+    ztitle: np.array
+        title of marthe grid file read
+    dims  : np.array
+        list of dimensions of grid [maingrid[x, y, z], nestedgrid1[...], ...]
+    """
+    nu_zoomx = _lecsem.modgridmarthe.scan_nu_zoomx(xfile) # scan nb of nested grids (gig)
+    dims, nbsteps = _lecsem.modgridmarthe.scan_dim(xfile, varname, nu_zoomx)
+    nbtot = np.prod(dims, axis=1).sum() # product deprecated => prod // DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead.
+    if nbtot == 0:
+        raise ValueError(f'Varname ({varname}) not found in xfile. No data to parse.')
+    
+    if shallow_only:
+        res = list(_lecsem.modgridmarthe.read_grid_shallow( xfile, varname, nbsteps, dims[0][-1] ,nbtot, nu_zoomx ))
+    else:
+        res = list(_lecsem.modgridmarthe.read_grid( xfile, varname, nbsteps, nbtot, nu_zoomx))
+    
+    res.append(dims)
+    return res
+
+
+def _transform_xcoords(zxcol, zylig, zdxlu, nlayer=1, factor=1):
+    xcols, dxlus = [], []
+    for igig in range(zxcol.shape[0]):
+        nb = np.extract(zylig[igig] != 1e+20, zylig[igig]).shape[0]
+        xcols2 = np.tile(zxcol[igig], nb)
+        xcols2 = np.extract(xcols2 != 1e+20, xcols2)
+        dxlus2 = np.tile(zdxlu[igig], nb)
+        dxlus2 = np.extract(dxlus2 != 1e+20, dxlus2)
+        if nlayer > 1:
+            # need to paste coords for multilayer to match dims of zvar
+            xcols2 = np.tile(xcols2, nlayer)
+            dxlus2 = np.tile(dxlus2, nlayer)
+        xcols.append(xcols2)
+        dxlus.append(dxlus2)
+    xcols = np.hstack(xcols)*factor
+    dxlus = np.hstack(dxlus)*factor
+    return xcols, dxlus
+
+
+def _transform_ycoords(zxcol, zylig, zdylu, nlayer=1, factor=1):
+    yligs, dylus = [], []
+    for igig in range(zylig.shape[0]):
+        yligs2, dylus2 = [], []
+        for i in range(len(zxcol[igig][zxcol[igig] != 1e+20])):
+            tmp1 = zylig[igig][zylig[igig] != 1e+20]
+            tmp2 = zdylu[igig][zdylu[igig] != 1e+20]
+            if nlayer > 1:
+                # need to paste coords for multilayer to match dims of zvar
+                tmp1 = np.tile(tmp1, nlayer)
+                tmp2 = np.tile(tmp2, nlayer)
+            yligs2.append(tmp1)
+            dylus2.append(tmp2)
+        yligs2 = np.vstack(yligs2).transpose().flatten()
+        dylus2 = np.vstack(dylus2).transpose().flatten()
+        yligs.append(yligs2)
+        dylus.append(dylus2)
+    yligs = np.hstack(yligs)*factor
+    dylus = np.hstack(dylus)*factor
+    return yligs, dylus
+
+
+def _set_layers(dims):
+    # add layer to match dim of zvar
+    zlay = []
+    for igig in range(len(dims)):
+        for z in range(dims[igig][-1]):
+            zlay.append(np.tile(z+1, dims[igig][0] * dims[igig][1]))
+    zlay = np.hstack(zlay)
+    return zlay
+
+
+def _decode_title(title, encoding='ISO-8859-1'):
+    title = title.decode(encoding)
+    title = re.search(r'(\D+)\s+Pas\s+\d+;', title)
+    if title is not None:
+        return title.group(1).strip()
+    else:
+        return None
+
+
+def _get_col_and_lig(dims):
+    """ Add col/lig indexes (i,j) """
+    # cols are xcoords index (x are sorted asc)
+    # ligs are ycoords index (y are sorted dsc)
+    # dims = [maingrid[x, y, z], gig[x, y, z], ...]
+    # cols and lig indexes are a range from 1 to len(x), for each grid. Same index col/lig, for every layer (z dim).
+    cols, ligs = [], []
+    for grid in dims:
+        zcols = np.arange(1, grid[0]+1)
+        zligs = np.arange(1, grid[1]+1) # lig 0 is max y ; max lig is min y.
+        # add res tiled on y and z dims, for xcols
+        cols = np.append(cols, np.tile(zcols, grid[-1] * grid[1]))
+        # for ylig, it's a bit different, we need to map ylig on shape of xcol for each ylig, then tile on z dim
+        # e.g. we need:
+        # [xcol] 1, 2, 3, 4, 5
+        # [ylig]   [ value ]
+        # 1,     1  1  1  1  1
+        # 2,     2  2  2  2  2
+        # 3,     ...
+        # but flattened, so: repeat ylig value on xcol size, then tile on z_dim size
+        ligs = np.append( ligs, np.tile( np.repeat(zligs, zcols.shape[0]), grid[-1] ) )
+    return cols.astype(np.int32), ligs.astype(np.int32)
+
+
+def _get_id_grid(dims):
+    # add id grid : 0 = main grid, >0 = nested grid(s)
+    id_grids = []
+    for igig in range(len(dims)):
+        id_grids.append(np.tile(igig, np.prod(dims[igig])))
+    id_grids = np.hstack(id_grids)
+    return id_grids
+
+
+def _parse_dims_from_xr_attrs(str_dims):
+    if str_dims is None:
+        return None
+    else:
+        return [list(map(int, x.split(' '))) for x in str_dims.strip('x, y, z [grids]: ').split('; ')]
+
+# def sort_data(ds):
+    # TODO:
+    # s'assurer de l'ordre si ds a été retravaillé :
+        # order by z, y, x, dx
+    # extraire les x, y, dx, dy selon dims = pas de doublons
+    # print('not yet available')
+
+
+def _extract_zvar_from_ds(ds, varname):
+    
+    zvar    = ds[varname].data
+    zdates  = ds.time.data
+    zxcol   = ds.x.data
+    zylig   = ds.y.data
+    zdxlu   = ds.dx.data
+    zdylu   = ds.dy.data
+    # from pymarthe : dx, dy = map(abs, map(np.gradient, [xcc,ycc])) # Using the absolute gradient TODO
+    ztitle  = ds.attrs.get('title')
+    izdates = _datetime64_to_float(zdates)
+
+    return (
+        zvar, zdates,
+        zxcol, zylig, zdxlu, zdylu,
+        ztitle, izdates
+    )
+
+
+if __name__ == '__main__':
+    
+    print(_lecsem.__doc__)
+    print(_lecsem.modgridmarthe.__doc__)
+    
+
diff --git a/src/gridmarthe/operasem.py b/src/gridmarthe/operasem.py
deleted file mode 100644
index a543b26..0000000
--- a/src/gridmarthe/operasem.py
+++ /dev/null
@@ -1,261 +0,0 @@
-#! /usr/bin/env python3
-# -*- coding: utf-8 -*-
-
-import pandas as pd
-import numpy as np
-import xarray as xr #needs netcdf4, rioxarray
-
-from shapely.geometry import Polygon
-import geopandas as gpd
-
-from .utils import _get_scale, _nearest_node
-
-"""
-Some useful functions to manage MartheGrid in python
-"""
-# TODO:   add functions available in winmarthe or operasem.
-#         eg. get_layer_depths(), get_layer_thickness(),
-#         get_runoff_direction(), remove_layer(), remove_nested(), etc.
-
-# -------------------------------------------------------- #
-#  Operation on Marthe Grids (semis, marthe easter eggs).  #
-# -------------------------------------------------------- #
-
-def get_new_coords(ds, res=1000):
-    """ Reset xy with a range from min to max, with res as step"""
-    xmin, xmax = np.min(ds.x).values, np.max(ds.x).values
-    ymin, ymax = np.min(ds.y).values, np.max(ds.y).values
-    
-    new_x = np.arange(xmin, xmax+res, res)
-    new_y = np.arange(ymin, ymax+res, res)
-    
-    return new_x, new_y
-
-def coarse_nested_grid(da, varname='charge', dx=None, dy=None):
-    """ Coarse nested grid to res of main grid
-    only realy valid if nested grid resolution is a multiple of maingrid resolution
-    coords needs to be assign first
-    """
-    if dx is None or dy is None:
-        dx, dy = _get_scale(da)
-    dx1, dy1 = dx.pop(0), dy.pop(0)
-    grid = da.where(da['dx'] == dx1, drop=True) # & da['dy'] == dy1
-    for dx2, dy2 in zip(dx, dy):
-        gig = da.where(da['dx'] == dx2, drop=True)
-        gig = gig[varname].coarsen(x=int(dx1/dx2), y=int(dy1/dy2), boundary='trim').mean()
-        grid = xr.combine_by_coords([grid, gig])
-    return grid
-
-def interp_grid(da, new_x=None, new_y=None, method='nearest', **kwargs):
-    """ Interpolate on a new grid using `xarray.Dataset.interp`
-
-    Parameters
-    ----------
-    da: xr.Dataset
-        the input dataset to interpolate on new coordinates.
-    new_x: array-like
-        the new x-axis coordinate to use
-    new_y: array-like
-        the new y-axis coordinate to use
-    method: str, Optionnal (default='nearest')
-        `xr.Dataset.interp` method to use. Default is 'nearest'
-    **kwargs: dict, Optionnal.
-        Any keywords argument to pass to `xr.Dataset.interp`.
-    
-    Returns
-    -------
-        interpolated xr.Dataset
-    """
-    # https://docs.xarray.dev/en/stable/user-guide/interpolation.html
-    # https://earth-env-data-science.github.io/lectures/xarray/xarray-part2.html
-    if new_x is None or new_y is None:
-        new_x = np.linspace(da['x'][0], da['x'][-1], int(da['x'].size / 2) ) # da.dims["lat"]
-        new_y = np.linspace(da['y'][0], da['y'][-1], int(da['y'].size / 2) )
-    return da.interp(x=new_x, y=new_y, method=method, **kwargs)
-
-def rescale(da, res=1000, **kwargs):
-    """ Wrapper function that uses `get_new_coords()` and `interp_grid()` together
-    
-    See also
-    --------
-    `get_new_coords`
-    `interp_grid`
-    """
-    new_x, new_y = get_new_coords(da, res)
-    new_da = interp_grid(da, new_x, new_y, **kwargs) # here da with assign coords
-    return new_da
-
-def get_min_layer(ds, aquif_layers=None):
-    """ Compute surface mask of marthe domain
-    
-    This function return min layer for every zone of a grimarthe dataset with z coords
-    A subset on specific (aquifers) layers can be performed with `aquif_layers`.
-    if set, aquif_layers must be a sequence (list, tuple, array) of layer (list of int).
-    
-    This should be used to get a surface mask, ie get zone to filter a dataset.
-    
-    Examples
-    --------
-    >>>    mask = get_min_layer(ds, [6,8,9])
-    >>>    ds_surf = ds.sel(zone=mask.zone.data)
-        
-    Parameters
-    ----------
-        ds: xr.Dataset
-        aquif_layers: sequence (list, tuple, array) of int
-            representing layers to subset ds
-    Returns
-    -------
-        surface_mask: xr.Dataset
-    """
-    df = ds.to_dataframe()
-    df = df.reset_index()
-    
-    if aquif_layers is not None:
-        df = df[df['z'].isin(aquif_layers)]
-    
-    idx_z_min = df.groupby(['x', 'y', 'time']).z.idxmin() # get index of min z ("layer") for each x,y,t groups
-    first_aquif_lay = df.loc[idx_z_min].reset_index().set_index('zone').drop('index', axis=1)
-    # time not needed here, zone are independant from time coords
-    return first_aquif_lay.to_xarray()
-
-
-def get_mask(ds, varname: str='permeab', nanval: list=[-9999., 0.], fileout: str='mask.shp'):
-    """ Filter dataset on non-nan values, and dissolve results to get a mask shape 
-    input ds should be the permh dataset (read from permh file, ie Horizontal hydraulic conductivity)
-    """
-    mask = ds.where(~ds[varname].isin(nanval), drop=True)
-    mask = ds.sel(zone=mask['zone'])
-    gdf  = to_geodataframe(mask)
-    gdf  = gdf.dissolve()
-    gdf.to_file(fileout)
-    return gdf
-
-
-def search_zone(ds, i=None, j=None, x=None, y=None, z=None):
-    """ search zone number in marthe grid,
-    based on xy or ij (col, lig)
-    
-    if ds is multilayered, you need to provide the layer you want (int)
-    ds should contains dx and dy
-    ds should not have assigned coords (x and y are variables, zone is the dimension coordinates (with time))
-    """
-    ds_search = ds.copy()
-    
-    if z is not None:
-        ds_search = ds_search.where(ds_search.z == z, drop=True)
-
-    if x is not None:
-        assert y is not None, 'if x is provided, y cannot be None'
-        ## mask = ds.sel(x=x, y=y, method='nearest') # possible uniquement si x,y sont des coordonnées/dim
-        nearest = _nearest_node(np.array([(x, y)]), np.array(list(zip(ds_search['x'].data, ds_search['y'].data))))
-        nearest_zone = ds_search.isel(zone=nearest)
-        
-        # check if xy is in a cell == dx and dy are not greater than grid resolution
-        dx = np.abs(nearest_zone.x.data - x)
-        dy = np.abs(nearest_zone.y.data - y)
-        mask = ds_search['zone'] == nearest_zone.zone if (dx <= nearest_zone.dx.data) & (dy <= nearest_zone.dy.data) else ds_search['zone'].isnull()
-
-    if i is not None:
-        assert j is not None, 'if i is provided, j cannot be None'
-        mask = (ds_search['col'] == i) & (ds_search['lig'] == j)
-
-    # zone = ds.where(mask, drop=True)['zone'].data
-    zone = ds_search.where(mask, drop=True)
-    return zone
-
-# -------------------------------------------------------- #
-#                      GIS Functions                       #
-# -------------------------------------------------------- #
-
-def subset_with_coords(da, dims=['x', 'y'], gdf=None, xmin=None, ymin=None, xmax=None, ymax=None):
-    """
-    subset DataArray or Dataset with gpd.GeoDataFrame or bounds
-    TODO: real shp clip
-    """
-    if gdf is not None:
-        # edit, one line with total_bounds attribute instead of bounds
-        # xmin, ymin, xmax, ymax = gdf.bounds.T.values # or .T.to_numpy(), in any case return np.array // total_bounds instead of bounds
-        # xmin, ymin, xmax, ymax = xmin[0], ymin[0], xmax[0], ymax[0]
-        xmin, ymin, xmax, ymax = gdf.total_bounds #gdf.bounds.T.values # or .T.to_numpy(), in any case return np.array // total_bounds instead of bounds
-    else:
-        assert xmin is not None, "When using manual bounds, all must be set"
-        assert xmax is not None, "When using manual bounds, all must be set"
-        assert ymin is not None, "When using manual bounds, all must be set"
-        assert ymax is not None, "When using manual bounds, all must be set"
-    
-    mask_lon = ( da[dims[0]] >= xmin) & ( da[dims[0]] <= xmax) #da.xc
-    mask_lat = ( da[dims[1]] >= ymin) & ( da[dims[1]] <= ymax)
-    
-    # imin, imax = np.where(da[var[0]].values==xmin)[0], np.where(da[var[0]].values==xmax)[0]
-    # jmin, jmax = np.where(da[var[1]].values==ymin)[0], np.where(da[var[1]].values==ymax)[0]
-
-    # sub_da = da.isel(i=slice(int(imin), int(imax)+1), j=slice(int(jmax), int(jmin)+1)) # j in reverse order / +1 on imax, jmin because upper is exclude in py slicing
-    
-    return da.where(mask_lon & mask_lat, drop=True)
-
-
-def _mk_cell_polygon(xleft, ylower, xright, yupper):
-    return Polygon(
-        (
-            (xleft , ylower),
-            (xright, ylower),
-            (xright, yupper),
-            (xleft , yupper),
-            (xleft , ylower)
-        )
-    )
-
-_polygonize = np.vectorize(_mk_cell_polygon)
-
-
-def _build_polyg(ds):
-    """ build a (rectangular) polygon shape from marthegrid dataset """
-    
-    x0 = ds.x.values - (ds.dx.values / 2.)
-    y0 = ds.y.values - (ds.dy.values / 2.)
-    x1 = ds.x.values + (ds.dx.values / 2.)
-    y1 = ds.y.values + (ds.dy.values / 2.)
-    
-    return _polygonize(x0, y0, x1, y1)
-
-
-def to_geodataframe(ds, epsg='EPSG:27572', fmt='long'):
-    """ Convert marthegrid.Dataset to a geodataframe 
-    fmt must be long or wide, default is long
-    """
-    
-    polygons = _build_polyg(ds.isel(time=0))
-    df = ds.to_dataframe() #.to_pandas() # only for 1 dim
-    
-    if 'time' in ds.dims.keys():
-        polygons = np.tile(polygons.flatten(), len(np.unique(df.index.get_level_values('time')))) # ad geom for every timestep
-    
-    gdf = gpd.GeoDataFrame(
-        df,
-        geometry=polygons,
-        crs=epsg
-    )
-    
-    if fmt == "wide":
-        # here no wide fmt if no time, so no if 'time' in ds.dims.keys():
-        gdf = gdf.unstack('time')
-        gdf.columns = [
-            '{}_{}'.format(x, y.strftime('%Y%m%d'))\
-            if x not in ['x', 'y', 'dx', 'dy', 'z', 'geometry'] else x\
-            for x, y in gdf.columns
-        ]
-        gdf = gdf.loc[:,~gdf.columns.duplicated()].copy() # drop duplicated cols
-        gdf = gdf.set_geometry('geometry') # need to make again geom after drop dupl
-    
-    return gdf
-
-def write_raster_from_da(da, x_dim='x', y_dim='y', epsg=27572, fout='raster.tiff'):
-    """ Write a xr.DataArray to a raster file
-    need xarray with rioxarray installed
-    """
-    da = da.copy().rio.write_crs('epsg:{}'.format(epsg))
-    da = da.rio.set_spatial_dims(x_dim=x_dim, y_dim=y_dim)
-    da.rio.to_raster(fout)
-    return None
-
diff --git a/src/gridmarthe/operasem/gis.py b/src/gridmarthe/operasem/gis.py
new file mode 100644
index 0000000..8fe95f1
--- /dev/null
+++ b/src/gridmarthe/operasem/gis.py
@@ -0,0 +1,117 @@
+#! /usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import numpy as np
+
+from shapely.geometry import Polygon
+import geopandas as gpd
+
+from pyproj import Transformer
+
+
+
+def transf_proj(ds, from_epsg="EPSG:2154", to_epsg="EPSG:27572"):
+    """ Transform coordinates of a dataset using pyproj.
+    """
+    transformer = Transformer.from_crs(from_epsg, to_epsg, always_xy=True)
+    x_source, y_source = ds.x.data, ds.y.values
+    x_target, y_target = transformer.transform(x_source, y_source)
+    ds = ds.copy()
+    ds['x'], ds['y'] = x_target, y_target
+    return ds
+
+
+
+def _mk_cell_polygon(xleft, ylower, xright, yupper):
+    return Polygon(
+        (
+            (xleft , ylower),
+            (xright, ylower),
+            (xright, yupper),
+            (xleft , yupper),
+            (xleft , ylower)
+        )
+    )
+
+_polygonize = np.vectorize(_mk_cell_polygon)
+
+
+def _build_polyg(ds):
+    """ build a (rectangular) polygon shape from marthegrid dataset """
+    
+    x0 = ds.x.values - (ds.dx.values / 2.)
+    y0 = ds.y.values - (ds.dy.values / 2.)
+    x1 = ds.x.values + (ds.dx.values / 2.)
+    y1 = ds.y.values + (ds.dy.values / 2.)
+    
+    return _polygonize(x0, y0, x1, y1)
+
+
+def to_geodataframe(ds, epsg='EPSG:27572', fmt='long'):
+    """ Convert marthegrid.Dataset to a geodataframe 
+    fmt must be long or wide, default is long
+    """
+    
+    polygons = _build_polyg(ds.isel(time=0))
+    df = ds.to_dataframe() #.to_pandas() # only for 1 dim
+    
+    if 'time' in ds.dims.keys():
+        polygons = np.tile(polygons.flatten(), len(np.unique(df.index.get_level_values('time')))) # ad geom for every timestep
+    
+    gdf = gpd.GeoDataFrame(
+        df,
+        geometry=polygons,
+        crs=epsg
+    )
+    
+    if fmt == "wide":
+        # here no wide fmt if no time, so no if 'time' in ds.dims.keys():
+        gdf = gdf.unstack('time')
+        gdf.columns = [
+            '{}_{}'.format(x, y.strftime('%Y%m%d'))\
+            if x not in ['x', 'y', 'dx', 'dy', 'z', 'geometry'] else x\
+            for x, y in gdf.columns
+        ]
+        gdf = gdf.loc[:,~gdf.columns.duplicated()].copy() # drop duplicated cols
+        gdf = gdf.set_geometry('geometry') # need to make again geom after drop dupl
+    
+    return gdf
+
+
+def subset_with_coords(da, dims=['x', 'y'], gdf=None, xmin=None, ymin=None, xmax=None, ymax=None):
+    """
+    subset DataArray or Dataset with gpd.GeoDataFrame or bounds
+    TODO: real shp clip
+    """
+    if gdf is not None:
+        # edit, one line with total_bounds attribute instead of bounds
+        # xmin, ymin, xmax, ymax = gdf.bounds.T.values # or .T.to_numpy(), in any case return np.array // total_bounds instead of bounds
+        # xmin, ymin, xmax, ymax = xmin[0], ymin[0], xmax[0], ymax[0]
+        xmin, ymin, xmax, ymax = gdf.total_bounds #gdf.bounds.T.values # or .T.to_numpy(), in any case return np.array // total_bounds instead of bounds
+    else:
+        assert xmin is not None, "When using manual bounds, all must be set"
+        assert xmax is not None, "When using manual bounds, all must be set"
+        assert ymin is not None, "When using manual bounds, all must be set"
+        assert ymax is not None, "When using manual bounds, all must be set"
+    
+    mask_lon = ( da[dims[0]] >= xmin) & ( da[dims[0]] <= xmax) #da.xc
+    mask_lat = ( da[dims[1]] >= ymin) & ( da[dims[1]] <= ymax)
+    
+    # imin, imax = np.where(da[var[0]].values==xmin)[0], np.where(da[var[0]].values==xmax)[0]
+    # jmin, jmax = np.where(da[var[1]].values==ymin)[0], np.where(da[var[1]].values==ymax)[0]
+
+    # sub_da = da.isel(i=slice(int(imin), int(imax)+1), j=slice(int(jmax), int(jmin)+1)) # j in reverse order / +1 on imax, jmin because upper is exclude in py slicing
+    
+    return da.where(mask_lon & mask_lat, drop=True)
+
+
+
+def write_raster_from_da(da, x_dim='x', y_dim='y', epsg=27572, fout='raster.tiff'):
+    """ Write a xr.DataArray to a raster file
+    need xarray with rioxarray installed
+    """
+    da = da.copy().rio.write_crs('epsg:{}'.format(epsg))
+    da = da.rio.set_spatial_dims(x_dim=x_dim, y_dim=y_dim)
+    da.rio.to_raster(fout)
+    return None
+
diff --git a/src/gridmarthe/operasem/interp.py b/src/gridmarthe/operasem/interp.py
new file mode 100644
index 0000000..50ac24f
--- /dev/null
+++ b/src/gridmarthe/operasem/interp.py
@@ -0,0 +1,76 @@
+#! /usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import numpy as np
+import xarray as xr #needs netcdf4, rioxarray
+
+from ..utils import _get_scale
+
+
+def get_new_coords(ds, res=1000):
+    """ Reset xy with a range from min to max, with res as step"""
+    xmin, xmax = np.min(ds.x).values, np.max(ds.x).values
+    ymin, ymax = np.min(ds.y).values, np.max(ds.y).values
+    
+    new_x = np.arange(xmin, xmax+res, res)
+    new_y = np.arange(ymin, ymax+res, res)
+    
+    return new_x, new_y
+
+
+def coarse_nested_grid(da, varname='charge', dx=None, dy=None):
+    """ Coarse nested grid to res of main grid
+    only realy valid if nested grid resolution is a multiple of maingrid resolution
+    coords needs to be assign first
+    """
+    if dx is None or dy is None:
+        dx, dy = _get_scale(da)
+    dx1, dy1 = dx.pop(0), dy.pop(0)
+    grid = da.where(da['dx'] == dx1, drop=True) # & da['dy'] == dy1
+    for dx2, dy2 in zip(dx, dy):
+        gig = da.where(da['dx'] == dx2, drop=True)
+        gig = gig[varname].coarsen(x=int(dx1/dx2), y=int(dy1/dy2), boundary='trim').mean()
+        grid = xr.combine_by_coords([grid, gig])
+    return grid
+
+
+def interp_grid(da, new_x=None, new_y=None, method='nearest', **kwargs):
+    """ Interpolate on a new grid using `xarray.Dataset.interp`
+
+    Parameters
+    ----------
+    da: xr.Dataset
+        the input dataset to interpolate on new coordinates.
+    new_x: array-like
+        the new x-axis coordinate to use
+    new_y: array-like
+        the new y-axis coordinate to use
+    method: str, Optionnal (default='nearest')
+        `xr.Dataset.interp` method to use. Default is 'nearest'
+    **kwargs: dict, Optionnal.
+        Any keywords argument to pass to `xr.Dataset.interp`.
+    
+    Returns
+    -------
+        interpolated xr.Dataset
+    """
+    # https://docs.xarray.dev/en/stable/user-guide/interpolation.html
+    # https://earth-env-data-science.github.io/lectures/xarray/xarray-part2.html
+    if new_x is None or new_y is None:
+        new_x = np.linspace(da['x'][0], da['x'][-1], int(da['x'].size / 2) ) # da.dims["lat"]
+        new_y = np.linspace(da['y'][0], da['y'][-1], int(da['y'].size / 2) )
+    return da.interp(x=new_x, y=new_y, method=method, **kwargs)
+
+
+def rescale(da, res=1000, **kwargs):
+    """ Wrapper function that uses `get_new_coords()` and `interp_grid()` together
+    
+    See also
+    --------
+    `get_new_coords`
+    `interp_grid`
+    """
+    new_x, new_y = get_new_coords(da, res)
+    new_da = interp_grid(da, new_x, new_y, **kwargs) # here da with assign coords
+    return new_da
+
diff --git a/src/gridmarthe/plot.py b/src/gridmarthe/plot.py
index 8cd19ac..ebbc1c3 100644
--- a/src/gridmarthe/plot.py
+++ b/src/gridmarthe/plot.py
@@ -15,6 +15,7 @@
 
 def plot_nested_grid(da, ax=None, var='charge', **kwargs):
     """ Usefull function to plot nested grids, keeping heterogeneous resolution
+    TODO: remove var arg: should be a xr.DataArray with coords assigned, same as xarray API for plots
     
     Parameters
     ----------
diff --git a/src/gridmarthe/scripts/cleanmgrid.py b/src/gridmarthe/scripts/cleanmgrid.py
index 06a646b..4661244 100644
--- a/src/gridmarthe/scripts/cleanmgrid.py
+++ b/src/gridmarthe/scripts/cleanmgrid.py
@@ -4,15 +4,21 @@
 # objectif, lire l'ensemble des fichiers maillés et les corriger.
 # sinon, a minima le permh
 
-import os, sys, re, shutil
+import os, sys, re, shutil, textwrap
 from pathlib import Path
+from argparse import ArgumentParser, RawDescriptionHelpFormatter
 
+from gridmarthe.__version__ import _copyleft
 
 MARTGRID_FILES = {
     # ext: VARIABLE_NAME
     'topog' : 'H_TOPOGR',
     'hsubs' : 'H_SUBSTRAT',
+    'sepon' : 'SUBS_EPONTE',
+    'kepon' : 'PERM_EPONTE',
     'permh' : 'PERMEAB',
+    'poros' : 'POROSITE',
+    'press' : 'PRESSION',
     'perm_r': 'PERM_LIT_RIVI',
     'anisv' : 'ANISO_VERTI',
     'anish' : 'ANISO_HORIZ',
@@ -29,24 +35,72 @@
     'lon_r' : 'LONG_RIVI',
     'trc_r' : 'TRONC_RIVI',
     'qext_r': 'Q_EXTER_RIVI',
-    'd_ava' : 'DIRECT_AVAL',# Q_AMONT_RIVI, EPAI_LIT_RIV, RUGOS_RIVI, PENTE_RIVI
+    'd_ava' : 'DIRECT_AVAL',
+    # : 'Q_AMONT_RIVI',
+    # : 'EPAI_LIT_RIV',
+    # : 'RUGOS_RIVI',
+    # : 'PENTE_RIVI',
     'meteo' : 'ZONE_METEO',
     'zonep' : 'ZONE_SOL',
     'zgeom' : 'ZONE_GEOM',
     'zoneg2': 'ZONE_2',
     'zoneg3': 'ZONE_3',
-    # 'ZONE_CULTUR'
+    'zonei' : 'ZONE_IRRIG'
 }
 
-def print_help():
-    msg = """ Usage: 
-    `cleanmgrid PATH_TO_RMA`
+# legacy, switch to ArgumentParser
+# def print_help():
+    # msg = """ Usage: 
+    # `cleanmgrid PATH_TO_FILE`
     
-    PATH_TO_RMA can be a relative path, need to end with '.rma'
+    # PATH_TO_FILE can be a relative path, if it ends with '.rma' all grid file in rma project will be processed.
+
+    # Only works for marthe grid v9.0 (a check is performed and <v9 are skipped)
+    
+    # {}
+    # """.format(_copyleft)
+    # print(msg)
+
+# def parse_args():
+    # if len(sys.argv) < 2:
+        # print('cleanmgrid NO argument were passed')
+        # print_help()
+        # sys.exit(1)
+    # finputs  = sys.argv[1]
+    # if finputs in ['h', '-h', '--help']: # or not finputs.endswith('rma'):
+        # print_help()
+        # sys.exit(1)
+    # return finputs
+
+
+def parse_args():
+    """ CLI program """
+    parser = ArgumentParser(
+        prog='cleanmgrid',
+        formatter_class=RawDescriptionHelpFormatter,
+        description="Clean marthe grid file for miswritten attributes. Only works for marthe grid v9.0 (a check is performed and <v9 are skipped)",
+        epilog=textwrap.dedent(_copyleft)
+    )
+    
+    parser.add_argument('opt', metavar='PATH_TO_FILE', type=str, nargs=1, help='PATH_TO_FILE can be a relative path, if it ends with ".rma" all grid file in rma project will be processed.')
+    parser.add_argument('--layer' , '-l', type=int, default=None, help='Number of layer. Only if PATH_TO_FILE is *NOT* a rma file. Otherwise, it will be parsed from Marthe\'s files.')
+    parser.add_argument('--grid'  , '-g', type=int, default=None, help='Number of nested grid. Only if PATH_TO_FILE is *NOT* a rma file. Otherwise, it will be parsed from Marthe\'s files.')
+    parser.add_argument('--output', '-o', type=str, default=None, help='Output file. Only if PATH_TO_FILE is a single grid file and *NOT* a rma file. Otherwise, all files will be bakup and clean')
+    parser.add_argument(
+        '--no_overwrite' , '-n',
+        action="store_const", const=True, default=False,
+        help='Do no overwrite file, add `.fix` extension. By default file is bakup and then overwrite.'
+    )
+    
+    args = parser.parse_args()
+    
+    if not args.opt[0].endswith('rma') and (args.layer is None or args.grid is None):
+        print('File {} is not a Marthe project ("*.rma"). Please provide `-l` and `-g` argument when using on a single grid file. See `cleanmgrid -h`')
+        sys.exit(1)
+
+    return args
+
 
-    Only works for marthe grid v9.0 (a check is performed and <v9 are skipped)
-    """
-    print(msg)
 
 def fread(file:str):
     with open(file, 'r', encoding='ISO-8859-1') as f:
@@ -137,29 +191,46 @@ def write_res(string, fname):
         f.write(string)
     return 0
 
-def parse_args():
-    if len(sys.argv) < 2:
-        print('cleanmgrid NO argument were passed')
-        print_help()
-        sys.exit(1)
-    frma  = sys.argv[1]
-    if frma in ['h', '-h', '--help'] or not frma.endswith('rma'):
-        print_help()
-        sys.exit(1)
-    return frma
+
 
 def main():
-    frma = parse_args()
-    # root = os.path.dirname(frma) # edit no, if not ./MONMODEL.rma but MONMODEL.rma, dirname is '' so /bakup => not allowed in linux non root
-    root = os.getcwd()
-    os.makedirs('{}/bakup'.format(root), exist_ok=True)
-    files, layers, ngrid = read_files_from_rma(frma)
+    """ CLEANMGRID """
+    
+    args = parse_args()
+    finputs = args.opt[0]
+    
+    root = os.path.dirname(finputs) # edit no, if not ./MONMODEL.rma but MONMODEL.rma, dirname is '' so /bakup => not allowed in linux non root
+    if root == '' or root is None:
+        root = os.getcwd()
+    if args.output is None and not args.no_overwrite:
+        os.makedirs('{}/bakup'.format(root), exist_ok=True)
+    filename = os.path.split(finputs)[-1]
+    
+    # --- get geom
+    if finputs.endswith('rma'):
+        files, layers, ngrid = read_files_from_rma(finputs)
+    else:
+        ext = os.path.splitext(finputs)[-1].replace('.', '')
+        key = MARTGRID_FILES.get(ext)
+        if key is None:
+            print('Unkwnown key field for grid kind {} (file: {})'.format(ext, finputs))
+            sys.exit(1)
+        files, layers, ngrid = [(ext, filename, key)], list(range(1, args.layer + 1)), str(args.grid)
+    
+    
     for ext, file, key in files:
+        
+        # --- treatment of each grid file --- #
+        # --- read and scan var
         fpath = Path(root, file)
-        grid = fread(fpath)
+        grid  = fread(fpath)
         version = scan_vers_semi(grid)
+        fileout = fpath
+        
         if version != 9.0:
             continue
+        
+        # --- clean attributes:
         grid = clean_grid_str(grid, r'\nField=(.?)', key, test=lambda x: len(x) < 1 )
         grid = clean_grid_str(grid, pattern=r'\nLayer=([0-9]*)'  , fillvalue=layers * (int(ngrid)+1)   , test=lambda x: int(x) == 0)
         grid = clean_grid_str(grid, pattern=r'Max_Layer=([0-9]*)', fillvalue=str(max(map(int, layers))), test=lambda x: int(x) == 0)
@@ -168,8 +239,17 @@ def main():
         grid = clean_grid_str(grid, pattern=r'Nest_grid=([0-9]*)', fillvalue=x, test=lambda x: int(x) == 0)
         grid = clean_grid_str(grid, pattern=r'Max_NestG=([0-9]*)', fillvalue=ngrid                     , test=lambda x: int(x) == 0)
         grid = clean_grid_str(grid, pattern=r'Time=([0-9]*\.[0-9]*E[|\-|\+][0-9]*)', fillvalue='0', test=lambda x: float(x) != 0)
-        shutil.copy(fpath, Path(root, 'bakup', file))
-        write_res(grid, fpath)
+        
+        # --- save results
+        if args.no_overwrite:
+            fpath = '{}.fix'.format(str(fpath))
+        elif args.output is not None:
+            fileout = Path(root, args.output)
+        else:
+            shutil.copy(fpath, Path(root, 'bakup', file))
+        
+        write_res(grid, fileout)
+    
     return 0
 
 
diff --git a/src/gridmarthe/scripts/ncmart.py b/src/gridmarthe/scripts/ncmart.py
index 545f12d..184afdb 100644
--- a/src/gridmarthe/scripts/ncmart.py
+++ b/src/gridmarthe/scripts/ncmart.py
@@ -1,10 +1,15 @@
 #!/usr/bin/env python3
 # -*- coding:utf-8 -*-
 
-import os, sys
-from argparse import ArgumentParser
-import gridmarthe as gm
+#    gridmarthe is a python library to manage grid files for 
+#    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
+#    Copyright (C) 2024  BRGM
+#    Released under the GNU/GPL-v3 (or later) license <https://www.gnu.org/licenses/gpl-3.0.txt>
 
+import os, sys, textwrap
+from argparse import ArgumentParser, RawDescriptionHelpFormatter
+import gridmarthe as gm
+from gridmarthe.__version__ import _copyleft #, _show_c, _show_w
 
 # Usage: `ncmart PATH_CHASIM PATH_PASTP [-o output] [-v varname]` 
 
@@ -12,16 +17,33 @@ def parse_args():
     """ CLI program """
     parser = ArgumentParser(
         prog='ncmart',
-        description="Convert a Marthe GridFile to netCDF format."
+        formatter_class=RawDescriptionHelpFormatter,
+        description="Convert a Marthe GridFile to netCDF format.",
+        epilog=textwrap.dedent(_copyleft)
     )
     
-    parser.add_argument('opt', metavar='chasim pastp', type=str, nargs='+', help='Paths to chasim and pastp files are expected')
-    parser.add_argument('--output'  , '-o'  , type=str, default=None, help='Output filename. Default is input.nc')
-    parser.add_argument('--variable', '-v'  , type=str, default=None, help='Variable to read, default is None; i.e variable will be parse from file and ONLY the first variable will be read.')
-    parser.add_argument('--as2d', '-d', action="store_const", const=True, default=False, help='Store grid as 2D (or more), default is 1D for space dimension') #choices=('True','False'), dest='monnomdevariable'
+    parser.add_argument('opt', metavar='grid timesteps', type=str, nargs='*', help='Paths to grid and timesteps files are expected') # nargs='+'
+    parser.add_argument('--output'  , '-o', type=str, default=None, help='Output filename. Default is input.nc')
+    parser.add_argument('--variable', '-v', type=str, default=None, help='Variable to read, default is None; i.e variable will be parsed from file and ONLY the first variable will be read.')
+    parser.add_argument('--as2d'    , '-d', action="store_const", const=True, default=False, help='Store grid as 2D (or more), default is 1D for space dimension') #choices=('True','False'), dest='monnomdevariable'
     parser.add_argument('--xyfactor', '-x', type=float, default=1., help='Transformation factor for coordinates. Optionnal, default is 1 (no transformation).')
+    # parser.add_argument('--show', type=str, default='', choices=('c', 'w'), help='Print licensing for warranty (w) and redistribution conditions (c)')
+    parser.add_argument('--version', '-v', action="store_const", const=True, default=False, help='Show version and exit')
+    
     args = parser.parse_args()
     
+    # if args.show != '':
+        # if args.show == 'c':
+            # _show_c()
+        # if args.show == 'w':
+            # _show_w()
+        # sys.exit(0)
+    if args.version:
+        print('gridmarthe {}'.format(gm.__version__))
+        print(_copyleft)
+        sys.exit(0)
+    
+    
     if args.output is not None:
         dirout = os.path.dirname(args.output)
         if dirout != '':
diff --git a/src/gridmarthe/utils.py b/src/gridmarthe/utils.py
index fba3e21..0a92772 100644
--- a/src/gridmarthe/utils.py
+++ b/src/gridmarthe/utils.py
@@ -1,11 +1,21 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import re
+from datetime import datetime
+import pandas as pd
 import numpy as np
 
+from typing import Union
+
+
 def _datetime64_to_float(zdates, origin='1970-01-01T00:00:00'):
     # Memo: here, origin should be defined from pastp (time since timestep 0)
     idate = (zdates - np.datetime64(origin)) / np.timedelta64(1, 's')
     idate = np.where(idate < 0., 0., idate) # fake dates from load_marthe_grid will be set to 0, meaning timestep -9999. (eg used in parameters grids)
     return idate
 
+
 def _is_sorted(a):
     return np.all(a[:-1] <= a[1:])
 
@@ -31,3 +41,140 @@ def _nearest_node(node, nodes):
     dist_2 = np.sum((nodes - node)**2, axis=1)
     return np.argmin(dist_2)
 
+
+def read_dates_from_pastp(fpastp, encoding='ISO-8859-1'):
+    """Read simulation timesteps from a .pastp file
+    """
+    # reading file as raw df - not str ; faster with pandas func
+    pastp = pd.read_csv(
+        fpastp,
+        header=None,
+        encoding=encoding
+    ).squeeze('columns')
+
+    # First, get steady state time
+    idx_0  = pastp.loc[pastp.str.contains(r' \*\*\* D.*but de la simulation.*', regex=True)].index.values[0]
+    date_0 = re.findall(r'[0-9]+', pastp.iloc[idx_0] )
+    
+    # convert as DF
+    timesteps = pd.DataFrame([{
+        'timestep': 0, 
+        'date': datetime(int(date_0[2]), int(date_0[1]), int(date_0[0]) ) 
+    }])
+
+    # Then, get all ending times for transient state
+    idx  = pastp.loc[pastp.str.contains(r'^ \*\*\* Le pas.*\d+: se termine.*', regex=True)]
+    # extract dates from strings
+    dates= pd.DataFrame(
+        idx.str.findall(r'[0-9]+').to_list(),
+        columns=['timestep', 'day', 'month', 'year'],
+        #dtype={'timestep':int, 'day':int, 'month':int, 'year':int}
+    )
+    
+    # assign dtype
+    dates['timestep'] = pd.to_numeric(dates['timestep'])
+
+    # convert data as datetime object
+    dates['date'] = pd.to_datetime(dates[['day', 'month', 'year']])
+    dates = dates.drop(['month','year', 'day'], axis=1)
+    
+    return pd.concat([timesteps, dates], axis=0)
+
+
+def dropna(ds, varname: str, nanval: Union[list, float]):
+    """ Drop values corrresponding to NaN (marthe convention, eg. code 9999.) 
+    for 1D (or 2D (time, zone)) array
+    zone must me a coordinate dimension.
+    
+    Returns
+    -------
+    dataset where variable != nanval
+    """
+    if isinstance(nanval, (float, int, str)):
+        nanval = [nanval]
+    nanval = nanval + [1e+20]
+    mask = ds[varname.lower()].where(~ds[varname.lower()].isin(nanval)).dropna(dim='zone') # drop nanval
+    ds_no_nan = ds.sel(zone=mask['zone'])
+    return ds_no_nan
+
+
+def subset(ds, varname: str, value: Union[list, float]):
+    """ Subset dataset based on variable name and value.
+    --> inverse of :py:func:`dropna`
+    
+    Returns
+    -------
+    dataset where variable = value
+    """
+    if isinstance(value, (float, int, str)):
+        value = [value]
+    mask = ds[varname.lower()].where(ds[varname.lower()].isin(value)).dropna(dim='zone')
+    ds_filter = ds.sel(zone=mask['zone'])
+    return ds_filter
+
+
+def replace(ds, varname: str, value: float, replace: float):
+    """ Replace a value in xr.Dataset for a variable
+    """
+    ds[varname].data = np.where(ds[varname].data == value, replace, ds[varname].data)
+    return ds
+
+
+def fillna(ds, varname, value):
+    """ Replace real nan (np.nan) value in dataset[varname], edge case of :py:func:`replace()`
+    """
+    ds[varname].data = np.where(np.isnan(ds[varname].data), value, ds[varname].data)
+    return ds
+
+
+def assign_coords(da_in, add_lay=True, coords=['x', 'y', 'z'], keep_zone=False, zone_label='zone'):
+    """ assign coords to transform a 1D or 2D (time, zone) array to 3D or 4D
+    """
+    if len(coords) == 3:
+        z_coords = da_in.get(coords[2], None) # assert z is here, or bypass
+    else:
+        z_coords = None
+    
+    if add_lay is False:
+        # in some case, even if z is included it should not be treated as coord (ex. plot outcrop)
+        z_coords = None
+    
+    da = da_in.assign_coords(
+        #x=(zone_label, np.around(da_in[coords[0]].data, 1) ),
+        x=(zone_label, da_in[coords[0]].data ),
+        y=(zone_label, da_in[coords[1]].data ),
+    )
+    dims = ['y', 'x']
+    
+    if z_coords is not None:
+        da = da.assign_coords(z=(zone_label, da_in[coords[2]].data))
+        dims.insert(0, 'z')
+    
+    da = da.set_index(zone=dims)
+    if not keep_zone:
+        da = da.drop_duplicates(zone_label).unstack(zone_label) # drop duplicates is a security for nested grids, if dropnan was not performed
+    return da.sortby(dims)
+
+
+def stack_coords(ds, coords=['z', 'y', 'x'], dropna=False):
+    """ Transform a 3 or 4D aray into 1 or 2D array 
+    inverse of  :py:func:`assign_coords`
+    """
+    # create zone index
+    coords = [d for d in coords if d in ds.coords.keys()] # make sure to drop coords that are not present
+    dims = np.prod( [len(ds[d]) for d in coords] ) # create new zone dim
+    zone = np.arange(dims)
+    
+    # stack coords
+    ds2 = ds.copy().stack(zone=coords) # multiindex zone grouping coords key
+    
+    # keep only zone as dim
+    ds3 = ds2.drop_vars(['zone'] + coords).assign_coords(zone=('zone', zone))
+    
+    # get back xy[z] as var
+    for c in coords:
+        ds3[c] = ('zone', ds2[c].data)
+    
+    if dropna:
+        ds3 = ds3.dropna(dim='zone')
+    return ds3
\ No newline at end of file

From 59fd8274657c08c548a41e6d8e3761f65ecf11a9 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Fri, 14 Feb 2025 10:50:27 +0100
Subject: [PATCH 05/31] test: add test files (scripts and data)

---
 tests/data/chasim_hallue.nc           | Bin 0 -> 644486 bytes
 tests/data/grid_wrong_attrs.hsubs     | 905 ++++++++++++++++++++++++++
 tests/data/grid_wrong_attrs.hsubs.fix | 905 ++++++++++++++++++++++++++
 tests/test_all_var.py                 |   9 +
 tests/test_cleanm.sh                  |   3 +
 tests/test_convert.sh                 |   3 +
 6 files changed, 1825 insertions(+)
 create mode 100644 tests/data/chasim_hallue.nc
 create mode 100644 tests/data/grid_wrong_attrs.hsubs
 create mode 100644 tests/data/grid_wrong_attrs.hsubs.fix
 create mode 100644 tests/test_all_var.py
 create mode 100644 tests/test_cleanm.sh

diff --git a/tests/data/chasim_hallue.nc b/tests/data/chasim_hallue.nc
new file mode 100644
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diff --git a/tests/data/grid_wrong_attrs.hsubs b/tests/data/grid_wrong_attrs.hsubs
new file mode 100644
index 0000000..9bb7058
--- /dev/null
+++ b/tests/data/grid_wrong_attrs.hsubs
@@ -0,0 +1,905 @@
+Marthe_Grid Version=9.0
+Title=Bidon                                                                  H_SUBSTRAT     1
+[Infos]
+Field=
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=0
+Max_Layer=0
+Nest_grid=0
+Max_NestG=0
+[Structure]
+X_Left_Corner=528
+Y_Lower_Corner=2503
+Ncolumn=320
+Nrows=189
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Colums    >
+[Data]
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Bidon                                                                1 H_SUBSTRAT     1
+[Infos]
+Field=
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=0
+Max_Layer=0
+Nest_grid=0
+Max_NestG=0
+[Structure]
+X_Left_Corner=550.5
+Y_Lower_Corner=2552
+Ncolumn=322
+Nrows=237
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Colums    >
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+Title=Bidon                                                                2 H_SUBSTRAT     1
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+6	2551.05	14.94	14.59	14.59	14.59	14.59	14.59	14.9	14.9	14.9	14.9	14.9	16.06	16.06	16.06	16.06	16.06	18.41	18.41	18.41	18.41	18.41	20.02	20.02	20.02	20.02	20.02	21.47	21.47	21.47	21.47	21.47	21.84	21.84	21.84	21.84	21.84	22.04	22.04	22.04	22.04	22.04	22.58	22.58	22.58	22.58	22.58	25.14	25.14	25.14	25.14	25.14	27.29	27.29	27.29	27.29	27.29	30.52	30.52	30.52	30.52	30.52	31.31	31.31	31.31	31.31	31.31	30.86	30.86	30.86	30.86	30.86	30.28	30.28	30.28	30.28	30.28	29.57	29.57	29.57	29.57	29.57	29.39	29.39	29.39	29.39	29.39	29.73	29.73	29.73	29.73	29.73	30.3	30.3	30.3	30.3	30.3	31.22	31.22	31.22	31.22	31.22	31.93	31.93	31.93	31.93	31.93	33.16	33.16	33.16	33.16	33.16	34.14	34.14	34.14	34.14	34.14	35.66	35.66	35.66	35.66	35.66	36.49	36.49	36.49	36.49	36.49	37.48	37.48	37.48	37.48	37.48	37.92	37.92	37.92	37.92	37.92	38.3	38.3	38.3	38.3	38.3	38.56	38.56	38.56	38.56	38.56	38.92	38.92	38.92	38.92	38.92	39.08	39.08	39.08	39.08	39.08	39.28	39.28	39.28	39.28	39.28	39.61	39.61	39.61	39.61	39.61	40.35	40.35	40.35	40.35	40.35	40.73	40.73	40.73	40.73	40.73	41.04	41.04	41.04	41.04	41.04	41.2	41.2	41.2	41.2	41.2	42.11	42.11	42.11	42.11	42.11	43.24	43.24	43.24	43.24	43.24	44.89	44.89	44.89	44.89	44.89	45.79	45.79	45.79	45.79	45.79	47.06	47.06	47.06	47.06	47.06	47.91	47.91	47.91	47.91	47.91	48.79	.1000977	
+7	2550.95	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+8	2550.85	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+9	2550.75	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+10	2550.65	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+11	2550.55	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+12	2550.45	17.11	17.05	17.05	17.05	17.05	17.05	17.43	17.43	17.43	17.43	17.43	18.03	18.03	18.03	18.03	18.03	19.19	19.19	19.19	19.19	19.19	22	22	22	22	22	21.01	21.01	21.01	21.01	21.01	21.46	21.46	21.46	21.46	21.46	21.83	21.83	21.83	21.83	21.83	22.2	22.2	22.2	22.2	22.2	24.56	24.56	24.56	24.56	24.56	26.55	26.55	26.55	26.55	26.55	29.1	29.1	29.1	29.1	29.1	29.55	29.55	29.55	29.55	29.55	28.69	28.69	28.69	28.69	28.69	27.84	27.84	27.84	27.84	27.84	27.13	27.13	27.13	27.13	27.13	27.28	27.28	27.28	27.28	27.28	28.18	28.18	28.18	28.18	28.18	29.03	29.03	29.03	29.03	29.03	30.21	30.21	30.21	30.21	30.21	31.16	31.16	31.16	31.16	31.16	32.8	32.8	32.8	32.8	32.8	33.68	33.68	33.68	33.68	33.68	34.73	34.73	34.73	34.73	34.73	35.14	35.14	35.14	35.14	35.14	35.64	35.64	35.64	35.64	35.64	36.18	36.18	36.18	36.18	36.18	36.95	36.95	36.95	36.95	36.95	37.54	37.54	37.54	37.54	37.54	38.36	38.36	38.36	38.36	38.36	38.77	38.77	38.77	38.77	38.77	39.17	39.17	39.17	39.17	39.17	39.4	39.4	39.4	39.4	39.4	40.08	40.08	40.08	40.08	40.08	40.35	40.35	40.35	40.35	40.35	40.74	40.74	40.74	40.74	40.74	41.14	41.14	41.14	41.14	41.14	41.67	41.67	41.67	41.67	41.67	42.48	42.48	42.48	42.48	42.48	43.72	43.72	43.72	43.72	43.72	44.59	44.59	44.59	44.59	44.59	46.15	46.15	46.15	46.15	46.15	47.17	47.17	47.17	47.17	47.17	48.39	.1000977	
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+14	2550.25	17.11	17.05	17.05	17.05	17.05	17.05	17.43	17.43	17.43	17.43	17.43	18.03	18.03	18.03	18.03	18.03	19.19	19.19	19.19	19.19	19.19	22	22	22	22	22	21.01	21.01	21.01	21.01	21.01	21.46	21.46	21.46	21.46	21.46	21.83	21.83	21.83	21.83	21.83	22.2	22.2	22.2	22.2	22.2	24.56	24.56	24.56	24.56	24.56	26.55	26.55	26.55	26.55	26.55	29.1	29.1	29.1	29.1	29.1	29.55	29.55	29.55	29.55	29.55	28.69	28.69	28.69	28.69	28.69	27.84	27.84	27.84	27.84	27.84	27.13	27.13	27.13	27.13	27.13	27.28	27.28	27.28	27.28	27.28	28.18	28.18	28.18	28.18	28.18	29.03	29.03	29.03	29.03	29.03	30.21	30.21	30.21	30.21	30.21	31.16	31.16	31.16	31.16	31.16	32.8	32.8	32.8	32.8	32.8	33.68	33.68	33.68	33.68	33.68	34.73	34.73	34.73	34.73	34.73	35.14	35.14	35.14	35.14	35.14	35.64	35.64	35.64	35.64	35.64	36.18	36.18	36.18	36.18	36.18	36.95	36.95	36.95	36.95	36.95	37.54	37.54	37.54	37.54	37.54	38.36	38.36	38.36	38.36	38.36	38.77	38.77	38.77	38.77	38.77	39.17	39.17	39.17	39.17	39.17	39.4	39.4	39.4	39.4	39.4	40.08	40.08	40.08	40.08	40.08	40.35	40.35	40.35	40.35	40.35	40.74	40.74	40.74	40.74	40.74	41.14	41.14	41.14	41.14	41.14	41.67	41.67	41.67	41.67	41.67	42.48	42.48	42.48	42.48	42.48	43.72	43.72	43.72	43.72	43.72	44.59	44.59	44.59	44.59	44.59	46.15	46.15	46.15	46.15	46.15	47.17	47.17	47.17	47.17	47.17	48.39	.1000977	
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+28	2548.85	19.15	18.84	18.84	18.84	18.84	18.84	18.55	18.55	18.55	18.55	18.55	18.61	18.61	18.61	18.61	18.61	22	22	22	22	22	19.4	19.4	19.4	19.4	19.4	20.05	20.05	20.05	20.05	20.05	20.22	20.22	20.22	20.22	20.22	20.33	20.33	20.33	20.33	20.33	20.41	20.41	20.41	20.41	20.41	20.9	20.9	20.9	20.9	20.9	21.73	21.73	21.73	21.73	21.73	23.13	23.13	23.13	23.13	23.13	24.09	24.09	24.09	24.09	24.09	24.92	24.92	24.92	24.92	24.92	25.37	25.37	25.37	25.37	25.37	26.15	26.15	26.15	26.15	26.15	26.97	26.97	26.97	26.97	26.97	28.72	28.72	28.72	28.72	28.72	29.91	29.91	29.91	29.91	29.91	31.15	31.15	31.15	31.15	31.15	31.62	31.62	31.62	31.62	31.62	32.13	32.13	32.13	32.13	32.13	32.33	32.33	32.33	32.33	32.33	35	35	35	35	35	33.33	33.33	33.33	33.33	33.33	34.52	34.52	34.52	34.52	34.52	35.47	35.47	35.47	35.47	35.47	36.93	36.93	36.93	36.93	36.93	37.83	37.83	37.83	37.83	37.83	38.97	38.97	38.97	38.97	38.97	39.57	39.57	39.57	39.57	39.57	40.07	40.07	40.07	40.07	40.07	40.14	40.14	40.14	40.14	40.14	39.98	39.98	39.98	39.98	39.98	40.05	40.05	40.05	40.05	40.05	40.69	40.69	40.69	40.69	40.69	41.44	41.44	41.44	41.44	41.44	42.52	42.52	42.52	42.52	42.52	42.95	42.95	42.95	42.95	42.95	43.15	43.15	43.15	43.15	43.15	43.2	43.2	43.2	43.2	43.2	43.67	43.67	43.67	43.67	43.67	44.29	44.29	44.29	44.29	44.29	45.75	.1000977	
+29	2548.75	19.15	18.84	18.84	18.84	18.84	18.84	18.55	18.55	18.55	18.55	18.55	18.61	18.61	18.61	18.61	18.61	22	22	22	22	22	19.4	19.4	19.4	19.4	19.4	20.05	20.05	20.05	20.05	20.05	20.22	20.22	20.22	20.22	20.22	20.33	20.33	20.33	20.33	20.33	20.41	20.41	20.41	20.41	20.41	20.9	20.9	20.9	20.9	20.9	21.73	21.73	21.73	21.73	21.73	23.13	23.13	23.13	23.13	23.13	24.09	24.09	24.09	24.09	24.09	24.92	24.92	24.92	24.92	24.92	25.37	25.37	25.37	25.37	25.37	26.15	26.15	26.15	26.15	26.15	26.97	26.97	26.97	26.97	26.97	28.72	28.72	28.72	28.72	28.72	29.91	29.91	29.91	29.91	29.91	31.15	31.15	31.15	31.15	31.15	31.62	31.62	31.62	31.62	31.62	32.13	32.13	32.13	32.13	32.13	32.33	32.33	32.33	32.33	32.33	35	35	35	35	35	33.33	33.33	33.33	33.33	33.33	34.52	34.52	34.52	34.52	34.52	35.47	35.47	35.47	35.47	35.47	36.93	36.93	36.93	36.93	36.93	37.83	37.83	37.83	37.83	37.83	38.97	38.97	38.97	38.97	38.97	39.57	39.57	39.57	39.57	39.57	40.07	40.07	40.07	40.07	40.07	40.14	40.14	40.14	40.14	40.14	39.98	39.98	39.98	39.98	39.98	40.05	40.05	40.05	40.05	40.05	40.69	40.69	40.69	40.69	40.69	41.44	41.44	41.44	41.44	41.44	42.52	42.52	42.52	42.52	42.52	42.95	42.95	42.95	42.95	42.95	43.15	43.15	43.15	43.15	43.15	43.2	43.2	43.2	43.2	43.2	43.67	43.67	43.67	43.67	43.67	44.29	44.29	44.29	44.29	44.29	45.75	.1000977	
+30	2548.65	19.15	18.84	18.84	18.84	18.84	18.84	18.55	18.55	18.55	18.55	18.55	18.61	18.61	18.61	18.61	18.61	22	22	22	22	22	19.4	19.4	19.4	19.4	19.4	20.05	20.05	20.05	20.05	20.05	20.22	20.22	20.22	20.22	20.22	20.33	20.33	20.33	20.33	20.33	20.41	20.41	20.41	20.41	20.41	20.9	20.9	20.9	20.9	20.9	21.73	21.73	21.73	21.73	21.73	23.13	23.13	23.13	23.13	23.13	24.09	24.09	24.09	24.09	24.09	24.92	24.92	24.92	24.92	24.92	25.37	25.37	25.37	25.37	25.37	26.15	26.15	26.15	26.15	26.15	26.97	26.97	26.97	26.97	26.97	28.72	28.72	28.72	28.72	28.72	29.91	29.91	29.91	29.91	29.91	31.15	31.15	31.15	31.15	31.15	31.62	31.62	31.62	31.62	31.62	32.13	32.13	32.13	32.13	32.13	32.33	32.33	32.33	32.33	32.33	35	35	35	35	35	33.33	33.33	33.33	33.33	33.33	34.52	34.52	34.52	34.52	34.52	35.47	35.47	35.47	35.47	35.47	36.93	36.93	36.93	36.93	36.93	37.83	37.83	37.83	37.83	37.83	38.97	38.97	38.97	38.97	38.97	39.57	39.57	39.57	39.57	39.57	40.07	40.07	40.07	40.07	40.07	40.14	40.14	40.14	40.14	40.14	39.98	39.98	39.98	39.98	39.98	40.05	40.05	40.05	40.05	40.05	40.69	40.69	40.69	40.69	40.69	41.44	41.44	41.44	41.44	41.44	42.52	42.52	42.52	42.52	42.52	42.95	42.95	42.95	42.95	42.95	43.15	43.15	43.15	43.15	43.15	43.2	43.2	43.2	43.2	43.2	43.67	43.67	43.67	43.67	43.67	44.29	44.29	44.29	44.29	44.29	45.75	.1000977	
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+50	2546.65	21.67	20.63	20.63	20.63	20.63	20.63	17.85	17.85	17.85	17.85	17.85	15.82	15.82	15.82	15.82	15.82	13.84	13.84	13.84	13.84	13.84	13.51	13.51	13.51	13.51	13.51	14.17	14.17	14.17	14.17	14.17	14.78	14.78	14.78	14.78	14.78	15.29	15.29	15.29	15.29	15.29	15.5	15.5	15.5	15.5	15.5	16.02	16.02	16.02	16.02	16.02	16.93	16.93	16.93	16.93	16.93	19.24	19.24	19.24	19.24	19.24	20.94	20.94	20.94	20.94	20.94	23.19	23.19	23.19	23.19	23.19	24.3	24.3	24.3	24.3	24.3	25.26	25.26	25.26	25.26	25.26	25.92	25.92	25.92	25.92	25.92	27.01	27.01	27.01	27.01	27.01	27.77	27.77	27.77	27.77	27.77	29.24	29.24	29.24	29.24	29.24	30.23	30.23	30.23	30.23	30.23	31.62	31.62	31.62	31.62	31.62	32.4	32.4	32.4	32.4	32.4	33.28	33.28	33.28	33.28	33.28	33.73	33.73	33.73	33.73	33.73	34.42	34.42	34.42	34.42	34.42	35.4	35.4	35.4	35.4	35.4	37.47	37.47	37.47	37.47	37.47	39.06	39.06	39.06	39.06	39.06	41.07	41.07	41.07	41.07	41.07	41.58	41.58	41.58	41.58	41.58	41.79	41.79	41.79	41.79	41.79	41.75	41.75	41.75	41.75	41.75	41.79	41.79	41.79	41.79	41.79	41.85	41.85	41.85	41.85	41.85	41.96	41.96	41.96	41.96	41.96	42.07	42.07	42.07	42.07	42.07	42.23	42.23	42.23	42.23	42.23	42.29	42.29	42.29	42.29	42.29	42.31	42.31	42.31	42.31	42.31	42.29	42.29	42.29	42.29	42.29	42.22	42.22	42.22	42.22	42.22	42.17	42.17	42.17	42.17	42.17	42.13	.1000977	
+51	2546.55	21.67	20.63	20.63	20.63	20.63	20.63	17.85	17.85	17.85	17.85	17.85	15.82	15.82	15.82	15.82	15.82	13.84	13.84	13.84	13.84	13.84	13.51	13.51	13.51	13.51	13.51	14.17	14.17	14.17	14.17	14.17	14.78	14.78	14.78	14.78	14.78	15.29	15.29	15.29	15.29	15.29	15.5	15.5	15.5	15.5	15.5	16.02	16.02	16.02	16.02	16.02	16.93	16.93	16.93	16.93	16.93	19.24	19.24	19.24	19.24	19.24	20.94	20.94	20.94	20.94	20.94	23.19	23.19	23.19	23.19	23.19	24.3	24.3	24.3	24.3	24.3	25.26	25.26	25.26	25.26	25.26	25.92	25.92	25.92	25.92	25.92	27.01	27.01	27.01	27.01	27.01	27.77	27.77	27.77	27.77	27.77	29.24	29.24	29.24	29.24	29.24	30.23	30.23	30.23	30.23	30.23	31.62	31.62	31.62	31.62	31.62	32.4	32.4	32.4	32.4	32.4	33.28	33.28	33.28	33.28	33.28	33.73	33.73	33.73	33.73	33.73	34.42	34.42	34.42	34.42	34.42	35.4	35.4	35.4	35.4	35.4	37.47	37.47	37.47	37.47	37.47	39.06	39.06	39.06	39.06	39.06	41.07	41.07	41.07	41.07	41.07	41.58	41.58	41.58	41.58	41.58	41.79	41.79	41.79	41.79	41.79	41.75	41.75	41.75	41.75	41.75	41.79	41.79	41.79	41.79	41.79	41.85	41.85	41.85	41.85	41.85	41.96	41.96	41.96	41.96	41.96	42.07	42.07	42.07	42.07	42.07	42.23	42.23	42.23	42.23	42.23	42.29	42.29	42.29	42.29	42.29	42.31	42.31	42.31	42.31	42.31	42.29	42.29	42.29	42.29	42.29	42.22	42.22	42.22	42.22	42.22	42.17	42.17	42.17	42.17	42.17	42.13	.1000977	
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+91	2542.55	25.91	24.95	24.95	24.95	24.95	24.95	23.46	23.46	23.46	23.46	23.46	22.41	22.41	22.41	22.41	22.41	20.89	20.89	20.89	20.89	20.89	20.1	20.1	20.1	20.1	20.1	18.05	18.05	18.05	18.05	18.05	15.44	15.44	15.44	15.44	15.44	11.84	11.84	11.84	11.84	11.84	10.93	10.93	10.93	10.93	10.93	12.91	12.91	12.91	12.91	12.91	16.21	16.21	16.21	16.21	16.21	20.11	20.11	20.11	20.11	20.11	21.33	21.33	21.33	21.33	21.33	21.85	21.85	21.85	21.85	21.85	22.36	22.36	22.36	22.36	22.36	23.99	23.99	23.99	23.99	23.99	25.18	25.18	25.18	25.18	25.18	27.13	27.13	27.13	27.13	27.13	28.18	28.18	28.18	28.18	28.18	29.49	29.49	29.49	29.49	29.49	30.2	30.2	30.2	30.2	30.2	31.49	31.49	31.49	31.49	31.49	32.35	32.35	32.35	32.35	32.35	33.38	33.38	33.38	33.38	33.38	33.94	33.94	33.94	33.94	33.94	34.51	34.51	34.51	34.51	34.51	35.07	35.07	35.07	35.07	35.07	36.03	36.03	36.03	36.03	36.03	36.65	36.65	36.65	36.65	36.65	37.52	37.52	37.52	37.52	37.52	38.11	38.11	38.11	38.11	38.11	38.77	38.77	38.77	38.77	38.77	38.93	38.93	38.93	38.93	38.93	38.92	38.92	38.92	38.92	38.92	38.97	38.97	38.97	38.97	38.97	39.26	39.26	39.26	39.26	39.26	39.52	39.52	39.52	39.52	39.52	40.01	40.01	40.01	40.01	40.01	40.15	40.15	40.15	40.15	40.15	42	42	42	42	42	40.55	40.55	40.55	40.55	40.55	41.12	41.12	41.12	41.12	41.12	41.99	41.99	41.99	41.99	41.99	42.98	.1000977	
+92	2542.45	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+93	2542.35	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+94	2542.25	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+95	2542.15	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+96	2542.05	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+97	2541.95	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+98	2541.85	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+99	2541.75	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+100	2541.65	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+101	2541.55	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+102	2541.45	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+103	2541.35	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+104	2541.25	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+105	2541.15	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+106	2541.05	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+107	2540.95	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
+108	2540.85	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
+109	2540.75	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
+110	2540.65	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
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+112	2540.45	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+113	2540.35	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+114	2540.25	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+115	2540.15	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+116	2540.05	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+117	2539.95	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
+118	2539.85	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
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+120	2539.65	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
+121	2539.55	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
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+192	2532.45	36.37	35.59	35.59	35.59	35.59	35.59	34.26	34.26	34.26	34.26	34.26	33.14	33.14	33.14	33.14	33.14	31.63	31.63	31.63	31.63	31.63	30.63	30.63	30.63	30.63	30.63	29.28	29.28	29.28	29.28	29.28	28.24	28.24	28.24	28.24	28.24	27.07	27.07	27.07	27.07	27.07	26.57	26.57	26.57	26.57	26.57	26.17	26.17	26.17	26.17	26.17	25.86	25.86	25.86	25.86	25.86	25.33	25.33	25.33	25.33	25.33	25.09	25.09	25.09	25.09	25.09	27	27	27	27	27	25.52	25.52	25.52	25.52	25.52	26.69	26.69	26.69	26.69	26.69	27.22	27.22	27.22	27.22	27.22	28.37	28.37	28.37	28.37	28.37	29.25	29.25	29.25	29.25	29.25	30.65	30.65	30.65	30.65	30.65	31.33	31.33	31.33	31.33	31.33	31.35	31.35	31.35	31.35	31.35	31.01	31.01	31.01	31.01	31.01	30.48	30.48	30.48	30.48	30.48	30.32	30.32	30.32	30.32	30.32	30.64	30.64	30.64	30.64	30.64	31.18	31.18	31.18	31.18	31.18	32.12	32.12	32.12	32.12	32.12	32.58	32.58	32.58	32.58	32.58	33.04	33.04	33.04	33.04	33.04	33.76	33.76	33.76	33.76	33.76	34.91	34.91	34.91	34.91	34.91	35.72	35.72	35.72	35.72	35.72	36.57	36.57	36.57	36.57	36.57	36.85	36.85	36.85	36.85	36.85	37.71	37.71	37.71	37.71	37.71	38.56	38.56	38.56	38.56	38.56	39.72	39.72	39.72	39.72	39.72	40.33	40.33	40.33	40.33	40.33	40.8	40.8	40.8	40.8	40.8	40.82	40.82	40.82	40.82	40.82	40.6	40.6	40.6	40.6	40.6	40.32	40.32	40.32	40.32	40.32	39.7	.1000977	
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+199	2531.75	35.99	35.17	35.17	35.17	35.17	35.17	33.81	33.81	33.81	33.81	33.81	32.67	32.67	32.67	32.67	32.67	31.33	31.33	31.33	31.33	31.33	30.4	30.4	30.4	30.4	30.4	29.21	29.21	29.21	29.21	29.21	28.32	28.32	28.32	28.32	28.32	27.27	27.27	27.27	27.27	27.27	26.82	26.82	26.82	26.82	26.82	26.27	26.27	26.27	26.27	26.27	26.12	26.12	26.12	26.12	26.12	25.51	25.51	25.51	25.51	25.51	25.23	25.23	25.23	25.23	25.23	27	27	27	27	27	25.11	25.11	25.11	25.11	25.11	25.8	25.8	25.8	25.8	25.8	26.08	26.08	26.08	26.08	26.08	27.04	27.04	27.04	27.04	27.04	28.04	28.04	28.04	28.04	28.04	29.62	29.62	29.62	29.62	29.62	30.45	30.45	30.45	30.45	30.45	30.3	30.3	30.3	30.3	30.3	29.85	29.85	29.85	29.85	29.85	29.39	29.39	29.39	29.39	29.39	29.47	29.47	29.47	29.47	29.47	30.18	30.18	30.18	30.18	30.18	30.79	30.79	30.79	30.79	30.79	31.77	31.77	31.77	31.77	31.77	32.29	32.29	32.29	32.29	32.29	32.9	32.9	32.9	32.9	32.9	33.63	33.63	33.63	33.63	33.63	34.75	34.75	34.75	34.75	34.75	35.36	35.36	35.36	35.36	35.36	35.85	35.85	35.85	35.85	35.85	36	36	36	36	36	36.65	36.65	36.65	36.65	36.65	37.4	37.4	37.4	37.4	37.4	38.52	38.52	38.52	38.52	38.52	39.12	39.12	39.12	39.12	39.12	39.71	39.71	39.71	39.71	39.71	39.86	39.86	39.86	39.86	39.86	39.9	39.9	39.9	39.9	39.9	39.78	39.78	39.78	39.78	39.78	39.36	.1000977	
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+202	2531.45	35.3	34.49	34.49	34.49	34.49	34.49	33.24	33.24	33.24	33.24	33.24	32.21	32.21	32.21	32.21	32.21	30.97	30.97	30.97	30.97	30.97	30.12	30.12	30.12	30.12	30.12	29.04	29.04	29.04	29.04	29.04	28.46	28.46	28.46	28.46	28.46	27.6	27.6	27.6	27.6	27.6	27.08	27.08	27.08	27.08	27.08	26.78	26.78	26.78	26.78	26.78	26.75	26.75	26.75	26.75	26.75	26.27	26.27	26.27	26.27	26.27	28	28	28	28	28	24.83	24.83	24.83	24.83	24.83	27	27	27	27	27	27	27	27	27	27	24.49	24.49	24.49	24.49	24.49	25.34	25.34	25.34	25.34	25.34	26.4	26.4	26.4	26.4	26.4	28.09	28.09	28.09	28.09	28.09	28.89	28.89	28.89	28.89	28.89	28.48	28.48	28.48	28.48	28.48	28.21	28.21	28.21	28.21	28.21	28.03	28.03	28.03	28.03	28.03	28.54	28.54	28.54	28.54	28.54	30.09	30.09	30.09	30.09	30.09	30.82	30.82	30.82	30.82	30.82	31.69	31.69	31.69	31.69	31.69	32.04	32.04	32.04	32.04	32.04	32.53	32.53	32.53	32.53	32.53	33.06	33.06	33.06	33.06	33.06	33.87	33.87	33.87	33.87	33.87	34.24	34.24	34.24	34.24	34.24	34.44	34.44	34.44	34.44	34.44	34.58	34.58	34.58	34.58	34.58	35.19	35.19	35.19	35.19	35.19	35.82	35.82	35.82	35.82	35.82	37.01	37.01	37.01	37.01	37.01	37.65	37.65	37.65	37.65	37.65	38.32	38.32	38.32	38.32	38.32	38.59	38.59	38.59	38.59	38.59	38.74	38.74	38.74	38.74	38.74	38.78	38.78	38.78	38.78	38.78	38.61	.1000977	
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+[End_Grid]
diff --git a/tests/data/grid_wrong_attrs.hsubs.fix b/tests/data/grid_wrong_attrs.hsubs.fix
new file mode 100644
index 0000000..696ea7e
--- /dev/null
+++ b/tests/data/grid_wrong_attrs.hsubs.fix
@@ -0,0 +1,905 @@
+Marthe_Grid Version=9.0
+Title=Bidon                                                                  H_SUBSTRAT     1
+[Infos]
+Field=H_SUBSTRAT
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=1
+Max_Layer=1
+Nest_grid=0
+Max_NestG=3
+[Structure]
+X_Left_Corner=528
+Y_Lower_Corner=2503
+Ncolumn=320
+Nrows=189
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Colums    >
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+6	2551.05	14.94	14.59	14.59	14.59	14.59	14.59	14.9	14.9	14.9	14.9	14.9	16.06	16.06	16.06	16.06	16.06	18.41	18.41	18.41	18.41	18.41	20.02	20.02	20.02	20.02	20.02	21.47	21.47	21.47	21.47	21.47	21.84	21.84	21.84	21.84	21.84	22.04	22.04	22.04	22.04	22.04	22.58	22.58	22.58	22.58	22.58	25.14	25.14	25.14	25.14	25.14	27.29	27.29	27.29	27.29	27.29	30.52	30.52	30.52	30.52	30.52	31.31	31.31	31.31	31.31	31.31	30.86	30.86	30.86	30.86	30.86	30.28	30.28	30.28	30.28	30.28	29.57	29.57	29.57	29.57	29.57	29.39	29.39	29.39	29.39	29.39	29.73	29.73	29.73	29.73	29.73	30.3	30.3	30.3	30.3	30.3	31.22	31.22	31.22	31.22	31.22	31.93	31.93	31.93	31.93	31.93	33.16	33.16	33.16	33.16	33.16	34.14	34.14	34.14	34.14	34.14	35.66	35.66	35.66	35.66	35.66	36.49	36.49	36.49	36.49	36.49	37.48	37.48	37.48	37.48	37.48	37.92	37.92	37.92	37.92	37.92	38.3	38.3	38.3	38.3	38.3	38.56	38.56	38.56	38.56	38.56	38.92	38.92	38.92	38.92	38.92	39.08	39.08	39.08	39.08	39.08	39.28	39.28	39.28	39.28	39.28	39.61	39.61	39.61	39.61	39.61	40.35	40.35	40.35	40.35	40.35	40.73	40.73	40.73	40.73	40.73	41.04	41.04	41.04	41.04	41.04	41.2	41.2	41.2	41.2	41.2	42.11	42.11	42.11	42.11	42.11	43.24	43.24	43.24	43.24	43.24	44.89	44.89	44.89	44.89	44.89	45.79	45.79	45.79	45.79	45.79	47.06	47.06	47.06	47.06	47.06	47.91	47.91	47.91	47.91	47.91	48.79	.1000977	
+7	2550.95	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+8	2550.85	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+9	2550.75	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+10	2550.65	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+11	2550.55	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+12	2550.45	17.11	17.05	17.05	17.05	17.05	17.05	17.43	17.43	17.43	17.43	17.43	18.03	18.03	18.03	18.03	18.03	19.19	19.19	19.19	19.19	19.19	22	22	22	22	22	21.01	21.01	21.01	21.01	21.01	21.46	21.46	21.46	21.46	21.46	21.83	21.83	21.83	21.83	21.83	22.2	22.2	22.2	22.2	22.2	24.56	24.56	24.56	24.56	24.56	26.55	26.55	26.55	26.55	26.55	29.1	29.1	29.1	29.1	29.1	29.55	29.55	29.55	29.55	29.55	28.69	28.69	28.69	28.69	28.69	27.84	27.84	27.84	27.84	27.84	27.13	27.13	27.13	27.13	27.13	27.28	27.28	27.28	27.28	27.28	28.18	28.18	28.18	28.18	28.18	29.03	29.03	29.03	29.03	29.03	30.21	30.21	30.21	30.21	30.21	31.16	31.16	31.16	31.16	31.16	32.8	32.8	32.8	32.8	32.8	33.68	33.68	33.68	33.68	33.68	34.73	34.73	34.73	34.73	34.73	35.14	35.14	35.14	35.14	35.14	35.64	35.64	35.64	35.64	35.64	36.18	36.18	36.18	36.18	36.18	36.95	36.95	36.95	36.95	36.95	37.54	37.54	37.54	37.54	37.54	38.36	38.36	38.36	38.36	38.36	38.77	38.77	38.77	38.77	38.77	39.17	39.17	39.17	39.17	39.17	39.4	39.4	39.4	39.4	39.4	40.08	40.08	40.08	40.08	40.08	40.35	40.35	40.35	40.35	40.35	40.74	40.74	40.74	40.74	40.74	41.14	41.14	41.14	41.14	41.14	41.67	41.67	41.67	41.67	41.67	42.48	42.48	42.48	42.48	42.48	43.72	43.72	43.72	43.72	43.72	44.59	44.59	44.59	44.59	44.59	46.15	46.15	46.15	46.15	46.15	47.17	47.17	47.17	47.17	47.17	48.39	.1000977	
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+14	2550.25	17.11	17.05	17.05	17.05	17.05	17.05	17.43	17.43	17.43	17.43	17.43	18.03	18.03	18.03	18.03	18.03	19.19	19.19	19.19	19.19	19.19	22	22	22	22	22	21.01	21.01	21.01	21.01	21.01	21.46	21.46	21.46	21.46	21.46	21.83	21.83	21.83	21.83	21.83	22.2	22.2	22.2	22.2	22.2	24.56	24.56	24.56	24.56	24.56	26.55	26.55	26.55	26.55	26.55	29.1	29.1	29.1	29.1	29.1	29.55	29.55	29.55	29.55	29.55	28.69	28.69	28.69	28.69	28.69	27.84	27.84	27.84	27.84	27.84	27.13	27.13	27.13	27.13	27.13	27.28	27.28	27.28	27.28	27.28	28.18	28.18	28.18	28.18	28.18	29.03	29.03	29.03	29.03	29.03	30.21	30.21	30.21	30.21	30.21	31.16	31.16	31.16	31.16	31.16	32.8	32.8	32.8	32.8	32.8	33.68	33.68	33.68	33.68	33.68	34.73	34.73	34.73	34.73	34.73	35.14	35.14	35.14	35.14	35.14	35.64	35.64	35.64	35.64	35.64	36.18	36.18	36.18	36.18	36.18	36.95	36.95	36.95	36.95	36.95	37.54	37.54	37.54	37.54	37.54	38.36	38.36	38.36	38.36	38.36	38.77	38.77	38.77	38.77	38.77	39.17	39.17	39.17	39.17	39.17	39.4	39.4	39.4	39.4	39.4	40.08	40.08	40.08	40.08	40.08	40.35	40.35	40.35	40.35	40.35	40.74	40.74	40.74	40.74	40.74	41.14	41.14	41.14	41.14	41.14	41.67	41.67	41.67	41.67	41.67	42.48	42.48	42.48	42.48	42.48	43.72	43.72	43.72	43.72	43.72	44.59	44.59	44.59	44.59	44.59	46.15	46.15	46.15	46.15	46.15	47.17	47.17	47.17	47.17	47.17	48.39	.1000977	
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+28	2548.85	19.15	18.84	18.84	18.84	18.84	18.84	18.55	18.55	18.55	18.55	18.55	18.61	18.61	18.61	18.61	18.61	22	22	22	22	22	19.4	19.4	19.4	19.4	19.4	20.05	20.05	20.05	20.05	20.05	20.22	20.22	20.22	20.22	20.22	20.33	20.33	20.33	20.33	20.33	20.41	20.41	20.41	20.41	20.41	20.9	20.9	20.9	20.9	20.9	21.73	21.73	21.73	21.73	21.73	23.13	23.13	23.13	23.13	23.13	24.09	24.09	24.09	24.09	24.09	24.92	24.92	24.92	24.92	24.92	25.37	25.37	25.37	25.37	25.37	26.15	26.15	26.15	26.15	26.15	26.97	26.97	26.97	26.97	26.97	28.72	28.72	28.72	28.72	28.72	29.91	29.91	29.91	29.91	29.91	31.15	31.15	31.15	31.15	31.15	31.62	31.62	31.62	31.62	31.62	32.13	32.13	32.13	32.13	32.13	32.33	32.33	32.33	32.33	32.33	35	35	35	35	35	33.33	33.33	33.33	33.33	33.33	34.52	34.52	34.52	34.52	34.52	35.47	35.47	35.47	35.47	35.47	36.93	36.93	36.93	36.93	36.93	37.83	37.83	37.83	37.83	37.83	38.97	38.97	38.97	38.97	38.97	39.57	39.57	39.57	39.57	39.57	40.07	40.07	40.07	40.07	40.07	40.14	40.14	40.14	40.14	40.14	39.98	39.98	39.98	39.98	39.98	40.05	40.05	40.05	40.05	40.05	40.69	40.69	40.69	40.69	40.69	41.44	41.44	41.44	41.44	41.44	42.52	42.52	42.52	42.52	42.52	42.95	42.95	42.95	42.95	42.95	43.15	43.15	43.15	43.15	43.15	43.2	43.2	43.2	43.2	43.2	43.67	43.67	43.67	43.67	43.67	44.29	44.29	44.29	44.29	44.29	45.75	.1000977	
+29	2548.75	19.15	18.84	18.84	18.84	18.84	18.84	18.55	18.55	18.55	18.55	18.55	18.61	18.61	18.61	18.61	18.61	22	22	22	22	22	19.4	19.4	19.4	19.4	19.4	20.05	20.05	20.05	20.05	20.05	20.22	20.22	20.22	20.22	20.22	20.33	20.33	20.33	20.33	20.33	20.41	20.41	20.41	20.41	20.41	20.9	20.9	20.9	20.9	20.9	21.73	21.73	21.73	21.73	21.73	23.13	23.13	23.13	23.13	23.13	24.09	24.09	24.09	24.09	24.09	24.92	24.92	24.92	24.92	24.92	25.37	25.37	25.37	25.37	25.37	26.15	26.15	26.15	26.15	26.15	26.97	26.97	26.97	26.97	26.97	28.72	28.72	28.72	28.72	28.72	29.91	29.91	29.91	29.91	29.91	31.15	31.15	31.15	31.15	31.15	31.62	31.62	31.62	31.62	31.62	32.13	32.13	32.13	32.13	32.13	32.33	32.33	32.33	32.33	32.33	35	35	35	35	35	33.33	33.33	33.33	33.33	33.33	34.52	34.52	34.52	34.52	34.52	35.47	35.47	35.47	35.47	35.47	36.93	36.93	36.93	36.93	36.93	37.83	37.83	37.83	37.83	37.83	38.97	38.97	38.97	38.97	38.97	39.57	39.57	39.57	39.57	39.57	40.07	40.07	40.07	40.07	40.07	40.14	40.14	40.14	40.14	40.14	39.98	39.98	39.98	39.98	39.98	40.05	40.05	40.05	40.05	40.05	40.69	40.69	40.69	40.69	40.69	41.44	41.44	41.44	41.44	41.44	42.52	42.52	42.52	42.52	42.52	42.95	42.95	42.95	42.95	42.95	43.15	43.15	43.15	43.15	43.15	43.2	43.2	43.2	43.2	43.2	43.67	43.67	43.67	43.67	43.67	44.29	44.29	44.29	44.29	44.29	45.75	.1000977	
+30	2548.65	19.15	18.84	18.84	18.84	18.84	18.84	18.55	18.55	18.55	18.55	18.55	18.61	18.61	18.61	18.61	18.61	22	22	22	22	22	19.4	19.4	19.4	19.4	19.4	20.05	20.05	20.05	20.05	20.05	20.22	20.22	20.22	20.22	20.22	20.33	20.33	20.33	20.33	20.33	20.41	20.41	20.41	20.41	20.41	20.9	20.9	20.9	20.9	20.9	21.73	21.73	21.73	21.73	21.73	23.13	23.13	23.13	23.13	23.13	24.09	24.09	24.09	24.09	24.09	24.92	24.92	24.92	24.92	24.92	25.37	25.37	25.37	25.37	25.37	26.15	26.15	26.15	26.15	26.15	26.97	26.97	26.97	26.97	26.97	28.72	28.72	28.72	28.72	28.72	29.91	29.91	29.91	29.91	29.91	31.15	31.15	31.15	31.15	31.15	31.62	31.62	31.62	31.62	31.62	32.13	32.13	32.13	32.13	32.13	32.33	32.33	32.33	32.33	32.33	35	35	35	35	35	33.33	33.33	33.33	33.33	33.33	34.52	34.52	34.52	34.52	34.52	35.47	35.47	35.47	35.47	35.47	36.93	36.93	36.93	36.93	36.93	37.83	37.83	37.83	37.83	37.83	38.97	38.97	38.97	38.97	38.97	39.57	39.57	39.57	39.57	39.57	40.07	40.07	40.07	40.07	40.07	40.14	40.14	40.14	40.14	40.14	39.98	39.98	39.98	39.98	39.98	40.05	40.05	40.05	40.05	40.05	40.69	40.69	40.69	40.69	40.69	41.44	41.44	41.44	41.44	41.44	42.52	42.52	42.52	42.52	42.52	42.95	42.95	42.95	42.95	42.95	43.15	43.15	43.15	43.15	43.15	43.2	43.2	43.2	43.2	43.2	43.67	43.67	43.67	43.67	43.67	44.29	44.29	44.29	44.29	44.29	45.75	.1000977	
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+50	2546.65	21.67	20.63	20.63	20.63	20.63	20.63	17.85	17.85	17.85	17.85	17.85	15.82	15.82	15.82	15.82	15.82	13.84	13.84	13.84	13.84	13.84	13.51	13.51	13.51	13.51	13.51	14.17	14.17	14.17	14.17	14.17	14.78	14.78	14.78	14.78	14.78	15.29	15.29	15.29	15.29	15.29	15.5	15.5	15.5	15.5	15.5	16.02	16.02	16.02	16.02	16.02	16.93	16.93	16.93	16.93	16.93	19.24	19.24	19.24	19.24	19.24	20.94	20.94	20.94	20.94	20.94	23.19	23.19	23.19	23.19	23.19	24.3	24.3	24.3	24.3	24.3	25.26	25.26	25.26	25.26	25.26	25.92	25.92	25.92	25.92	25.92	27.01	27.01	27.01	27.01	27.01	27.77	27.77	27.77	27.77	27.77	29.24	29.24	29.24	29.24	29.24	30.23	30.23	30.23	30.23	30.23	31.62	31.62	31.62	31.62	31.62	32.4	32.4	32.4	32.4	32.4	33.28	33.28	33.28	33.28	33.28	33.73	33.73	33.73	33.73	33.73	34.42	34.42	34.42	34.42	34.42	35.4	35.4	35.4	35.4	35.4	37.47	37.47	37.47	37.47	37.47	39.06	39.06	39.06	39.06	39.06	41.07	41.07	41.07	41.07	41.07	41.58	41.58	41.58	41.58	41.58	41.79	41.79	41.79	41.79	41.79	41.75	41.75	41.75	41.75	41.75	41.79	41.79	41.79	41.79	41.79	41.85	41.85	41.85	41.85	41.85	41.96	41.96	41.96	41.96	41.96	42.07	42.07	42.07	42.07	42.07	42.23	42.23	42.23	42.23	42.23	42.29	42.29	42.29	42.29	42.29	42.31	42.31	42.31	42.31	42.31	42.29	42.29	42.29	42.29	42.29	42.22	42.22	42.22	42.22	42.22	42.17	42.17	42.17	42.17	42.17	42.13	.1000977	
+51	2546.55	21.67	20.63	20.63	20.63	20.63	20.63	17.85	17.85	17.85	17.85	17.85	15.82	15.82	15.82	15.82	15.82	13.84	13.84	13.84	13.84	13.84	13.51	13.51	13.51	13.51	13.51	14.17	14.17	14.17	14.17	14.17	14.78	14.78	14.78	14.78	14.78	15.29	15.29	15.29	15.29	15.29	15.5	15.5	15.5	15.5	15.5	16.02	16.02	16.02	16.02	16.02	16.93	16.93	16.93	16.93	16.93	19.24	19.24	19.24	19.24	19.24	20.94	20.94	20.94	20.94	20.94	23.19	23.19	23.19	23.19	23.19	24.3	24.3	24.3	24.3	24.3	25.26	25.26	25.26	25.26	25.26	25.92	25.92	25.92	25.92	25.92	27.01	27.01	27.01	27.01	27.01	27.77	27.77	27.77	27.77	27.77	29.24	29.24	29.24	29.24	29.24	30.23	30.23	30.23	30.23	30.23	31.62	31.62	31.62	31.62	31.62	32.4	32.4	32.4	32.4	32.4	33.28	33.28	33.28	33.28	33.28	33.73	33.73	33.73	33.73	33.73	34.42	34.42	34.42	34.42	34.42	35.4	35.4	35.4	35.4	35.4	37.47	37.47	37.47	37.47	37.47	39.06	39.06	39.06	39.06	39.06	41.07	41.07	41.07	41.07	41.07	41.58	41.58	41.58	41.58	41.58	41.79	41.79	41.79	41.79	41.79	41.75	41.75	41.75	41.75	41.75	41.79	41.79	41.79	41.79	41.79	41.85	41.85	41.85	41.85	41.85	41.96	41.96	41.96	41.96	41.96	42.07	42.07	42.07	42.07	42.07	42.23	42.23	42.23	42.23	42.23	42.29	42.29	42.29	42.29	42.29	42.31	42.31	42.31	42.31	42.31	42.29	42.29	42.29	42.29	42.29	42.22	42.22	42.22	42.22	42.22	42.17	42.17	42.17	42.17	42.17	42.13	.1000977	
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+91	2542.55	25.91	24.95	24.95	24.95	24.95	24.95	23.46	23.46	23.46	23.46	23.46	22.41	22.41	22.41	22.41	22.41	20.89	20.89	20.89	20.89	20.89	20.1	20.1	20.1	20.1	20.1	18.05	18.05	18.05	18.05	18.05	15.44	15.44	15.44	15.44	15.44	11.84	11.84	11.84	11.84	11.84	10.93	10.93	10.93	10.93	10.93	12.91	12.91	12.91	12.91	12.91	16.21	16.21	16.21	16.21	16.21	20.11	20.11	20.11	20.11	20.11	21.33	21.33	21.33	21.33	21.33	21.85	21.85	21.85	21.85	21.85	22.36	22.36	22.36	22.36	22.36	23.99	23.99	23.99	23.99	23.99	25.18	25.18	25.18	25.18	25.18	27.13	27.13	27.13	27.13	27.13	28.18	28.18	28.18	28.18	28.18	29.49	29.49	29.49	29.49	29.49	30.2	30.2	30.2	30.2	30.2	31.49	31.49	31.49	31.49	31.49	32.35	32.35	32.35	32.35	32.35	33.38	33.38	33.38	33.38	33.38	33.94	33.94	33.94	33.94	33.94	34.51	34.51	34.51	34.51	34.51	35.07	35.07	35.07	35.07	35.07	36.03	36.03	36.03	36.03	36.03	36.65	36.65	36.65	36.65	36.65	37.52	37.52	37.52	37.52	37.52	38.11	38.11	38.11	38.11	38.11	38.77	38.77	38.77	38.77	38.77	38.93	38.93	38.93	38.93	38.93	38.92	38.92	38.92	38.92	38.92	38.97	38.97	38.97	38.97	38.97	39.26	39.26	39.26	39.26	39.26	39.52	39.52	39.52	39.52	39.52	40.01	40.01	40.01	40.01	40.01	40.15	40.15	40.15	40.15	40.15	42	42	42	42	42	40.55	40.55	40.55	40.55	40.55	41.12	41.12	41.12	41.12	41.12	41.99	41.99	41.99	41.99	41.99	42.98	.1000977	
+92	2542.45	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+93	2542.35	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+94	2542.25	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+95	2542.15	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+96	2542.05	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+97	2541.95	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+98	2541.85	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+99	2541.75	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+100	2541.65	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+101	2541.55	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+102	2541.45	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+103	2541.35	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+104	2541.25	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+105	2541.15	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+106	2541.05	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+107	2540.95	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
+108	2540.85	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
+109	2540.75	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
+110	2540.65	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
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+112	2540.45	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+113	2540.35	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+114	2540.25	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+115	2540.15	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+116	2540.05	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+117	2539.95	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
+118	2539.85	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
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+120	2539.65	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
+121	2539.55	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
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+192	2532.45	36.37	35.59	35.59	35.59	35.59	35.59	34.26	34.26	34.26	34.26	34.26	33.14	33.14	33.14	33.14	33.14	31.63	31.63	31.63	31.63	31.63	30.63	30.63	30.63	30.63	30.63	29.28	29.28	29.28	29.28	29.28	28.24	28.24	28.24	28.24	28.24	27.07	27.07	27.07	27.07	27.07	26.57	26.57	26.57	26.57	26.57	26.17	26.17	26.17	26.17	26.17	25.86	25.86	25.86	25.86	25.86	25.33	25.33	25.33	25.33	25.33	25.09	25.09	25.09	25.09	25.09	27	27	27	27	27	25.52	25.52	25.52	25.52	25.52	26.69	26.69	26.69	26.69	26.69	27.22	27.22	27.22	27.22	27.22	28.37	28.37	28.37	28.37	28.37	29.25	29.25	29.25	29.25	29.25	30.65	30.65	30.65	30.65	30.65	31.33	31.33	31.33	31.33	31.33	31.35	31.35	31.35	31.35	31.35	31.01	31.01	31.01	31.01	31.01	30.48	30.48	30.48	30.48	30.48	30.32	30.32	30.32	30.32	30.32	30.64	30.64	30.64	30.64	30.64	31.18	31.18	31.18	31.18	31.18	32.12	32.12	32.12	32.12	32.12	32.58	32.58	32.58	32.58	32.58	33.04	33.04	33.04	33.04	33.04	33.76	33.76	33.76	33.76	33.76	34.91	34.91	34.91	34.91	34.91	35.72	35.72	35.72	35.72	35.72	36.57	36.57	36.57	36.57	36.57	36.85	36.85	36.85	36.85	36.85	37.71	37.71	37.71	37.71	37.71	38.56	38.56	38.56	38.56	38.56	39.72	39.72	39.72	39.72	39.72	40.33	40.33	40.33	40.33	40.33	40.8	40.8	40.8	40.8	40.8	40.82	40.82	40.82	40.82	40.82	40.6	40.6	40.6	40.6	40.6	40.32	40.32	40.32	40.32	40.32	39.7	.1000977	
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+199	2531.75	35.99	35.17	35.17	35.17	35.17	35.17	33.81	33.81	33.81	33.81	33.81	32.67	32.67	32.67	32.67	32.67	31.33	31.33	31.33	31.33	31.33	30.4	30.4	30.4	30.4	30.4	29.21	29.21	29.21	29.21	29.21	28.32	28.32	28.32	28.32	28.32	27.27	27.27	27.27	27.27	27.27	26.82	26.82	26.82	26.82	26.82	26.27	26.27	26.27	26.27	26.27	26.12	26.12	26.12	26.12	26.12	25.51	25.51	25.51	25.51	25.51	25.23	25.23	25.23	25.23	25.23	27	27	27	27	27	25.11	25.11	25.11	25.11	25.11	25.8	25.8	25.8	25.8	25.8	26.08	26.08	26.08	26.08	26.08	27.04	27.04	27.04	27.04	27.04	28.04	28.04	28.04	28.04	28.04	29.62	29.62	29.62	29.62	29.62	30.45	30.45	30.45	30.45	30.45	30.3	30.3	30.3	30.3	30.3	29.85	29.85	29.85	29.85	29.85	29.39	29.39	29.39	29.39	29.39	29.47	29.47	29.47	29.47	29.47	30.18	30.18	30.18	30.18	30.18	30.79	30.79	30.79	30.79	30.79	31.77	31.77	31.77	31.77	31.77	32.29	32.29	32.29	32.29	32.29	32.9	32.9	32.9	32.9	32.9	33.63	33.63	33.63	33.63	33.63	34.75	34.75	34.75	34.75	34.75	35.36	35.36	35.36	35.36	35.36	35.85	35.85	35.85	35.85	35.85	36	36	36	36	36	36.65	36.65	36.65	36.65	36.65	37.4	37.4	37.4	37.4	37.4	38.52	38.52	38.52	38.52	38.52	39.12	39.12	39.12	39.12	39.12	39.71	39.71	39.71	39.71	39.71	39.86	39.86	39.86	39.86	39.86	39.9	39.9	39.9	39.9	39.9	39.78	39.78	39.78	39.78	39.78	39.36	.1000977	
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+202	2531.45	35.3	34.49	34.49	34.49	34.49	34.49	33.24	33.24	33.24	33.24	33.24	32.21	32.21	32.21	32.21	32.21	30.97	30.97	30.97	30.97	30.97	30.12	30.12	30.12	30.12	30.12	29.04	29.04	29.04	29.04	29.04	28.46	28.46	28.46	28.46	28.46	27.6	27.6	27.6	27.6	27.6	27.08	27.08	27.08	27.08	27.08	26.78	26.78	26.78	26.78	26.78	26.75	26.75	26.75	26.75	26.75	26.27	26.27	26.27	26.27	26.27	28	28	28	28	28	24.83	24.83	24.83	24.83	24.83	27	27	27	27	27	27	27	27	27	27	24.49	24.49	24.49	24.49	24.49	25.34	25.34	25.34	25.34	25.34	26.4	26.4	26.4	26.4	26.4	28.09	28.09	28.09	28.09	28.09	28.89	28.89	28.89	28.89	28.89	28.48	28.48	28.48	28.48	28.48	28.21	28.21	28.21	28.21	28.21	28.03	28.03	28.03	28.03	28.03	28.54	28.54	28.54	28.54	28.54	30.09	30.09	30.09	30.09	30.09	30.82	30.82	30.82	30.82	30.82	31.69	31.69	31.69	31.69	31.69	32.04	32.04	32.04	32.04	32.04	32.53	32.53	32.53	32.53	32.53	33.06	33.06	33.06	33.06	33.06	33.87	33.87	33.87	33.87	33.87	34.24	34.24	34.24	34.24	34.24	34.44	34.44	34.44	34.44	34.44	34.58	34.58	34.58	34.58	34.58	35.19	35.19	35.19	35.19	35.19	35.82	35.82	35.82	35.82	35.82	37.01	37.01	37.01	37.01	37.01	37.65	37.65	37.65	37.65	37.65	38.32	38.32	38.32	38.32	38.32	38.59	38.59	38.59	38.59	38.59	38.74	38.74	38.74	38.74	38.74	38.78	38.78	38.78	38.78	38.78	38.61	.1000977	
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+246	2527.05	36.21	35.17	35.17	35.17	35.17	35.17	32.91	32.91	32.91	32.91	32.91	30.77	30.77	30.77	30.77	30.77	27.26	27.26	27.26	27.26	27.26	25.09	25.09	25.09	25.09	25.09	22.96	22.96	22.96	22.96	22.96	22.31	22.31	22.31	22.31	22.31	22.09	22.09	22.09	22.09	22.09	22.11	22.11	22.11	22.11	22.11	22.44	22.44	22.44	22.44	22.44	23.24	23.24	23.24	23.24	23.24	24.92	24.92	24.92	24.92	24.92	26.12	26.12	26.12	26.12	26.12	27.75	27.75	27.75	27.75	27.75	31	31	31	31	31	28.69	28.69	28.69	28.69	28.69	28.99	28.99	28.99	28.99	28.99	29.46	29.46	29.46	29.46	29.46	29.71	29.71	29.71	29.71	29.71	29.8	29.8	29.8	29.8	29.8	29.64	29.64	29.64	29.64	29.64	32	32	32	32	32	28.63	28.63	28.63	28.63	28.63	27.81	27.81	27.81	27.81	27.81	27.35	27.35	27.35	27.35	27.35	27.43	27.43	27.43	27.43	27.43	27.98	27.98	27.98	27.98	27.98	29.36	29.36	29.36	29.36	29.36	30.19	30.19	30.19	30.19	30.19	99.35	99.35	99.35	99.35	99.35	99.749	99.749	99.749	99.749	99.749	31.9	31.9	31.9	31.9	31.9	32.41	32.41	32.41	32.41	32.41	33.22	33.22	33.22	33.22	33.22	33.69	33.69	33.69	33.69	33.69	103.59	103.59	103.59	103.59	103.59	107	107	107	107	107	107	107	107	107	107	103.34	103.34	103.34	103.34	103.34	37	37	37	37	37	37	37	37	37	37	37	37	37	37	37	37	37	37	37	37	37	.1000977	
+247	2526.75	36.41	35.66	35.66	35.66	35.66	35.66	34.08	34.08	34.08	34.08	34.08	32.45	32.45	32.45	32.45	32.45	29.2	29.2	29.2	29.2	29.2	26.87	26.87	26.87	26.87	26.87	24.23	24.23	24.23	24.23	24.23	23.18	23.18	23.18	23.18	23.18	22.62	22.62	22.62	22.62	22.62	22.62	22.62	22.62	22.62	22.62	23.01	23.01	23.01	23.01	23.01	23.79	23.79	23.79	23.79	23.79	25.42	25.42	25.42	25.42	25.42	26.62	26.62	26.62	26.62	26.62	30	30	30	30	30	28.68	28.68	28.68	28.68	28.68	29.36	29.36	29.36	29.36	29.36	29.88	29.88	29.88	29.88	29.88	30.41	30.41	30.41	30.41	30.41	30.63	30.63	30.63	30.63	30.63	30.5	30.5	30.5	30.5	30.5	30.16	30.16	30.16	30.16	30.16	29.37	29.37	29.37	29.37	29.37	28.82	28.82	28.82	28.82	28.82	28.11	28.11	28.11	28.11	28.11	27.77	27.77	27.77	27.77	27.77	27.87	27.87	27.87	27.87	27.87	28.4	28.4	28.4	28.4	28.4	29.7	29.7	29.7	29.7	29.7	98.314	98.314	98.314	98.314	98.314	102.35	102.35	102.35	102.35	102.35	100.09	100.09	100.09	100.09	100.09	100.11	100.11	100.11	100.11	100.11	32.61	32.61	32.61	32.61	32.61	33.48	33.48	33.48	33.48	33.48	34.01	34.01	34.01	34.01	34.01	102.86	102.86	102.86	102.86	102.86	34.47	34.47	34.47	34.47	34.47	107	107	107	107	107	107	107	107	107	107	107	107	107	107	107	38	38	38	38	38	37	37	37	37	37	37	37	37	37	37	34.93	.5	
+0	0	.5	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	.5	
+[End_Grid]
diff --git a/tests/test_all_var.py b/tests/test_all_var.py
new file mode 100644
index 0000000..ae39304
--- /dev/null
+++ b/tests/test_all_var.py
@@ -0,0 +1,9 @@
+import gridmarthe as gm
+
+
+ds = gm.load_marthe_grid(
+    'Jordan_aquifers.out', 
+    'all', 
+    fpastp='Jordan_aquifers.pastp',
+    drop_nan=True
+)
diff --git a/tests/test_cleanm.sh b/tests/test_cleanm.sh
new file mode 100644
index 0000000..ee8793f
--- /dev/null
+++ b/tests/test_cleanm.sh
@@ -0,0 +1,3 @@
+#!/bin/bash
+
+cleanmgrid data/grid_wrong_attrs.hsubs -l 1 -g 3
\ No newline at end of file
diff --git a/tests/test_convert.sh b/tests/test_convert.sh
index c84392c..2c223a7 100644
--- a/tests/test_convert.sh
+++ b/tests/test_convert.sh
@@ -3,7 +3,10 @@
 # CLI interface to convert MartheGrid to netCDF
 # Usage: `ncmart PATH_CHASIM PATH_PASTP [-o output] [-v varname]`
 
+mkdir -p nc
 # ncmart -h
 # ncmart ./data/chasim_hallue.out ./data/hallue.pastp
 # ncmart ./data/chasim_hallue.out ./data/hallue.pastp -o hallue.nc
 ncmart ./data/chasim_hallue.out ./data/hallue.pastp -o nc/hallue.nc
+ncmart ./data/chasim_hallue.out ./data/hallue.pastp -o nc/hallue.nc -x 1000
+ncmart ./data/chasim_hallue.out ./data/hallue.pastp -o nc/hallue.nc -x 1000 -v all

From 76512b430c0c570547594c72c2310bb0eef2ae3d Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Fri, 14 Feb 2025 10:53:37 +0100
Subject: [PATCH 06/31] build: minor fix for development build, add editable
 meson install in makefile

---
 Makefile    | 31 +++++++++++++++++++------------
 README.md   |  3 ++-
 meson.build | 12 +++++++-----
 3 files changed, 28 insertions(+), 18 deletions(-)

diff --git a/Makefile b/Makefile
index 16d2e99..197b459 100644
--- a/Makefile
+++ b/Makefile
@@ -31,30 +31,31 @@ PIPFLAGS ?= -e
 #Flags are primarily useful for initial check that code compiles correctly
 F2PYOPT =--backend=meson --lower
 
-FFLAGS = 
-# FFLAGS +=-fdefault-real-8 # no
-# already O3 in f2py ? does not seem to force it.
+FFLAGS = -fdefault-real-8
+# already O3 in f2py, change it here
 FFLAGS +=-O2 
 # Position-Independent Code, si shared library, utile
 # FFLAGS +=-fPIC -shared
 FFLAGS +=-ffree-line-length-none
 # FFLAGS +=-fallow-argument-mismatch # only gfortran > 12.0
 FFLAGS +=-std=legacy
-# FFLAGS +=-static
+# FFLAGS +=-static # only windows // and not for dev
 
 COMPILE = CC=$(CC) FC=$(FC) FFLAGS="$(FFLAGS)" $(F2PY) -c $(F90FILES) -m lecsem $(F2PYOPT)
-# COMPILE = CC=$(CC) FC=$(FC) $(F2PY) -c $(F90FILES) -m lecsem $(F2PYOPT)
 
 
-# ---- Rules ---- #
-
-.PHONY: all docs clean requirements
-all: clean install bakup_pyproj
+# ------------- Rules ------------- #
 
+.PHONY: all docs clean requirements wheel
+# all: clean install bakup_pyproj
+all: clean editm
+# only compile with f2py for develop purpose
+lib: lecsem.so
 
 doc:
 	cd docs; $(MAKE) html
 
+
 setuptools: pyproject.toml
 	cp pyproject.toml pyproject.bak ; sed -i '16s/# //' pyproject.toml ; sed -i '17s/^/# /' pyproject.toml
     # change to setuptools for editable version
@@ -66,9 +67,6 @@ bakup_pyproj: pyproject.toml
 requirements:
 	$(PY) -m pip install charset_normalizer numpy meson meson-python
 
-# only compile with f2py for develop purpose
-lib: lecsem.so
-
 # install: requirements lecsem.pyf lecsem.so
 install: requirements lecsem.so setuptools
 	$(PY) -m pip install $(PIPFLAGS) .
@@ -85,6 +83,15 @@ lecsem.so:
     # because meson/f2py does not allow path separator in files.
 	# FC="$(FC)" FFLAGS="$(FFLAGS)" python -m numpy.f2py -c lecsem.pyf lecsem.f90 edsemigl.f90 scan_grid.f90 -m lecsem --backend=meson --lower
 
+# meson editable for test
+editm: requirements
+	$(PY) -m pip install --no-build-isolation --editable . -vvv
+    # meson version of editable - for future replacement of setuptools
+
+wheel:
+	$(PY) -m pip install build
+	$(PY) -m build .
+
 clean:
 	cd $(F90SRCDIR); \
 	rm -f *.so *.o *.mod *.c *pywrappers* *.dll *.pyd ; \
diff --git a/README.md b/README.md
index 937f015..b913d5c 100644
--- a/README.md
+++ b/README.md
@@ -127,7 +127,8 @@ Simple examples can be found in the
 
 ## License
 
-This software is open-source and released under the [GNU General Public License (v3+)](LICENSE).
+This program is free software and released under the terms of the
+[GNU General Public License (version 3 or later)](LICENSE).
 
 
 ## Authors and acknowledgment
diff --git a/meson.build b/meson.build
index 04c8472..e952f70 100644
--- a/meson.build
+++ b/meson.build
@@ -36,6 +36,9 @@ largs = []  # arg de link
 
 if fc.get_id() == 'gcc'
   
+  fargs += ['-fdefault-real-8']
+  fargs += ['-O2', '-ffree-line-length-none']
+  
   if cc.version().version_compare('>=13.0')
     fargs += ['-fallow-argument-mismatch', '-std=legacy']
   endif
@@ -51,24 +54,23 @@ if fc.get_id() == 'gcc'
     quadmath = declare_dependency(link_args : ['-lquadmath'])
     deps += [quadmath_dep,quadmath]
   else
-      fargs += ['-O2', '-ffree-line-length-none']
       # fargs += ['-fPIC', '-shared'] # not really necessary here
-      # fargs += ['-fdefault-real-8'] # EDIT, no, in args: kind=4 / single precision
   endif
 
 elif fc.get_id() in ['llvm-flang', 'flang', 'flang-new']
-  
   # TODO add options for llvm-flang for conda-forge
   fargs += ['-fdefault-real-8', '-ffree-form']
   
-# elif cc.get_id() in ['msvc', 'intel-llvm', 'intel', 'intel-llvm-cl', 'intel-cl']
+elif cc.get_id() in ['intel-llvm', 'intel', 'intel-llvm-cl', 'intel-cl']
+  fargs += ['-real-size 64', '-stand f95']
 
 else
-  
+  # 'msvc' ?
   error('Build is recommended with GCC/gfortran')
 
 endif
 
+
 fortran_args = fc.get_supported_arguments(fargs)
 link_args = fc.get_supported_arguments(largs)
 add_project_arguments(fortran_args, language: 'fortran')

From 66a6069a5d803fd68d9885e9d614c16e39a085d0 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Fri, 14 Feb 2025 10:54:47 +0100
Subject: [PATCH 07/31] dev: add geometry features

---
 src/gridmarthe/operasem/__init__.py |  14 ++
 src/gridmarthe/operasem/geometry.py | 198 ++++++++++++++++++++++++++++
 2 files changed, 212 insertions(+)
 create mode 100644 src/gridmarthe/operasem/__init__.py
 create mode 100644 src/gridmarthe/operasem/geometry.py

diff --git a/src/gridmarthe/operasem/__init__.py b/src/gridmarthe/operasem/__init__.py
new file mode 100644
index 0000000..ff5b8df
--- /dev/null
+++ b/src/gridmarthe/operasem/__init__.py
@@ -0,0 +1,14 @@
+# -------------------------------------------------------- #
+#  Operation on Marthe Grids (semis, marthe easter eggs).  #
+# -------------------------------------------------------- #
+
+"""
+Some useful functions to manage MartheGrid in python
+"""
+# TODO:   add functions available in winmarthe or operasem.
+#         get_runoff_direction(), remove_layer(), remove_nested(), etc.
+
+
+from .geometry import *
+from .interp import *
+from .gis import *
diff --git a/src/gridmarthe/operasem/geometry.py b/src/gridmarthe/operasem/geometry.py
new file mode 100644
index 0000000..dc2cedb
--- /dev/null
+++ b/src/gridmarthe/operasem/geometry.py
@@ -0,0 +1,198 @@
+#! /usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import numpy as np
+import xarray as xr
+
+from .gis import to_geodataframe
+from ..utils import _nearest_node, subset
+
+
+def get_mask_array(ds, varname: str='permeab', nanval: list=[-9999., 0.]):
+    """ Get mask array of active domain, from permh file (hydraulic conductivity)
+    """
+    return ds.where(~ds[varname].isin(nanval), drop=True)
+
+
+def export_mask(ds, varname: str='permeab', nanval: list=[-9999., 0.], fileout: str='mask.shp'):
+    """ Filter dataset on non-nan values, and dissolve results to get a mask shape 
+    input ds should be the permh dataset (read from permh file, ie Horizontal hydraulic conductivity)
+    """
+    mask = get_mask_array(ds, varname, nanval)
+    mask = ds.sel(zone=mask['zone'])
+    gdf  = to_geodataframe(mask)
+    gdf  = gdf.dissolve()
+    gdf.to_file(fileout)
+    return gdf
+
+
+def _get_true_topo(topo, key='h_topogr'):
+    ds = topo.copy()
+    if 'z' not in list(topo.dims) + list(topo.keys()):
+        zdim = 1
+    else:
+        zdim = len(np.unique(topo.z.data))
+    true_topo = subset(topo, 'z', 1)[key].data  # true topo is only 1st layer
+    true_topo = np.tile(true_topo, zdim)  # set topo for all layers
+    ds[key] = (('time', 'zone'), true_topo)
+    return ds
+
+
+def _get_upper_alt(topo, hsubs):
+    """ Compute upper altitude of cells by layer
+    Topo should contains the same values in all layers, see :py_func:`_get_true_topo`
+
+    TODO: make valid version with time (if topo change with times)
+
+    Parameters
+    ----------
+
+    Returns
+    -------
+    dataset with only (time,zone), (h_topogr, h_substr, h_upper)
+    """
+    ds = xr.combine_by_coords([topo, hsubs], combine_attrs='override')
+    
+    df = ds.isel(time=0).to_dataframe().reset_index()  # time is constant! TODO change this/ check if working
+    df = df.sort_values(by=['x', 'y', 'z']).copy()  # assure data are sort in this way
+    # set nans for topo and hsubs
+    # this is constant in Marthe / should not be changed by user
+    for x in ['h_substrat', 'h_topogr']:
+        df[x] = df[x].replace(9999., np.nan)  # avoid doing this on full df, zone might be impacted
+    
+    # Compute z top of layers
+    df['h_topogr'] = df.groupby(['x', 'y'])['h_topogr'].transform('first')  # topo is always first of group
+    df['tmp']      = df.groupby(['x', 'y'])['h_substrat'].ffill()  # ffill z down for each group
+    df['h_upper']  = df.groupby(['x', 'y'])['tmp'].shift(1)  # then shift to initiate z top
+    # For the first layer (or if h_upper is NaN but h_substrat is valid), then h_topogr is z upper (first layer)
+    mask = (df['h_upper'].isna()) & (df['h_substrat'].notna())
+    df.loc[mask, 'h_upper'] = df.loc[mask, 'h_topogr']
+
+    # debug
+    # df.to_csv('toto.csv')
+
+    # # switch back to xarray backend
+    ds = df.set_index(['time','zone'])[['h_topogr', 'h_substrat', 'h_upper']].to_xarray()
+    return ds
+
+
+def _get_thickness(h_upper, hsubs):
+    """ Compute layer thickness from upper altitudes
+    and substratums.
+
+    See, :py_func:`_get_upper_alt`
+    """
+    return h_upper - hsubs
+
+
+def _get_depth(topo, h_upper):
+    return topo - h_upper
+
+
+def compute_geometry(topo, hsubs, mask=None):
+    """_summary_
+
+    Parameters
+    ----------
+    topo : _type_
+        _description_
+    hsubs : _type_
+        _description_
+    mask : numpy.array
+        list of indices (`zone`) to keep, if None (default) not used.
+
+    Returns
+    -------
+    _type_
+        _description_
+    """
+
+    # compute elements of geometry
+    xtopo = _get_true_topo(topo)  # map topo values to all layers
+    xhsubs = hsubs.copy()
+    
+    if mask is not None:
+        xtopo  = xtopo.sel(zone=mask)
+        xhsubs = xhsubs.sel(zone=mask)
+    
+    tmp   = _get_upper_alt(xtopo, xhsubs)
+    thick = _get_thickness(tmp['h_upper'].data, tmp['h_substrat'].data)
+    depth = _get_depth(tmp['h_topogr'].data, tmp['h_upper'].data)
+    
+    # put values in xr.Dataset
+    # ds = xr.combine_by_coords([ds, tmp])
+    ds = xtopo.copy()
+    ds['h_substrat'] = (('time', 'zone'), tmp['h_substrat'].data)
+    ds['h_upper']    = (('time', 'zone'), tmp['h_upper'].data)
+    ds['thickness']  = (('time', 'zone'), thick)
+    ds['depth']      = (('time', 'zone'), depth)
+    return ds
+
+
+def get_min_layer(ds, aquif_layers=None):
+    """ Compute surface mask of marthe domain
+    
+    This function return min layer for every zone of a grimarthe dataset with z coords
+    A subset on specific (aquifers) layers can be performed with `aquif_layers`.
+    if set, aquif_layers must be a sequence (list, tuple, array) of layer (list of int).
+    
+    This should be used to get a surface mask, ie get zone to filter a dataset.
+    
+    Examples
+    --------
+    >>>    mask = get_min_layer(ds, [6,8,9])
+    >>>    ds_surf = ds.sel(zone=mask.zone.data)
+        
+    Parameters
+    ----------
+        ds: xr.Dataset
+        aquif_layers: sequence (list, tuple, array) of int
+            representing layers to subset ds
+    Returns
+    -------
+        surface_mask: xr.Dataset
+    """
+    df = ds.to_dataframe()
+    df = df.reset_index()
+    
+    if aquif_layers is not None:
+        df = df[df['z'].isin(aquif_layers)]
+    
+    idx_z_min = df.groupby(['x', 'y', 'time']).z.idxmin() # get index of min z ("layer") for each x,y,t groups
+    first_aquif_lay = df.loc[idx_z_min].reset_index().set_index('zone').drop('index', axis=1)
+    # time not needed here, zone are independant from time coords
+    return first_aquif_lay.to_xarray()
+
+
+
+def search_zone(ds, i=None, j=None, x=None, y=None, z=None):
+    """ search zone number in marthe grid,
+    based on xy or ij (col, lig)
+    
+    if ds is multilayered, you need to provide the layer you want (int)
+    ds should contains dx and dy
+    ds should not have assigned coords (x and y are variables, zone is the dimension coordinates (with time))
+    """
+    ds_search = ds.copy()
+    
+    if z is not None:
+        ds_search = ds_search.where(ds_search.z == z, drop=True)
+
+    if x is not None:
+        assert y is not None, 'if x is provided, y cannot be None'
+        ## mask = ds.sel(x=x, y=y, method='nearest') # possible uniquement si x,y sont des coordonnées/dim
+        nearest = _nearest_node(np.array([(x, y)]), np.array(list(zip(ds_search['x'].data, ds_search['y'].data))))
+        nearest_zone = ds_search.isel(zone=nearest)
+        
+        # check if xy is in a cell == dx and dy are not greater than grid resolution
+        dx = np.abs(nearest_zone.x.data - x)
+        dy = np.abs(nearest_zone.y.data - y)
+        mask = ds_search['zone'] == nearest_zone.zone if (dx <= nearest_zone.dx.data) & (dy <= nearest_zone.dy.data) else ds_search['zone'].isnull()
+
+    if i is not None:
+        assert j is not None, 'if i is provided, j cannot be None'
+        mask = (ds_search['col'] == i) & (ds_search['lig'] == j)
+
+    # zone = ds.where(mask, drop=True)['zone'].data
+    zone = ds_search.where(mask, drop=True)
+    return zone

From 9c258beac06535f5097e4896b3022210f04e2ecf Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Fri, 14 Feb 2025 10:55:58 +0100
Subject: [PATCH 08/31] dev: add reprojection & minor fixes

---
 pyproject.toml                      |  1 +
 src/gridmarthe/operasem/geometry.py | 11 +++++++----
 src/gridmarthe/operasem/gis.py      | 13 ++++++-------
 3 files changed, 14 insertions(+), 11 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index ac6fb6f..9185f89 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -53,6 +53,7 @@ dependencies = [
     "pandas",
     "h5netcdf",
     "xarray",
+    "pyproj",
     "shapely",
     "matplotlib",
     "geopandas",
diff --git a/src/gridmarthe/operasem/geometry.py b/src/gridmarthe/operasem/geometry.py
index dc2cedb..b998203 100644
--- a/src/gridmarthe/operasem/geometry.py
+++ b/src/gridmarthe/operasem/geometry.py
@@ -14,7 +14,7 @@ def get_mask_array(ds, varname: str='permeab', nanval: list=[-9999., 0.]):
     return ds.where(~ds[varname].isin(nanval), drop=True)
 
 
-def export_mask(ds, varname: str='permeab', nanval: list=[-9999., 0.], fileout: str='mask.shp'):
+def export_mask(ds, varname: str='permeab', nanval: list=[-9999., 0.], fileout=None):
     """ Filter dataset on non-nan values, and dissolve results to get a mask shape 
     input ds should be the permh dataset (read from permh file, ie Horizontal hydraulic conductivity)
     """
@@ -22,7 +22,8 @@ def export_mask(ds, varname: str='permeab', nanval: list=[-9999., 0.], fileout:
     mask = ds.sel(zone=mask['zone'])
     gdf  = to_geodataframe(mask)
     gdf  = gdf.dissolve()
-    gdf.to_file(fileout)
+    if fileout is not None:
+        gdf.to_file(fileout)
     return gdf
 
 
@@ -129,7 +130,7 @@ def compute_geometry(topo, hsubs, mask=None):
     return ds
 
 
-def get_min_layer(ds, aquif_layers=None):
+def get_surface_layer(ds, aquif_layers=None):
     """ Compute surface mask of marthe domain
     
     This function return min layer for every zone of a grimarthe dataset with z coords
@@ -147,7 +148,9 @@ def get_min_layer(ds, aquif_layers=None):
     ----------
         ds: xr.Dataset
         aquif_layers: sequence (list, tuple, array) of int
-            representing layers to subset ds
+            representing layers to subset ds. Only active domain must 
+            be passed to function (ie drop nan first)
+            
     Returns
     -------
         surface_mask: xr.Dataset
diff --git a/src/gridmarthe/operasem/gis.py b/src/gridmarthe/operasem/gis.py
index 8fe95f1..fe7dc15 100644
--- a/src/gridmarthe/operasem/gis.py
+++ b/src/gridmarthe/operasem/gis.py
@@ -9,19 +9,18 @@
 from pyproj import Transformer
 
 
-
-def transf_proj(ds, from_epsg="EPSG:2154", to_epsg="EPSG:27572"):
+def transf_proj(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154"):
     """ Transform coordinates of a dataset using pyproj.
     """
     transformer = Transformer.from_crs(from_epsg, to_epsg, always_xy=True)
-    x_source, y_source = ds.x.data, ds.y.values
+    x_source, y_source = ds.x.data, ds.y.data
     x_target, y_target = transformer.transform(x_source, y_source)
     ds = ds.copy()
-    ds['x'], ds['y'] = x_target, y_target
+    ds['x'].data, ds['y'].data = x_target, y_target
+    ds.attrs['projection'] = to_epsg
     return ds
 
 
-
 def _mk_cell_polygon(xleft, ylower, xright, yupper):
     return Polygon(
         (
@@ -52,7 +51,7 @@ def to_geodataframe(ds, epsg='EPSG:27572', fmt='long'):
     fmt must be long or wide, default is long
     """
     
-    polygons = _build_polyg(ds.isel(time=0))
+    polygons = _build_polyg(ds) # .isel(time=0) # x,y does not vary in time
     df = ds.to_dataframe() #.to_pandas() # only for 1 dim
     
     if 'time' in ds.dims.keys():
@@ -64,7 +63,7 @@ def to_geodataframe(ds, epsg='EPSG:27572', fmt='long'):
         crs=epsg
     )
     
-    if fmt == "wide":
+    if fmt == "wide" and 'time' in ds.dims.keys():
         # here no wide fmt if no time, so no if 'time' in ds.dims.keys():
         gdf = gdf.unstack('time')
         gdf.columns = [

From 44b40b64b5db016c2c9ea4e38652002be511b595 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Fri, 14 Feb 2025 12:33:54 +0100
Subject: [PATCH 09/31] fix: plot outcrop for xarray dataset

---
 src/gridmarthe/plot.py     | 31 ++++++++++++++-----
 tests/test_surface_mask.py | 61 ++++++++++++++++++++++++++++++++++++++
 2 files changed, 84 insertions(+), 8 deletions(-)
 create mode 100644 tests/test_surface_mask.py

diff --git a/src/gridmarthe/plot.py b/src/gridmarthe/plot.py
index ebbc1c3..00cc044 100644
--- a/src/gridmarthe/plot.py
+++ b/src/gridmarthe/plot.py
@@ -13,6 +13,16 @@
 """ Module for visualisation of gridmarthe files
 """
 
+
+def _set_map_lims(ax, xmin, ymin, xmax, ymax, perc=.05):
+    x_range = xmax - xmin
+    y_range = ymax - ymin
+    # and add 5% margin around bounds (2.5% on each side)
+    ax.set_xlim([xmin - (perc * x_range)/2, xmax + (perc * x_range)/2])
+    ax.set_ylim([ymin - (perc * y_range)/2, ymax + (perc * y_range)/2])
+    return None
+
+
 def plot_nested_grid(da, ax=None, var='charge', **kwargs):
     """ Usefull function to plot nested grids, keeping heterogeneous resolution
     TODO: remove var arg: should be a xr.DataArray with coords assigned, same as xarray API for plots
@@ -55,6 +65,8 @@ def plot_nested_grid(da, ax=None, var='charge', **kwargs):
         gig[var].plot.pcolormesh(x='x', y='y', ax=ax, vmin=vmin, vmax=vmax, add_colorbar=False, **{k:v for k,v in kwargs.items() if k != 'add_colorbar'})
     grid[var].plot.pcolormesh(x='x', y='y', ax=ax, vmin=vmin, vmax=vmax, cbar_kwargs=cbar_kwargs, **kwargs)
     
+    _set_map_lims(ax, da.x.min().data, da.y.min().data, da.x.max().data, da.y.max().data)
+    
     return ax
 
 def plot_mesh_time_serie(*arg, zone: int, varname='charge', show=False, figsize=(12,4), **kwargs):
@@ -114,16 +126,18 @@ def plot_outcrop(ds_outcrop, fout=None, engine='xr', show=False):
     """
     if isinstance(ds_outcrop, xr.Dataset):
         assert 'z' in ds_outcrop.keys(), "No `z` dimension. Outcrop plot is not possible."
-        maxn = np.max(ds_outcrop['z'].data)
-    elif isinstance(ds_outcrop, gpd.GeoDataframe):
+        maxn = np.nanmax(ds_outcrop['z'].data)
+    elif isinstance(ds_outcrop, gpd.geodataframe.GeoDataFrame):
         assert 'z' in ds_outcrop.columns, "No `z` dimension. Outcrop plot is not possible."
-        maxn = np.max(ds_outcrop['z'].to_numpy())
+        maxn = np.nanmax(ds_outcrop['z'].to_numpy())
 
     # custom cbar to force categories
     cmap = cm.tab10 if maxn <= 10 else cm.tab20
-    cmap = colors.ListedColormap(cmap.colors[:maxn]) # subset on number of colors, if not wrong legend
+    cmap = colors.ListedColormap(cmap.colors[:int(maxn)]) # subset on number of colors, if not wrong legend
     bounds = np.arange(1, maxn+1)
-    norm = colors.BoundaryNorm(bounds, cmap.N,)  # set bins to custom values
+    if len(bounds) == 1:
+        bounds = np.append(bounds, [maxn+1])
+    norm = colors.BoundaryNorm(bounds, cmap.N+1,)  # set bins to custom values
     cbar = plt.cm.ScalarMappable(norm=norm, cmap=cmap)
     
     fig, ax = plt.subplots(1, 1)
@@ -131,8 +145,9 @@ def plot_outcrop(ds_outcrop, fout=None, engine='xr', show=False):
     cax = divider.append_axes("right", size="5%", pad=0.1)
     
     if engine == 'xr':
-        the_plot = ds_outcrop['z'].plot.pcolormesh(
-            x='x', y='y',
+        the_plot = plot_nested_grid(
+            # x='x', y='y',
+            ds_outcrop, var='z',
             ax=ax,
             cmap=cmap,
             levels=bounds,
@@ -157,7 +172,7 @@ def plot_outcrop(ds_outcrop, fout=None, engine='xr', show=False):
         label='Layers',
     )
     ax_cbar.ax.tick_params(size=0)
-    ax_cbar.set_ticklabels(bounds)
+    ax_cbar.set_ticklabels(ax_cbar.set_ticklabels(['{:.0f}'.format(x) for x in bounds]))
     
     if fout is not None:
         plt.savefig(fout, dpi=300)
diff --git a/tests/test_surface_mask.py b/tests/test_surface_mask.py
new file mode 100644
index 0000000..e0e5b8f
--- /dev/null
+++ b/tests/test_surface_mask.py
@@ -0,0 +1,61 @@
+# import modules
+import gridmarthe as gm
+import matplotlib.pyplot as plt
+
+grid = gm.load_marthe_grid('./data/craie_npc.permh', drop_nan=True)
+surf = gm.get_surface_layer(ds=grid)
+gdf = gm.to_geodataframe(surf)
+gm.plot_outcrop(gdf, engine='gpd')
+plt.show()
+
+toto = gm.assign_coords(surf, add_lay=False)
+# gm.plot_nested_grid(toto, var='z')
+gm.plot_outcrop(toto)
+plt.show()
+
+
+# from matplotlib import pyplot as plt
+# from mpl_toolkits.axes_grid1 import make_axes_locatable
+# from matplotlib import (colors, cm)
+
+# import numpy as np
+# import xarray as xr
+# import geopandas as gpd
+
+# ds_outcrop=toto.copy()
+# ds_outcrop['z'] = ds_outcrop['z']
+# assert 'z' in ds_outcrop.keys(), "No `z` dimension. Outcrop plot is not possible."
+# maxn = np.nanmax(ds_outcrop['z'].data)
+
+# # custom cbar to force categories
+# cmap = cm.tab10 if maxn <= 10 else cm.tab20
+# cmap = colors.ListedColormap(cmap.colors[:int(maxn)]) # subset on number of colors, if not wrong legend
+# bounds = np.arange(1, maxn+1)
+# if len(bounds) == 1:
+#     bounds = np.append(bounds, [maxn+1])
+# norm = colors.BoundaryNorm(bounds, cmap.N+1,)  # set bins to custom values
+# cbar = plt.cm.ScalarMappable(norm=norm, cmap=cmap)
+
+# fig, ax = plt.subplots(1, 1)
+# divider = make_axes_locatable(ax)
+# cax = divider.append_axes("right", size="5%", pad=0.1)
+
+# # the_plot = ds_outcrop['z'].plot.pcolormesh(
+# the_plot = gm.plot_nested_grid(
+#     # x='x', y='y',
+#     ds_outcrop, var='z',
+#     ax=ax,
+#     cmap=cmap,
+#     levels=bounds,
+#     # add_colorbar=False,
+# )
+
+# ax_cbar = fig.colorbar(
+#     cbar, ax=ax, cax=cax,
+#     orientation='vertical',
+#     ticks=[x+0.5 for x in bounds], # set labels in the middle of class
+#     label='Layers',
+# )
+# ax_cbar.ax.tick_params(size=0)
+# ax_cbar.set_ticklabels(ax_cbar.set_ticklabels(['{:.0f}'.format(x) for x in bounds]))
+# plt.show()
\ No newline at end of file

From 8c31daad0bba46ef07fd13ba947aed7e62065f3d Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Fri, 28 Feb 2025 16:11:25 +0100
Subject: [PATCH 10/31] fix: syntax error in gis; add: clip method from
 rioxarray

---
 src/gridmarthe/operasem/geometry.py |  2 +-
 src/gridmarthe/operasem/gis.py      | 18 +++++++++--
 src/gridmarthe/operasem/interp.py   | 46 ++++++++++++++++++-----------
 3 files changed, 45 insertions(+), 21 deletions(-)

diff --git a/src/gridmarthe/operasem/geometry.py b/src/gridmarthe/operasem/geometry.py
index b998203..07a34e5 100644
--- a/src/gridmarthe/operasem/geometry.py
+++ b/src/gridmarthe/operasem/geometry.py
@@ -14,7 +14,7 @@ def get_mask_array(ds, varname: str='permeab', nanval: list=[-9999., 0.]):
     return ds.where(~ds[varname].isin(nanval), drop=True)
 
 
-def export_mask(ds, varname: str='permeab', nanval: list=[-9999., 0.], fileout=None):
+def get_active_mask(ds, varname: str='permeab', nanval: list=[-9999., 0.], fileout=None):
     """ Filter dataset on non-nan values, and dissolve results to get a mask shape 
     input ds should be the permh dataset (read from permh file, ie Horizontal hydraulic conductivity)
     """
diff --git a/src/gridmarthe/operasem/gis.py b/src/gridmarthe/operasem/gis.py
index fe7dc15..9f8b3fd 100644
--- a/src/gridmarthe/operasem/gis.py
+++ b/src/gridmarthe/operasem/gis.py
@@ -16,7 +16,7 @@ def transf_proj(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154"):
     x_source, y_source = ds.x.data, ds.y.data
     x_target, y_target = transformer.transform(x_source, y_source)
     ds = ds.copy()
-    ds['x'].data, ds['y'].data = x_target, y_target
+    ds['x'].data, ds['y'].data = np.astype(x_target, np.float32), np.astype(y_target, np.float32)
     ds.attrs['projection'] = to_epsg
     return ds
 
@@ -71,12 +71,24 @@ def to_geodataframe(ds, epsg='EPSG:27572', fmt='long'):
             if x not in ['x', 'y', 'dx', 'dy', 'z', 'geometry'] else x\
             for x, y in gdf.columns
         ]
-        gdf = gdf.loc[:,~gdf.columns.duplicated()].copy() # drop duplicated cols
-        gdf = gdf.set_geometry('geometry') # need to make again geom after drop dupl
+        gdf = gdf.loc[:,~gdf.columns.duplicated()].copy()  # drop duplicated cols
+        gdf = gdf.set_geometry('geometry')  # need to make again geom after drop dupl
     
     return gdf
 
 
+def clip_dataset(ds, gdf, crs=27572, engine='gdf'):
+    """ Clip a xarray Dataset with a gpd.GeoDataFrame
+    Needs rioxarray
+    See: https://corteva.github.io/rioxarray/html/examples/clip_geom.html
+    Todo: shapely version
+    """
+    shp = gdf.to_crs(crs)
+    da = gm.assign_coords(ds.rio.write_crs("EPSG:{}".format(crs)))
+    clipped_da = da.rio.clip(shp.geometry.values, shp.crs, drop=True)
+    return clipped_da
+
+
 def subset_with_coords(da, dims=['x', 'y'], gdf=None, xmin=None, ymin=None, xmax=None, ymax=None):
     """
     subset DataArray or Dataset with gpd.GeoDataFrame or bounds
diff --git a/src/gridmarthe/operasem/interp.py b/src/gridmarthe/operasem/interp.py
index 50ac24f..0a556c6 100644
--- a/src/gridmarthe/operasem/interp.py
+++ b/src/gridmarthe/operasem/interp.py
@@ -18,22 +18,6 @@ def get_new_coords(ds, res=1000):
     return new_x, new_y
 
 
-def coarse_nested_grid(da, varname='charge', dx=None, dy=None):
-    """ Coarse nested grid to res of main grid
-    only realy valid if nested grid resolution is a multiple of maingrid resolution
-    coords needs to be assign first
-    """
-    if dx is None or dy is None:
-        dx, dy = _get_scale(da)
-    dx1, dy1 = dx.pop(0), dy.pop(0)
-    grid = da.where(da['dx'] == dx1, drop=True) # & da['dy'] == dy1
-    for dx2, dy2 in zip(dx, dy):
-        gig = da.where(da['dx'] == dx2, drop=True)
-        gig = gig[varname].coarsen(x=int(dx1/dx2), y=int(dy1/dy2), boundary='trim').mean()
-        grid = xr.combine_by_coords([grid, gig])
-    return grid
-
-
 def interp_grid(da, new_x=None, new_y=None, method='nearest', **kwargs):
     """ Interpolate on a new grid using `xarray.Dataset.interp`
 
@@ -62,7 +46,7 @@ def interp_grid(da, new_x=None, new_y=None, method='nearest', **kwargs):
     return da.interp(x=new_x, y=new_y, method=method, **kwargs)
 
 
-def rescale(da, res=1000, **kwargs):
+def rescale_grid(da, res=1000, **kwargs):
     """ Wrapper function that uses `get_new_coords()` and `interp_grid()` together
     
     See also
@@ -74,3 +58,31 @@ def rescale(da, res=1000, **kwargs):
     new_da = interp_grid(da, new_x, new_y, **kwargs) # here da with assign coords
     return new_da
 
+
+def coarse_nested_grid(da, varname='charge', dx=None, dy=None):
+    """ Coarse nested grid to res of main grid
+    only realy valid if nested grid resolution is a multiple of maingrid resolution
+    coords needs to be assign first
+    """
+    if dx is None or dy is None:
+        dx, dy = _get_scale(da)
+    dx1, dy1 = dx.pop(0), dy.pop(0)
+    grid = da.where(da['dx'] == dx1, drop=True) # & da['dy'] == dy1
+    for dx2, dy2 in zip(dx, dy):
+        gig = da.where(da['dx'] == dx2, drop=True)
+        gig = gig[varname].coarsen(x=int(dx1/dx2), y=int(dy1/dy2), boundary='trim').mean()
+        grid = xr.combine_by_coords([grid, gig])
+    return grid
+
+
+def aggregate_to_grid(value_grid, target_grid):
+    # Définir un facteur d'agrégation basé sur les résolutions
+    factor_x = int(round((value_grid.x.size / target_grid.x.size)))
+    factor_y = int(round((value_grid.y.size / target_grid.y.size)))
+
+    # Vérifier que le facteur est valide
+    if factor_x > 1 and factor_y > 1:
+        value_grid_coarse = value_grid.coarsen(x=factor_x, y=factor_y, boundary="trim").mean()
+    else:
+        raise ValueError("Les tailles des grilles ne permettent pas une agrégation nette.")
+    return value_grid_coarse

From d609601c8051d4366232217a273be4d23b00ac0b Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Fri, 28 Feb 2025 16:12:01 +0100
Subject: [PATCH 11/31] dev: fix+add docstring for plot outcrop methods

---
 src/gridmarthe/plot.py | 34 +++++++++++++++++++++++-----------
 1 file changed, 23 insertions(+), 11 deletions(-)

diff --git a/src/gridmarthe/plot.py b/src/gridmarthe/plot.py
index 00cc044..71a2cd6 100644
--- a/src/gridmarthe/plot.py
+++ b/src/gridmarthe/plot.py
@@ -105,24 +105,37 @@ def plot_mesh_time_serie(*arg, zone: int, varname='charge', show=False, figsize=
         plt.show(block=False)
     return ax
 
-def plot_outcrop(ds_outcrop, fout=None, engine='xr', show=False):
+def plot_outcrop(ds_outcrop, file_out=None, engine='xr', show=False):
     
     """ Usefull function to plot outcrop layers of a marthe (multilayer) grid
     
-    The Marthe grid must have a `z` dimension.
-    
-    There is two mode implementend yet, using xr.plot or gpd.plot (useful for nested grid)
-    TODO xr version for nested with `plot_nested_grid()`, see func below in src
+    There is two mode implementend yet, using xr.plot or
+    gpd.plot (useful for nested grid)
 
-    if engine == 'xr' => ds_outcrop need to get coords before (use `gm.assign_coords(ds_outcrop, add_lay=False)`)
-    if engine == 'gpd => ds_outcrop need to be a gpd.GeoDataframe (use `gm.to_geodataframe(ds_outcrop)`)
+    if engine == 'xr' => ds_outcrop need to get coords before
+        (use `gm.assign_coords(ds_outcrop, add_lay=False)`)
+    if engine == 'gpd => ds_outcrop need to be a gpd.GeoDataframe
+        (use `gm.to_geodataframe(ds_outcrop)`)
+    
+    nb: The Marthe grid must have a `z` dimension.
     
     Parameters
     ----------
-    TODO docstring
+    ds_outcrop: xr.Dataset
+        output of `gm.get_surface_mask()`
+    
+    file_out: str, Optionnal.
+        If not None (default), file name to write plot
+    
+    engine: str, Optionnal.
+        Engine to use for plotting (default is `xr`).
+    
+    show: bool, Optionnal.
+        Show result (`plt.show()`), default is False.
     
     Returns
     -------
+    fig, ax, ax_cbar if not `show`, otherwise return None
     """
     if isinstance(ds_outcrop, xr.Dataset):
         assert 'z' in ds_outcrop.keys(), "No `z` dimension. Outcrop plot is not possible."
@@ -146,7 +159,6 @@ def plot_outcrop(ds_outcrop, fout=None, engine='xr', show=False):
     
     if engine == 'xr':
         the_plot = plot_nested_grid(
-            # x='x', y='y',
             ds_outcrop, var='z',
             ax=ax,
             cmap=cmap,
@@ -174,8 +186,8 @@ def plot_outcrop(ds_outcrop, fout=None, engine='xr', show=False):
     ax_cbar.ax.tick_params(size=0)
     ax_cbar.set_ticklabels(ax_cbar.set_ticklabels(['{:.0f}'.format(x) for x in bounds]))
     
-    if fout is not None:
-        plt.savefig(fout, dpi=300)
+    if file_out is not None:
+        plt.savefig(file_out, dpi=300)
     if show:
         plt.show()
         plt.close()

From 2bcd70784b9f3854ff3275d1522cbb9e2b8648fa Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Wed, 5 Mar 2025 11:47:01 +0100
Subject: [PATCH 12/31] fix: bad float kind for fortran writing module, wrong
 end_index for xcol, dx in write mod

---
 .gitignore                                 |   1 +
 src/gridmarthe/__init__.py                 |   4 -
 src/gridmarthe/gridmarthe.py               |  10 +-
 src/gridmarthe/lecsem/__init__.py          |   2 +-
 src/gridmarthe/lecsem/_parse_gridmarthe.py |  20 ++--
 src/gridmarthe/lecsem/edsemigl.f90         |  19 ++--
 src/gridmarthe/lecsem/lecsem.f90           |  35 +++++++
 src/gridmarthe/lecsem/scan_grid.f90        | 101 +++++++++++++--------
 src/gridmarthe/operasem/gis.py             |   5 +-
 src/gridmarthe/utils.py                    |   4 +-
 tests/test_edsemi.py                       |  21 +++--
 11 files changed, 144 insertions(+), 78 deletions(-)

diff --git a/.gitignore b/.gitignore
index fa02029..bf12a3b 100644
--- a/.gitignore
+++ b/.gitignore
@@ -5,6 +5,7 @@ __pycache__/
 
 # C extensions
 *.so
+*.mod
 *.pyd
 *.dll
 
diff --git a/src/gridmarthe/__init__.py b/src/gridmarthe/__init__.py
index 2fd6e9c..9264373 100644
--- a/src/gridmarthe/__init__.py
+++ b/src/gridmarthe/__init__.py
@@ -24,7 +24,6 @@
 import xarray as xr
 from typing import Union
 
-
 from .__version__ import __version__
 from .gridmarthe import *
 from .operasem import *
@@ -74,9 +73,6 @@ def to_raster(self, x_dim='x', y_dim='y', time=None, epsg=27572, fout_template='
         
         return None
     
-    def get_outcrop(self, subset_layers=None):
-        return get_min_layer(self.obj, subset_layers)
-    
     def subset_coords(self, dims=['x', 'y'], gdf=None, xmin=None, ymin=None, xmax=None, ymax=None):
         return subset_with_coords(self.obj, dims, gdf, xmin, ymin, xmax, ymax)
     
diff --git a/src/gridmarthe/gridmarthe.py b/src/gridmarthe/gridmarthe.py
index baaad02..4181d1f 100644
--- a/src/gridmarthe/gridmarthe.py
+++ b/src/gridmarthe/gridmarthe.py
@@ -6,10 +6,10 @@
 
 import pandas as pd
 import numpy as np
-import xarray as xr #needs netcdf4
+import xarray as xr
 
 from .lecsem import (
-    _lecsem,
+    modgridmarthe,
     _read_marthe_grid,
     _transform_xcoords,
     _transform_ycoords,
@@ -347,7 +347,7 @@ def load_marthe_grid(
         data_vars=dic_data,
         coords={
             'time': dates,
-            'zone': range(1, zvar.shape[1] + 1),
+            'zone': np.arange(1, zvar.shape[1] + 1, dtype=np.int32),
             # 'xc': (['zone'], xcols), # TODO coordinates directly as coords depending on dims ?
             # 'yc': (['zone'], yligs),
             # 'domain_size': dims, # add non dimension coordinate for info
@@ -526,8 +526,8 @@ def write_marthe_grid(ds, fileout='grid.out', varname='charge', file_permh: str
         title = 'Marthe Grid ' # dummy arg to set type as string
     
     # call fortran module to write marthe grid
-    status = _lecsem.modgridmarthe.write_grid(
-        xvar=zvar,
+    status = modgridmarthe.write_grid(
+        zvar=zvar,
         xcol=zxcol,
         ylig=zylig,
         dxlu=zdxlu,
diff --git a/src/gridmarthe/lecsem/__init__.py b/src/gridmarthe/lecsem/__init__.py
index 95ff588..8549712 100644
--- a/src/gridmarthe/lecsem/__init__.py
+++ b/src/gridmarthe/lecsem/__init__.py
@@ -1,5 +1,5 @@
 from ._parse_gridmarthe import (
-    _lecsem,
+    modgridmarthe,
     _read_marthe_grid,
     _transform_xcoords,
     _transform_ycoords,
diff --git a/src/gridmarthe/lecsem/_parse_gridmarthe.py b/src/gridmarthe/lecsem/_parse_gridmarthe.py
index 15c7a43..035ea0c 100644
--- a/src/gridmarthe/lecsem/_parse_gridmarthe.py
+++ b/src/gridmarthe/lecsem/_parse_gridmarthe.py
@@ -4,15 +4,13 @@
 import re
 import numpy as np
 
-from . import lecsem as _lecsem
-
+from .lecsem import modgridmarthe
 from ..utils import _datetime64_to_float
 
 
-
 def scan_var(xfile):
     """ List all variables stored in a Marthe grid file """
-    var = _lecsem.modgridmarthe.scan_typevar(xfile) # get a list of unique type_var that are in xfile
+    var = modgridmarthe.scan_typevar(xfile) # get a list of unique type_var that are in xfile
     var = np.char.strip(np.char.decode(var, 'ISO-8859-1')) # decode byte array provided by f2py
     var = var[var != ''] # get rid of empty element provided by fortran code
     return var
@@ -51,16 +49,16 @@ def _read_marthe_grid(xfile, varname='CHARGE', shallow_only=False):
     dims  : np.array
         list of dimensions of grid [maingrid[x, y, z], nestedgrid1[...], ...]
     """
-    nu_zoomx = _lecsem.modgridmarthe.scan_nu_zoomx(xfile) # scan nb of nested grids (gig)
-    dims, nbsteps = _lecsem.modgridmarthe.scan_dim(xfile, varname, nu_zoomx)
+    nu_zoomx = modgridmarthe.scan_nu_zoomx(xfile) # scan nb of nested grids (gig)
+    dims, nbsteps = modgridmarthe.scan_dim(xfile, varname, nu_zoomx)
     nbtot = np.prod(dims, axis=1).sum() # product deprecated => prod // DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead.
     if nbtot == 0:
         raise ValueError(f'Varname ({varname}) not found in xfile. No data to parse.')
     
     if shallow_only:
-        res = list(_lecsem.modgridmarthe.read_grid_shallow( xfile, varname, nbsteps, dims[0][-1] ,nbtot, nu_zoomx ))
+        res = list(modgridmarthe.read_grid_shallow( xfile, varname, nbsteps, dims[0][-1] ,nbtot, nu_zoomx ))
     else:
-        res = list(_lecsem.modgridmarthe.read_grid( xfile, varname, nbsteps, nbtot, nu_zoomx))
+        res = list(modgridmarthe.read_grid( xfile, varname, nbsteps, nbtot, nu_zoomx))
     
     res.append(dims)
     return res
@@ -114,7 +112,7 @@ def _set_layers(dims):
         for z in range(dims[igig][-1]):
             zlay.append(np.tile(z+1, dims[igig][0] * dims[igig][1]))
     zlay = np.hstack(zlay)
-    return zlay
+    return zlay.astype(np.int32)
 
 
 def _decode_title(title, encoding='ISO-8859-1'):
@@ -194,7 +192,7 @@ def _extract_zvar_from_ds(ds, varname):
 
 if __name__ == '__main__':
     
-    print(_lecsem.__doc__)
-    print(_lecsem.modgridmarthe.__doc__)
+    # print(_lecsem.__doc__)
+    print(modgridmarthe.__doc__)
     
 
diff --git a/src/gridmarthe/lecsem/edsemigl.f90 b/src/gridmarthe/lecsem/edsemigl.f90
index b2d56c1..f74452e 100644
--- a/src/gridmarthe/lecsem/edsemigl.f90
+++ b/src/gridmarthe/lecsem/edsemigl.f90
@@ -17,22 +17,22 @@
 !
 ! (Provenance MARTHE, file : edsemi.f90, convert utf-8 )
 !
-! MARTHE License:
-!Copyright © 2002-2024 BRGM
+! MARTHE, Copyright (c) 1990-2024 BRGM
 !
+! Copyright (c) 1990-2025  BRGM
+
 ! Permission is granted under the following conditions :
 ! The User undertakes:
 ! 1.  To use the software only at his own premises.
 ! 2.  Not to use the software simultaneously on several computers or through a network or server.
 ! 3.  To ensure that the Marthe software is not passed to any third party (subcontractor, client, etc.) and to take every precaution necessary to prevent illegal copying of the software.
-!
+
 ! The User is nevertheless permitted:
 ! 1.  To make one or more backup copies of the software for his own use.
 ! 2.  To install the software on several workstations at his premises (for instance a desktop and a lap top computer) provided that the software will be never used simultaneously on several computers.
 
 ! Limitation of liability:
 ! The greatest care was taken to the realization of this software, however BRGM will not be held liable for any direct or indirect damage (including lost profits, lost savings, costs, fees, or expenses of any kind) rising from the use or impossibility of using the software.
-!
 !
       SUBROUTINE EDSEMI7_0(FONC, NKOL, NLIG, XCOL, YLIG, X0, Y0, INVY &
        ,TITSEM, IEREDI, IOUMAI, DXLU, DYLU)
@@ -228,6 +228,7 @@ END SUBROUTINE Ecrit_Opti_12Car
       ENDDO
       IF ((NLIG <= 0).OR.(NKOL <= 0)) THEN
          IEREDI = 2
+         print *, 'nlig or nkol <= 0'
          GO TO 999
       ENDIF
 !     =========================================================
@@ -245,11 +246,14 @@ END SUBROUTINE Ecrit_Opti_12Car
          ENDIF
          XP = AUX
       ENDDO
+      if (IEREDI == 2) then
+         print *, 'Writing marthe grid Fortran error: X not sorted'
+         ! GO TO 999
+      endif
 !     ===================================================================
 !      Dans cette version : On continue si X = XP ou Y = YP (IEREDI = 1)
 !                       Mais on sort si si X < XP ou Y < YP (IEREDI = 2)
 !     ===================================================================
-      IF (IEREDI == 2) GO TO 999
       DO I=1,NLIG
          IND = MERGE( I , NLIG-I+1 , (INVY >= 1) )
          AUX = YLIG(IND)
@@ -259,7 +263,10 @@ END SUBROUTINE Ecrit_Opti_12Car
          ENDIF
          YP = AUX
       ENDDO
-      IF (IEREDI == 2) GO TO 999
+      IF (IEREDI == 2) then
+         print *, 'Writing marthe grid Fortran error: Y not sorted'
+         GO TO 999
+      endif
       NTOT = NLIG * NKOL
 !     =========================================
 !      Vérification si la Grille est constante
diff --git a/src/gridmarthe/lecsem/lecsem.f90 b/src/gridmarthe/lecsem/lecsem.f90
index dab9fe5..c9093d5 100644
--- a/src/gridmarthe/lecsem/lecsem.f90
+++ b/src/gridmarthe/lecsem/lecsem.f90
@@ -1,4 +1,39 @@
+! Copyright 2024, BRGM
+! 
+! This file is part of Gridmarthe.
+! 
+! Gridmarthe is free software: you can redistribute it and/or modify it under the
+! terms of the GNU General Public License as published by the Free Software
+! Foundation, either version 3 of the License, or (at your option) any later
+! version.
+! 
+! Gridmarthe is distributed in the hope that it will be useful, but WITHOUT ANY
+! WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
+! PARTICULAR PURPOSE. See the GNU General Public License for more details.
+! 
+! You should have received a copy of the GNU General Public License along with
+! Gridmarthe. If not, see <https://www.gnu.org/licenses/>.
+!
+!
 ! (Provenance MARTHE, Fichier : lecsem.f90, convert utf-8 )
+!
+! MARTHE, Copyright (c) 1990-2024 BRGM
+!
+! Copyright (c) 1990-2025  BRGM
+
+! Permission is granted under the following conditions :
+! The User undertakes:
+! 1.  To use the software only at his own premises.
+! 2.  Not to use the software simultaneously on several computers or through a network or server.
+! 3.  To ensure that the Marthe software is not passed to any third party (subcontractor, client, etc.) and to take every precaution necessary to prevent illegal copying of the software.
+
+! The User is nevertheless permitted:
+! 1.  To make one or more backup copies of the software for his own use.
+! 2.  To install the software on several workstations at his premises (for instance a desktop and a lap top computer) provided that the software will be never used simultaneously on several computers.
+
+! Limitation of liability:
+! The greatest care was taken to the realization of this software, however BRGM will not be held liable for any direct or indirect damage (including lost profits, lost savings, costs, fees, or expenses of any kind) rising from the use or impossibility of using the software.
+!
       SUBROUTINE LECSEM8_0(X0, Y0, FONC, XCOL, YLIG, NLIG, NKOL, INVERS, TITSEM &
        , IOUCON, LEC, IERLEC, NUMERR, NTOT &
        , LIRE_DXDY, LU_DXDY, LU_XY, DXLU, DYLU)
diff --git a/src/gridmarthe/lecsem/scan_grid.f90 b/src/gridmarthe/lecsem/scan_grid.f90
index 5400ed6..d33b937 100644
--- a/src/gridmarthe/lecsem/scan_grid.f90
+++ b/src/gridmarthe/lecsem/scan_grid.f90
@@ -1,3 +1,19 @@
+! Copyright 2024, BRGM
+! 
+! This file is part of Gridmarthe.
+! 
+! Gridmarthe is free software: you can redistribute it and/or modify it under the
+! terms of the GNU General Public License as published by the Free Software
+! Foundation, either version 3 of the License, or (at your option) any later
+! version.
+! 
+! Gridmarthe is distributed in the hope that it will be useful, but WITHOUT ANY
+! WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
+! PARTICULAR PURPOSE. See the GNU General Public License for more details.
+! 
+! You should have received a copy of the GNU General Public License along with
+! Gridmarthe. If not, see <https://www.gnu.org/licenses/>.
+!
 MODULE MODGRIDMARTHE
 !   MODGRIDMARTHE
 !   -------------
@@ -30,8 +46,9 @@ MODULE MODGRIDMARTHE
     REAL, DIMENSION(999) :: YLIG        ! YLIG  = Tableau des ordonnées (si LU_XY > 0)
     REAL, DIMENSION(999) :: DXLU        ! DXLU  = DX lus si LU_DXDY > 0
     REAL, DIMENSION(999) :: DYLU        ! DYLU  = DY lus si LU_DXDY > 0
-    REAL    :: X0                       ! X0    = Abscisse du cote ouest de la colonne n°1    (si LU_XY > 0)
-    REAL    :: Y0                       ! Y0    = Ordonnée du    bas     de la ligne   n°NLIG (si LU_XY > 0)
+    REAL  :: X0                         ! X0    = Abscisse du cote ouest de la colonne n°1    (si LU_XY > 0)
+    REAL  :: Y0                         ! Y0    = Ordonnée du    bas     de la ligne   n°NLIG (si LU_XY > 0)
+    REAL  :: DATE                       ! DATE     = Date associée à la Grille
     REAL, DIMENSION(999*999) :: FONC    ! FONC  = Tableau des valeurs lues
     INTEGER :: IERLEC                   ! IERLEC =  0 Si normal
                                         ! IERLEC = -1 Si erreur dans les nombres de Ligne, Colonne ou Panneau
@@ -52,7 +69,6 @@ MODULE MODGRIDMARTHE
     INTEGER    :: NUMERR                ! Maille NUMERR
     INTEGER    :: NCOUC_MX              ! NCOUC_MX = Nombre maxi de Couches
     INTEGER    :: NU_ZOOMX              ! NU_ZOOMX = Nombre maxi de Gigognes
-    REAL       :: DATE                  ! DATE     = Date associée à la Grille
 
 CONTAINS
 
@@ -152,8 +168,8 @@ SUBROUTINE READ_GRID(XFILE, XTYP_DON, KNBSTEP, KNBTOT, KNU_ZOOMX, PVAR, PDATES,
         INTEGER, INTENT(IN)                           :: KNU_ZOOMX
         INTEGER, DIMENSION(KNBSTEP), INTENT(OUT)      :: KSTEPS
         REAL(KIND=4), DIMENSION(KNBSTEP), INTENT(OUT) :: PDATES
-        REAL(KIND=4), DIMENSION(KNBSTEP, KNBTOT), INTENT(OUT) :: PVAR
         REAL(KIND=4), DIMENSION(KNU_ZOOMX + 1, 999), INTENT(OUT) :: PXCOL, PYLIG, PDXLU, PDYLU
+        REAL(KIND=8), DIMENSION(KNBSTEP, KNBTOT), INTENT(OUT) :: PVAR
         CHARACTER (LEN=132), INTENT(OUT)              :: TITSEM             ! Modifs AM: ajout TITSEM dans les sorties de la subroutine (+ ajout en `dummy argument` càd réf dans la list d'arg de la procedure)
         !
         INTEGER    :: ISTEPINC, ISTEP_TEMP, INTOT_TEMP
@@ -201,13 +217,13 @@ SUBROUTINE READ_GRID(XFILE, XTYP_DON, KNBSTEP, KNBTOT, KNU_ZOOMX, PVAR, PDATES,
                     ISTEP_TEMP = ISTEP
                     INTOT_TEMP = 1
                     KSTEPS(ISTEPINC) = ISTEP
-                    PDATES(ISTEPINC) = DATE
+                    PDATES(ISTEPINC) = real(DATE, 4)
                 ENDIF
                 IF (ISTEPINC == 1 .AND. N_COUCH == 1) THEN
-                    PXCOL(NU_ZOO + 1, :NKOL) = XCOL(:NKOL)
-                    PYLIG(NU_ZOO + 1, :NLIG) = YLIG(:NLIG)
-                    PDXLU(NU_ZOO + 1, :NKOL) = DXLU(:NKOL)
-                    PDYLU(NU_ZOO + 1, :NLIG) = DYLU(:NLIG)
+                    PXCOL(NU_ZOO + 1, :NKOL) = real(XCOL(:NKOL), 4)
+                    PYLIG(NU_ZOO + 1, :NLIG) = real(YLIG(:NLIG), 4)
+                    PDXLU(NU_ZOO + 1, :NKOL) = real(DXLU(:NKOL), 4)
+                    PDYLU(NU_ZOO + 1, :NLIG) = real(DYLU(:NLIG), 4)
                 ENDIF
                 PVAR(ISTEPINC, INTOT_TEMP:INTOT_TEMP + NTOT -1) = FONC(:NTOT)
                 INTOT_TEMP = INTOT_TEMP + NTOT
@@ -233,14 +249,14 @@ SUBROUTINE READ_GRID_SHALLOW(XFILE, XTYP_DON, KNBSTEP, KN_COUCHMX, KNBTOT, &
         INTEGER, INTENT(IN)                           :: KNU_ZOOMX
         INTEGER, DIMENSION(KNBSTEP), INTENT(OUT)      :: KSTEPS
         REAL(KIND=4), DIMENSION(KNBSTEP), INTENT(OUT) :: PDATES
-        REAL(KIND=4), DIMENSION(KNBSTEP, KNU_ZOOMX + 1, KNBTOT), INTENT(OUT) :: PVAR
         REAL(KIND=4), DIMENSION(KNU_ZOOMX + 1, 999), INTENT(OUT) :: PXCOL, PYLIG, PDXLU, PDYLU
+        REAL(KIND=8), DIMENSION(KNBSTEP, KNU_ZOOMX + 1, KNBTOT), INTENT(OUT) :: PVAR
         CHARACTER (LEN=132), INTENT(OUT)              :: TITSEM
         !
         !
         INTEGER    :: ISTEPINC, ISTEP_TEMP, INTOT_TEMP, N_COUCH2
-        REAL(KIND=4), DIMENSION(KNBSTEP, KNU_ZOOMX + 1, KN_COUCHMX, KNBTOT) :: ZTEMP
         INTEGER, DIMENSION(KNU_ZOOMX + 1, 3) :: KDIMEN
+        REAL(KIND=8), DIMENSION(KNBSTEP, KNU_ZOOMX + 1, KN_COUCHMX, KNBTOT) :: ZTEMP
         !
         !
         LIRE_DXDY =  1
@@ -287,13 +303,13 @@ SUBROUTINE READ_GRID_SHALLOW(XFILE, XTYP_DON, KNBSTEP, KN_COUCHMX, KNBTOT, &
                     ISTEP_TEMP = ISTEP
                     INTOT_TEMP = 1
                     KSTEPS(ISTEPINC) = ISTEP
-                    PDATES(ISTEPINC) = DATE
+                    PDATES(ISTEPINC) = real(DATE, 4)
                 ENDIF
                 IF (ISTEPINC == 1 .AND. N_COUCH == 1) THEN
-                    PXCOL(NU_ZOO + 1, :NKOL) = XCOL(:NKOL)
-                    PYLIG(NU_ZOO + 1, :NLIG) = YLIG(:NLIG)
-                    PDXLU(NU_ZOO + 1, :NKOL) = DXLU(:NKOL)
-                    PDYLU(NU_ZOO + 1, :NLIG) = DYLU(:NLIG)
+                    PXCOL(NU_ZOO + 1, :NKOL) = real(XCOL(:NKOL), 4)
+                    PYLIG(NU_ZOO + 1, :NLIG) = real(YLIG(:NLIG), 4)
+                    PDXLU(NU_ZOO + 1, :NKOL) = real(DXLU(:NKOL), 4)
+                    PDYLU(NU_ZOO + 1, :NLIG) = real(DYLU(:NLIG), 4)
                 ENDIF
                 ZTEMP(ISTEPINC, NU_ZOO + 1, N_COUCH, :NTOT) = FONC(:NTOT)
             ENDIF
@@ -384,20 +400,21 @@ end function is_in_array_strings
     !
     !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
     !
-    SUBROUTINE WRITE_GRID(XVAR, XCOL, YLIG, DXLU, DYLU, TYP_DON, TITSEM, &
+    SUBROUTINE WRITE_GRID(ZVAR, XCOL, YLIG, DXLU, DYLU, TYP_DON, TITSEM, &
                           N_DIMS, NVAL, NGRID, NSTEPS, DATES, XFILE, DEBUG, IEREDI)
         ! --- Write array to Marthe Grid format (v9.0) ---
-        ! XVAR should not have missing value (if nan, set 9999. before writing !)
-        ! BUT, XVAR should contain all possible value (9999. if nan but do NOT drop nan before)
-        ! XVAR shoult be sorted according to sorted indexes (in this order) : Time(asc), GRID(main/gig, asc) LAYER(asc), YCOL (dsc), XCOL (asc)
+        ! ZVAR should not have missing value (if nan, set 9999. before writing !)
+        ! BUT, ZVAR should contain all possible value (9999. if nan but do NOT drop nan before)
+        ! ZVAR shoult be sorted according to sorted indexes (in this order) : 
+        !       Time(asc), GRID(main/gig, asc) LAYER(asc), YCOL (dsc), XCOL (asc)
         IMPLICIT NONE
         !
         !inputs
         integer, intent(in)                          :: NVAL, NGRID, NSTEPS
         integer, intent(in), dimension(NGRID, 3)     :: N_DIMS
-        real(KIND=4), intent(in), dimension(NSTEPS, NVAL) :: XVAR
-        real(KIND=4), intent(in), dimension(NVAL)         :: DXLU, DYLU, XCOL, YLIG
-        real(KIND=4), intent(in), dimension(NSTEPS)       :: DATES
+        real(kind=8), intent(in), dimension(NSTEPS, NVAL) :: ZVAR
+        real(kind=4), intent(in), dimension(NVAL)         :: DXLU, DYLU, XCOL, YLIG
+        real(kind=4), intent(in), dimension(NSTEPS)       :: DATES
         character(len=13)  , intent(in)              :: TYP_DON
         character(len=132) , intent(in)              :: TITSEM, XFILE
         logical, optional                            :: DEBUG
@@ -407,8 +424,9 @@ SUBROUTINE WRITE_GRID(XVAR, XCOL, YLIG, DXLU, DYLU, TYP_DON, TITSEM, &
         !
         ! local
         integer :: ISTEP, TMP_ISTEP, NU_ZOO, NU_GRID, N_COUCH, LEC, INVY, NKOL, NLIG, NTOT, NLAY, NGIG, start_idx, end_idx, shift, i
-        real(KIND=4) :: X0, Y0
-        real(KIND=4), dimension(:), allocatable :: XTEMPVAR, XTEMPCOL, YTEMPLIG, DXTEMP, DYTEMP
+        real :: X0, Y0
+        real, dimension(:), allocatable :: XTEMPCOL, YTEMPLIG, DXTEMP, DYTEMP
+        real, dimension(:), allocatable :: ZTEMPVAR
         logical :: DEBUGG
         
         INVY   = 0
@@ -435,7 +453,7 @@ SUBROUTINE WRITE_GRID(XVAR, XCOL, YLIG, DXLU, DYLU, TYP_DON, TITSEM, &
                 NKOL = N_DIMS(NU_GRID, 1)
                 NLIG = N_DIMS(NU_GRID, 2)
                 
-                ! To navigate through XVAR, before computing start_idx, end_idx based on NLAY, NLIG, NKOL,
+                ! To navigate through ZVAR, before computing start_idx, end_idx based on NLAY, NLIG, NKOL,
                 ! we compute a 'shift' index, to jump over previous grids, if id_grid > 0
                 ! number of value to skip depends on nlay and nkol, nlig of every previous grid (main, and each gig)
                 ! wich might not be equals
@@ -453,20 +471,16 @@ SUBROUTINE WRITE_GRID(XVAR, XCOL, YLIG, DXLU, DYLU, TYP_DON, TITSEM, &
                     start_idx = ((N_COUCH - 1) * NTOT ) + shift + 1     ! +1 to get 0-based (n-couch -1) to 1-based starting index. if 1st layer return 1 (cause n-couch-1 would be 0)
                     end_idx   = start_idx + NTOT - 1                    ! here minus 1 cause upper bound is included in fortran, would cause error (idx > len)
                     
-                    ! if (DEBUG) then
-                    ! print *, 'start_idx=', start_idx, 'end_idx=', end_idx
-                    ! endif
-                    
-                    XTEMPVAR = XVAR(ISTEP, start_idx:end_idx)
-                    XTEMPCOL = XCOL(start_idx:end_idx)      ! x is repeated for every different y, but EDSEMI_3 will subset to NKOL
-                    YTEMPLIG = YLIG(start_idx:end_idx:NKOL) ! here, same y for each x, so we sample y every nkol (n_x) to get every unique y values, EDSEMI_3 will subset to NLIG
-                    DXTEMP   = DXLU(start_idx:end_idx)
-                    DYTEMP   = DYLU(start_idx:end_idx:NKOL) ! same here
+                    ! Get current var and coords + transf to real 8 for edsemigl
+                    ZTEMPVAR = ZVAR(ISTEP, start_idx:end_idx)
+                    XTEMPCOL = XCOL(start_idx:start_idx + NKOL - 1)  ! x is repeated for every different y, but EDSEMI_3 will subset to NKOL
+                    YTEMPLIG = YLIG(start_idx:end_idx:NKOL)          ! here, same y for each x, so we sample y every nkol (n_x) to get every unique y values, EDSEMI_3 will subset to NLIG
+                    DXTEMP   = DXLU(start_idx:start_idx + NKOL - 1)
+                    DYTEMP   = DYLU(start_idx:end_idx:NKOL)
                     !
                     X0 = minval(XTEMPCOL) - (DXTEMP(1)/2)                   ! x0 is lowerleft coordinate, xy read are center of cells
                     Y0 = minval(YTEMPLIG) - (DYTEMP(Ubound(DYTEMP, 1))/2)   ! y0 is lowerleft coordinate, xy read are center of cells
                     !
-                    !
                     ! ISTEP = -9999 is code value for no timestep (eg. used in parameters field)
                     IF (DATE == 0.) THEN
                         TMP_ISTEP = -9999
@@ -475,7 +489,7 @@ SUBROUTINE WRITE_GRID(XVAR, XCOL, YLIG, DXLU, DYLU, TYP_DON, TITSEM, &
                     ENDIF
                     
                     CALL EDSEMI_3(&
-                        XTEMPVAR, NKOL, NLIG, XTEMPCOL, YTEMPLIG, X0, Y0, INVY &
+                        ZTEMPVAR, NKOL, NLIG, XTEMPCOL, YTEMPLIG, X0, Y0, INVY &
                         ,TITSEM, IEREDI, LEC, TYP_DON &
                         ! //////// Not used now
                         ,TYP_DON3, N_ELEMCH, &
@@ -490,9 +504,16 @@ SUBROUTINE WRITE_GRID(XVAR, XCOL, YLIG, DXLU, DYLU, TYP_DON, TITSEM, &
                     if (IEREDI /= 0) then
                         if (DEBUGG) then
                             ! errors might come from non-sorted XY or negatives XY
-                            write (LEC, *),"Writing error, status ", IEREDI, "Lay=", N_COUCH, "Grid=", NU_ZOO, "X0=", X0, "Y0=", Y0
-                            write (LEC, *), XTEMPCOL, ''
-                            write (LEC, *), YTEMPLIG, ''
+                            write (LEC, *)"Writing error, status ", IEREDI
+                            write (LEC, *) "Lay=", N_COUCH, "Grid=", NU_ZOO, "X0=", X0, "Y0=", Y0
+                            write (LEC, *) "NCOL=", NKOL, "NLIG=", NLIG, 'NTOT=', NTOT
+                            write (LEC, *) "len(X)=", size(XTEMPCOL), "len(Y)=", size(YTEMPLIG), "len(v)", size(ZTEMPVAR)
+                            write (LEC, *) 'start_idx=', start_idx, 'end_idx=', end_idx, 'shift_idx=', shift
+                            write (LEC, *) 'X: ', XTEMPCOL, ''
+                            write (LEC, *) 'Y: ', YTEMPLIG, ''
+                            write (LEC, *) 'dx:', DXTEMP, ''
+                            write (LEC, *) 'dy:', DYTEMP, ''
+                            write (LEC, *) 'v: ', ZTEMPVAR, ''
                         endif
                     endif
                     !
diff --git a/src/gridmarthe/operasem/gis.py b/src/gridmarthe/operasem/gis.py
index 9f8b3fd..6b781cb 100644
--- a/src/gridmarthe/operasem/gis.py
+++ b/src/gridmarthe/operasem/gis.py
@@ -4,9 +4,10 @@
 import numpy as np
 
 from shapely.geometry import Polygon
+from pyproj import Transformer
 import geopandas as gpd
 
-from pyproj import Transformer
+from ..utils import assign_coords
 
 
 def transf_proj(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154"):
@@ -84,7 +85,7 @@ def clip_dataset(ds, gdf, crs=27572, engine='gdf'):
     Todo: shapely version
     """
     shp = gdf.to_crs(crs)
-    da = gm.assign_coords(ds.rio.write_crs("EPSG:{}".format(crs)))
+    da  = assign_coords(ds.rio.write_crs("EPSG:{}".format(crs)))
     clipped_da = da.rio.clip(shp.geometry.values, shp.crs, drop=True)
     return clipped_da
 
diff --git a/src/gridmarthe/utils.py b/src/gridmarthe/utils.py
index 0a92772..58135d3 100644
--- a/src/gridmarthe/utils.py
+++ b/src/gridmarthe/utils.py
@@ -152,7 +152,7 @@ def assign_coords(da_in, add_lay=True, coords=['x', 'y', 'z'], keep_zone=False,
     
     da = da.set_index(zone=dims)
     if not keep_zone:
-        da = da.drop_duplicates(zone_label).unstack(zone_label) # drop duplicates is a security for nested grids, if dropnan was not performed
+        da = da.drop_duplicates(zone_label).unstack(zone_label)  # drop duplicates is a security for nested grids, if dropnan was not performed
     return da.sortby(dims)
 
 
@@ -177,4 +177,4 @@ def stack_coords(ds, coords=['z', 'y', 'x'], dropna=False):
     
     if dropna:
         ds3 = ds3.dropna(dim='zone')
-    return ds3
\ No newline at end of file
+    return ds3
diff --git a/tests/test_edsemi.py b/tests/test_edsemi.py
index 2eeef61..51129bb 100644
--- a/tests/test_edsemi.py
+++ b/tests/test_edsemi.py
@@ -1,6 +1,6 @@
 
 import gridmarthe as gm
-from gridmarthe.gridmarthe import _extract_zvar, _parse_dims
+from gridmarthe.lecsem import _extract_zvar_from_ds, _parse_dims_from_xr_attrs, modgridmarthe
 import numpy as np
 
 
@@ -8,25 +8,26 @@
     
     import os;os.chdir('./tests')
     
-    martfile = './data/craie_npc.permh'
-    martfile = './data/Somme_V3_Surfex.permh'
+    martfile = './data/craie_npc.permh'   # multilayer
+    martfile = './data/Somme_V3_Surfex.permh'  # nested
+    martfile = './data/hallue.permh'  # simple, single layer
     varname  = 'PERMEAB'
     
     
     ds = gm.load_marthe_grid(martfile, varname)
 
-    dims = _parse_dims(ds.attrs.get('original_dimensions'))
+    dims = _parse_dims_from_xr_attrs(ds.attrs.get('original_dimensions'))
     (
         zvar, zdates,
         zxcol, zylig, zdxlu, zdylu,
         ztitle, izdates
-    ) = _extract_zvar(ds, varname.lower())
+    ) = _extract_zvar_from_ds(ds, varname.lower())
     
     np.prod(np.array(dims), axis=1).sum() == np.size(zvar)
     
     # help(gm.lecsem.modgridmarthe.write_grid)
-    gm.lecsem.modgridmarthe.write_grid(
-        xvar=zvar,
+    modgridmarthe.write_grid(
+        zvar=zvar,
         xcol=zxcol,
         ylig=zylig,
         dxlu=zdxlu.round(2),
@@ -42,5 +43,11 @@
         xfile='test.out'
     )
 
+    # t = np.arange(1, 2862)
+    # t2 = np.arange(1, 2862, dtype=np.int32)
+    # t.dtype
+    # t2.dtype
+    # np.allclose(t, t2)
+
     ds2 = gm.load_marthe_grid(martfile, varname, drop_nan=True, nanval=[0.,-9999.])
     gm.write_marthe_grid(ds2, varname='permeab', file_permh=martfile)

From 32d836a21a7e7ca721a92548a57827ddb99e62f4 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Fri, 14 Mar 2025 14:48:36 +0100
Subject: [PATCH 13/31] fix ncmart conflict in variables

---
 src/gridmarthe/scripts/ncmart.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/gridmarthe/scripts/ncmart.py b/src/gridmarthe/scripts/ncmart.py
index 184afdb..b7d794e 100644
--- a/src/gridmarthe/scripts/ncmart.py
+++ b/src/gridmarthe/scripts/ncmart.py
@@ -24,11 +24,11 @@ def parse_args():
     
     parser.add_argument('opt', metavar='grid timesteps', type=str, nargs='*', help='Paths to grid and timesteps files are expected') # nargs='+'
     parser.add_argument('--output'  , '-o', type=str, default=None, help='Output filename. Default is input.nc')
-    parser.add_argument('--variable', '-v', type=str, default=None, help='Variable to read, default is None; i.e variable will be parsed from file and ONLY the first variable will be read.')
+    parser.add_argument('--variable', '-v', type=str, default=None, help='Variable (field) to read, default is None; i.e variable will be parsed from file and ONLY the first variable will be read.')
     parser.add_argument('--as2d'    , '-d', action="store_const", const=True, default=False, help='Store grid as 2D (or more), default is 1D for space dimension') #choices=('True','False'), dest='monnomdevariable'
     parser.add_argument('--xyfactor', '-x', type=float, default=1., help='Transformation factor for coordinates. Optionnal, default is 1 (no transformation).')
     # parser.add_argument('--show', type=str, default='', choices=('c', 'w'), help='Print licensing for warranty (w) and redistribution conditions (c)')
-    parser.add_argument('--version', '-v', action="store_const", const=True, default=False, help='Show version and exit')
+    parser.add_argument('--version', '-V', action="store_const", const=True, default=False, help='Show version and exit')
     
     args = parser.parse_args()
     

From 3e1a00ada06892561c00c0f82485ab7515f93cc1 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Wed, 26 Mar 2025 20:58:02 +0100
Subject: [PATCH 14/31] doc: general update

---
 .gitignore                                    |     1 +
 docs/source/_templates/autosummary/module.rst |     6 +
 .../gridmarthe.load_marthe_grid.rst           |     6 -
 .../api/_autosummary/gridmarthe.operasem.rst  |    21 -
 .../api/_autosummary/gridmarthe.plot.rst      |    14 -
 .../gridmarthe.write_marthe_grid.rst          |     6 -
 docs/source/api/index.rst                     |    50 +-
 docs/source/api/io_operations.rst             |    12 +
 docs/source/api/operasem.rst                  |    13 +
 docs/source/api/plotting.rst                  |    13 +
 docs/source/conf.py                           |    19 +-
 docs/source/index.rst                         |     4 +-
 .../user_guide/example/chasim_hallue.nc       |   Bin 644486 -> 0 bytes
 .../user_guide/example/chasim_hallue.out      | 17220 ----------------
 docs/source/user_guide/example/cli.ipynb      |    46 +-
 .../user_guide/example/data/chasim_hallue.nc  |   Bin 0 -> 1112692 bytes
 .../user_guide/example/data/craie_npc.permh   |  6564 ++++++
 .../user_guide/example/data/example.hsubs     |  2730 +++
 .../user_guide/example/data/example.topog     |   595 +
 .../user_guide/example/data/grid_clean.hsubs  |   905 +
 .../example/data/grid_wrong_attrs.hsubs       |   905 +
 .../example/{ => data}/hallue.pastp           |     0
 .../example/{ => data}/nested.permh           |     0
 docs/source/user_guide/example/gigogne.ipynb  |     4 +-
 .../user_guide/example/gm_example.ipynb       |     4 +-
 docs/source/user_guide/example/preproc.ipynb  |   221 +
 .../user_guide/example/treatments.ipynb       |  1590 ++
 docs/source/user_guide/index.rst              |     4 +-
 28 files changed, 13612 insertions(+), 17341 deletions(-)
 create mode 100644 docs/source/_templates/autosummary/module.rst
 delete mode 100644 docs/source/api/_autosummary/gridmarthe.load_marthe_grid.rst
 delete mode 100644 docs/source/api/_autosummary/gridmarthe.operasem.rst
 delete mode 100644 docs/source/api/_autosummary/gridmarthe.plot.rst
 delete mode 100644 docs/source/api/_autosummary/gridmarthe.write_marthe_grid.rst
 create mode 100644 docs/source/api/io_operations.rst
 create mode 100644 docs/source/api/operasem.rst
 create mode 100644 docs/source/api/plotting.rst
 delete mode 100644 docs/source/user_guide/example/chasim_hallue.nc
 delete mode 100644 docs/source/user_guide/example/chasim_hallue.out
 create mode 100644 docs/source/user_guide/example/data/chasim_hallue.nc
 create mode 100644 docs/source/user_guide/example/data/craie_npc.permh
 create mode 100644 docs/source/user_guide/example/data/example.hsubs
 create mode 100644 docs/source/user_guide/example/data/example.topog
 create mode 100644 docs/source/user_guide/example/data/grid_clean.hsubs
 create mode 100644 docs/source/user_guide/example/data/grid_wrong_attrs.hsubs
 rename docs/source/user_guide/example/{ => data}/hallue.pastp (100%)
 rename docs/source/user_guide/example/{ => data}/nested.permh (100%)
 create mode 100644 docs/source/user_guide/example/preproc.ipynb
 create mode 100644 docs/source/user_guide/example/treatments.ipynb

diff --git a/.gitignore b/.gitignore
index bf12a3b..13610a9 100644
--- a/.gitignore
+++ b/.gitignore
@@ -73,6 +73,7 @@ instance/
 
 # Sphinx documentation
 docs/_build/
+generated
 
 # PyBuilder
 .pybuilder/
diff --git a/docs/source/_templates/autosummary/module.rst b/docs/source/_templates/autosummary/module.rst
new file mode 100644
index 0000000..18460ed
--- /dev/null
+++ b/docs/source/_templates/autosummary/module.rst
@@ -0,0 +1,6 @@
+{{ fullname | escape | underline }}
+
+.. automodule:: {{ fullname }}
+   :members:
+   :undoc-members:
+   :show-inheritance:
diff --git a/docs/source/api/_autosummary/gridmarthe.load_marthe_grid.rst b/docs/source/api/_autosummary/gridmarthe.load_marthe_grid.rst
deleted file mode 100644
index 2ef3385..0000000
--- a/docs/source/api/_autosummary/gridmarthe.load_marthe_grid.rst
+++ /dev/null
@@ -1,6 +0,0 @@
-gridmarthe.load\_marthe\_grid
-=============================
-
-.. currentmodule:: gridmarthe
-
-.. autofunction:: load_marthe_grid
\ No newline at end of file
diff --git a/docs/source/api/_autosummary/gridmarthe.operasem.rst b/docs/source/api/_autosummary/gridmarthe.operasem.rst
deleted file mode 100644
index cef1799..0000000
--- a/docs/source/api/_autosummary/gridmarthe.operasem.rst
+++ /dev/null
@@ -1,21 +0,0 @@
-gridmarthe.operasem
-===================
-
-.. automodule:: gridmarthe.operasem
-
-   
-   .. rubric:: Functions
-
-   .. autosummary::
-   
-      coarse_nested_grid
-      get_mask
-      get_min_layer
-      get_new_coords
-      interp_grid
-      rescale
-      search_zone
-      subset_with_coords
-      to_geodataframe
-      write_raster_from_da
-   
\ No newline at end of file
diff --git a/docs/source/api/_autosummary/gridmarthe.plot.rst b/docs/source/api/_autosummary/gridmarthe.plot.rst
deleted file mode 100644
index 2644e4e..0000000
--- a/docs/source/api/_autosummary/gridmarthe.plot.rst
+++ /dev/null
@@ -1,14 +0,0 @@
-gridmarthe.plot
-===============
-
-.. automodule:: gridmarthe.plot
-
-   
-   .. rubric:: Functions
-
-   .. autosummary::
-   
-      plot_mesh_time_serie
-      plot_nested_grid
-      plot_outcrop
-   
\ No newline at end of file
diff --git a/docs/source/api/_autosummary/gridmarthe.write_marthe_grid.rst b/docs/source/api/_autosummary/gridmarthe.write_marthe_grid.rst
deleted file mode 100644
index 65ed37c..0000000
--- a/docs/source/api/_autosummary/gridmarthe.write_marthe_grid.rst
+++ /dev/null
@@ -1,6 +0,0 @@
-gridmarthe.write\_marthe\_grid
-==============================
-
-.. currentmodule:: gridmarthe
-
-.. autofunction:: write_marthe_grid
\ No newline at end of file
diff --git a/docs/source/api/index.rst b/docs/source/api/index.rst
index c97005e..516421c 100644
--- a/docs/source/api/index.rst
+++ b/docs/source/api/index.rst
@@ -1,44 +1,16 @@
+=============
 API Reference
 =============
 
-.. toctree::
-    :maxdepth: 3
-
-
-Summary
--------
-
-.. autosummary::
-    :toctree: _autosummary
-
-    gridmarthe.load_marthe_grid
-    gridmarthe.write_marthe_grid
-    gridmarthe.plot
-    gridmarthe.operasem
-
-
-
-Full Guide
-----------
-
-IO Operations
-~~~~~~~~~~~~~
-
-.. automodule:: gridmarthe.gridmarthe
-    :members:
-    :undoc-members:
-    :show-inheritance:
-
-
-Visualisation
-~~~~~~~~~~~~~
-
-.. automodule:: gridmarthe.plot
-    :members:
-    :undoc-members:
-    :show-inheritance:
-
-
-
+This section contains the Documentation of the Application Programming
+Interface (API) of gridmarthe. The information in this section is automatically
+created from the documentation strings in original Python code. In the
+left-hand menu you will find the different categories of the API documentation.
 
 
+.. toctree::
+    :maxdepth: 2
+    
+    io_operations
+    operasem
+    plotting
diff --git a/docs/source/api/io_operations.rst b/docs/source/api/io_operations.rst
new file mode 100644
index 0000000..b148108
--- /dev/null
+++ b/docs/source/api/io_operations.rst
@@ -0,0 +1,12 @@
+.. currentmodule:: gridmarthe
+.. default-role:: obj
+
+IO operations
+-------------
+
+.. autosummary::
+    :toctree: ./generated
+    
+    load_marthe_grid
+    
+    write_marthe_grid
diff --git a/docs/source/api/operasem.rst b/docs/source/api/operasem.rst
new file mode 100644
index 0000000..1c7bebc
--- /dev/null
+++ b/docs/source/api/operasem.rst
@@ -0,0 +1,13 @@
+.. currentmodule:: gridmarthe
+.. default-role:: obj
+
+Grid operations
+---------------
+
+.. autosummary::
+    :toctree: ./generated
+    
+    reset_geometry
+    operasem.geometry
+    operasem.gis
+
diff --git a/docs/source/api/plotting.rst b/docs/source/api/plotting.rst
new file mode 100644
index 0000000..bbc1141
--- /dev/null
+++ b/docs/source/api/plotting.rst
@@ -0,0 +1,13 @@
+.. currentmodule:: gridmarthe
+.. default-role:: obj
+
+Plotting
+--------
+
+.. autosummary::
+    :toctree: ./generated
+    
+    
+    plot_nested_grid
+    
+    plot_outcrop
diff --git a/docs/source/conf.py b/docs/source/conf.py
index b17d7fe..d6b7b74 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -11,8 +11,9 @@
 from gridmarthe import __version__
 
 project = 'gridmarthe'
-copyright = '2024, Adrien Manlay, Jean-Pierre Vergnes - BRGM'
-author = 'Jean-Pierre Vergnes, Adrien Manlay'
+authors = 'Jean-Pierre Vergnes, Adrien Manlay'
+# copyright = '2024,  BRGM.\nAuthors: {}'.format(authors)
+copyright = '2024,  BRGM'
 
 release = __version__
 
@@ -77,14 +78,15 @@
     "show_nav_level": 1,
     "navbar_align": "content",
     "navbar_start": ["navbar-logo"],
-    "navbar_end": ["version-switcher","theme-switcher", "navbar-icon-links"],
+    #"navbar_end": ["version-switcher","theme-switcher", "navbar-icon-links"],
+    "navbar_end": ["theme-switcher", "navbar-icon-links"],
     "footer_start": ["copyright", "sphinx-version", "last-updated"],
     # "footer_end": ["corporate-logo"],
     "header_links_before_dropdown": 6,
-    "switcher": {
-        "json_url": f"{html_baseurl}/en/latest/_static/switcher.json",
-        "version_match": release
-    },
+    # "switcher": {
+    #     "json_url": f"{html_baseurl}/en/latest/_static/switcher.json",
+    #     "version_match": release
+    # },
 }
 
 html_last_updated_fmt = '%b %d, %Y'
@@ -97,6 +99,7 @@
 # https://www.sphinx-doc.org/en/master/usage/extensions/autosummary.html
 
 autosummary_generate = True
+autosummary_template = 'autosummary/module.rst'  # add template to always show doc in module
 
 
 # ----------------------------------------------------------------------
@@ -105,7 +108,7 @@
 # https://www.sphinx-doc.org/en/master/usage/extensions/autodoc.html
 
 autodoc_member_order = 'bysource'
-#autodoc_default_options = {"members":True}#, "show-inheritance":True}
+#autodoc_default_options = {"members":True}#, "show-inheritance":True}  # could be enought instead of tpl ?
 autodoc_typehints = 'none' # signature, description, none, both
 autoclass_content = 'class'
 
diff --git a/docs/source/index.rst b/docs/source/index.rst
index c0cd1cc..cd5113a 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -8,12 +8,12 @@
    documentation for details.
 
 ==========
-GridMarthe
+gridmarthe
 ==========
 **Date** : |today| **Version**: |release|
 
 
-Gridmarthe is a Python project for (fast) operations on Marthe grid files.
+`gridmarthe` is a Python project for (fast) operations on Marthe grid files.
 
 `Marthe <https://www.brgm.fr/en/software/marthe-modelling-software-groundwater-flows>`_
 is a hydrogeological modelling code developped at BRGM, French Geological Survey
diff --git a/docs/source/user_guide/example/chasim_hallue.nc b/docs/source/user_guide/example/chasim_hallue.nc
deleted file mode 100644
index bc8940e18ed05577fb20a2bb87aa7f217af0bb13..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

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z9VZ=(l=kk0?S}2&dZhepZl`N+_iYtX-YNA?l!w2_jde84sKriMT|~)1f0X<wH8uZM
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diff --git a/docs/source/user_guide/example/chasim_hallue.out b/docs/source/user_guide/example/chasim_hallue.out
deleted file mode 100644
index d553013..0000000
--- a/docs/source/user_guide/example/chasim_hallue.out
+++ /dev/null
@@ -1,17220 +0,0 @@
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas       1;    CHARGE  1                    <> CHARGE 1
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas      32;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=32
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-[Structure]
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-[Data_Descript]
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-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
-[Data]
-0	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	27	28	29	30	31	32	33	34	35	36	37	38	39	40	41	42	43	44	45	46	47	48	49	50	51	52	53	
-0	0	596.75	597.25	597.75	598.25	598.75	599.25	599.75	600.25	600.75	601.25	601.75	602.25	602.75	603.25	603.75	604.25	604.75	605.25	605.75	606.25	606.75	607.25	607.75	608.25	608.75	609.25	609.75	610.25	610.75	611.25	611.75	612.25	612.75	613.25	613.75	614.25	614.75	615.25	615.75	616.25	616.75	617.25	617.75	618.25	618.75	619.25	619.75	620.25	620.75	621.25	621.75	622.25	622.75	
-1	2568.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-2	2568.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-3	2567.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-4	2567.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-5	2566.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	100.0473	100.6405	101.1256	101.6138	102.6527	103.3882	103.5225	9999	9999	9999	9999	0.5	
-6	2566.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	96.99962	98.23103	99.02129	99.65898	100.3174	100.7386	9999	9999	9999	9999	9999	0.5	
-7	2565.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	94.18056	95.24717	96.24004	97.02431	97.65107	98.13734	98.38033	9999	9999	9999	9999	9999	0.5	
-8	2565.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	92.61234	93.59289	94.43556	95.1583	95.74929	96.15098	96.20794	95.51396	9999	9999	9999	9999	0.5	
-9	2564.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	92.77721	9999	92.3271	92.25778	92.0494	91.71433	92.1167	92.73935	93.39773	94.0055	94.49403	94.79177	94.83413	9999	9999	9999	9999	0.5	
-10	2564.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	81.21423	81.73922	9999	9999	9999	9999	9999	9999	9999	9999	86.67855	88.49463	88.13597	89.43047	89.87015	90.01255	90.11397	90.47324	91.03084	91.69643	92.3959	93.07333	93.69909	94.25895	9999	9999	9999	9999	0.5	
-11	2563.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	79.01985	75.55431	77.8076	78.01385	75.58805	81.28172	87.74904	9999	9999	9999	9999	83.38008	84.70237	85.85411	86.3998	87.16393	87.67449	88.00419	88.31003	88.72394	89.29209	90.01357	90.8753	91.79062	92.73814	9999	9999	9999	9999	9999	0.5	
-12	2563.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	75.54619	75.54619	76.33541	75.77189	76.27961	76.56435	76.79815	79.09435	81.59371	9999	9999	9999	9999	82.05246	82.77387	83.63629	84.35858	85.05418	85.62388	86.08427	86.50791	86.98335	87.5707	88.35495	89.40884	90.56694	9999	9999	9999	9999	9999	9999	0.5	
-13	2562.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	74.79017	74.96989	74.89353	75.06435	75.31877	75.75871	76.75872	77.68135	9999	9999	9999	9999	80.066	80.74252	81.56383	82.34811	83.07536	83.71969	84.27964	84.78752	85.28687	85.85119	86.60088	87.98172	9999	9999	9999	9999	9999	9999	9999	0.5	
-14	2562.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	73.77667	73.68958	73.88048	73.90534	73.86155	73.91511	74.07847	74.3687	74.76238	74.91384	74.04284	73.97155	74.52797	75.68914	77.6043	78.73164	79.67232	80.5257	81.30571	82.00901	82.63275	83.17535	83.65315	84.07003	84.40646	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-15	2561.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	88.04246	82.97794	80.84483	9999	74.47714	73.86266	73.41775	73.16392	72.96878	72.82283	72.79635	72.87868	73.04384	73.24231	73.33484	73.22212	73.39331	73.94894	74.87578	76.07247	77.11191	78.04583	78.91418	79.72489	80.47267	81.14426	81.717	82.1759	82.51097	82.7071	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-16	2561.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	96.97939	91.33454	87.16228	83.20786	80.17086	77.31641	75.08048	73.79414	72.97224	72.42253	72.04329	71.7942	71.68735	71.70286	71.80073	71.9461	72.08783	72.23542	72.55884	73.12022	73.90838	74.84306	75.77093	76.65947	77.51118	78.3267	79.09346	79.7859	80.37471	80.83452	81.14127	81.28028	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-17	2560.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	93.57829	89.48536	85.70184	82.23928	79.27076	76.72302	74.70903	73.27586	72.26552	71.54593	71.03485	70.70554	70.53196	70.492	70.56324	70.70889	70.9023	71.17441	71.58995	72.17318	72.90541	73.73482	74.59059	75.43861	76.26666	77.07307	77.84071	78.55303	79.16789	79.64842	79.95727	80.03095	79.65455	9999	9999	9999	9999	9999	9999	9999	0.5	
-18	2560.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	91.92925	87.12233	83.6557	80.61419	77.93409	75.64869	73.79712	72.3729	71.2859	70.46755	69.86873	69.46488	69.25634	69.19444	69.25413	69.40869	69.67001	70.02327	70.51103	71.12841	71.85576	72.65364	73.47933	74.30473	75.11953	75.91507	76.69107	77.41859	78.06799	78.60504	79.00563	79.23533	79.28088	9999	9999	9999	9999	9999	9999	9999	0.5	
-19	2559.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	83.049	80.94312	78.51504	76.21594	74.20062	72.50752	71.10198	69.98664	69.1121	68.47783	68.06109	67.83395	67.76799	67.83646	68.02544	68.33288	68.76601	69.31612	69.98828	70.7372	71.55395	72.38788	73.2195	74.03989	74.84005	75.62092	76.37296	77.07121	77.6858	78.19792	78.61014	78.95054	9999	9999	9999	9999	9999	9999	9999	0.5	
-20	2559.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	84.52543	80.82389	78.38183	76.21337	74.22711	72.45003	70.90479	69.5883	68.48915	67.60047	66.9426	66.50247	66.26588	66.21083	66.29986	66.53224	66.90413	67.41022	68.02257	68.74473	69.54084	70.38953	71.25684	72.1253	72.97337	73.79924	74.60879	75.39202	76.13653	76.82785	77.46093	78.04417	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-21	2558.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	78.71039	77.09527	75.3695	73.65497	72.00821	70.47514	69.08859	67.8642	66.81004	65.93954	65.28478	64.83714	64.58088	64.522	64.63315	64.91496	65.3566	65.9365	66.61769	67.39312	68.25846	69.16547	70.08825	71.01277	71.92103	72.79051	73.63781	74.45394	75.24367	76.00812	76.7446	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-22	2558.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	73.96429	73.22616	72.13219	70.87142	69.55339	68.27596	67.08369	65.98419	65.00233	64.18188	63.54957	63.07771	62.77476	62.66737	62.78406	63.13391	63.68121	64.36817	65.133	65.97339	66.90739	67.88764	68.87678	69.89792	70.8819	71.80815	72.69256	73.54969	74.37655	75.19479	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-23	2557.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	69.66127	69.45274	68.86238	68.03308	67.04413	65.99263	64.95251	63.97194	63.092	62.33317	61.69275	61.17396	60.78825	60.58955	60.65203	61.1265	61.86177	62.6921	63.53569	64.42994	65.4738	66.56147	67.57924	68.78236	69.87692	70.85534	71.77046	72.64023	73.494	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-24	2557.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	63.34096	65.38432	65.91043	65.76967	65.26253	64.5104	63.65652	62.75104	61.86871	61.05262	60.31007	59.64097	59.04072	58.51981	58.14544	58.04582	58.68385	59.83755	60.93621	61.8457	62.68839	63.97595	65.25663	65.99997	67.72836	68.94846	69.95256	70.87724	71.76352	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-25	2556.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	58.55285	59.44466	61.17177	62.40451	62.94001	62.956	62.60944	62.02386	61.26591	60.4714	59.66177	58.8573	58.0862	57.33614	56.54712	55.79228	55.24996	55.11795	55.30924	57.65067	59.19252	60.07935	60.28658	62.35264	64.44465	65.81821	67.1143	68.18206	69.11108	69.99851	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-26	2556.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	57.0066	57.69262	58.44419	59.36671	60.0908	60.45539	60.45576	60.16042	59.62749	58.95603	58.18999	57.39728	56.56552	55.70923	54.78111	53.77764	52.67619	51.36126	52.17416	54.28653	56.01934	57.98111	59.77671	60.80184	62.56835	64.26738	65.61578	66.6949	67.54509	68.32374	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-27	2555.75	9999	9999	9999	9999	9999	9999	9999	55.51212	55.73885	56.29164	56.7892	57.28975	57.79761	58.16587	58.31489	58.22226	57.8997	57.37613	56.71956	55.98226	55.18304	54.2793	53.28288	52.16133	50.92866	49.30802	50.0955	51.38701	52.8494	54.30889	56.18696	58.40714	60.56892	62.66029	64.16843	65.49755	66.42494	66.98175	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-28	2555.25	9999	9999	9999	9999	9999	55.1276	55.15559	55.26042	55.38055	55.61834	55.88321	56.13983	56.3611	56.47052	56.42455	56.20092	55.79834	55.26149	54.61214	53.89351	53.06387	52.0712	50.88472	49.46951	48.23065	48.87028	49.47826	50.41385	51.46646	52.56443	54.00141	56.43694	60.13157	62.68003	63.66112	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-29	2554.75	9999	9999	9999	9999	9999	55.09481	55.06552	54.96955	54.92686	54.94794	54.99139	55.02376	55.01178	54.91856	54.70486	54.36703	53.89647	53.3343	52.70084	51.96951	51.09906	50.01396	48.58565	46.33951	47.03207	47.84269	48.58129	49.34436	50.09662	50.8047	51.58365	53.54122	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-30	2554.25	9999	9999	9999	9999	9999	9999	9999	54.69346	54.48486	54.30637	54.13214	53.94326	53.72333	53.45208	53.09833	52.66139	52.14955	51.56926	50.92775	50.19611	49.32045	48.22961	46.86454	45.1857	46.17129	46.9262	47.63527	48.29802	48.86953	49.28701	49.48918	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-31	2553.75	9999	9999	9999	9999	9999	9999	9999	9999	54.0969	53.7047	53.29858	52.88468	52.46568	52.03423	51.57919	51.08737	50.54919	49.97715	49.34901	48.6121	47.72379	46.63771	45.16514	45.01168	45.4986	46.0977	46.73087	47.32845	47.81904	48.13448	48.2409	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-32	2553.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	53.09408	52.46505	51.83723	51.23927	50.68673	50.15675	49.62806	49.07811	48.49782	47.86018	47.13904	46.28776	45.28204	44.08	44.30879	44.73209	45.26416	45.86722	46.44738	46.93358	47.25294	47.38662	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-33	2552.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	51.62581	50.78687	50.01683	49.37427	48.80191	48.25968	47.71511	47.14358	46.51056	45.7905	44.96106	44.04484	43.06791	43.42486	43.87842	44.41287	45.01596	45.65838	46.20309	46.5843	46.79545	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-34	2552.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	49.73841	48.75723	48.08103	47.51021	46.97614	46.43182	45.85891	45.22846	44.50922	43.69598	42.81212	42.02609	42.43898	42.96461	43.53517	44.19693	44.99614	45.64136	46.0919	46.44815	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-35	2551.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	47.29223	46.77203	46.23988	45.72654	45.20555	44.63944	44.00689	43.28216	42.45478	41.42115	40.20206	41.33379	41.98683	42.57887	43.28353	44.51737	45.28348	45.68749	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-36	2551.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	46.39226	45.51876	44.97846	44.49146	43.98075	43.43433	42.82633	42.11155	41.29089	40.14481	40.09731	40.62623	41.11917	41.58255	41.9477	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-37	2550.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	43.93775	43.65278	43.25869	42.79017	42.26201	41.67483	41.03797	40.41361	39.9608	39.68622	39.90166	40.29354	40.71646	41.04623	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-38	2550.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	42.60557	42.41051	42.07686	41.64412	41.13574	40.55299	39.93217	39.33358	38.96224	38.79146	39.01027	39.40811	39.95451	40.49959	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-39	2549.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	41.19782	41.45157	41.29775	40.97984	40.56213	40.06154	39.47142	38.78551	37.99586	37.07952	37.49849	37.88548	38.35429	39.16294	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-40	2549.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	40.94247	40.69245	40.34103	39.96818	39.54771	39.04926	38.44642	37.70865	36.75105	35.19926	36.23897	36.70358	36.9596	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-41	2548.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	40.04168	39.4	38.98956	38.58308	38.1138	37.5378	36.82623	35.95031	35.07796	35.48815	35.71201	35.80406	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas      93;    CHARGE  1                    <> CHARGE 1
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-[Data_Descript]
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas     185;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas     275;    CHARGE  1                    <> CHARGE 1
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas     306;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Structure]
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-[Data_Descript]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas     398;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=398
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas     459;    CHARGE  1                    <> CHARGE 1
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas     489;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=489
-Time=701
-Layer=1
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-[Structure]
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas     551;    CHARGE  1                    <> CHARGE 1
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas     579;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=579
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-Layer=1
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas     640;    CHARGE  1                    <> CHARGE 1
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas     671;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=671
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-[Structure]
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas     763;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=763
-Time=975
-Layer=1
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-[Structure]
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas     793;    CHARGE  1                    <> CHARGE 1
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-[Data_Descript]
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas     854;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
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-[Data_Descript]
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-35	2551.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	47.54987	47.01248	46.45587	45.91274	45.35776	44.75908	44.10591	43.36097	42.50965	41.44698	40.20532	41.36602	42.04	42.64953	43.37006	44.62258	45.40293	45.81588	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-36	2551.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	46.63857	45.74895	45.18943	44.67844	44.14071	43.567	42.93386	42.19211	41.33975	40.14986	40.10828	40.66243	41.17372	41.65115	42.02555	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-38	2550.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	42.81812	42.61363	42.26382	41.80989	41.27663	40.66569	40.01398	39.37952	38.96592	38.81487	39.05102	39.46253	40.01911	40.57098	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas     944;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1036;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1066;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Structure]
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-[Data_Descript]
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-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1158;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=1158
-Time=1370
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1219;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1250;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=1250
-Time=1462
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
-Y_Lower_Corner=2542
-Ncolumn=53
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-42	2548.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	39.05128	38.76633	38.35062	37.83371	37.182	36.33273	35.13315	35.00597	35.03269	35.01401	34.95873	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1309;    CHARGE  1                    <> CHARGE 1
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1340;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=1340
-Time=1552
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-Ncolumn=53
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1401;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1431;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
-Elem_Number=0
-Name=
-Time_Step=1431
-Time=1643
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1523;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=1523
-Time=1735
-Layer=1
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1554;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1615;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-33	2552.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	54.34532	53.38507	52.47892	51.68702	50.94577	50.20932	49.43779	48.57538	47.78711	46.82803	45.70528	44.46706	43.10327	43.67481	44.32026	45.04441	45.80931	46.58625	47.2338	47.68681	47.94147	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-35	2551.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	49.5471	48.93091	48.26443	47.58712	46.8755	46.09696	45.2295	44.22516	43.08854	41.71268	40.23717	41.66223	42.51838	43.27402	44.11537	45.49099	46.35777	46.81544	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-36	2551.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	48.57464	47.58762	46.92492	46.27982	45.58852	44.84177	43.99515	42.98519	41.81279	40.19996	40.21213	40.99929	41.67367	42.27187	42.72301	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-38	2550.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	44.45587	44.19061	43.73246	43.13085	42.41159	41.57503	40.68584	39.7574	38.99823	39.03161	39.43197	39.96962	40.61974	41.23302	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-39	2549.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	42.98649	43.23406	43.00777	42.56241	41.98078	41.28027	40.45045	39.48631	38.38899	37.11414	37.74272	38.30175	38.89052	39.79285	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1706;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=1706
-Time=1918
-Layer=1
-Max_Layer=1
-Nest_grid=0
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-[Structure]
-X_Left_Corner=596.5
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-Ncolumn=53
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1736;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-32	2553.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	56.83633	56.07846	55.29622	54.52483	53.7833	53.04668	52.28777	51.47651	50.60953	49.69573	48.65815	47.4245	45.94878	44.12872	44.51804	45.13756	45.84796	46.6147	47.33266	47.9281	48.32633	48.50572	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-35	2551.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	50.21346	49.57271	48.87581	48.16364	47.40579	46.56844	45.63304	44.55253	43.31726	41.81732	40.24152	41.66357	42.52402	43.28002	44.12409	45.50903	46.3751	46.8322	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-36	2551.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	49.21216	48.19154	47.50276	46.83465	46.10194	45.29207	44.37535	43.28207	42.00202	40.21532	40.21375	40.99363	41.66751	42.26532	42.71401	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-37	2550.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	46.43258	46.04957	45.49846	44.82081	44.03685	43.1392	42.12509	41.04463	40.01087	39.90314	40.30106	40.84613	41.38059	41.77436	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-39	2549.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	43.48624	43.71711	43.47401	43.0146	42.40418	41.66005	40.7703	39.72904	38.52384	37.1201	37.7423	38.28529	38.8667	39.76446	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-40	2549.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	43.20387	42.88004	42.41884	41.90121	41.29173	40.55298	39.65495	38.56897	37.22244	35.23255	36.47677	37.07738	37.41079	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-41	2548.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	42.13996	41.36532	40.81314	40.22326	39.5164	38.64248	37.57384	36.29835	35.1133	35.71727	36.06231	36.21872	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1767;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Time_Step=1767
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1797;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=1797
-Time=2009
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[Infos]
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-[Data_Descript]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1889;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1920;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1950;    CHARGE  1                    <> CHARGE 1
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1981;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=1981
-Time=2193
-Layer=1
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2012;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Time_Step=2012
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-[Data_Descript]
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2071;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Time_Step=2071
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2101;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=2101
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-[Structure]
-X_Left_Corner=596.5
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2193;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
-Elem_Number=0
-Name=
-Time_Step=2193
-Time=2405
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-Ncolumn=53
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2254;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2285;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=2285
-Time=2497
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-Ncolumn=53
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2377;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=2377
-Time=2589
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2466;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Time_Step=2466
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[Infos]
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-[Data_Descript]
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-35	2551.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	50.76224	50.10158	49.37778	48.63303	47.83479	46.94898	45.95714	44.8099	43.49468	41.89944	40.24832	41.7111	42.60112	43.37947	44.24231	45.64768	46.52562	46.98848	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2527;    CHARGE  1                    <> CHARGE 1
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-[Data_Descript]
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2558;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Structure]
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-[Data_Descript]
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-[Data_Descript]
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-27	2555.75	9999	9999	9999	9999	9999	9999	9999	58.31947	58.44571	58.83576	59.18522	59.53629	59.89196	60.12084	60.14528	59.94042	59.51342	58.88013	58.1064	57.24204	56.30297	55.21601	54.0258	52.69006	51.22499	49.34058	50.1151	51.48519	52.9865	54.45867	56.33947	58.58322	60.83815	63.03459	64.63667	66.05673	67.08442	67.7151	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-35	2551.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	49.26485	48.65972	48.01177	47.35891	46.67068	45.9156	45.08402	44.13013	43.03434	41.68727	40.22551	41.5093	42.27221	42.95066	43.72944	45.04504	45.86414	46.29625	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-36	2551.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	48.29294	47.31746	46.67532	46.06721	45.40452	44.67574	43.86099	42.89671	41.7712	40.19079	40.16057	40.82009	41.40811	41.94223	42.35109	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-38	2550.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	44.19178	43.94108	43.51276	42.95028	42.2798	41.4969	40.62207	39.72432	38.98912	38.92088	39.22489	39.69164	40.29005	40.86895	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-39	2549.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	42.74027	42.97287	42.75887	42.35064	41.80698	41.14527	40.35539	39.43092	38.35591	37.10489	37.62883	38.09508	38.62176	39.47616	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-41	2548.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	41.44655	40.71539	40.21148	39.68471	39.05752	38.28293	37.33003	36.18257	35.09914	35.61052	35.89664	36.02217	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2650;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=2650
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[Data_Descript]
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-35	2551.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	48.5725	47.99437	47.38267	46.77344	46.13959	45.44869	44.68713	43.81366	42.81585	41.58678	40.21827	41.46596	42.20115	42.85934	43.62081	44.91668	45.72648	46.15491	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-38	2550.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	43.64169	43.40845	43.00872	42.48611	41.8662	41.14817	40.36745	39.57886	38.98023	38.88848	39.17625	39.62833	40.21529	40.78709	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-39	2549.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	42.20684	42.45012	42.25622	41.87349	41.3683	40.75841	40.03536	39.19336	38.22312	37.09667	37.59686	38.04895	38.56395	39.40857	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-40	2549.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	41.94237	41.66216	41.26382	40.82522	40.31771	39.71028	38.97523	38.08329	36.95516	35.21342	36.33588	36.85827	37.14676	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2742;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Time_Step=2742
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-[Infos]
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-[Data_Descript]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2831;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2862;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=2862
-Time=3074
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
-Y_Lower_Corner=2542
-Ncolumn=53
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2954;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=2954
-Time=3166
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3015;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3045;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=3045
-Time=3257
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3107;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Time_Step=3107
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3136;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=3136
-Time=3348
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-Ncolumn=53
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3228;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=3228
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3320;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=3320
-Time=3532
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
-Y_Lower_Corner=2542
-Ncolumn=53
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3411;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Name=
-Time_Step=3411
-Time=3623
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3501;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Name=
-Time_Step=3501
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-Layer=1
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[Infos]
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-[Data_Descript]
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-35	2551.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	47.56064	47.02236	46.46421	45.91906	45.36217	44.762	44.10769	43.36114	42.50913	41.44684	40.20601	41.37632	42.05684	42.6719	43.39705	44.65422	45.43801	45.85265	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-36	2551.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	46.64923	45.75874	45.1977	44.68407	44.14448	43.57008	42.93589	42.1927	41.33927	40.15019	40.11164	40.67437	41.19164	41.6736	42.05101	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-37	2550.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	44.16513	43.86712	43.45229	42.95766	42.40254	41.78718	41.12007	40.4604	39.96532	39.71341	39.95424	40.36703	40.80537	41.14452	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-38	2550.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	42.82735	42.62194	42.27035	41.81422	41.27841	40.66498	40.01388	39.37929	38.96639	38.82198	39.06435	39.48062	40.04089	40.5953	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-39	2549.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	41.42162	41.67214	41.50816	41.17252	40.73223	40.20513	39.58484	38.86563	38.04053	37.08365	37.52954	37.93877	38.42334	39.24433	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3593;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3623;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3685;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3715;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=3715
-Time=3927
-Layer=1
-Max_Layer=1
-Nest_grid=0
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-[Structure]
-X_Left_Corner=596.5
-Y_Lower_Corner=2542
-Ncolumn=53
-Nrows=54
-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3776;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3807;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=3807
-Time=4019
-Layer=1
-Max_Layer=1
-Nest_grid=0
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-[Structure]
-X_Left_Corner=596.5
-Y_Lower_Corner=2542
-Ncolumn=53
-Nrows=54
-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
-[Data]
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3866;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3897;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=3897
-Time=4109
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-Ncolumn=53
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3958;    CHARGE  1                    <> CHARGE 1
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3988;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=3988
-Time=4200
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-Ncolumn=53
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4050;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4080;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=4080
-Time=4292
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
-Y_Lower_Corner=2542
-Ncolumn=53
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4172;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=4172
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4262;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Time_Step=4262
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-[Data_Descript]
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-28	2555.25	9999	9999	9999	9999	9999	58.11736	58.07195	58.05319	58.06516	58.18253	58.31964	58.44423	58.53169	58.51219	58.33989	57.98842	57.45338	56.77604	55.9759	55.10189	54.10082	52.91993	51.5098	49.81764	48.27421	48.9205	49.65542	50.68689	51.80766	52.95129	54.4277	56.91564	60.71344	63.32146	64.30583	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-31	2553.75	9999	9999	9999	9999	9999	9999	9999	9999	56.74143	56.27021	55.76601	55.23796	54.69316	54.12641	53.52624	52.87337	52.16229	51.40777	50.59366	49.65102	48.52041	47.13469	45.22602	45.059	45.72346	46.46267	47.21886	47.91994	48.4947	48.87622	49.03061	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-32	2553.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	55.61716	54.89686	54.15967	53.4387	52.75144	52.07303	51.37669	50.63953	49.85682	49.04144	48.11642	47.01823	45.71059	44.11241	44.46101	45.03019	45.69733	46.42378	47.10757	47.67593	48.05482	48.2235	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-33	2552.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	54.00101	53.05407	52.16356	51.39071	50.67253	49.96285	49.21668	48.37787	47.6259	46.70999	45.63247	44.42495	43.09741	43.62169	44.22679	44.89636	45.6205	46.36636	46.99016	47.42461	47.66378	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-35	2551.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	49.24163	48.6373	47.98924	47.33564	46.64907	45.89701	45.0635	44.10429	43.01094	41.6765	40.22949	41.57813	42.38608	43.10124	43.91051	45.25717	46.09867	46.54282	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-36	2551.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	48.27351	47.29956	46.65555	46.04049	45.37609	44.65183	43.83785	42.87241	41.75034	40.19114	40.18254	40.89973	41.52834	42.0927	42.52079	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-38	2550.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	44.18378	43.93069	43.49642	42.92655	42.24703	41.45585	40.59384	39.70669	38.99135	38.9702	39.31586	39.81452	40.4365	41.03068	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-39	2549.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	42.7283	42.96759	42.7523	42.33518	41.78444	41.11775	40.32549	39.40243	38.34063	37.10728	37.67931	38.1848	38.73885	39.61474	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-40	2549.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	42.4582	42.15955	41.73377	41.26104	40.70962	40.04759	39.24597	38.27608	37.06123	35.22227	36.41581	36.98377	37.29848	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-41	2548.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	41.45146	40.72131	40.21386	39.6813	39.05016	38.27242	37.32208	36.18149	35.10282	35.65892	35.9748	36.11561	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4353;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Time_Step=4353
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-[End_Grid]
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-[Infos]
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-[Structure]
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-[Data_Descript]
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-28	2555.25	9999	9999	9999	9999	9999	57.25608	57.22388	57.22888	57.26361	57.40753	57.5745	57.73221	57.85545	57.87068	57.73492	57.42367	56.93392	56.30758	55.56492	54.74379	53.79907	52.66101	51.30923	49.70108	48.25818	48.89677	49.56888	50.55398	51.64292	52.76678	54.22947	56.70867	60.49765	63.0915	64.0751	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-32	2553.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	54.87031	54.16742	53.45362	52.7624	52.11032	51.47239	50.8241	50.13259	49.39812	48.65372	47.80733	46.79449	45.58061	44.10102	44.39197	44.89225	45.49266	46.16007	46.79567	47.32671	47.67898	47.83171	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-33	2552.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	53.28805	52.3608	51.49799	50.75771	50.07674	49.40784	48.70094	47.88931	47.23306	46.40765	45.42459	44.30874	43.08654	43.53169	44.06569	44.6684	45.33478	46.03284	46.62103	47.03224	47.25961	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-35	2551.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	48.62283	48.04139	47.42528	46.81069	46.1694	45.4708	44.70683	43.83309	42.83139	41.59427	40.21812	41.46129	42.1952	42.8514	43.61169	44.90775	45.71512	46.14174	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-36	2551.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	47.6726	46.72797	46.11509	45.54129	44.92352	44.25173	43.50518	42.62547	41.60453	40.17509	40.14254	40.76724	41.33017	41.84589	42.24363	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-37	2550.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	45.06509	44.73341	44.26579	43.70111	43.05529	42.32792	41.52172	40.69485	39.98208	39.7702	40.05451	40.5051	40.97106	41.3254	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-38	2550.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	43.67474	43.44074	43.04083	42.51792	41.89791	41.17896	40.38884	39.59163	38.98043	38.88488	39.16648	39.61509	40.19982	40.7699	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-39	2549.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	42.24131	42.48027	42.28487	41.90373	41.39861	40.78729	40.06125	39.21454	38.23479	37.09679	37.59276	38.03821	38.54966	39.39189	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-40	2549.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	41.9718	41.68753	41.28662	40.84823	40.34254	39.73397	38.99579	38.0986	36.96391	35.21333	36.33099	36.84682	37.13233	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-41	2548.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	40.99832	40.29964	39.82391	39.33267	38.75345	38.04066	37.16494	36.10611	35.09263	35.57716	35.84737	35.96454	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4445;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[Data_Descript]
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-27	2555.75	9999	9999	9999	9999	9999	9999	9999	56.54118	56.72717	57.21465	57.65348	58.09547	58.54445	58.85929	58.96093	58.82611	58.46505	57.90176	57.20367	56.42208	55.57456	54.60664	53.54264	52.34633	51.03243	49.3194	50.10237	51.42192	52.89889	54.36434	56.24606	58.48029	60.68733	62.8241	64.36897	65.72716	66.69244	67.27824	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-31	2553.75	9999	9999	9999	9999	9999	9999	9999	9999	55.09682	54.66648	54.21411	53.74834	53.27483	52.78707	52.27286	51.71805	51.1093	50.46567	49.77707	48.97609	48.00784	46.81754	45.18634	45.02423	45.55524	46.18829	46.85237	47.47699	47.99046	48.32449	48.44465	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-33	2552.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	52.50825	51.61382	50.78849	50.0888	49.45323	48.83658	48.19385	47.46869	46.85164	46.09026	45.18963	44.17566	43.07698	43.47537	43.967	44.53395	45.16768	45.83759	46.40436	46.80148	47.02194	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-36	2551.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	47.05242	46.1411	45.56117	45.02687	44.45805	43.84478	43.16574	42.36828	41.44766	40.15975	40.11866	40.69243	41.21834	41.70652	42.08724	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-37	2550.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	44.51947	44.2093	43.77579	43.25627	42.66627	42.00663	41.28309	40.55601	39.97135	39.72586	39.97348	40.39292	40.83609	41.17743	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-38	2550.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	43.1603	42.94448	42.57573	42.09546	41.52883	40.87571	40.16671	39.46584	38.97132	38.83571	39.08392	39.50555	40.06979	40.62649	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-39	2549.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	41.74538	41.98947	41.81357	41.46261	40.9988	40.43982	39.77836	39.00852	38.11963	37.08821	37.54348	37.95808	38.4469	39.27077	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-40	2549.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	41.48315	41.21604	40.83973	40.43261	39.96708	39.40991	38.73507	37.91286	36.86209	35.20638	36.28351	36.7728	37.04306	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-41	2548.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	40.54863	39.88084	39.43585	38.98351	38.45463	37.80497	37.00535	36.03193	35.08543	35.53222	35.77918	35.884	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4537;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[Data_Descript]
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-27	2555.75	9999	9999	9999	9999	9999	9999	9999	56.35312	56.55006	57.05405	57.50684	57.96194	58.42353	58.74904	58.85847	58.72804	58.36822	57.80923	57.11693	56.34216	55.5019	54.55609	53.509	52.3267	51.02273	49.31908	50.10373	51.43033	52.91089	54.37835	56.26195	58.49848	60.72134	62.85891	64.39658	65.73718	66.69236	67.27243	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-28	2555.25	9999	9999	9999	9999	9999	56.04973	56.05342	56.11794	56.20272	56.39949	56.62016	56.83115	57.00658	57.07249	56.98418	56.71818	56.27271	55.69222	54.99784	54.23487	53.35681	52.31262	51.06353	49.56913	48.24319	48.88486	49.5303	50.4951	51.57023	52.68694	54.14876	56.63668	60.44139	62.99088	63.94903	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-31	2553.75	9999	9999	9999	9999	9999	9999	9999	9999	54.93993	54.5112	54.06094	53.59769	53.12711	52.64243	52.13192	51.57965	50.97952	50.34787	49.6709	48.88302	47.93393	46.77015	45.1817	45.02458	45.55977	46.19974	46.86916	47.49818	48.01569	48.35363	48.47716	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-33	2552.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	52.37271	51.47368	50.64986	49.95379	49.32291	48.71189	48.07755	47.36295	46.75875	46.01068	45.12712	44.14078	43.07559	43.47711	43.97148	44.54622	45.18561	45.86035	46.43195	46.83445	47.0609	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-35	2551.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	47.85368	47.3032	46.72871	46.16415	45.58421	44.95726	44.2719	43.48893	42.59543	41.48602	40.2094	41.4008	42.09634	42.72356	43.45935	44.72847	45.52085	45.9405	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-36	2551.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	46.93174	46.02654	45.4508	44.91945	44.3579	43.75699	43.09142	42.3098	41.41008	40.15695	40.12059	40.70168	41.23213	41.724	42.10777	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-37	2550.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	44.41518	44.10746	43.67711	43.16172	42.58084	41.93401	41.22857	40.523	39.96993	39.72974	39.98402	40.40802	40.85454	41.19851	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-38	2550.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	43.06466	42.851	42.48502	42.00901	41.44816	40.80388	40.1151	39.43613	38.97029	38.84016	39.09507	39.52117	40.0887	40.64788	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-39	2549.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	41.65255	41.90069	41.72798	41.37822	40.91835	40.36636	39.71546	38.96011	38.09287	37.08734	37.54815	37.96936	38.46233	39.28954	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-40	2549.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	41.39628	41.13476	40.7639	40.35952	39.89601	39.34525	38.68078	37.87314	36.83999	35.20584	36.28822	36.78349	37.05685	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-41	2548.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	40.47473	39.81721	39.37429	38.92352	38.39944	37.75799	36.97226	36.01702	35.08501	35.53646	35.78893	35.89667	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4628;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4719;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Time_Step=4719
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4750;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=4750
-Time=4962
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
-Y_Lower_Corner=2542
-Ncolumn=53
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4811;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Time_Step=4811
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4842;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=4842
-Time=5054
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-Ncolumn=53
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4903;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Time_Step=4903
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4934;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=4934
-Time=5146
-Layer=1
-Max_Layer=1
-Nest_grid=0
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-[Structure]
-X_Left_Corner=596.5
-Y_Lower_Corner=2542
-Ncolumn=53
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
-[Data]
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4993;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Time_Step=4993
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5023;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=5023
-Time=5235
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
-Y_Lower_Corner=2542
-Ncolumn=53
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-42	2548.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	39.13765	38.8523	38.4347	37.90846	37.24192	36.37221	35.13589	35.00263	35.01715	34.99108	34.93242	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5084;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=5084
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-Layer=1
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5115;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=5115
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-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5176;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5207;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=5207
-Time=5419
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-Ncolumn=53
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5268;    CHARGE  1                    <> CHARGE 1
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5299;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=5299
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-Layer=1
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5358;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5388;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
-Elem_Number=0
-Name=
-Time_Step=5388
-Time=5600
-Layer=1
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5419;    CHARGE  1                    <> CHARGE 1
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-[Data_Descript]
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5480;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-[Infos]
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-[Structure]
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-[Data_Descript]
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-[Data]
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-10	2564.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	81.21423	81.73922	9999	9999	9999	9999	9999	9999	9999	9999	87.1364	88.81408	88.49837	89.69106	90.1132	90.28012	90.46386	90.90528	91.52353	92.22874	92.9513	93.63818	94.26549	94.81999	9999	9999	9999	9999	0.5	
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-33	2552.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	53.12521	52.21307	51.3613	50.6305	49.95865	49.29897	48.60143	47.79867	47.15781	46.34825	45.38259	44.28532	43.08459	43.51681	44.03882	44.63067	45.28675	45.97527	46.55526	46.95974	47.18208	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-38	2550.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	43.57388	43.34354	42.95027	42.43655	41.82811	41.12314	40.34814	39.56892	38.97855	38.87187	39.14397	39.58497	40.16401	40.73035	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-39	2549.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	42.14263	42.38202	42.19023	41.81593	41.32008	40.7202	40.00778	39.17661	38.2138	37.09498	37.57945	38.01594	38.52097	39.35838	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-40	2549.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	41.87301	41.59033	41.19297	40.76149	40.26565	39.66892	38.94457	38.06287	36.94471	35.21179	36.31766	36.82543	37.1063	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
-41	2548.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	40.90185	40.20523	39.7371	39.25641	38.68993	37.99207	37.13287	36.09141	35.09089	35.56376	35.8263	35.93921	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5572;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=5572
-Time=5784
-Layer=1
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-[Structure]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[Data_Descript]
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-[Infos]
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-[Data_Descript]
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-[Infos]
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-[Data_Descript]
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5753;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5784;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=5784
-Time=5996
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
-Y_Lower_Corner=2542
-Ncolumn=53
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5845;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5876;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=5876
-Time=6088
-Layer=1
-Max_Layer=1
-Nest_grid=0
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-[Structure]
-X_Left_Corner=596.5
-Y_Lower_Corner=2542
-Ncolumn=53
-Nrows=54
-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
-[Data]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5937;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5967;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=5967
-Time=6179
-Layer=1
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-Nest_grid=0
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-[Structure]
-X_Left_Corner=596.5
-Y_Lower_Corner=2542
-Ncolumn=53
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-[Data_Descript]
-! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
-! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
-[Data]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    6058;    CHARGE  1                    <> CHARGE 1
-[Infos]
-Field=CHARGE
-Type=
-Elem_Number=0
-Name=
-Time_Step=6058
-Time=6270
-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-Ncolumn=53
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
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-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    6119;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-[Data_Descript]
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-[End_Grid]
-Marthe_Grid Version=9.0
-Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    6150;    CHARGE  1                    <> CHARGE 1
-[Infos]
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-Type=
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-Name=
-Time_Step=6150
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-Layer=1
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-[Structure]
-X_Left_Corner=596.5
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-[Data_Descript]
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-! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
-! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
-! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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-[End_Grid]
diff --git a/docs/source/user_guide/example/cli.ipynb b/docs/source/user_guide/example/cli.ipynb
index 207fe61..1b206e1 100644
--- a/docs/source/user_guide/example/cli.ipynb
+++ b/docs/source/user_guide/example/cli.ipynb
@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 1,
    "metadata": {
     "vscode": {
      "languageId": "shellscript"
@@ -27,27 +27,32 @@
      "output_type": "stream",
      "text": [
       "usage: ncmart [-h] [--output OUTPUT] [--variable VARIABLE] [--as2d]\n",
-      "              [--xyfactor XYFACTOR]\n",
-      "              chasim pastp [chasim pastp ...]\n",
+      "              [--xyfactor XYFACTOR] [--version]\n",
+      "              [grid timesteps ...]\n",
       "\n",
       "Convert a Marthe GridFile to netCDF format.\n",
       "\n",
       "positional arguments:\n",
-      "  chasim pastp          Paths to chasim and pastp files are expected\n",
+      "  grid timesteps        Paths to grid and timesteps files are expected\n",
       "\n",
       "options:\n",
       "  -h, --help            show this help message and exit\n",
       "  --output OUTPUT, -o OUTPUT\n",
       "                        Output filename. Default is input.nc\n",
       "  --variable VARIABLE, -v VARIABLE\n",
-      "                        Variable to read, default is None; i.e variable will\n",
-      "                        be parse from file and ONLY the first variable will be\n",
-      "                        read.\n",
+      "                        Variable (field) to read, default is None; i.e\n",
+      "                        variable will be parsed from file and ONLY the first\n",
+      "                        variable will be read.\n",
       "  --as2d, -d            Store grid as 2D (or more), default is 1D for space\n",
       "                        dimension\n",
       "  --xyfactor XYFACTOR, -x XYFACTOR\n",
       "                        Transformation factor for coordinates. Optionnal,\n",
-      "                        default is 1 (no transformation).\n"
+      "                        default is 1 (no transformation).\n",
+      "  --version, -V         Show version and exit\n",
+      "\n",
+      "gridmarthe  Copyright (C) 2024  BRGM.\n",
+      "This program comes with ABSOLUTELY NO WARRANTY.\n",
+      "This is free software, see GNU General Public Lisence v3 for copying.\n"
      ]
     }
    ],
@@ -58,7 +63,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 2,
    "metadata": {
     "vscode": {
      "languageId": "shellscript"
@@ -67,12 +72,13 @@
    "outputs": [],
    "source": [
     "# minimal setup: call ncmart with a grid file and a timestep file\n",
-    "!ncmart chasim_hallue.out hallue.pastp"
+    "# this will write the output with input filename and 'nc' extension\n",
+    "!ncmart ./data/chasim_hallue.out ./data/hallue.pastp"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 3,
    "metadata": {
     "vscode": {
      "languageId": "shellscript"
@@ -88,8 +94,8 @@
       "\ttime = 205 ;\n",
       "\tzone = 927 ;\n",
       "variables:\n",
-      "\tfloat charge(time, zone) ;\n",
-      "\t\tcharge:_FillValue = NaNf ;\n",
+      "\tdouble charge(time, zone) ;\n",
+      "\t\tcharge:_FillValue = NaN ;\n",
       "\t\tstring charge:varname = \"CHARGE\" ;\n",
       "\t\tstring charge:units = \"m\" ;\n",
       "\t\tcharge:missing_value = 9999. ;\n",
@@ -112,7 +118,7 @@
       "\tint64 time(time) ;\n",
       "\t\tstring time:units = \"days since 1995-07-31 00:00:00\" ;\n",
       "\t\tstring time:calendar = \"proleptic_gregorian\" ;\n",
-      "\tint64 zone(zone) ;\n",
+      "\tint zone(zone) ;\n",
       "\n",
       "// global attributes:\n",
       "\t\tstring :conventions = \"CF-1.10\" ;\n",
@@ -124,11 +130,11 @@
       "\t\t:scale_factor = 1. ;\n",
       "\t\tstring :nested_grid = \"False\" ;\n",
       "\t\tstring :extend = \"xymin : 596.75 2542.25; xymax: 622.75 2568.75\" ;\n",
-      "\t\tstring :frequency = \"30 day(s)\" ;\n",
       "\t\tstring :period = \"1995-2012\" ;\n",
-      "\t\tstring :creation_date = \"Created on 2025-01-07T15:54:32Z UTC\" ;\n",
+      "\t\tstring :frequency = \"30 day(s)\" ;\n",
+      "\t\tstring :creation_date = \"Created on 2025-03-26T13:28:35Z UTC\" ;\n",
       "\t\tstring :institution = \"BRGM, French Geological Survey, Orléans, France\" ;\n",
-      "\t\tstring :comment = \"Hydrogeological model created with MARTHE code (Thiery, D. 2020. Guidelines for MARTHE v7.8 computer code for hydro-systems modelling. report BRGM/RP-69660-FR).\" ;\n",
+      "\t\tstring :comment = \"Hydrogeological model created with MARTHE code (Thiery, D. 2020. Guidelines for MARTHE v7.8 computer codefor hydro-systems modelling. report BRGM/RP-69660-FR).\" ;\n",
       "\t\tstring :resolution_units = \"m\" ;\n",
       "\t\tstring :projection = \"epsg:27572\" ;\n",
       "\t\tstring :domain = \"FR-France\" ;\n",
@@ -138,13 +144,13 @@
    ],
    "source": [
     "# print variables headers and dimensions with nco tools\n",
-    "!ncdump -h chasim_hallue.nc"
+    "!ncdump -h ./data/chasim_hallue.nc"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "am",
+   "display_name": "gm",
    "language": "python",
    "name": "python3"
   },
@@ -158,7 +164,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.11.2"
   }
  },
  "nbformat": 4,
diff --git a/docs/source/user_guide/example/data/chasim_hallue.nc b/docs/source/user_guide/example/data/chasim_hallue.nc
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diff --git a/docs/source/user_guide/example/data/craie_npc.permh b/docs/source/user_guide/example/data/craie_npc.permh
new file mode 100644
index 0000000..36d4be6
--- /dev/null
+++ b/docs/source/user_guide/example/data/craie_npc.permh
@@ -0,0 +1,6564 @@
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_SU   RPERMEAB        1
+[Infos]
+Field=PERMEAB
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=1
+Max_Layer=10
+Nest_grid=0
+Max_NestG=1
+[Structure]
+X_Left_Corner=543500
+Y_Lower_Corner=2526100
+Ncolumn=387
+Nrows=304
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
+[Data]
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+Title=Craie NPC                                                      H_SU   RPERMEAB        2
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+Title=Craie NPC                                                      H_SU   RPERMEAB        3
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+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_SU   RPERMEAB        4
+[Infos]
+Field=PERMEAB
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=4
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+Ncolumn=387
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+[Data_Descript]
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+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+Title=Craie NPC                                                      H_SU   RPERMEAB        6
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+Title=Craie NPC                                                      H_SU   RPERMEAB        7
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+Title=Craie NPC                                                      H_SU   RPERMEAB        9
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+Title=Craie NPC                                                      H_SU   RPERMEAB       10
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_SU  1RPERMEAB        1
+[Infos]
+Field=PERMEAB
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=1
+Max_Layer=10
+Nest_grid=1
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+[Structure]
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+Ncolumn=307
+Nrows=442
+[Data_Descript]
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+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_SU  1RPERMEAB        2
+[Infos]
+Field=PERMEAB
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=2
+Max_Layer=10
+Nest_grid=1
+Max_NestG=1
+[Structure]
+X_Left_Corner=637500
+Y_Lower_Corner=2586600
+Ncolumn=307
+Nrows=442
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+Title=Craie NPC                                                      H_SU  1RPERMEAB        3
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_SU  1RPERMEAB        4
+[Infos]
+Field=PERMEAB
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=4
+Max_Layer=10
+Nest_grid=1
+Max_NestG=1
+[Structure]
+X_Left_Corner=637500
+Y_Lower_Corner=2586600
+Ncolumn=307
+Nrows=442
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_SU  1RPERMEAB        5
+[Infos]
+Field=PERMEAB
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=5
+Max_Layer=10
+Nest_grid=1
+Max_NestG=1
+[Structure]
+X_Left_Corner=637500
+Y_Lower_Corner=2586600
+Ncolumn=307
+Nrows=442
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_SU  1RPERMEAB        6
+[Infos]
+Field=PERMEAB
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=6
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+[Structure]
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+Ncolumn=307
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+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_SU  1RPERMEAB        7
+[Infos]
+Field=PERMEAB
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=7
+Max_Layer=10
+Nest_grid=1
+Max_NestG=1
+[Structure]
+X_Left_Corner=637500
+Y_Lower_Corner=2586600
+Ncolumn=307
+Nrows=442
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_SU  1RPERMEAB        8
+[Infos]
+Field=PERMEAB
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=8
+Max_Layer=10
+Nest_grid=1
+Max_NestG=1
+[Structure]
+X_Left_Corner=637500
+Y_Lower_Corner=2586600
+Ncolumn=307
+Nrows=442
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_SU  1RPERMEAB        9
+[Infos]
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+Type=
+Elem_Number=0
+Name=
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+[Structure]
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+[Data_Descript]
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+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
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+Title=Craie NPC                                                      H_SU  1RPERMEAB       10
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+[Num_Rows_/_y_/_dy]
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+[End_Grid]
diff --git a/docs/source/user_guide/example/data/example.hsubs b/docs/source/user_guide/example/data/example.hsubs
new file mode 100644
index 0000000..8cf0cb6
--- /dev/null
+++ b/docs/source/user_guide/example/data/example.hsubs
@@ -0,0 +1,2730 @@
+Marthe_Grid Version=9.0
+Title=                                                                       H_SUBSTRAT     1
+[Infos]
+Field=H_SUBSTRAT
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=1
+Max_Layer=10
+Nest_grid=0
+Max_NestG=0
+[Structure]
+X_Left_Corner=543500
+Y_Lower_Corner=2526100
+Ncolumn=387
+Nrows=304
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+Title=                                                                       H_SUBSTRAT     5
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+[Data_Descript]
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+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
+[Data]
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+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
+[Data]
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+[End_Grid]
diff --git a/docs/source/user_guide/example/data/example.topog b/docs/source/user_guide/example/data/example.topog
new file mode 100644
index 0000000..18d9ccf
--- /dev/null
+++ b/docs/source/user_guide/example/data/example.topog
@@ -0,0 +1,595 @@
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_TO   RH_TOPOGR       1
+[Infos]
+Field=H_TOPOGR
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=1
+Max_Layer=10
+Nest_grid=0
+Max_NestG=0
+[Structure]
+X_Left_Corner=543500
+Y_Lower_Corner=2526100
+Ncolumn=387
+Nrows=304
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
+[Data]
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+Title=Craie NPC                                                      H_TO   RH_TOPOGR       3
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+Title=Craie NPC                                                      H_TO   RH_TOPOGR       4
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+Title=Craie NPC                                                      H_TO   RH_TOPOGR       5
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_TO   RH_TOPOGR       6
+[Infos]
+Field=H_TOPOGR
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=6
+Max_Layer=10
+Nest_grid=0
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+[Constant_Data]
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_TO   RH_TOPOGR       7
+[Infos]
+Field=H_TOPOGR
+Type=
+Elem_Number=0
+Name=
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+[Constant_Data]
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_TO   RH_TOPOGR       8
+[Infos]
+Field=H_TOPOGR
+Type=
+Elem_Number=0
+Name=
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+[Constant_Data]
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_TO   RH_TOPOGR       9
+[Infos]
+Field=H_TOPOGR
+Type=
+Elem_Number=0
+Name=
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+[Constant_Data]
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_TO   RH_TOPOGR      10
+[Infos]
+Field=H_TOPOGR
+Type=
+Elem_Number=0
+Name=
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+Ncolumn=387
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+[Constant_Data]
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+[End_Grid]
diff --git a/docs/source/user_guide/example/data/grid_clean.hsubs b/docs/source/user_guide/example/data/grid_clean.hsubs
new file mode 100644
index 0000000..696ea7e
--- /dev/null
+++ b/docs/source/user_guide/example/data/grid_clean.hsubs
@@ -0,0 +1,905 @@
+Marthe_Grid Version=9.0
+Title=Bidon                                                                  H_SUBSTRAT     1
+[Infos]
+Field=H_SUBSTRAT
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=1
+Max_Layer=1
+Nest_grid=0
+Max_NestG=3
+[Structure]
+X_Left_Corner=528
+Y_Lower_Corner=2503
+Ncolumn=320
+Nrows=189
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Colums    >
+[Data]
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Bidon                                                                1 H_SUBSTRAT     1
+[Infos]
+Field=H_SUBSTRAT
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=1
+Max_Layer=1
+Nest_grid=1
+Max_NestG=3
+[Structure]
+X_Left_Corner=550.5
+Y_Lower_Corner=2552
+Ncolumn=322
+Nrows=237
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Colums    >
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+6	2551.05	14.94	14.59	14.59	14.59	14.59	14.59	14.9	14.9	14.9	14.9	14.9	16.06	16.06	16.06	16.06	16.06	18.41	18.41	18.41	18.41	18.41	20.02	20.02	20.02	20.02	20.02	21.47	21.47	21.47	21.47	21.47	21.84	21.84	21.84	21.84	21.84	22.04	22.04	22.04	22.04	22.04	22.58	22.58	22.58	22.58	22.58	25.14	25.14	25.14	25.14	25.14	27.29	27.29	27.29	27.29	27.29	30.52	30.52	30.52	30.52	30.52	31.31	31.31	31.31	31.31	31.31	30.86	30.86	30.86	30.86	30.86	30.28	30.28	30.28	30.28	30.28	29.57	29.57	29.57	29.57	29.57	29.39	29.39	29.39	29.39	29.39	29.73	29.73	29.73	29.73	29.73	30.3	30.3	30.3	30.3	30.3	31.22	31.22	31.22	31.22	31.22	31.93	31.93	31.93	31.93	31.93	33.16	33.16	33.16	33.16	33.16	34.14	34.14	34.14	34.14	34.14	35.66	35.66	35.66	35.66	35.66	36.49	36.49	36.49	36.49	36.49	37.48	37.48	37.48	37.48	37.48	37.92	37.92	37.92	37.92	37.92	38.3	38.3	38.3	38.3	38.3	38.56	38.56	38.56	38.56	38.56	38.92	38.92	38.92	38.92	38.92	39.08	39.08	39.08	39.08	39.08	39.28	39.28	39.28	39.28	39.28	39.61	39.61	39.61	39.61	39.61	40.35	40.35	40.35	40.35	40.35	40.73	40.73	40.73	40.73	40.73	41.04	41.04	41.04	41.04	41.04	41.2	41.2	41.2	41.2	41.2	42.11	42.11	42.11	42.11	42.11	43.24	43.24	43.24	43.24	43.24	44.89	44.89	44.89	44.89	44.89	45.79	45.79	45.79	45.79	45.79	47.06	47.06	47.06	47.06	47.06	47.91	47.91	47.91	47.91	47.91	48.79	.1000977	
+7	2550.95	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+8	2550.85	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+9	2550.75	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+10	2550.65	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+11	2550.55	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+12	2550.45	17.11	17.05	17.05	17.05	17.05	17.05	17.43	17.43	17.43	17.43	17.43	18.03	18.03	18.03	18.03	18.03	19.19	19.19	19.19	19.19	19.19	22	22	22	22	22	21.01	21.01	21.01	21.01	21.01	21.46	21.46	21.46	21.46	21.46	21.83	21.83	21.83	21.83	21.83	22.2	22.2	22.2	22.2	22.2	24.56	24.56	24.56	24.56	24.56	26.55	26.55	26.55	26.55	26.55	29.1	29.1	29.1	29.1	29.1	29.55	29.55	29.55	29.55	29.55	28.69	28.69	28.69	28.69	28.69	27.84	27.84	27.84	27.84	27.84	27.13	27.13	27.13	27.13	27.13	27.28	27.28	27.28	27.28	27.28	28.18	28.18	28.18	28.18	28.18	29.03	29.03	29.03	29.03	29.03	30.21	30.21	30.21	30.21	30.21	31.16	31.16	31.16	31.16	31.16	32.8	32.8	32.8	32.8	32.8	33.68	33.68	33.68	33.68	33.68	34.73	34.73	34.73	34.73	34.73	35.14	35.14	35.14	35.14	35.14	35.64	35.64	35.64	35.64	35.64	36.18	36.18	36.18	36.18	36.18	36.95	36.95	36.95	36.95	36.95	37.54	37.54	37.54	37.54	37.54	38.36	38.36	38.36	38.36	38.36	38.77	38.77	38.77	38.77	38.77	39.17	39.17	39.17	39.17	39.17	39.4	39.4	39.4	39.4	39.4	40.08	40.08	40.08	40.08	40.08	40.35	40.35	40.35	40.35	40.35	40.74	40.74	40.74	40.74	40.74	41.14	41.14	41.14	41.14	41.14	41.67	41.67	41.67	41.67	41.67	42.48	42.48	42.48	42.48	42.48	43.72	43.72	43.72	43.72	43.72	44.59	44.59	44.59	44.59	44.59	46.15	46.15	46.15	46.15	46.15	47.17	47.17	47.17	47.17	47.17	48.39	.1000977	
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+14	2550.25	17.11	17.05	17.05	17.05	17.05	17.05	17.43	17.43	17.43	17.43	17.43	18.03	18.03	18.03	18.03	18.03	19.19	19.19	19.19	19.19	19.19	22	22	22	22	22	21.01	21.01	21.01	21.01	21.01	21.46	21.46	21.46	21.46	21.46	21.83	21.83	21.83	21.83	21.83	22.2	22.2	22.2	22.2	22.2	24.56	24.56	24.56	24.56	24.56	26.55	26.55	26.55	26.55	26.55	29.1	29.1	29.1	29.1	29.1	29.55	29.55	29.55	29.55	29.55	28.69	28.69	28.69	28.69	28.69	27.84	27.84	27.84	27.84	27.84	27.13	27.13	27.13	27.13	27.13	27.28	27.28	27.28	27.28	27.28	28.18	28.18	28.18	28.18	28.18	29.03	29.03	29.03	29.03	29.03	30.21	30.21	30.21	30.21	30.21	31.16	31.16	31.16	31.16	31.16	32.8	32.8	32.8	32.8	32.8	33.68	33.68	33.68	33.68	33.68	34.73	34.73	34.73	34.73	34.73	35.14	35.14	35.14	35.14	35.14	35.64	35.64	35.64	35.64	35.64	36.18	36.18	36.18	36.18	36.18	36.95	36.95	36.95	36.95	36.95	37.54	37.54	37.54	37.54	37.54	38.36	38.36	38.36	38.36	38.36	38.77	38.77	38.77	38.77	38.77	39.17	39.17	39.17	39.17	39.17	39.4	39.4	39.4	39.4	39.4	40.08	40.08	40.08	40.08	40.08	40.35	40.35	40.35	40.35	40.35	40.74	40.74	40.74	40.74	40.74	41.14	41.14	41.14	41.14	41.14	41.67	41.67	41.67	41.67	41.67	42.48	42.48	42.48	42.48	42.48	43.72	43.72	43.72	43.72	43.72	44.59	44.59	44.59	44.59	44.59	46.15	46.15	46.15	46.15	46.15	47.17	47.17	47.17	47.17	47.17	48.39	.1000977	
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+28	2548.85	19.15	18.84	18.84	18.84	18.84	18.84	18.55	18.55	18.55	18.55	18.55	18.61	18.61	18.61	18.61	18.61	22	22	22	22	22	19.4	19.4	19.4	19.4	19.4	20.05	20.05	20.05	20.05	20.05	20.22	20.22	20.22	20.22	20.22	20.33	20.33	20.33	20.33	20.33	20.41	20.41	20.41	20.41	20.41	20.9	20.9	20.9	20.9	20.9	21.73	21.73	21.73	21.73	21.73	23.13	23.13	23.13	23.13	23.13	24.09	24.09	24.09	24.09	24.09	24.92	24.92	24.92	24.92	24.92	25.37	25.37	25.37	25.37	25.37	26.15	26.15	26.15	26.15	26.15	26.97	26.97	26.97	26.97	26.97	28.72	28.72	28.72	28.72	28.72	29.91	29.91	29.91	29.91	29.91	31.15	31.15	31.15	31.15	31.15	31.62	31.62	31.62	31.62	31.62	32.13	32.13	32.13	32.13	32.13	32.33	32.33	32.33	32.33	32.33	35	35	35	35	35	33.33	33.33	33.33	33.33	33.33	34.52	34.52	34.52	34.52	34.52	35.47	35.47	35.47	35.47	35.47	36.93	36.93	36.93	36.93	36.93	37.83	37.83	37.83	37.83	37.83	38.97	38.97	38.97	38.97	38.97	39.57	39.57	39.57	39.57	39.57	40.07	40.07	40.07	40.07	40.07	40.14	40.14	40.14	40.14	40.14	39.98	39.98	39.98	39.98	39.98	40.05	40.05	40.05	40.05	40.05	40.69	40.69	40.69	40.69	40.69	41.44	41.44	41.44	41.44	41.44	42.52	42.52	42.52	42.52	42.52	42.95	42.95	42.95	42.95	42.95	43.15	43.15	43.15	43.15	43.15	43.2	43.2	43.2	43.2	43.2	43.67	43.67	43.67	43.67	43.67	44.29	44.29	44.29	44.29	44.29	45.75	.1000977	
+29	2548.75	19.15	18.84	18.84	18.84	18.84	18.84	18.55	18.55	18.55	18.55	18.55	18.61	18.61	18.61	18.61	18.61	22	22	22	22	22	19.4	19.4	19.4	19.4	19.4	20.05	20.05	20.05	20.05	20.05	20.22	20.22	20.22	20.22	20.22	20.33	20.33	20.33	20.33	20.33	20.41	20.41	20.41	20.41	20.41	20.9	20.9	20.9	20.9	20.9	21.73	21.73	21.73	21.73	21.73	23.13	23.13	23.13	23.13	23.13	24.09	24.09	24.09	24.09	24.09	24.92	24.92	24.92	24.92	24.92	25.37	25.37	25.37	25.37	25.37	26.15	26.15	26.15	26.15	26.15	26.97	26.97	26.97	26.97	26.97	28.72	28.72	28.72	28.72	28.72	29.91	29.91	29.91	29.91	29.91	31.15	31.15	31.15	31.15	31.15	31.62	31.62	31.62	31.62	31.62	32.13	32.13	32.13	32.13	32.13	32.33	32.33	32.33	32.33	32.33	35	35	35	35	35	33.33	33.33	33.33	33.33	33.33	34.52	34.52	34.52	34.52	34.52	35.47	35.47	35.47	35.47	35.47	36.93	36.93	36.93	36.93	36.93	37.83	37.83	37.83	37.83	37.83	38.97	38.97	38.97	38.97	38.97	39.57	39.57	39.57	39.57	39.57	40.07	40.07	40.07	40.07	40.07	40.14	40.14	40.14	40.14	40.14	39.98	39.98	39.98	39.98	39.98	40.05	40.05	40.05	40.05	40.05	40.69	40.69	40.69	40.69	40.69	41.44	41.44	41.44	41.44	41.44	42.52	42.52	42.52	42.52	42.52	42.95	42.95	42.95	42.95	42.95	43.15	43.15	43.15	43.15	43.15	43.2	43.2	43.2	43.2	43.2	43.67	43.67	43.67	43.67	43.67	44.29	44.29	44.29	44.29	44.29	45.75	.1000977	
+30	2548.65	19.15	18.84	18.84	18.84	18.84	18.84	18.55	18.55	18.55	18.55	18.55	18.61	18.61	18.61	18.61	18.61	22	22	22	22	22	19.4	19.4	19.4	19.4	19.4	20.05	20.05	20.05	20.05	20.05	20.22	20.22	20.22	20.22	20.22	20.33	20.33	20.33	20.33	20.33	20.41	20.41	20.41	20.41	20.41	20.9	20.9	20.9	20.9	20.9	21.73	21.73	21.73	21.73	21.73	23.13	23.13	23.13	23.13	23.13	24.09	24.09	24.09	24.09	24.09	24.92	24.92	24.92	24.92	24.92	25.37	25.37	25.37	25.37	25.37	26.15	26.15	26.15	26.15	26.15	26.97	26.97	26.97	26.97	26.97	28.72	28.72	28.72	28.72	28.72	29.91	29.91	29.91	29.91	29.91	31.15	31.15	31.15	31.15	31.15	31.62	31.62	31.62	31.62	31.62	32.13	32.13	32.13	32.13	32.13	32.33	32.33	32.33	32.33	32.33	35	35	35	35	35	33.33	33.33	33.33	33.33	33.33	34.52	34.52	34.52	34.52	34.52	35.47	35.47	35.47	35.47	35.47	36.93	36.93	36.93	36.93	36.93	37.83	37.83	37.83	37.83	37.83	38.97	38.97	38.97	38.97	38.97	39.57	39.57	39.57	39.57	39.57	40.07	40.07	40.07	40.07	40.07	40.14	40.14	40.14	40.14	40.14	39.98	39.98	39.98	39.98	39.98	40.05	40.05	40.05	40.05	40.05	40.69	40.69	40.69	40.69	40.69	41.44	41.44	41.44	41.44	41.44	42.52	42.52	42.52	42.52	42.52	42.95	42.95	42.95	42.95	42.95	43.15	43.15	43.15	43.15	43.15	43.2	43.2	43.2	43.2	43.2	43.67	43.67	43.67	43.67	43.67	44.29	44.29	44.29	44.29	44.29	45.75	.1000977	
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+50	2546.65	21.67	20.63	20.63	20.63	20.63	20.63	17.85	17.85	17.85	17.85	17.85	15.82	15.82	15.82	15.82	15.82	13.84	13.84	13.84	13.84	13.84	13.51	13.51	13.51	13.51	13.51	14.17	14.17	14.17	14.17	14.17	14.78	14.78	14.78	14.78	14.78	15.29	15.29	15.29	15.29	15.29	15.5	15.5	15.5	15.5	15.5	16.02	16.02	16.02	16.02	16.02	16.93	16.93	16.93	16.93	16.93	19.24	19.24	19.24	19.24	19.24	20.94	20.94	20.94	20.94	20.94	23.19	23.19	23.19	23.19	23.19	24.3	24.3	24.3	24.3	24.3	25.26	25.26	25.26	25.26	25.26	25.92	25.92	25.92	25.92	25.92	27.01	27.01	27.01	27.01	27.01	27.77	27.77	27.77	27.77	27.77	29.24	29.24	29.24	29.24	29.24	30.23	30.23	30.23	30.23	30.23	31.62	31.62	31.62	31.62	31.62	32.4	32.4	32.4	32.4	32.4	33.28	33.28	33.28	33.28	33.28	33.73	33.73	33.73	33.73	33.73	34.42	34.42	34.42	34.42	34.42	35.4	35.4	35.4	35.4	35.4	37.47	37.47	37.47	37.47	37.47	39.06	39.06	39.06	39.06	39.06	41.07	41.07	41.07	41.07	41.07	41.58	41.58	41.58	41.58	41.58	41.79	41.79	41.79	41.79	41.79	41.75	41.75	41.75	41.75	41.75	41.79	41.79	41.79	41.79	41.79	41.85	41.85	41.85	41.85	41.85	41.96	41.96	41.96	41.96	41.96	42.07	42.07	42.07	42.07	42.07	42.23	42.23	42.23	42.23	42.23	42.29	42.29	42.29	42.29	42.29	42.31	42.31	42.31	42.31	42.31	42.29	42.29	42.29	42.29	42.29	42.22	42.22	42.22	42.22	42.22	42.17	42.17	42.17	42.17	42.17	42.13	.1000977	
+51	2546.55	21.67	20.63	20.63	20.63	20.63	20.63	17.85	17.85	17.85	17.85	17.85	15.82	15.82	15.82	15.82	15.82	13.84	13.84	13.84	13.84	13.84	13.51	13.51	13.51	13.51	13.51	14.17	14.17	14.17	14.17	14.17	14.78	14.78	14.78	14.78	14.78	15.29	15.29	15.29	15.29	15.29	15.5	15.5	15.5	15.5	15.5	16.02	16.02	16.02	16.02	16.02	16.93	16.93	16.93	16.93	16.93	19.24	19.24	19.24	19.24	19.24	20.94	20.94	20.94	20.94	20.94	23.19	23.19	23.19	23.19	23.19	24.3	24.3	24.3	24.3	24.3	25.26	25.26	25.26	25.26	25.26	25.92	25.92	25.92	25.92	25.92	27.01	27.01	27.01	27.01	27.01	27.77	27.77	27.77	27.77	27.77	29.24	29.24	29.24	29.24	29.24	30.23	30.23	30.23	30.23	30.23	31.62	31.62	31.62	31.62	31.62	32.4	32.4	32.4	32.4	32.4	33.28	33.28	33.28	33.28	33.28	33.73	33.73	33.73	33.73	33.73	34.42	34.42	34.42	34.42	34.42	35.4	35.4	35.4	35.4	35.4	37.47	37.47	37.47	37.47	37.47	39.06	39.06	39.06	39.06	39.06	41.07	41.07	41.07	41.07	41.07	41.58	41.58	41.58	41.58	41.58	41.79	41.79	41.79	41.79	41.79	41.75	41.75	41.75	41.75	41.75	41.79	41.79	41.79	41.79	41.79	41.85	41.85	41.85	41.85	41.85	41.96	41.96	41.96	41.96	41.96	42.07	42.07	42.07	42.07	42.07	42.23	42.23	42.23	42.23	42.23	42.29	42.29	42.29	42.29	42.29	42.31	42.31	42.31	42.31	42.31	42.29	42.29	42.29	42.29	42.29	42.22	42.22	42.22	42.22	42.22	42.17	42.17	42.17	42.17	42.17	42.13	.1000977	
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+91	2542.55	25.91	24.95	24.95	24.95	24.95	24.95	23.46	23.46	23.46	23.46	23.46	22.41	22.41	22.41	22.41	22.41	20.89	20.89	20.89	20.89	20.89	20.1	20.1	20.1	20.1	20.1	18.05	18.05	18.05	18.05	18.05	15.44	15.44	15.44	15.44	15.44	11.84	11.84	11.84	11.84	11.84	10.93	10.93	10.93	10.93	10.93	12.91	12.91	12.91	12.91	12.91	16.21	16.21	16.21	16.21	16.21	20.11	20.11	20.11	20.11	20.11	21.33	21.33	21.33	21.33	21.33	21.85	21.85	21.85	21.85	21.85	22.36	22.36	22.36	22.36	22.36	23.99	23.99	23.99	23.99	23.99	25.18	25.18	25.18	25.18	25.18	27.13	27.13	27.13	27.13	27.13	28.18	28.18	28.18	28.18	28.18	29.49	29.49	29.49	29.49	29.49	30.2	30.2	30.2	30.2	30.2	31.49	31.49	31.49	31.49	31.49	32.35	32.35	32.35	32.35	32.35	33.38	33.38	33.38	33.38	33.38	33.94	33.94	33.94	33.94	33.94	34.51	34.51	34.51	34.51	34.51	35.07	35.07	35.07	35.07	35.07	36.03	36.03	36.03	36.03	36.03	36.65	36.65	36.65	36.65	36.65	37.52	37.52	37.52	37.52	37.52	38.11	38.11	38.11	38.11	38.11	38.77	38.77	38.77	38.77	38.77	38.93	38.93	38.93	38.93	38.93	38.92	38.92	38.92	38.92	38.92	38.97	38.97	38.97	38.97	38.97	39.26	39.26	39.26	39.26	39.26	39.52	39.52	39.52	39.52	39.52	40.01	40.01	40.01	40.01	40.01	40.15	40.15	40.15	40.15	40.15	42	42	42	42	42	40.55	40.55	40.55	40.55	40.55	41.12	41.12	41.12	41.12	41.12	41.99	41.99	41.99	41.99	41.99	42.98	.1000977	
+92	2542.45	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+93	2542.35	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+94	2542.25	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+95	2542.15	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+96	2542.05	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+97	2541.95	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+98	2541.85	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+99	2541.75	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+100	2541.65	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+101	2541.55	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+102	2541.45	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+103	2541.35	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+104	2541.25	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+105	2541.15	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+106	2541.05	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+107	2540.95	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
+108	2540.85	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
+109	2540.75	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
+110	2540.65	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
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+112	2540.45	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+113	2540.35	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+114	2540.25	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+115	2540.15	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+116	2540.05	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+117	2539.95	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
+118	2539.85	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
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+120	2539.65	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
+121	2539.55	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
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+192	2532.45	36.37	35.59	35.59	35.59	35.59	35.59	34.26	34.26	34.26	34.26	34.26	33.14	33.14	33.14	33.14	33.14	31.63	31.63	31.63	31.63	31.63	30.63	30.63	30.63	30.63	30.63	29.28	29.28	29.28	29.28	29.28	28.24	28.24	28.24	28.24	28.24	27.07	27.07	27.07	27.07	27.07	26.57	26.57	26.57	26.57	26.57	26.17	26.17	26.17	26.17	26.17	25.86	25.86	25.86	25.86	25.86	25.33	25.33	25.33	25.33	25.33	25.09	25.09	25.09	25.09	25.09	27	27	27	27	27	25.52	25.52	25.52	25.52	25.52	26.69	26.69	26.69	26.69	26.69	27.22	27.22	27.22	27.22	27.22	28.37	28.37	28.37	28.37	28.37	29.25	29.25	29.25	29.25	29.25	30.65	30.65	30.65	30.65	30.65	31.33	31.33	31.33	31.33	31.33	31.35	31.35	31.35	31.35	31.35	31.01	31.01	31.01	31.01	31.01	30.48	30.48	30.48	30.48	30.48	30.32	30.32	30.32	30.32	30.32	30.64	30.64	30.64	30.64	30.64	31.18	31.18	31.18	31.18	31.18	32.12	32.12	32.12	32.12	32.12	32.58	32.58	32.58	32.58	32.58	33.04	33.04	33.04	33.04	33.04	33.76	33.76	33.76	33.76	33.76	34.91	34.91	34.91	34.91	34.91	35.72	35.72	35.72	35.72	35.72	36.57	36.57	36.57	36.57	36.57	36.85	36.85	36.85	36.85	36.85	37.71	37.71	37.71	37.71	37.71	38.56	38.56	38.56	38.56	38.56	39.72	39.72	39.72	39.72	39.72	40.33	40.33	40.33	40.33	40.33	40.8	40.8	40.8	40.8	40.8	40.82	40.82	40.82	40.82	40.82	40.6	40.6	40.6	40.6	40.6	40.32	40.32	40.32	40.32	40.32	39.7	.1000977	
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+199	2531.75	35.99	35.17	35.17	35.17	35.17	35.17	33.81	33.81	33.81	33.81	33.81	32.67	32.67	32.67	32.67	32.67	31.33	31.33	31.33	31.33	31.33	30.4	30.4	30.4	30.4	30.4	29.21	29.21	29.21	29.21	29.21	28.32	28.32	28.32	28.32	28.32	27.27	27.27	27.27	27.27	27.27	26.82	26.82	26.82	26.82	26.82	26.27	26.27	26.27	26.27	26.27	26.12	26.12	26.12	26.12	26.12	25.51	25.51	25.51	25.51	25.51	25.23	25.23	25.23	25.23	25.23	27	27	27	27	27	25.11	25.11	25.11	25.11	25.11	25.8	25.8	25.8	25.8	25.8	26.08	26.08	26.08	26.08	26.08	27.04	27.04	27.04	27.04	27.04	28.04	28.04	28.04	28.04	28.04	29.62	29.62	29.62	29.62	29.62	30.45	30.45	30.45	30.45	30.45	30.3	30.3	30.3	30.3	30.3	29.85	29.85	29.85	29.85	29.85	29.39	29.39	29.39	29.39	29.39	29.47	29.47	29.47	29.47	29.47	30.18	30.18	30.18	30.18	30.18	30.79	30.79	30.79	30.79	30.79	31.77	31.77	31.77	31.77	31.77	32.29	32.29	32.29	32.29	32.29	32.9	32.9	32.9	32.9	32.9	33.63	33.63	33.63	33.63	33.63	34.75	34.75	34.75	34.75	34.75	35.36	35.36	35.36	35.36	35.36	35.85	35.85	35.85	35.85	35.85	36	36	36	36	36	36.65	36.65	36.65	36.65	36.65	37.4	37.4	37.4	37.4	37.4	38.52	38.52	38.52	38.52	38.52	39.12	39.12	39.12	39.12	39.12	39.71	39.71	39.71	39.71	39.71	39.86	39.86	39.86	39.86	39.86	39.9	39.9	39.9	39.9	39.9	39.78	39.78	39.78	39.78	39.78	39.36	.1000977	
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+202	2531.45	35.3	34.49	34.49	34.49	34.49	34.49	33.24	33.24	33.24	33.24	33.24	32.21	32.21	32.21	32.21	32.21	30.97	30.97	30.97	30.97	30.97	30.12	30.12	30.12	30.12	30.12	29.04	29.04	29.04	29.04	29.04	28.46	28.46	28.46	28.46	28.46	27.6	27.6	27.6	27.6	27.6	27.08	27.08	27.08	27.08	27.08	26.78	26.78	26.78	26.78	26.78	26.75	26.75	26.75	26.75	26.75	26.27	26.27	26.27	26.27	26.27	28	28	28	28	28	24.83	24.83	24.83	24.83	24.83	27	27	27	27	27	27	27	27	27	27	24.49	24.49	24.49	24.49	24.49	25.34	25.34	25.34	25.34	25.34	26.4	26.4	26.4	26.4	26.4	28.09	28.09	28.09	28.09	28.09	28.89	28.89	28.89	28.89	28.89	28.48	28.48	28.48	28.48	28.48	28.21	28.21	28.21	28.21	28.21	28.03	28.03	28.03	28.03	28.03	28.54	28.54	28.54	28.54	28.54	30.09	30.09	30.09	30.09	30.09	30.82	30.82	30.82	30.82	30.82	31.69	31.69	31.69	31.69	31.69	32.04	32.04	32.04	32.04	32.04	32.53	32.53	32.53	32.53	32.53	33.06	33.06	33.06	33.06	33.06	33.87	33.87	33.87	33.87	33.87	34.24	34.24	34.24	34.24	34.24	34.44	34.44	34.44	34.44	34.44	34.58	34.58	34.58	34.58	34.58	35.19	35.19	35.19	35.19	35.19	35.82	35.82	35.82	35.82	35.82	37.01	37.01	37.01	37.01	37.01	37.65	37.65	37.65	37.65	37.65	38.32	38.32	38.32	38.32	38.32	38.59	38.59	38.59	38.59	38.59	38.74	38.74	38.74	38.74	38.74	38.78	38.78	38.78	38.78	38.78	38.61	.1000977	
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+[End_Grid]
diff --git a/docs/source/user_guide/example/data/grid_wrong_attrs.hsubs b/docs/source/user_guide/example/data/grid_wrong_attrs.hsubs
new file mode 100644
index 0000000..9bb7058
--- /dev/null
+++ b/docs/source/user_guide/example/data/grid_wrong_attrs.hsubs
@@ -0,0 +1,905 @@
+Marthe_Grid Version=9.0
+Title=Bidon                                                                  H_SUBSTRAT     1
+[Infos]
+Field=
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=0
+Max_Layer=0
+Nest_grid=0
+Max_NestG=0
+[Structure]
+X_Left_Corner=528
+Y_Lower_Corner=2503
+Ncolumn=320
+Nrows=189
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Colums    >
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+Title=Bidon                                                                2 H_SUBSTRAT     1
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+6	2551.05	14.94	14.59	14.59	14.59	14.59	14.59	14.9	14.9	14.9	14.9	14.9	16.06	16.06	16.06	16.06	16.06	18.41	18.41	18.41	18.41	18.41	20.02	20.02	20.02	20.02	20.02	21.47	21.47	21.47	21.47	21.47	21.84	21.84	21.84	21.84	21.84	22.04	22.04	22.04	22.04	22.04	22.58	22.58	22.58	22.58	22.58	25.14	25.14	25.14	25.14	25.14	27.29	27.29	27.29	27.29	27.29	30.52	30.52	30.52	30.52	30.52	31.31	31.31	31.31	31.31	31.31	30.86	30.86	30.86	30.86	30.86	30.28	30.28	30.28	30.28	30.28	29.57	29.57	29.57	29.57	29.57	29.39	29.39	29.39	29.39	29.39	29.73	29.73	29.73	29.73	29.73	30.3	30.3	30.3	30.3	30.3	31.22	31.22	31.22	31.22	31.22	31.93	31.93	31.93	31.93	31.93	33.16	33.16	33.16	33.16	33.16	34.14	34.14	34.14	34.14	34.14	35.66	35.66	35.66	35.66	35.66	36.49	36.49	36.49	36.49	36.49	37.48	37.48	37.48	37.48	37.48	37.92	37.92	37.92	37.92	37.92	38.3	38.3	38.3	38.3	38.3	38.56	38.56	38.56	38.56	38.56	38.92	38.92	38.92	38.92	38.92	39.08	39.08	39.08	39.08	39.08	39.28	39.28	39.28	39.28	39.28	39.61	39.61	39.61	39.61	39.61	40.35	40.35	40.35	40.35	40.35	40.73	40.73	40.73	40.73	40.73	41.04	41.04	41.04	41.04	41.04	41.2	41.2	41.2	41.2	41.2	42.11	42.11	42.11	42.11	42.11	43.24	43.24	43.24	43.24	43.24	44.89	44.89	44.89	44.89	44.89	45.79	45.79	45.79	45.79	45.79	47.06	47.06	47.06	47.06	47.06	47.91	47.91	47.91	47.91	47.91	48.79	.1000977	
+7	2550.95	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+8	2550.85	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+9	2550.75	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+10	2550.65	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+11	2550.55	15.81	15.59	15.59	15.59	15.59	15.59	15.87	15.87	15.87	15.87	15.87	16.82	16.82	16.82	16.82	16.82	18.7	18.7	18.7	18.7	18.7	20.08	20.08	20.08	20.08	20.08	21.29	21.29	21.29	21.29	21.29	21.7	21.7	21.7	21.7	21.7	21.97	21.97	21.97	21.97	21.97	22.61	22.61	22.61	22.61	22.61	25.38	25.38	25.38	25.38	25.38	27.55	27.55	27.55	27.55	27.55	30.62	30.62	30.62	30.62	30.62	30.86	30.86	30.86	30.86	30.86	29.97	29.97	29.97	29.97	29.97	29.22	29.22	29.22	29.22	29.22	28.45	28.45	28.45	28.45	28.45	28.41	28.41	28.41	28.41	28.41	28.97	28.97	28.97	28.97	28.97	29.51	29.51	29.51	29.51	29.51	30.43	30.43	30.43	30.43	30.43	31.27	31.27	31.27	31.27	31.27	32.86	32.86	32.86	32.86	32.86	33.88	33.88	33.88	33.88	33.88	35.27	35.27	35.27	35.27	35.27	35.91	35.91	35.91	35.91	35.91	36.55	36.55	36.55	36.55	36.55	37.01	37.01	37.01	37.01	37.01	37.61	37.61	37.61	37.61	37.61	38.07	38.07	38.07	38.07	38.07	38.66	38.66	38.66	38.66	38.66	38.91	38.91	38.91	38.91	38.91	39.13	39.13	39.13	39.13	39.13	39.42	39.42	39.42	39.42	39.42	40.37	40.37	40.37	40.37	40.37	40.78	40.78	40.78	40.78	40.78	41.05	41.05	41.05	41.05	41.05	41.3	41.3	41.3	41.3	41.3	41.94	41.94	41.94	41.94	41.94	42.92	42.92	42.92	42.92	42.92	44.39	44.39	44.39	44.39	44.39	45.27	45.27	45.27	45.27	45.27	46.69	46.69	46.69	46.69	46.69	47.61	47.61	47.61	47.61	47.61	48.53	.1000977	
+12	2550.45	17.11	17.05	17.05	17.05	17.05	17.05	17.43	17.43	17.43	17.43	17.43	18.03	18.03	18.03	18.03	18.03	19.19	19.19	19.19	19.19	19.19	22	22	22	22	22	21.01	21.01	21.01	21.01	21.01	21.46	21.46	21.46	21.46	21.46	21.83	21.83	21.83	21.83	21.83	22.2	22.2	22.2	22.2	22.2	24.56	24.56	24.56	24.56	24.56	26.55	26.55	26.55	26.55	26.55	29.1	29.1	29.1	29.1	29.1	29.55	29.55	29.55	29.55	29.55	28.69	28.69	28.69	28.69	28.69	27.84	27.84	27.84	27.84	27.84	27.13	27.13	27.13	27.13	27.13	27.28	27.28	27.28	27.28	27.28	28.18	28.18	28.18	28.18	28.18	29.03	29.03	29.03	29.03	29.03	30.21	30.21	30.21	30.21	30.21	31.16	31.16	31.16	31.16	31.16	32.8	32.8	32.8	32.8	32.8	33.68	33.68	33.68	33.68	33.68	34.73	34.73	34.73	34.73	34.73	35.14	35.14	35.14	35.14	35.14	35.64	35.64	35.64	35.64	35.64	36.18	36.18	36.18	36.18	36.18	36.95	36.95	36.95	36.95	36.95	37.54	37.54	37.54	37.54	37.54	38.36	38.36	38.36	38.36	38.36	38.77	38.77	38.77	38.77	38.77	39.17	39.17	39.17	39.17	39.17	39.4	39.4	39.4	39.4	39.4	40.08	40.08	40.08	40.08	40.08	40.35	40.35	40.35	40.35	40.35	40.74	40.74	40.74	40.74	40.74	41.14	41.14	41.14	41.14	41.14	41.67	41.67	41.67	41.67	41.67	42.48	42.48	42.48	42.48	42.48	43.72	43.72	43.72	43.72	43.72	44.59	44.59	44.59	44.59	44.59	46.15	46.15	46.15	46.15	46.15	47.17	47.17	47.17	47.17	47.17	48.39	.1000977	
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+14	2550.25	17.11	17.05	17.05	17.05	17.05	17.05	17.43	17.43	17.43	17.43	17.43	18.03	18.03	18.03	18.03	18.03	19.19	19.19	19.19	19.19	19.19	22	22	22	22	22	21.01	21.01	21.01	21.01	21.01	21.46	21.46	21.46	21.46	21.46	21.83	21.83	21.83	21.83	21.83	22.2	22.2	22.2	22.2	22.2	24.56	24.56	24.56	24.56	24.56	26.55	26.55	26.55	26.55	26.55	29.1	29.1	29.1	29.1	29.1	29.55	29.55	29.55	29.55	29.55	28.69	28.69	28.69	28.69	28.69	27.84	27.84	27.84	27.84	27.84	27.13	27.13	27.13	27.13	27.13	27.28	27.28	27.28	27.28	27.28	28.18	28.18	28.18	28.18	28.18	29.03	29.03	29.03	29.03	29.03	30.21	30.21	30.21	30.21	30.21	31.16	31.16	31.16	31.16	31.16	32.8	32.8	32.8	32.8	32.8	33.68	33.68	33.68	33.68	33.68	34.73	34.73	34.73	34.73	34.73	35.14	35.14	35.14	35.14	35.14	35.64	35.64	35.64	35.64	35.64	36.18	36.18	36.18	36.18	36.18	36.95	36.95	36.95	36.95	36.95	37.54	37.54	37.54	37.54	37.54	38.36	38.36	38.36	38.36	38.36	38.77	38.77	38.77	38.77	38.77	39.17	39.17	39.17	39.17	39.17	39.4	39.4	39.4	39.4	39.4	40.08	40.08	40.08	40.08	40.08	40.35	40.35	40.35	40.35	40.35	40.74	40.74	40.74	40.74	40.74	41.14	41.14	41.14	41.14	41.14	41.67	41.67	41.67	41.67	41.67	42.48	42.48	42.48	42.48	42.48	43.72	43.72	43.72	43.72	43.72	44.59	44.59	44.59	44.59	44.59	46.15	46.15	46.15	46.15	46.15	47.17	47.17	47.17	47.17	47.17	48.39	.1000977	
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+28	2548.85	19.15	18.84	18.84	18.84	18.84	18.84	18.55	18.55	18.55	18.55	18.55	18.61	18.61	18.61	18.61	18.61	22	22	22	22	22	19.4	19.4	19.4	19.4	19.4	20.05	20.05	20.05	20.05	20.05	20.22	20.22	20.22	20.22	20.22	20.33	20.33	20.33	20.33	20.33	20.41	20.41	20.41	20.41	20.41	20.9	20.9	20.9	20.9	20.9	21.73	21.73	21.73	21.73	21.73	23.13	23.13	23.13	23.13	23.13	24.09	24.09	24.09	24.09	24.09	24.92	24.92	24.92	24.92	24.92	25.37	25.37	25.37	25.37	25.37	26.15	26.15	26.15	26.15	26.15	26.97	26.97	26.97	26.97	26.97	28.72	28.72	28.72	28.72	28.72	29.91	29.91	29.91	29.91	29.91	31.15	31.15	31.15	31.15	31.15	31.62	31.62	31.62	31.62	31.62	32.13	32.13	32.13	32.13	32.13	32.33	32.33	32.33	32.33	32.33	35	35	35	35	35	33.33	33.33	33.33	33.33	33.33	34.52	34.52	34.52	34.52	34.52	35.47	35.47	35.47	35.47	35.47	36.93	36.93	36.93	36.93	36.93	37.83	37.83	37.83	37.83	37.83	38.97	38.97	38.97	38.97	38.97	39.57	39.57	39.57	39.57	39.57	40.07	40.07	40.07	40.07	40.07	40.14	40.14	40.14	40.14	40.14	39.98	39.98	39.98	39.98	39.98	40.05	40.05	40.05	40.05	40.05	40.69	40.69	40.69	40.69	40.69	41.44	41.44	41.44	41.44	41.44	42.52	42.52	42.52	42.52	42.52	42.95	42.95	42.95	42.95	42.95	43.15	43.15	43.15	43.15	43.15	43.2	43.2	43.2	43.2	43.2	43.67	43.67	43.67	43.67	43.67	44.29	44.29	44.29	44.29	44.29	45.75	.1000977	
+29	2548.75	19.15	18.84	18.84	18.84	18.84	18.84	18.55	18.55	18.55	18.55	18.55	18.61	18.61	18.61	18.61	18.61	22	22	22	22	22	19.4	19.4	19.4	19.4	19.4	20.05	20.05	20.05	20.05	20.05	20.22	20.22	20.22	20.22	20.22	20.33	20.33	20.33	20.33	20.33	20.41	20.41	20.41	20.41	20.41	20.9	20.9	20.9	20.9	20.9	21.73	21.73	21.73	21.73	21.73	23.13	23.13	23.13	23.13	23.13	24.09	24.09	24.09	24.09	24.09	24.92	24.92	24.92	24.92	24.92	25.37	25.37	25.37	25.37	25.37	26.15	26.15	26.15	26.15	26.15	26.97	26.97	26.97	26.97	26.97	28.72	28.72	28.72	28.72	28.72	29.91	29.91	29.91	29.91	29.91	31.15	31.15	31.15	31.15	31.15	31.62	31.62	31.62	31.62	31.62	32.13	32.13	32.13	32.13	32.13	32.33	32.33	32.33	32.33	32.33	35	35	35	35	35	33.33	33.33	33.33	33.33	33.33	34.52	34.52	34.52	34.52	34.52	35.47	35.47	35.47	35.47	35.47	36.93	36.93	36.93	36.93	36.93	37.83	37.83	37.83	37.83	37.83	38.97	38.97	38.97	38.97	38.97	39.57	39.57	39.57	39.57	39.57	40.07	40.07	40.07	40.07	40.07	40.14	40.14	40.14	40.14	40.14	39.98	39.98	39.98	39.98	39.98	40.05	40.05	40.05	40.05	40.05	40.69	40.69	40.69	40.69	40.69	41.44	41.44	41.44	41.44	41.44	42.52	42.52	42.52	42.52	42.52	42.95	42.95	42.95	42.95	42.95	43.15	43.15	43.15	43.15	43.15	43.2	43.2	43.2	43.2	43.2	43.67	43.67	43.67	43.67	43.67	44.29	44.29	44.29	44.29	44.29	45.75	.1000977	
+30	2548.65	19.15	18.84	18.84	18.84	18.84	18.84	18.55	18.55	18.55	18.55	18.55	18.61	18.61	18.61	18.61	18.61	22	22	22	22	22	19.4	19.4	19.4	19.4	19.4	20.05	20.05	20.05	20.05	20.05	20.22	20.22	20.22	20.22	20.22	20.33	20.33	20.33	20.33	20.33	20.41	20.41	20.41	20.41	20.41	20.9	20.9	20.9	20.9	20.9	21.73	21.73	21.73	21.73	21.73	23.13	23.13	23.13	23.13	23.13	24.09	24.09	24.09	24.09	24.09	24.92	24.92	24.92	24.92	24.92	25.37	25.37	25.37	25.37	25.37	26.15	26.15	26.15	26.15	26.15	26.97	26.97	26.97	26.97	26.97	28.72	28.72	28.72	28.72	28.72	29.91	29.91	29.91	29.91	29.91	31.15	31.15	31.15	31.15	31.15	31.62	31.62	31.62	31.62	31.62	32.13	32.13	32.13	32.13	32.13	32.33	32.33	32.33	32.33	32.33	35	35	35	35	35	33.33	33.33	33.33	33.33	33.33	34.52	34.52	34.52	34.52	34.52	35.47	35.47	35.47	35.47	35.47	36.93	36.93	36.93	36.93	36.93	37.83	37.83	37.83	37.83	37.83	38.97	38.97	38.97	38.97	38.97	39.57	39.57	39.57	39.57	39.57	40.07	40.07	40.07	40.07	40.07	40.14	40.14	40.14	40.14	40.14	39.98	39.98	39.98	39.98	39.98	40.05	40.05	40.05	40.05	40.05	40.69	40.69	40.69	40.69	40.69	41.44	41.44	41.44	41.44	41.44	42.52	42.52	42.52	42.52	42.52	42.95	42.95	42.95	42.95	42.95	43.15	43.15	43.15	43.15	43.15	43.2	43.2	43.2	43.2	43.2	43.67	43.67	43.67	43.67	43.67	44.29	44.29	44.29	44.29	44.29	45.75	.1000977	
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+50	2546.65	21.67	20.63	20.63	20.63	20.63	20.63	17.85	17.85	17.85	17.85	17.85	15.82	15.82	15.82	15.82	15.82	13.84	13.84	13.84	13.84	13.84	13.51	13.51	13.51	13.51	13.51	14.17	14.17	14.17	14.17	14.17	14.78	14.78	14.78	14.78	14.78	15.29	15.29	15.29	15.29	15.29	15.5	15.5	15.5	15.5	15.5	16.02	16.02	16.02	16.02	16.02	16.93	16.93	16.93	16.93	16.93	19.24	19.24	19.24	19.24	19.24	20.94	20.94	20.94	20.94	20.94	23.19	23.19	23.19	23.19	23.19	24.3	24.3	24.3	24.3	24.3	25.26	25.26	25.26	25.26	25.26	25.92	25.92	25.92	25.92	25.92	27.01	27.01	27.01	27.01	27.01	27.77	27.77	27.77	27.77	27.77	29.24	29.24	29.24	29.24	29.24	30.23	30.23	30.23	30.23	30.23	31.62	31.62	31.62	31.62	31.62	32.4	32.4	32.4	32.4	32.4	33.28	33.28	33.28	33.28	33.28	33.73	33.73	33.73	33.73	33.73	34.42	34.42	34.42	34.42	34.42	35.4	35.4	35.4	35.4	35.4	37.47	37.47	37.47	37.47	37.47	39.06	39.06	39.06	39.06	39.06	41.07	41.07	41.07	41.07	41.07	41.58	41.58	41.58	41.58	41.58	41.79	41.79	41.79	41.79	41.79	41.75	41.75	41.75	41.75	41.75	41.79	41.79	41.79	41.79	41.79	41.85	41.85	41.85	41.85	41.85	41.96	41.96	41.96	41.96	41.96	42.07	42.07	42.07	42.07	42.07	42.23	42.23	42.23	42.23	42.23	42.29	42.29	42.29	42.29	42.29	42.31	42.31	42.31	42.31	42.31	42.29	42.29	42.29	42.29	42.29	42.22	42.22	42.22	42.22	42.22	42.17	42.17	42.17	42.17	42.17	42.13	.1000977	
+51	2546.55	21.67	20.63	20.63	20.63	20.63	20.63	17.85	17.85	17.85	17.85	17.85	15.82	15.82	15.82	15.82	15.82	13.84	13.84	13.84	13.84	13.84	13.51	13.51	13.51	13.51	13.51	14.17	14.17	14.17	14.17	14.17	14.78	14.78	14.78	14.78	14.78	15.29	15.29	15.29	15.29	15.29	15.5	15.5	15.5	15.5	15.5	16.02	16.02	16.02	16.02	16.02	16.93	16.93	16.93	16.93	16.93	19.24	19.24	19.24	19.24	19.24	20.94	20.94	20.94	20.94	20.94	23.19	23.19	23.19	23.19	23.19	24.3	24.3	24.3	24.3	24.3	25.26	25.26	25.26	25.26	25.26	25.92	25.92	25.92	25.92	25.92	27.01	27.01	27.01	27.01	27.01	27.77	27.77	27.77	27.77	27.77	29.24	29.24	29.24	29.24	29.24	30.23	30.23	30.23	30.23	30.23	31.62	31.62	31.62	31.62	31.62	32.4	32.4	32.4	32.4	32.4	33.28	33.28	33.28	33.28	33.28	33.73	33.73	33.73	33.73	33.73	34.42	34.42	34.42	34.42	34.42	35.4	35.4	35.4	35.4	35.4	37.47	37.47	37.47	37.47	37.47	39.06	39.06	39.06	39.06	39.06	41.07	41.07	41.07	41.07	41.07	41.58	41.58	41.58	41.58	41.58	41.79	41.79	41.79	41.79	41.79	41.75	41.75	41.75	41.75	41.75	41.79	41.79	41.79	41.79	41.79	41.85	41.85	41.85	41.85	41.85	41.96	41.96	41.96	41.96	41.96	42.07	42.07	42.07	42.07	42.07	42.23	42.23	42.23	42.23	42.23	42.29	42.29	42.29	42.29	42.29	42.31	42.31	42.31	42.31	42.31	42.29	42.29	42.29	42.29	42.29	42.22	42.22	42.22	42.22	42.22	42.17	42.17	42.17	42.17	42.17	42.13	.1000977	
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+91	2542.55	25.91	24.95	24.95	24.95	24.95	24.95	23.46	23.46	23.46	23.46	23.46	22.41	22.41	22.41	22.41	22.41	20.89	20.89	20.89	20.89	20.89	20.1	20.1	20.1	20.1	20.1	18.05	18.05	18.05	18.05	18.05	15.44	15.44	15.44	15.44	15.44	11.84	11.84	11.84	11.84	11.84	10.93	10.93	10.93	10.93	10.93	12.91	12.91	12.91	12.91	12.91	16.21	16.21	16.21	16.21	16.21	20.11	20.11	20.11	20.11	20.11	21.33	21.33	21.33	21.33	21.33	21.85	21.85	21.85	21.85	21.85	22.36	22.36	22.36	22.36	22.36	23.99	23.99	23.99	23.99	23.99	25.18	25.18	25.18	25.18	25.18	27.13	27.13	27.13	27.13	27.13	28.18	28.18	28.18	28.18	28.18	29.49	29.49	29.49	29.49	29.49	30.2	30.2	30.2	30.2	30.2	31.49	31.49	31.49	31.49	31.49	32.35	32.35	32.35	32.35	32.35	33.38	33.38	33.38	33.38	33.38	33.94	33.94	33.94	33.94	33.94	34.51	34.51	34.51	34.51	34.51	35.07	35.07	35.07	35.07	35.07	36.03	36.03	36.03	36.03	36.03	36.65	36.65	36.65	36.65	36.65	37.52	37.52	37.52	37.52	37.52	38.11	38.11	38.11	38.11	38.11	38.77	38.77	38.77	38.77	38.77	38.93	38.93	38.93	38.93	38.93	38.92	38.92	38.92	38.92	38.92	38.97	38.97	38.97	38.97	38.97	39.26	39.26	39.26	39.26	39.26	39.52	39.52	39.52	39.52	39.52	40.01	40.01	40.01	40.01	40.01	40.15	40.15	40.15	40.15	40.15	42	42	42	42	42	40.55	40.55	40.55	40.55	40.55	41.12	41.12	41.12	41.12	41.12	41.99	41.99	41.99	41.99	41.99	42.98	.1000977	
+92	2542.45	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+93	2542.35	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+94	2542.25	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+95	2542.15	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+96	2542.05	26.53	25.48	25.48	25.48	25.48	25.48	23.77	23.77	23.77	23.77	23.77	22.6	22.6	22.6	22.6	22.6	21.06	21.06	21.06	21.06	21.06	20.34	20.34	20.34	20.34	20.34	18.71	18.71	18.71	18.71	18.71	16.99	16.99	16.99	16.99	16.99	14.39	14.39	14.39	14.39	14.39	14	14	14	14	14	16.17	16.17	16.17	16.17	16.17	18.46	18.46	18.46	18.46	18.46	20.44	20.44	20.44	20.44	20.44	20.78	20.78	20.78	20.78	20.78	20.94	20.94	20.94	20.94	20.94	22.01	22.01	22.01	22.01	22.01	24.74	24.74	24.74	24.74	24.74	26.37	26.37	26.37	26.37	26.37	28.55	28.55	28.55	28.55	28.55	29.38	29.38	29.38	29.38	29.38	29.99	29.99	29.99	29.99	29.99	30.25	30.25	30.25	30.25	30.25	30.95	30.95	30.95	30.95	30.95	31.54	31.54	31.54	31.54	31.54	32.28	32.28	32.28	32.28	32.28	32.69	32.69	32.69	32.69	32.69	33	33	33	33	33	33.29	33.29	33.29	33.29	33.29	33.92	33.92	33.92	33.92	33.92	34.46	34.46	34.46	34.46	34.46	35.69	35.69	35.69	35.69	35.69	36.69	36.69	36.69	36.69	36.69	38.05	38.05	38.05	38.05	38.05	38.73	38.73	38.73	38.73	38.73	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.12	39.03	39.03	39.03	39.03	39.03	38.96	38.96	38.96	38.96	38.96	39.07	39.07	39.07	39.07	39.07	39.1	39.1	39.1	39.1	39.1	42	42	42	42	42	39.5	39.5	39.5	39.5	39.5	40.73	40.73	40.73	40.73	40.73	41.81	41.81	41.81	41.81	41.81	43.18	.1000977	
+97	2541.95	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+98	2541.85	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+99	2541.75	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+100	2541.65	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+101	2541.55	26.9	25.86	25.86	25.86	25.86	25.86	24.03	24.03	24.03	24.03	24.03	22.88	22.88	22.88	22.88	22.88	21.51	21.51	21.51	21.51	21.51	20.76	20.76	20.76	20.76	20.76	19.16	19.16	19.16	19.16	19.16	18.09	18.09	18.09	18.09	18.09	16.69	16.69	16.69	16.69	16.69	16.62	16.62	16.62	16.62	16.62	18.45	18.45	18.45	18.45	18.45	19.7	19.7	19.7	19.7	19.7	20.24	20.24	20.24	20.24	20.24	20.25	20.25	20.25	20.25	20.25	20.48	20.48	20.48	20.48	20.48	21.74	21.74	21.74	21.74	21.74	24.89	24.89	24.89	24.89	24.89	26.68	26.68	26.68	26.68	26.68	28.78	28.78	28.78	28.78	28.78	29.44	29.44	29.44	29.44	29.44	29.9	29.9	29.9	29.9	29.9	30.04	30.04	30.04	30.04	30.04	30.38	30.38	30.38	30.38	30.38	30.75	30.75	30.75	30.75	30.75	31.21	31.21	31.21	31.21	31.21	31.52	31.52	31.52	31.52	31.52	32.03	32.03	32.03	32.03	32.03	32.44	32.44	32.44	32.44	32.44	32.97	32.97	32.97	32.97	32.97	33.42	33.42	33.42	33.42	33.42	34.72	34.72	34.72	34.72	34.72	35.77	35.77	35.77	35.77	35.77	37.49	37.49	37.49	37.49	37.49	38.34	38.34	38.34	38.34	38.34	39.27	39.27	39.27	39.27	39.27	39.25	39.25	39.25	39.25	39.25	38.89	38.89	38.89	38.89	38.89	38.62	38.62	38.62	38.62	38.62	38.52	38.52	38.52	38.52	38.52	38.46	38.46	38.46	38.46	38.46	38.57	38.57	38.57	38.57	38.57	39.07	39.07	39.07	39.07	39.07	40.46	40.46	40.46	40.46	40.46	41.82	41.82	41.82	41.82	41.82	43.47	.1000977	
+102	2541.45	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+103	2541.35	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+104	2541.25	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+105	2541.15	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+106	2541.05	27.41	26.42	26.42	26.42	26.42	26.42	24.66	24.66	24.66	24.66	24.66	23.69	23.69	23.69	23.69	23.69	22.54	22.54	22.54	22.54	22.54	21.7	21.7	21.7	21.7	21.7	23	23	23	23	23	22	22	22	22	22	18.62	18.62	18.62	18.62	18.62	18.87	18.87	18.87	18.87	18.87	20.07	20.07	20.07	20.07	20.07	20.53	20.53	20.53	20.53	20.53	20.17	20.17	20.17	20.17	20.17	20.1	20.1	20.1	20.1	20.1	20.75	20.75	20.75	20.75	20.75	22.06	22.06	22.06	22.06	22.06	24.95	24.95	24.95	24.95	24.95	26.5	26.5	26.5	26.5	26.5	28.15	28.15	28.15	28.15	28.15	28.81	28.81	28.81	28.81	28.81	29.38	29.38	29.38	29.38	29.38	29.56	29.56	29.56	29.56	29.56	29.68	29.68	29.68	29.68	29.68	29.61	29.61	29.61	29.61	29.61	29.58	29.58	29.58	29.58	29.58	30.04	30.04	30.04	30.04	30.04	31.05	31.05	31.05	31.05	31.05	31.92	31.92	31.92	31.92	31.92	32.69	32.69	32.69	32.69	32.69	33.1	33.1	33.1	33.1	33.1	37	37	37	37	37	38	38	38	38	38	38	38	38	38	38	38.08	38.08	38.08	38.08	38.08	38.85	38.85	38.85	38.85	38.85	39.14	39.14	39.14	39.14	39.14	38.7	38.7	38.7	38.7	38.7	38.54	38.54	38.54	38.54	38.54	38.35	38.35	38.35	38.35	38.35	38.22	38.22	38.22	38.22	38.22	38.71	38.71	38.71	38.71	38.71	39.48	39.48	39.48	39.48	39.48	41.11	41.11	41.11	41.11	41.11	42.59	42.59	42.59	42.59	42.59	44.42	.1000977	
+107	2540.95	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
+108	2540.85	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
+109	2540.75	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
+110	2540.65	27.68	26.7	26.7	26.7	26.7	26.7	25.04	25.04	25.04	25.04	25.04	24.16	24.16	24.16	24.16	24.16	23.16	23.16	23.16	23.16	23.16	22.39	22.39	22.39	22.39	22.39	20.64	20.64	20.64	20.64	20.64	22	22	22	22	22	19.24	19.24	19.24	19.24	19.24	19.59	19.59	19.59	19.59	19.59	20.35	20.35	20.35	20.35	20.35	20.6	20.6	20.6	20.6	20.6	20.5	20.5	20.5	20.5	20.5	20.58	20.58	20.58	20.58	20.58	21.5	21.5	21.5	21.5	21.5	22.77	22.77	22.77	22.77	22.77	25.08	25.08	25.08	25.08	25.08	26.31	26.31	26.31	26.31	26.31	27.68	27.68	27.68	27.68	27.68	28.35	28.35	28.35	28.35	28.35	29.01	29.01	29.01	29.01	29.01	29.27	29.27	29.27	29.27	29.27	29.41	29.41	29.41	29.41	29.41	29.15	29.15	29.15	29.15	29.15	29.11	29.11	29.11	29.11	29.11	29.61	29.61	29.61	29.61	29.61	30.87	30.87	30.87	30.87	30.87	31.92	31.92	31.92	31.92	31.92	32.94	32.94	32.94	32.94	32.94	33.46	33.46	33.46	33.46	33.46	34.99	34.99	34.99	34.99	34.99	37	37	37	37	37	37	37	37	37	37	33	33	33	33	33	40	40	40	40	40	39.43	39.43	39.43	39.43	39.43	39.12	39.12	39.12	39.12	39.12	38.91	38.91	38.91	38.91	38.91	38.81	38.81	38.81	38.81	38.81	38.79	38.79	38.79	38.79	38.79	39.47	39.47	39.47	39.47	39.47	40.33	40.33	40.33	40.33	40.33	41.99	41.99	41.99	41.99	41.99	43.5	43.5	43.5	43.5	43.5	45.39	.1000977	
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+112	2540.45	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+113	2540.35	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+114	2540.25	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+115	2540.15	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+116	2540.05	28.25	27.2	27.2	27.2	27.2	27.2	25.56	25.56	25.56	25.56	25.56	24.75	24.75	24.75	24.75	24.75	23.91	23.91	23.91	23.91	23.91	23.17	23.17	23.17	23.17	23.17	21.6	21.6	21.6	21.6	21.6	22	22	22	22	22	23	23	23	23	23	22	22	22	22	22	23	23	23	23	23	21.39	21.39	21.39	21.39	21.39	21.74	21.74	21.74	21.74	21.74	22.26	22.26	22.26	22.26	22.26	23.24	23.24	23.24	23.24	23.24	24.04	24.04	24.04	24.04	24.04	25.24	25.24	25.24	25.24	25.24	26.08	26.08	26.08	26.08	26.08	27.36	27.36	27.36	27.36	27.36	28.15	28.15	28.15	28.15	28.15	29.08	29.08	29.08	29.08	29.08	32	32	32	32	32	29.64	29.64	29.64	29.64	29.64	29.59	29.59	29.59	29.59	29.59	32	32	32	32	32	32	32	32	32	32	33	33	33	33	33	36	36	36	36	36	33.92	33.92	33.92	33.92	33.92	34.6	34.6	34.6	34.6	34.6	36.44	36.44	36.44	36.44	36.44	37.74	37.74	37.74	37.74	37.74	39.16	39.16	39.16	39.16	39.16	39.84	39.84	39.84	39.84	39.84	40.21	40.21	40.21	40.21	40.21	40.43	40.43	40.43	40.43	40.43	42	42	42	42	42	40.07	40.07	40.07	40.07	40.07	40.04	40.04	40.04	40.04	40.04	40.29	40.29	40.29	40.29	40.29	41.22	41.22	41.22	41.22	41.22	42.15	42.15	42.15	42.15	42.15	43.92	43.92	43.92	43.92	43.92	45.3	45.3	45.3	45.3	45.3	47.18	.1000977	
+117	2539.95	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
+118	2539.85	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
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+120	2539.65	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
+121	2539.55	28.78	27.63	27.63	27.63	27.63	27.63	26.03	26.03	26.03	26.03	26.03	25.14	25.14	25.14	25.14	25.14	24.17	24.17	24.17	24.17	24.17	23.43	23.43	23.43	23.43	23.43	21.92	21.92	21.92	21.92	21.92	21.4	21.4	21.4	21.4	21.4	21.28	21.28	21.28	21.28	21.28	21.46	21.46	21.46	21.46	21.46	21.92	21.92	21.92	21.92	21.92	22	22	22	22	22	22.43	22.43	22.43	22.43	22.43	22.97	22.97	22.97	22.97	22.97	23.86	23.86	23.86	23.86	23.86	24.35	24.35	24.35	24.35	24.35	28	28	28	28	28	25.69	25.69	25.69	25.69	25.69	27.14	27.14	27.14	27.14	27.14	28.13	28.13	28.13	28.13	28.13	29.46	29.46	29.46	29.46	29.46	29.98	29.98	29.98	29.98	29.98	30.49	30.49	30.49	30.49	30.49	32	32	32	32	32	31.23	31.23	31.23	31.23	31.23	32.16	32.16	32.16	32.16	32.16	33.65	33.65	33.65	33.65	33.65	34.37	34.37	34.37	34.37	34.37	34.89	34.89	34.89	34.89	34.89	35.49	35.49	35.49	35.49	35.49	37.58	37.58	37.58	37.58	37.58	39.28	39.28	39.28	39.28	39.28	40.85	40.85	40.85	40.85	40.85	41.24	41.24	41.24	41.24	41.24	41.17	41.17	41.17	41.17	41.17	41.26	41.26	41.26	41.26	41.26	41.09	41.09	41.09	41.09	41.09	40.95	40.95	40.95	40.95	40.95	41.12	41.12	41.12	41.12	41.12	41.42	41.42	41.42	41.42	41.42	42.45	42.45	42.45	42.45	42.45	43.46	43.46	43.46	43.46	43.46	45.32	45.32	45.32	45.32	45.32	46.65	46.65	46.65	46.65	46.65	48.47	.1000977	
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+192	2532.45	36.37	35.59	35.59	35.59	35.59	35.59	34.26	34.26	34.26	34.26	34.26	33.14	33.14	33.14	33.14	33.14	31.63	31.63	31.63	31.63	31.63	30.63	30.63	30.63	30.63	30.63	29.28	29.28	29.28	29.28	29.28	28.24	28.24	28.24	28.24	28.24	27.07	27.07	27.07	27.07	27.07	26.57	26.57	26.57	26.57	26.57	26.17	26.17	26.17	26.17	26.17	25.86	25.86	25.86	25.86	25.86	25.33	25.33	25.33	25.33	25.33	25.09	25.09	25.09	25.09	25.09	27	27	27	27	27	25.52	25.52	25.52	25.52	25.52	26.69	26.69	26.69	26.69	26.69	27.22	27.22	27.22	27.22	27.22	28.37	28.37	28.37	28.37	28.37	29.25	29.25	29.25	29.25	29.25	30.65	30.65	30.65	30.65	30.65	31.33	31.33	31.33	31.33	31.33	31.35	31.35	31.35	31.35	31.35	31.01	31.01	31.01	31.01	31.01	30.48	30.48	30.48	30.48	30.48	30.32	30.32	30.32	30.32	30.32	30.64	30.64	30.64	30.64	30.64	31.18	31.18	31.18	31.18	31.18	32.12	32.12	32.12	32.12	32.12	32.58	32.58	32.58	32.58	32.58	33.04	33.04	33.04	33.04	33.04	33.76	33.76	33.76	33.76	33.76	34.91	34.91	34.91	34.91	34.91	35.72	35.72	35.72	35.72	35.72	36.57	36.57	36.57	36.57	36.57	36.85	36.85	36.85	36.85	36.85	37.71	37.71	37.71	37.71	37.71	38.56	38.56	38.56	38.56	38.56	39.72	39.72	39.72	39.72	39.72	40.33	40.33	40.33	40.33	40.33	40.8	40.8	40.8	40.8	40.8	40.82	40.82	40.82	40.82	40.82	40.6	40.6	40.6	40.6	40.6	40.32	40.32	40.32	40.32	40.32	39.7	.1000977	
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+199	2531.75	35.99	35.17	35.17	35.17	35.17	35.17	33.81	33.81	33.81	33.81	33.81	32.67	32.67	32.67	32.67	32.67	31.33	31.33	31.33	31.33	31.33	30.4	30.4	30.4	30.4	30.4	29.21	29.21	29.21	29.21	29.21	28.32	28.32	28.32	28.32	28.32	27.27	27.27	27.27	27.27	27.27	26.82	26.82	26.82	26.82	26.82	26.27	26.27	26.27	26.27	26.27	26.12	26.12	26.12	26.12	26.12	25.51	25.51	25.51	25.51	25.51	25.23	25.23	25.23	25.23	25.23	27	27	27	27	27	25.11	25.11	25.11	25.11	25.11	25.8	25.8	25.8	25.8	25.8	26.08	26.08	26.08	26.08	26.08	27.04	27.04	27.04	27.04	27.04	28.04	28.04	28.04	28.04	28.04	29.62	29.62	29.62	29.62	29.62	30.45	30.45	30.45	30.45	30.45	30.3	30.3	30.3	30.3	30.3	29.85	29.85	29.85	29.85	29.85	29.39	29.39	29.39	29.39	29.39	29.47	29.47	29.47	29.47	29.47	30.18	30.18	30.18	30.18	30.18	30.79	30.79	30.79	30.79	30.79	31.77	31.77	31.77	31.77	31.77	32.29	32.29	32.29	32.29	32.29	32.9	32.9	32.9	32.9	32.9	33.63	33.63	33.63	33.63	33.63	34.75	34.75	34.75	34.75	34.75	35.36	35.36	35.36	35.36	35.36	35.85	35.85	35.85	35.85	35.85	36	36	36	36	36	36.65	36.65	36.65	36.65	36.65	37.4	37.4	37.4	37.4	37.4	38.52	38.52	38.52	38.52	38.52	39.12	39.12	39.12	39.12	39.12	39.71	39.71	39.71	39.71	39.71	39.86	39.86	39.86	39.86	39.86	39.9	39.9	39.9	39.9	39.9	39.78	39.78	39.78	39.78	39.78	39.36	.1000977	
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+202	2531.45	35.3	34.49	34.49	34.49	34.49	34.49	33.24	33.24	33.24	33.24	33.24	32.21	32.21	32.21	32.21	32.21	30.97	30.97	30.97	30.97	30.97	30.12	30.12	30.12	30.12	30.12	29.04	29.04	29.04	29.04	29.04	28.46	28.46	28.46	28.46	28.46	27.6	27.6	27.6	27.6	27.6	27.08	27.08	27.08	27.08	27.08	26.78	26.78	26.78	26.78	26.78	26.75	26.75	26.75	26.75	26.75	26.27	26.27	26.27	26.27	26.27	28	28	28	28	28	24.83	24.83	24.83	24.83	24.83	27	27	27	27	27	27	27	27	27	27	24.49	24.49	24.49	24.49	24.49	25.34	25.34	25.34	25.34	25.34	26.4	26.4	26.4	26.4	26.4	28.09	28.09	28.09	28.09	28.09	28.89	28.89	28.89	28.89	28.89	28.48	28.48	28.48	28.48	28.48	28.21	28.21	28.21	28.21	28.21	28.03	28.03	28.03	28.03	28.03	28.54	28.54	28.54	28.54	28.54	30.09	30.09	30.09	30.09	30.09	30.82	30.82	30.82	30.82	30.82	31.69	31.69	31.69	31.69	31.69	32.04	32.04	32.04	32.04	32.04	32.53	32.53	32.53	32.53	32.53	33.06	33.06	33.06	33.06	33.06	33.87	33.87	33.87	33.87	33.87	34.24	34.24	34.24	34.24	34.24	34.44	34.44	34.44	34.44	34.44	34.58	34.58	34.58	34.58	34.58	35.19	35.19	35.19	35.19	35.19	35.82	35.82	35.82	35.82	35.82	37.01	37.01	37.01	37.01	37.01	37.65	37.65	37.65	37.65	37.65	38.32	38.32	38.32	38.32	38.32	38.59	38.59	38.59	38.59	38.59	38.74	38.74	38.74	38.74	38.74	38.78	38.78	38.78	38.78	38.78	38.61	.1000977	
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+247	2526.75	36.41	35.66	35.66	35.66	35.66	35.66	34.08	34.08	34.08	34.08	34.08	32.45	32.45	32.45	32.45	32.45	29.2	29.2	29.2	29.2	29.2	26.87	26.87	26.87	26.87	26.87	24.23	24.23	24.23	24.23	24.23	23.18	23.18	23.18	23.18	23.18	22.62	22.62	22.62	22.62	22.62	22.62	22.62	22.62	22.62	22.62	23.01	23.01	23.01	23.01	23.01	23.79	23.79	23.79	23.79	23.79	25.42	25.42	25.42	25.42	25.42	26.62	26.62	26.62	26.62	26.62	30	30	30	30	30	28.68	28.68	28.68	28.68	28.68	29.36	29.36	29.36	29.36	29.36	29.88	29.88	29.88	29.88	29.88	30.41	30.41	30.41	30.41	30.41	30.63	30.63	30.63	30.63	30.63	30.5	30.5	30.5	30.5	30.5	30.16	30.16	30.16	30.16	30.16	29.37	29.37	29.37	29.37	29.37	28.82	28.82	28.82	28.82	28.82	28.11	28.11	28.11	28.11	28.11	27.77	27.77	27.77	27.77	27.77	27.87	27.87	27.87	27.87	27.87	28.4	28.4	28.4	28.4	28.4	29.7	29.7	29.7	29.7	29.7	98.314	98.314	98.314	98.314	98.314	102.35	102.35	102.35	102.35	102.35	100.09	100.09	100.09	100.09	100.09	100.11	100.11	100.11	100.11	100.11	32.61	32.61	32.61	32.61	32.61	33.48	33.48	33.48	33.48	33.48	34.01	34.01	34.01	34.01	34.01	102.86	102.86	102.86	102.86	102.86	34.47	34.47	34.47	34.47	34.47	107	107	107	107	107	107	107	107	107	107	107	107	107	107	107	38	38	38	38	38	37	37	37	37	37	37	37	37	37	37	34.93	.5	
+0	0	.5	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	9.99756E-02	.5	
+[End_Grid]
diff --git a/docs/source/user_guide/example/hallue.pastp b/docs/source/user_guide/example/data/hallue.pastp
similarity index 100%
rename from docs/source/user_guide/example/hallue.pastp
rename to docs/source/user_guide/example/data/hallue.pastp
diff --git a/docs/source/user_guide/example/nested.permh b/docs/source/user_guide/example/data/nested.permh
similarity index 100%
rename from docs/source/user_guide/example/nested.permh
rename to docs/source/user_guide/example/data/nested.permh
diff --git a/docs/source/user_guide/example/gigogne.ipynb b/docs/source/user_guide/example/gigogne.ipynb
index 25c34e8..114c845 100644
--- a/docs/source/user_guide/example/gigogne.ipynb
+++ b/docs/source/user_guide/example/gigogne.ipynb
@@ -21,12 +21,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "import gridmarthe as gm\n",
-    "ds = gm.load_marthe_grid('nested.permh', drop_nan=True, nanval=[0., -9999.])"
+    "ds = gm.load_marthe_grid('./data/nested.permh', drop_nan=True, nanval=[0., -9999.])"
    ]
   },
   {
diff --git a/docs/source/user_guide/example/gm_example.ipynb b/docs/source/user_guide/example/gm_example.ipynb
index 1c98d28..be27f47 100644
--- a/docs/source/user_guide/example/gm_example.ipynb
+++ b/docs/source/user_guide/example/gm_example.ipynb
@@ -93,12 +93,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "# lecture d'une grille marthe et stockage dans un Dataset (librairie xarray)\n",
-    "ds = gm.load_marthe_grid('./chasim_hallue.out', 'CHARGE', fpastp='./hallue.pastp', drop_nan=True) # si la valeur des nans n'est pas 9999 (ex. permh, NaNs = 0), on peut spécifier la valeur"
+    "ds = gm.load_marthe_grid('./data/chasim_hallue.out', 'CHARGE', fpastp='./data/hallue.pastp', drop_nan=True) # si la valeur des nans n'est pas 9999 (ex. permh, NaNs = 0), on peut spécifier la valeur"
    ]
   },
   {
diff --git a/docs/source/user_guide/example/preproc.ipynb b/docs/source/user_guide/example/preproc.ipynb
new file mode 100644
index 0000000..e4c9475
--- /dev/null
+++ b/docs/source/user_guide/example/preproc.ipynb
@@ -0,0 +1,221 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Command line executable to fix marthe fmt\n",
+    "\n",
+    "In some older version of MARTHE, grid attributes were miswritten.\n",
+    "A fix scripts is included in `gridmarthe` if users need to read such file.\n",
+    "This example show how to use this script, called `cleanmgrid`. All kind of gridfiles may not be included. Please make an issue if you appear to lack a treatment.\n",
+    "\n",
+    "\n",
+    "*nb: the next commands are shell commands, the '!' mark is only here for the python notebook version.*"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "vscode": {
+     "languageId": "shellscript"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Marthe_Grid Version=9.0\n",
+      "Title=Bidon                                                                  H_SUBSTRAT     1\n",
+      "[Infos]\n",
+      "Field=\n",
+      "Type=\n",
+      "Elem_Number=0\n",
+      "Name=\n",
+      "Time_Step=-9999\n",
+      "Time=0\n",
+      "Layer=0\n",
+      "Max_Layer=0\n",
+      "Nest_grid=0\n",
+      "Max_NestG=0\n",
+      "[Structure]\n",
+      "X_Left_Corner=528\n",
+      "Y_Lower_Corner=2503\n",
+      "Ncolumn=320\n",
+      "Nrows=189\n",
+      "[Data_Descript]\n",
+      "! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >\n",
+      "! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >\n",
+      "! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1\n",
+      "! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2\n",
+      "! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2\n",
+      "! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Colums    >\n",
+      "[Data]\n",
+      "0\t0\t1\t2\t3\t4\t5\t6\t7\t8\t9\t10\t11\t12\t13\t14\t15\t16\t17\t18\t19\t20\t21\t22\t23\t24\t25\t26\t27\t28\t29\t30\t31\t32\t33\t34\t35\t36\t37\t38\t39\t40\t41\t42\t43\t44\t45\t46\t47\t48\t49\t50\t51\t52\t53\t54\t55\t56\t57\t58\t59\t60\t61\t62\t63\t64\t65\t66\t67\t68\t69\t70\t71\t72\t73\t74\t75\t76\t77\t78\t79\t80\t81\t82\t83\t84\t85\t86\t87\t88\t89\t90\t91\t92\t93\t94\t95\t96\t97\t98\t99\t100\t101\t102\t103\t104\t105\t106\t107\t108\t109\t110\t111\t112\t113\t114\t115\t116\t117\t118\t119\t120\t121\t122\t123\t124\t125\t126\t127\t128\t129\t130\t131\t132\t133\t134\t135\t136\t137\t138\t139\t140\t141\t142\t143\t144\t145\t146\t147\t148\t149\t150\t151\t152\t153\t154\t155\t156\t157\t158\t159\t160\t161\t162\t163\t164\t165\t166\t167\t168\t169\t170\t171\t172\t173\t174\t175\t176\t177\t178\t179\t180\t181\t182\t183\t184\t185\t186\t187\t188\t189\t190\t191\t192\t193\t194\t195\t196\t197\t198\t199\t200\t201\t202\t203\t204\t205\t206\t207\t208\t209\t210\t211\t212\t213\t214\t215\t216\t217\t218\t219\t220\t221\t222\t223\t224\t225\t226\t227\t228\t229\t230\t231\t232\t233\t234\t235\t236\t237\t238\t239\t240\t241\t242\t243\t244\t245\t246\t247\t248\t249\t250\t251\t252\t253\t254\t255\t256\t257\t258\t259\t260\t261\t262\t263\t264\t265\t266\t267\t268\t269\t270\t271\t272\t273\t274\t275\t276\t277\t278\t279\t280\t281\t282\t283\t284\t285\t286\t287\t288\t289\t290\t291\t292\t293\t294\t295\t296\t297\t298\t299\t300\t301\t302\t303\t304\t305\t306\t307\t308\t309\t310\t311\t312\t313\t314\t315\t316\t317\t318\t319\t320\t\n",
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+      "2\t2596.75\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t-24.81\t-24.93\t-23\t-25.13\t-23\t-24.04\t-20\t-21.98\t-20.87\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t9999\t.5\t\n"
+     ]
+    }
+   ],
+   "source": [
+    "# how to use: print help message\n",
+    "!head -30 ./data/grid_wrong_attrs.hsubs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the above results, we can see that `Layer`, `Max_Layer`, `Nest_grid`, `Max_Nestg` are all set to 0.\n",
+    "This is an error which prevent successfull Marthe IO operations with `gridmarthe` or `pymarthe`.\n",
+    "The script `cleanmgrid` is going to fix it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "vscode": {
+     "languageId": "shellscript"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "usage: cleanmgrid [-h] [--layer LAYER] [--grid GRID] [--output OUTPUT]\n",
+      "                  [--no_overwrite]\n",
+      "                  PATH_TO_FILE\n",
+      "\n",
+      "Clean marthe grid file for miswritten attributes. Only works for marthe grid v9.0 (a check is performed and <v9 are skipped)\n",
+      "\n",
+      "positional arguments:\n",
+      "  PATH_TO_FILE          PATH_TO_FILE can be a relative path, if it ends with\n",
+      "                        \".rma\" all grid file in rma project will be processed.\n",
+      "\n",
+      "options:\n",
+      "  -h, --help            show this help message and exit\n",
+      "  --layer LAYER, -l LAYER\n",
+      "                        Number of layer. Only if PATH_TO_FILE is *NOT* a rma\n",
+      "                        file. Otherwise, it will be parsed from Marthe's\n",
+      "                        files.\n",
+      "  --grid GRID, -g GRID  Number of nested grid. Only if PATH_TO_FILE is *NOT* a\n",
+      "                        rma file. Otherwise, it will be parsed from Marthe's\n",
+      "                        files.\n",
+      "  --output OUTPUT, -o OUTPUT\n",
+      "                        Output file. Only if PATH_TO_FILE is a single grid\n",
+      "                        file and *NOT* a rma file. Otherwise, all files will\n",
+      "                        be bakup and clean\n",
+      "  --no_overwrite, -n    Do no overwrite file, add `.fix` extension. By default\n",
+      "                        file is bakup and then overwrite.\n",
+      "\n",
+      "gridmarthe  Copyright (C) 2024  BRGM.\n",
+      "This program comes with ABSOLUTELY NO WARRANTY.\n",
+      "This is free software, see GNU General Public Lisence v3 for copying.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# print help to check for accepted args\n",
+    "!cleanmgrid -h"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "vscode": {
+     "languageId": "shellscript"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# let's try for a simple case, with only one grid file\n",
+    "!cleanmgrid ./data/grid_wrong_attrs.hsubs -l 1 -g 3 -o grid_clean.hsubs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "vscode": {
+     "languageId": "shellscript"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Marthe_Grid Version=9.0\n",
+      "Title=Bidon                                                                  H_SUBSTRAT     1\n",
+      "[Infos]\n",
+      "Field=H_SUBSTRAT\n",
+      "Type=\n",
+      "Elem_Number=0\n",
+      "Name=\n",
+      "Time_Step=-9999\n",
+      "Time=0\n",
+      "Layer=1\n",
+      "Max_Layer=1\n",
+      "Nest_grid=0\n",
+      "Max_NestG=3\n",
+      "[Structure]\n",
+      "X_Left_Corner=528\n",
+      "Y_Lower_Corner=2503\n",
+      "Ncolumn=320\n",
+      "Nrows=189\n",
+      "[Data_Descript]\n",
+      "! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >\n",
+      "! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >\n",
+      "! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1\n",
+      "! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2\n",
+      "! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2\n",
+      "! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Colums    >\n",
+      "[Data]\n",
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+     ]
+    }
+   ],
+   "source": [
+    "# print variables headers and dimensions with nco tools\n",
+    "!head -30 ./data/grid_clean.hsubs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "`cleanmgrid` also work if you specified a `*.rma` file (Marthe Project). In such case, the program will try to fix all grid files of the project !"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "gm",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/docs/source/user_guide/example/treatments.ipynb b/docs/source/user_guide/example/treatments.ipynb
new file mode 100644
index 0000000..d407c2e
--- /dev/null
+++ b/docs/source/user_guide/example/treatments.ipynb
@@ -0,0 +1,1590 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Example of treatments available\n",
+    "\n",
+    "This notebook shows how to use some extra features for your gridmarthe treatments\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# import modules\n",
+    "import numpy as np\n",
+    "import gridmarthe as gm\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
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+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 3MB\n",
+       "Dimensions:  (time: 1, zone: 101209)\n",
+       "Coordinates:\n",
+       "  * time     (time) datetime64[ns] 8B 1850-01-01\n",
+       "  * zone     (zone) int32 405kB 47402 47403 47763 ... 2381150 2381151 2381457\n",
+       "Data variables:\n",
+       "    permeab  (time, zone) float64 810kB 1e-05 1e-05 1e-05 ... 0.0001 0.0001\n",
+       "    x        (zone) float32 405kB 6.372e+05 6.378e+05 ... 6.382e+05 6.38e+05\n",
+       "    y        (zone) float32 405kB 2.617e+06 2.617e+06 ... 2.592e+06 2.592e+06\n",
+       "    dx       (zone) float32 405kB 500.0 500.0 500.0 500.0 ... 100.0 100.0 100.0\n",
+       "    dy       (zone) float32 405kB 500.0 500.0 500.0 500.0 ... 100.0 100.0 100.0\n",
+       "    z        (zone) int32 405kB 1 1 1 1 1 1 1 1 1 1 1 ... 9 9 9 9 9 9 9 9 9 9 9\n",
+       "Attributes: (12/17)\n",
+       "    conventions:          CF-1.10\n",
+       "    title:                \n",
+       "    marthe_grid_version:  9.0\n",
+       "    original_dimensions:  x,y,z [grids]: 387 304 10; 307 442 10\n",
+       "    lon_resolution:       100.0, 500.0\n",
+       "    lat_resolution:       100.0, 500.0\n",
+       "    ...                   ...\n",
+       "    creation_date:        Created on 2025-03-26T13:40:44Z UTC\n",
+       "    institution:          BRGM, French Geological Survey, Orléans, France\n",
+       "    comment:              Hydrogeological model created with MARTHE code (Thi...\n",
+       "    resolution_units:     m\n",
+       "    projection:           epsg:27572\n",
+       "    domain:               FR-France</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-afbc2d7f-bfa8-4ac1-bf01-79c913ceea83' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-afbc2d7f-bfa8-4ac1-bf01-79c913ceea83' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>zone</span>: 101209</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1c44ca31-870a-4e26-abdd-ee80c5ddefd7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1c44ca31-870a-4e26-abdd-ee80c5ddefd7' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1850-01-01</div><input id='attrs-f69d479b-a7ab-40ea-8c47-f7a550712420' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f69d479b-a7ab-40ea-8c47-f7a550712420' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0718fbd-928d-4a70-bac8-69394d5e2e74' class='xr-var-data-in' type='checkbox'><label for='data-d0718fbd-928d-4a70-bac8-69394d5e2e74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1850-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zone</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>47402 47403 ... 2381151 2381457</div><input id='attrs-c56d7c69-58b6-443c-a72f-3fa13c81146b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c56d7c69-58b6-443c-a72f-3fa13c81146b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad443574-0a30-4a5b-83ef-39f03beb9016' class='xr-var-data-in' type='checkbox'><label for='data-ad443574-0a30-4a5b-83ef-39f03beb9016' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  47402,   47403,   47763, ..., 2381150, 2381151, 2381457],\n",
+       "      shape=(101209,), dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f1cc335f-4e45-49fa-98f0-3e75cf4070d0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f1cc335f-4e45-49fa-98f0-3e75cf4070d0' class='xr-section-summary' >Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>permeab</span></div><div class='xr-var-dims'>(time, zone)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1e-05 1e-05 1e-05 ... 0.0001 0.0001</div><input id='attrs-ff437518-f19e-4acb-ae14-d86fdb71e4be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff437518-f19e-4acb-ae14-d86fdb71e4be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f101874-8ab7-411a-ba98-e49723e5bcd4' class='xr-var-data-in' type='checkbox'><label for='data-9f101874-8ab7-411a-ba98-e49723e5bcd4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>varname :</span></dt><dd>PERMEAB</dd><dt><span>units :</span></dt><dd>m/s</dd><dt><span>missing_value :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>aquifer_hydraulic_conductivity</dd></dl></div><div class='xr-var-data'><pre>array([[1.e-05, 1.e-05, 1.e-05, ..., 1.e-04, 1.e-04, 1.e-04]],\n",
+       "      shape=(1, 101209))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>6.372e+05 6.378e+05 ... 6.38e+05</div><input id='attrs-f5a8f262-ed98-4209-8f27-4b0580d6ca88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5a8f262-ed98-4209-8f27-4b0580d6ca88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33ddae5a-1a77-49aa-83c7-d570b7a440cf' class='xr-var-data-in' type='checkbox'><label for='data-33ddae5a-1a77-49aa-83c7-d570b7a440cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([637250., 637750., 624250., ..., 638050., 638150., 638050.],\n",
+       "      shape=(101209,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.617e+06 2.617e+06 ... 2.592e+06</div><input id='attrs-fdcbe08e-feef-44ed-b3c8-3b18cb875b01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fdcbe08e-feef-44ed-b3c8-3b18cb875b01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdc6cc7a-1ce4-46e0-be0d-5ec5f962a041' class='xr-var-data-in' type='checkbox'><label for='data-fdc6cc7a-1ce4-46e0-be0d-5ec5f962a041' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([2616850., 2616850., 2616350., ..., 2592350., 2592350., 2592250.],\n",
+       "      shape=(101209,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dx</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>500.0 500.0 500.0 ... 100.0 100.0</div><input id='attrs-4d2fe11c-264a-47dc-b501-4929a0cc129a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4d2fe11c-264a-47dc-b501-4929a0cc129a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e9cdcd7-08f0-424b-bcd7-4c2f241ad0c5' class='xr-var-data-in' type='checkbox'><label for='data-8e9cdcd7-08f0-424b-bcd7-4c2f241ad0c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([500., 500., 500., ..., 100., 100., 100.],\n",
+       "      shape=(101209,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dy</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>500.0 500.0 500.0 ... 100.0 100.0</div><input id='attrs-259ef9ca-406f-4375-959c-566b1f785390' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-259ef9ca-406f-4375-959c-566b1f785390' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b890cdde-65e3-4c98-9b6c-c5cbeb2be57c' class='xr-var-data-in' type='checkbox'><label for='data-b890cdde-65e3-4c98-9b6c-c5cbeb2be57c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([500., 500., 500., ..., 100., 100., 100.],\n",
+       "      shape=(101209,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 9 9 9 9 9 9 9 9</div><input id='attrs-bad9043e-7990-4c2b-aaa8-3132611b7f9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bad9043e-7990-4c2b-aaa8-3132611b7f9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-960eeaea-55c6-4199-9754-9afef6962356' class='xr-var-data-in' type='checkbox'><label for='data-960eeaea-55c6-4199-9754-9afef6962356' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>long_name :</span></dt><dd>aquifer_layer</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 9, 9, 9], shape=(101209,), dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-97253ce9-96a1-43a2-875d-41f62654b9b3' class='xr-section-summary-in' type='checkbox'  ><label for='section-97253ce9-96a1-43a2-875d-41f62654b9b3' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-20956cdc-4e90-4445-bdc7-c9ddbd5afb4a' class='xr-index-data-in' type='checkbox'/><label for='index-20956cdc-4e90-4445-bdc7-c9ddbd5afb4a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1850-01-01&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>zone</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e7e6d3c6-5045-4529-90c2-31aa36f77c7d' class='xr-index-data-in' type='checkbox'/><label for='index-e7e6d3c6-5045-4529-90c2-31aa36f77c7d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  47402,   47403,   47763,   47764,   47765,   47766,   47767,   47770,\n",
+       "         47789,   47790,\n",
+       "       ...\n",
+       "       2380539, 2380540, 2380541, 2380843, 2380844, 2380845, 2380846, 2381150,\n",
+       "       2381151, 2381457],\n",
+       "      dtype=&#x27;int32&#x27;, name=&#x27;zone&#x27;, length=101209))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9c639434-797d-4838-8f7f-a7ed4daea3cc' class='xr-section-summary-in' type='checkbox'  ><label for='section-9c639434-797d-4838-8f7f-a7ed4daea3cc' class='xr-section-summary' >Attributes: <span>(17)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conventions :</span></dt><dd>CF-1.10</dd><dt><span>title :</span></dt><dd></dd><dt><span>marthe_grid_version :</span></dt><dd>9.0</dd><dt><span>original_dimensions :</span></dt><dd>x,y,z [grids]: 387 304 10; 307 442 10</dd><dt><span>lon_resolution :</span></dt><dd>100.0, 500.0</dd><dt><span>lat_resolution :</span></dt><dd>100.0, 500.0</dd><dt><span>scale_factor :</span></dt><dd>1.0</dd><dt><span>nested_grid :</span></dt><dd>True</dd><dt><span>extend :</span></dt><dd>xymin : 543750.0 2526350.0; xymax: 736750.0 2677850.0</dd><dt><span>period :</span></dt><dd>1850-1850</dd><dt><span>frequency :</span></dt><dd>nan day(s)</dd><dt><span>creation_date :</span></dt><dd>Created on 2025-03-26T13:40:44Z UTC</dd><dt><span>institution :</span></dt><dd>BRGM, French Geological Survey, Orléans, France</dd><dt><span>comment :</span></dt><dd>Hydrogeological model created with MARTHE code (Thiery, D. 2020. Guidelines for MARTHE v7.8 computer codefor hydro-systems modelling. report BRGM/RP-69660-FR).</dd><dt><span>resolution_units :</span></dt><dd>m</dd><dt><span>projection :</span></dt><dd>epsg:27572</dd><dt><span>domain :</span></dt><dd>FR-France</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 3MB\n",
+       "Dimensions:  (time: 1, zone: 101209)\n",
+       "Coordinates:\n",
+       "  * time     (time) datetime64[ns] 8B 1850-01-01\n",
+       "  * zone     (zone) int32 405kB 47402 47403 47763 ... 2381150 2381151 2381457\n",
+       "Data variables:\n",
+       "    permeab  (time, zone) float64 810kB 1e-05 1e-05 1e-05 ... 0.0001 0.0001\n",
+       "    x        (zone) float32 405kB 6.372e+05 6.378e+05 ... 6.382e+05 6.38e+05\n",
+       "    y        (zone) float32 405kB 2.617e+06 2.617e+06 ... 2.592e+06 2.592e+06\n",
+       "    dx       (zone) float32 405kB 500.0 500.0 500.0 500.0 ... 100.0 100.0 100.0\n",
+       "    dy       (zone) float32 405kB 500.0 500.0 500.0 500.0 ... 100.0 100.0 100.0\n",
+       "    z        (zone) int32 405kB 1 1 1 1 1 1 1 1 1 1 1 ... 9 9 9 9 9 9 9 9 9 9 9\n",
+       "Attributes: (12/17)\n",
+       "    conventions:          CF-1.10\n",
+       "    title:                \n",
+       "    marthe_grid_version:  9.0\n",
+       "    original_dimensions:  x,y,z [grids]: 387 304 10; 307 442 10\n",
+       "    lon_resolution:       100.0, 500.0\n",
+       "    lat_resolution:       100.0, 500.0\n",
+       "    ...                   ...\n",
+       "    creation_date:        Created on 2025-03-26T13:40:44Z UTC\n",
+       "    institution:          BRGM, French Geological Survey, Orléans, France\n",
+       "    comment:              Hydrogeological model created with MARTHE code (Thi...\n",
+       "    resolution_units:     m\n",
+       "    projection:           epsg:27572\n",
+       "    domain:               FR-France"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "grid = gm.load_marthe_grid('./data/craie_npc.permh', drop_nan=True)  # NaN needs to be drop or set (change 0 to nan for permh for example)\n",
+    "grid"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Get surface mask"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 841kB\n",
+       "Dimensions:  (zone: 21025)\n",
+       "Coordinates:\n",
+       "  * zone     (zone) int32 84kB 178171 177784 647989 ... 1389346 1660427 1660120\n",
+       "Data variables:\n",
+       "    time     (zone) datetime64[ns] 168kB 1850-01-01 1850-01-01 ... 1850-01-01\n",
+       "    permeab  (zone) float64 168kB 1e-06 1e-06 0.003068 ... 1e-06 2e-05 2e-05\n",
+       "    x        (zone) float32 84kB 6.188e+05 6.188e+05 ... 6.494e+05 6.494e+05\n",
+       "    y        (zone) float32 84kB 2.6e+06 2.6e+06 ... 2.606e+06 2.606e+06\n",
+       "    dx       (zone) float32 84kB 500.0 500.0 500.0 500.0 ... 100.0 100.0 100.0\n",
+       "    dy       (zone) float32 84kB 500.0 500.0 500.0 500.0 ... 100.0 100.0 100.0\n",
+       "    z        (zone) int32 84kB 2 2 6 6 8 8 8 8 5 2 6 6 ... 2 2 2 2 2 2 2 2 2 4 4</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5f72102b-85bb-4b35-8e52-c4336c57b4a1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5f72102b-85bb-4b35-8e52-c4336c57b4a1' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>zone</span>: 21025</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9b3ddb78-3fdb-4c00-9a93-7646afb7da69' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9b3ddb78-3fdb-4c00-9a93-7646afb7da69' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zone</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>178171 177784 ... 1660427 1660120</div><input id='attrs-5603307c-94a8-4c76-b968-4a7416916849' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5603307c-94a8-4c76-b968-4a7416916849' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e06e94d4-3464-473e-afe1-1f0fb84f75e1' class='xr-var-data-in' type='checkbox'><label for='data-e06e94d4-3464-473e-afe1-1f0fb84f75e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 178171,  177784,  647989, ..., 1389346, 1660427, 1660120],\n",
+       "      shape=(21025,), dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9b5eb1e1-1318-479a-98e1-43e252ba8935' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9b5eb1e1-1318-479a-98e1-43e252ba8935' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1850-01-01 ... 1850-01-01</div><input id='attrs-2c210d3c-d37e-4e9e-be6b-106fff576532' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2c210d3c-d37e-4e9e-be6b-106fff576532' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-edbec3f4-6fcd-40f6-a0c1-3659d4abc57b' class='xr-var-data-in' type='checkbox'><label for='data-edbec3f4-6fcd-40f6-a0c1-3659d4abc57b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1850-01-01T00:00:00.000000000&#x27;, &#x27;1850-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1850-01-01T00:00:00.000000000&#x27;, ...,\n",
+       "       &#x27;1850-01-01T00:00:00.000000000&#x27;, &#x27;1850-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1850-01-01T00:00:00.000000000&#x27;],\n",
+       "      shape=(21025,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>permeab</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1e-06 1e-06 ... 2e-05 2e-05</div><input id='attrs-bb62fb15-e9b5-41cd-ab07-e2fab201322f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bb62fb15-e9b5-41cd-ab07-e2fab201322f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d8edf61-7621-4751-8468-30072fcc58fe' class='xr-var-data-in' type='checkbox'><label for='data-0d8edf61-7621-4751-8468-30072fcc58fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.00000e-06, 1.00000e-06, 3.06763e-03, ..., 1.00000e-06,\n",
+       "       2.00000e-05, 2.00000e-05], shape=(21025,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>6.188e+05 6.188e+05 ... 6.494e+05</div><input id='attrs-c6bab899-a88d-41b3-8fa6-5f54e1e78097' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c6bab899-a88d-41b3-8fa6-5f54e1e78097' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-069b6b21-72c0-4902-ab64-253773ebfe19' class='xr-var-data-in' type='checkbox'><label for='data-069b6b21-72c0-4902-ab64-253773ebfe19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([618750., 618750., 618750., ..., 649350., 649350., 649350.],\n",
+       "      shape=(21025,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.6e+06 2.6e+06 ... 2.606e+06</div><input id='attrs-00f8ba19-db36-4f31-aa73-ef97ee12c4c9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-00f8ba19-db36-4f31-aa73-ef97ee12c4c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-206e694d-418e-457b-badb-df6020b338dc' class='xr-var-data-in' type='checkbox'><label for='data-206e694d-418e-457b-badb-df6020b338dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2599850., 2600350., 2600850., ..., 2606050., 2606150., 2606250.],\n",
+       "      shape=(21025,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dx</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>500.0 500.0 500.0 ... 100.0 100.0</div><input id='attrs-d5350f4a-12ab-4127-a46d-9e39eee284d4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d5350f4a-12ab-4127-a46d-9e39eee284d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f974990-2c7f-43c8-945f-bdf2cf45ec49' class='xr-var-data-in' type='checkbox'><label for='data-2f974990-2c7f-43c8-945f-bdf2cf45ec49' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([500., 500., 500., ..., 100., 100., 100.],\n",
+       "      shape=(21025,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dy</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>500.0 500.0 500.0 ... 100.0 100.0</div><input id='attrs-9aa60311-ae01-4b56-93cc-6f0f87ca95f4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9aa60311-ae01-4b56-93cc-6f0f87ca95f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b32a6c0e-a4c4-474f-80f8-bbb2f32c22e8' class='xr-var-data-in' type='checkbox'><label for='data-b32a6c0e-a4c4-474f-80f8-bbb2f32c22e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([500., 500., 500., ..., 100., 100., 100.],\n",
+       "      shape=(21025,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>2 2 6 6 8 8 8 8 ... 2 2 2 2 2 2 4 4</div><input id='attrs-25f7fa97-30fb-43c0-bb92-007dd33bd5d5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-25f7fa97-30fb-43c0-bb92-007dd33bd5d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0bf3f10-baf1-46a3-aec4-9caf0ef3f9d7' class='xr-var-data-in' type='checkbox'><label for='data-a0bf3f10-baf1-46a3-aec4-9caf0ef3f9d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2, 2, 6, ..., 2, 4, 4], shape=(21025,), dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2338be96-5406-4a3f-b0ef-d73446626806' class='xr-section-summary-in' type='checkbox'  ><label for='section-2338be96-5406-4a3f-b0ef-d73446626806' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>zone</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-83095d96-19ca-4aed-9eae-2a87feabf390' class='xr-index-data-in' type='checkbox'/><label for='index-83095d96-19ca-4aed-9eae-2a87feabf390' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 178171,  177784,  647989,  647602,  882511,  882124,  881737,  881350,\n",
+       "        528019,  179720,\n",
+       "       ...\n",
+       "       1391495, 1391188, 1390881, 1390574, 1390267, 1389960, 1389653, 1389346,\n",
+       "       1660427, 1660120],\n",
+       "      dtype=&#x27;int32&#x27;, name=&#x27;zone&#x27;, length=21025))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3e9c3ec9-ab4e-4122-a4f6-891429f395fc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3e9c3ec9-ab4e-4122-a4f6-891429f395fc' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 841kB\n",
+       "Dimensions:  (zone: 21025)\n",
+       "Coordinates:\n",
+       "  * zone     (zone) int32 84kB 178171 177784 647989 ... 1389346 1660427 1660120\n",
+       "Data variables:\n",
+       "    time     (zone) datetime64[ns] 168kB 1850-01-01 1850-01-01 ... 1850-01-01\n",
+       "    permeab  (zone) float64 168kB 1e-06 1e-06 0.003068 ... 1e-06 2e-05 2e-05\n",
+       "    x        (zone) float32 84kB 6.188e+05 6.188e+05 ... 6.494e+05 6.494e+05\n",
+       "    y        (zone) float32 84kB 2.6e+06 2.6e+06 ... 2.606e+06 2.606e+06\n",
+       "    dx       (zone) float32 84kB 500.0 500.0 500.0 500.0 ... 100.0 100.0 100.0\n",
+       "    dy       (zone) float32 84kB 500.0 500.0 500.0 500.0 ... 100.0 100.0 100.0\n",
+       "    z        (zone) int32 84kB 2 2 6 6 8 8 8 8 5 2 6 6 ... 2 2 2 2 2 2 2 2 2 4 4"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "surf = gm.get_surface_layer(grid)\n",
+    "surf"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              time       permeab         x          y     dx     dy  z  \\\n",
+      "zone                                                                     \n",
+      "178171  1850-01-01  1.000000e-06  618750.0  2599850.0  500.0  500.0  2   \n",
+      "177784  1850-01-01  1.000000e-06  618750.0  2600350.0  500.0  500.0  2   \n",
+      "647989  1850-01-01  3.067630e-03  618750.0  2600850.0  500.0  500.0  6   \n",
+      "647602  1850-01-01  2.484310e-03  618750.0  2601350.0  500.0  500.0  6   \n",
+      "882511  1850-01-01  1.770000e-07  618750.0  2601850.0  500.0  500.0  8   \n",
+      "...            ...           ...       ...        ...    ...    ... ..   \n",
+      "1389960 1850-01-01  1.000000e-06  649350.0  2605850.0  100.0  100.0  2   \n",
+      "1389653 1850-01-01  1.000000e-06  649350.0  2605950.0  100.0  100.0  2   \n",
+      "1389346 1850-01-01  1.000000e-06  649350.0  2606050.0  100.0  100.0  2   \n",
+      "1660427 1850-01-01  2.000000e-05  649350.0  2606150.0  100.0  100.0  4   \n",
+      "1660120 1850-01-01  2.000000e-05  649350.0  2606250.0  100.0  100.0  4   \n",
+      "\n",
+      "                                                  geometry  \n",
+      "zone                                                        \n",
+      "178171   POLYGON ((618500 2599600, 619000 2599600, 6190...  \n",
+      "177784   POLYGON ((618500 2600100, 619000 2600100, 6190...  \n",
+      "647989   POLYGON ((618500 2600600, 619000 2600600, 6190...  \n",
+      "647602   POLYGON ((618500 2601100, 619000 2601100, 6190...  \n",
+      "882511   POLYGON ((618500 2601600, 619000 2601600, 6190...  \n",
+      "...                                                    ...  \n",
+      "1389960  POLYGON ((649300 2605800, 649400 2605800, 6494...  \n",
+      "1389653  POLYGON ((649300 2605900, 649400 2605900, 6494...  \n",
+      "1389346  POLYGON ((649300 2606000, 649400 2606000, 6494...  \n",
+      "1660427  POLYGON ((649300 2606100, 649400 2606100, 6494...  \n",
+      "1660120  POLYGON ((649300 2606200, 649400 2606200, 6494...  \n",
+      "\n",
+      "[21025 rows x 8 columns]\n",
+      "<class 'geopandas.geodataframe.GeoDataFrame'>\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/manlaya/envs/gm/lib/python3.11/site-packages/gridmarthe/operasem/gis.py:58: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
+      "  if 'time' in ds.dims.keys():\n"
+     ]
+    }
+   ],
+   "source": [
+    "# transform to geodataframe (not necessary, just for example) \n",
+    "gdf = gm.to_geodataframe(surf)\n",
+    "print(gdf)\n",
+    "print(type(gdf))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "gm.plot_outcrop(gdf, engine='gpd')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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HpWrmtWmKc9fIR5yjRkRERGRSzKgREYUIcQZTyVBmIHcC0JLUezPNe+EwKPmAgRoRkcWJh9i1niOm9R6aRtJ83pm/OAxKCjBQIyKyIEfQIV5leTJmdJ3AytfFAIEU6L6ZJkATY7BGXnCOGhEREZFJMaNGRGRBnuqVeavwbzZm7ltAcc4ayWCgZjGLi/pIv9hV+qXbDh6XbddbeQEp/pTgkDMrfZfka7L3QIZcOQxvbcr1R47cfCH+kNKP3L2NHSF9nmxZDwPK3wTDZvf+bpCuJdMvjuAwKHnAoU8iIgvajThDisv6wlPxXPEfqeP0ZHSw6NW8eC/1MinUMFAjIiIiMikOfRIRWZinrJpzBwIDMm5qsmN6ZrlMPdQph8OghkhNTcWpU6fqPD9lyhQsXbrUgB4xUCMiIj+ZLTgLGlxkEHD79+/HlStXnI+PHDmCgQMH4q677jKsTxz6JCKyoN6o9LjyE7g6f038utSx/nCfa6ZEaVV+QIO0oAgIOWctYJo3b46WLVs6/+Tn56Nt27b4/e9/b1ifGKgRERERuampqcHKlSsxceJEhIWFGdYPDn2a0OKR6uZUeCvBoZbakiByRqZle7mmunbVUlt+wyiWnXfjRu59+JMJ0eP+xI5YJvOq/PXEWzz5Qq5cCFS0qeXcNat8Bq3ST684DBpwa9euxfnz5zF+/HhD+8FAjYjIghx1AZUGtGqDMy23eTJiGNL0tdPItN544w1kZWUhKSnwNRTFGKgREVnQ1Syd69wzM9dWS44Zqkuwple7psTVoAFx6tQpbN26FR9++KHRXeEcNSIiIiKx3NxcJCQk4Pbbbze6K8yoEREFE61Xd4ozVWbNXJmxT2Rddrsdubm5GDduHOrVMz5MMr4HREQUcO7zttwDMqXn+UJtQCWeJ+fp+iEXqHH4U1dbt27F6dOnMXHiRKO7AoCBGv1G7Ubnaq0+sUj2dblVod7O1YPcDwIjJiqbrT9mo9c8KLXX261Lu/5lztwDs0B8btRm5Bzn8LNNgTBo0CAIgmB0N5w4R42IiIjIpJhRIyKyIMfqTrk5aeLdCdxXgyrJThlV2kJ8zZAb1lSKddVCBgM1IiLyyKihRvfgjEOeFMoYqBERWZA4U+brSk8jAx89smWOuW+e2va0aEKv9y/1fpJjhqJole9FU9NHnfV+EBcWBD3OUSMiIiIyKWbUiIgsrDcqndtJqd1T1J2RqyzVXlN8Xu0qdsfq8D4ue/muPrEII9OUlSLxRW3G7K+eXxx19csNXdvqti8zBScGahaj9j/4hq5tNe6Jf7xtyq7PudIbr/szBONvbSgt2/RGj756a1euNIWVJoobURJFtl1RUCYXoHnaUkquZlog/00CFQiKyw/5871HTvqosy7Dm+KArGhVkuz3YMdr7t/fHe15HQLlwoKgxkCNiMjiHBk1wPesmlxgpnRSv9km/89K3+UMzsTZtNKqfA91GD3XkHScV7QqSdlcMVwNqBwBljg4k/slW+o1pdel4MY5akREREQmxYwaEZGFibNppVX5OBmgGmRGD1ur2U3Fl11NnO13BdLhe2ZLnCVTO/VEPPQpHlZlpi20MFAjIrIgcYAWKEqCMz2GPcXDmEoCNPFxgd4eT0wcoEnNQ1NCcWkPluoIShz6JCIiIjIpBmpEREHC6En8gP9Dop4yYLPSdzkn94u/1qsPSvokxzE06egry3GQPzj0aTFycxOMTPFbgdFzatxZqQSH2e6dEcwQBIk5Vnd6GwJ19Fvvf0Ol90fcD8ecMW9Dmr4OffoyF00p8XW9BYpA3e/VWgVrjvlq4vZdhkZXpdce93WRJtcj4zFQIyKyICPmqLnzNXh1DxYdNc1Kq7IxMq32udUnFkkGY2b4ZVRJkOZOvBjAfWGAL20AnsuFuJcFoeDCoU8iIiIik2JGjYgoiOk15OlLNs2XPsjtHKDHkKZSr6RNBgDMktnhRK6Ehvix+2veMmHuWThxVk3q3KIO6Rz+DBIM1IiIglig5qgFE0dQBgAPnchxeSwmHorVc8GAp2AsVIY5x1b9HrFCQ03b/KX6IhZiITIyMhAREQGbzQabzabpNbTEQI2IKIhpHaD5Oy/NH+JsW6Cya+5BWmpVHh46keN8LBWguQdScgvB5OafSbUnJrlXaAcuLJCzf/9+xMXV3QvXbDhHjYiIiMikmFGzGCNWPcnNGaHgwaExCgXuGTJxdszTEKfc0KdSvm7q7vNrji2u0l2fD5Xh0WDHQI2IKEglxwzVNABffWIRZqV7P85Bz+B/ZFq2JsOf3oIwT6/7Oh9NbkhTT85rcmspS+PQJxFRkBIHSr1R6Xd7vtYQM3KVpif+ZsYcska8iKwRL2rSFrNe5I2hgdqCBQuQkZGB2NhYJCQkYMSIESguLvZ63vnz52Gz2ZCYmIjo6Gi0a9cOGzZscL6+c+dODBs2DElJSQgLC8PatWvrtCEIAp566ikkJiaifv36GDBgAI4dO6bl2yMiIiLyi6FDn5999hlsNhsyMjJw+fJlPP744xg0aBC++uorNGzoeTluTU0NBg4ciISEBHzwwQdo1aoVTp06hcaNGzuPuXjxIrp27YqJEyfijjvu8NjO888/j//3//4fVqxYgbS0NDz55JMYPHgwvvrqK8TExOjxdomIAk6LTJqvHHNp5ea3aj0sa4SsES/ik7WPKDpWKnOmZJWnJsOmHP60LEMDtY0bN7o8Xr58ORISElBQUIC+fft6POfNN99EeXk59uzZg8jISABAamqqyzFZWVnIysqSvK4gCFiyZAmeeOIJDB8+HADw1ltvoUWLFli7di1GjRrlx7siIjInR9C2G/qVJFC64Km0Kt+l1IevQZsWw6q7EedzIKs0MJPiLejiUCi5M9VigoqK2mi/SZMmksesX78ePXv2hM1mw7p169C8eXOMHj0a2dnZiIiIUHSdEydOoKysDAMGDHA+Fx8fj8zMTOzdu9fwQM1slbm5WTeFCrNtvO4vrbNp7sGVr+TO9bUwr9IN2sXfT0ei7j1xBK3u31ul5rP5kkUTU5MVU1JfjYKfaQI1u92O6dOno1evXujUqZPkcd988w22b9+OMWPGYMOGDSgpKcGUKVNw6dIlzJ07V9G1ysrKAAAtWrRweb5FixbO19xVV1ejurra+biyMvDDCURERBRaTBOo2Ww2HDlyBLt375Y9zm63IyEhAcuWLUNERAS6d++OM2fO4IUXXlAcqKmxYMECPP3007q1T0SkB62HOR0ZL18ya75m4ZRk8Wv/9j7CsPrEIpesmtL74aiv5sisBSKL5j7s6XisWTZtXvxvf3OumpWYIlCbOnUq8vPzsXPnTiQnJ8sem5iYiMjISJdhzvT0dJSVlaGmpgZRUVFer9eyZUsAwLlz55CYmOh8/ty5c7jxxhs9njNnzhzMnDnT+biyshIpKSler0VEFIzEQ5TJMUM9DkPW1l3zraSHpyBNTXDo3g9AXfFutXPS0keddd4TX+8BkZihgZogCHjooYewZs0a7NixA2lpaV7P6dWrF/Ly8mC32xEeXltd5OjRo0hMTFQUpAFAWloaWrZsiW3btjkDs8rKSnzxxReYPNnzvITo6GhER0cre2NERCZwMmZ0QOaRllblY+Rv377FGSyt5vyJ23FtU9nCBSUBmi/7iDpqqMkFcUWrkoCuV79WkhVLH3VW+9WennAFqKUYWkfNZrNh5cqVyMvLQ2xsLMrKylBWVoZff/3VeczYsWMxZ84c5+PJkyejvLwc06ZNw9GjR/Hxxx9j/vz5sNlszmMuXLiAwsJCFBYWAqhdPFBYWIjTp08DAMLCwjB9+nQ8++yzWL9+PQ4fPoyxY8ciKSkJI0aMCMh7JyIiIvLG0IxaTk7tHIB+/fq5PJ+bm4vx48cDAE6fPu3MnAFASkoKNm3ahBkzZqBLly5o1aoVpk2bhuzsq78NHThwAP3793c+dgxZjhs3DsuXLwcAPPbYY7h48SL++te/4vz58+jduzc2btzIGmpEFDSMWJUtzkz5u0pUji/7HoszZFquqve2AtSx1ZQvmTGu7iR3hg99erNjx446z/Xs2RP79u2TPKdfv35e2w4LC8MzzzyDZ555xmsfzETtBunevgHJt8v5FURGSK3Kk3ztZMzoAPYkeCgNxnzdz9MTUwddXFhgGaZYTEBERNoLhur/UpTWUdODI4smteen2iA6IPPTyHK4KTsRERHRb86cOYN7770XTZs2Rf369dG5c2ccOHDAsP4wo0ZERLrRc56a0T5Z+4hLRs3f4WhDsmhcAeri559/Rq9evdC/f3988sknaN68OY4dO4ZrrrnGsD4xUCMiIl2511wzKy3mpZG1LVq0CCkpKcjNzXU+p6R0mJ449ElEFMSSY4aaKjgqrcoP2nlzVlS0KglFHdJR1CHd6K6Ywvr169GjRw/cddddSEhIQLdu3fD6668b2icGakRERESo3U88JycH119/PTZt2oTJkyfj4YcfxooVKwzrU5igpEYG1VFZWYn4+HhUVFQgLk7bvfTklM6WLpXhz2/NZvsNV+17Mdv7IGvRK/Mk97kMVLbLjP83pN67r0OlWq/+VDoEKp6f9snaR1zmmLmXVjFbORX3fUUBIP3rIt2vq/Rnp+O4r6Z/gtjohpr24Zfqi7hhSZbHPkRFRaFHjx7Ys2eP87mHH34Y+/fvx969ezXth1Kco0ZERD7rjUq/N3w3QwCrlHjbKPcAzZ0VgzQAKOqQHpBgzcwSExNxww03uDyXnp6O//znPwb1iIEaEVFICOaaaloRZ9I81UfzxGXVJ2oDMrMFZg5SARpd1atXLxQXF7s8d/ToUbRp08agHnGOGhEREREAYMaMGdi3bx/mz5+PkpIS5OXlYdmyZS77iQcaM2pERCTJMQRp5myc1rsUuGfT3Ic3xY+VZt7IGjIyMrBmzRrMmTMHzzzzDNLS0rBkyRKMGTPGsD4xUCMiIq8cQ6e9UQkAfs9P88YRGLrPVZN6XotgzdvcM0/Huxw3yq/LmwLnqQFDhw7F0KHmmSPJQI38YsSEXzP/Zk/Wptdny2wT4+VI9TW1Kg8nY4YCMhvFS/EnuJP6N/G2MnRWeu0KeXHwNjItW3ZT9odO5Di/3tC1LYDaeWuOrx0cc9nkgjnxggKzzlkja+AcNSIiIiKTYkaNiIi8zkXb/dtru31o05FJ05ujzyNFO/2kVk0GAOxOc83ijUzLdn69+sQivJI22WObjuyaI5smPu6V366jZHi0ti95psiqOeq8eVv96dilINSHQM2CgRoRUQhQWrNM/LV7PTB3juBDPHcN0H/+mhLiPoiHXsVDn1JBmvi1q8FYTp3X6sxREzkZM9rl/nm6l4EM3sTBWfqosyzVYSEM1IiIgkRpVb7k5Hsp3ubPOYIJR6DhKbhIdpu7JpVJ0zqYE7d3Mma0y3uVutYraZOd2bKHTuTIBmtAbTDmfpzj/FfSJjsXIHi6L+73zv35QBIHZwzSrIVz1IiIiIhMihk1IiKLU7IyUg2lmR9vQ6Ri3jJpchk+9/cjzlilVuV5nT/nyLJ5y6KJV38Ctas8Pc9Lu5pp8zQPzZf7EghK56g5sFSHOTBQI6+sVFqAyAje/o/oUfZDavK/r9fyNFzqiVzQJn7NW3Aini+mppiup746hj0dr9UGbXEu13NwD8KUENdXq1tr7eowqNx7N8NiArImDn0SERERmRQDNSIiCyqtyg948WclQ3neMke7EefMpjmGLJNjhjr/yJF73X1hQW9Uqs6muZbikB4mVbp9lJWzaUUd0p3lOsgYHPokIgpxSoc/tSC+jpYBjHs5DMfQ5+oTi4Dfaqd525nAQclqUE/nOHZDAMxTO82haFWSc44ay3NYCwM1IiJSRIvAQ67Mh1bEbY9Mc806+hKsAd4XHjhed8/WmSlIc2BwZk0c+iQiIiIyKWbUiIhCnNbDnkZlk5RcV0k2TUzNMGgwYqkO4zBQM6HS2bu8HxTkAj1JmsgfZv28JscMVdS3QM5RC5RA/5vcdvA4FqMPAGBW+i7N56hpPWTsmK8GcEjU7Dj0SUREhqwitQolq0XFgY/76li5QEhuJa1jVaz7nqG+FtJlIGZtDNSIiIiITIpDn0REQUKL4Uv3rJoVh0T1yAyKs2rilZ63HTwOAChCEtD16rHiUh3ibJuYt2yaHE+v+zIsqibL5qinFsi5ah+eehkxkZGatll16RIAICMjAxEREbDZbLDZbJpeQ0sM1IiILMyKgZRePAVo4vvjeH3kb3XV3CldaCAO2jZ0bQugNnhz7APqeE5qXpl7kCU+Ts3+oEoDNF/3+gx2+/fvR1yc/N6zZsBAjYjIgnzZvDwUiN+z+70RvyYVpGlNKuBSmkUTB19Fq5IU74LgCQvcWhvnqBERERGZFDNqFqN2mMOf37DlzjWiP0Tkmdb/r8w+rKp0Pp3jeW/3R5xtU1NvzTHkWTtv7Wr9NV+GMx3DqovRxzn/TY7e89I8tsOaagHFQI2IyOJC6Rcfb/PQ5HirK+cIztQOjzoCs1fSlG8ALw60UqvyXBYh4Le90ItWJTnnvzmGQB2PMUpVV8lCGKgREVmQnsGZWTNpcvPQlFJSBNjXbJoUb/uFnowZ7bJZulR2TLxq9CRqjylCbXZMfL4Y56QFD85RIyIiIjIpZtSIiEKYWbNnDnrUdfM0Zy05ZihmpV89ZnFRH5/adM+avZI2WfHwp7+MyJ4ZUVMtVDFQIyIKYWbd51McRPVGpfPrkxpeQ+37Fhe8dZDbvN39NccQp6cAy1PtNamyHcDVmm2eOBYjbOjaFrcdPO7X/p4s8WEcBmpBxJ/VmVzZSRT8zBiQeVJale8SnIlpvTm5FMekfk+ZNW9zzxw8BXTA1ffwCR6pc47jfXmrw+bpXF9oVvx2Xjwwr8K/NkgW56gRERERmRQzakREQcwqWTQHx1DsSaM7oiHxfDVPWThHVstldaeX7aQcZTqUzINTUo9NCU9ZuKJVSUifp0nzJIGBGhERGSoUpkmIh0EdX7vXRBMHQOmjznodBvXGtQCvf8RlQDhfLbAYqBERBRkrZNGCITiTW0AgxX016Ctpk+sWsUXt3DiX4rceru2Ne4CmJLhyX3DgqUab+LiiVUncqUBnnKNGREREZFLMqBERWZwVMmhW42sdNV9IrQYFXMttOPpwMt1zqQ5vxG3ddvC45FCo1ApQqWya+zEcBtVXmCAIgtGdsKLKykrEx8ejoqICcXFxmrZdOls63W0EPcpz+FMuhChUBGMApvT/tpHvXU2Q5usQKOC5zIe4xppUjTTx8XJDoErnpikJyLxSWKJD6c9Ox3HP/mkQYiIj/e+fSNWlS3hizWZdfn7rgRk1IiIyFTMEqOL5YUoCN1/mq4kDtIdO5Lg8VlInzdf5ad72AnVfxBDK5s2bh6efftrlufbt2+Prr782qEcM1IiIiIicOnbsiK1btzof16tnbKjEQI2IiALCKlMa5FZbakHJVlOOlaCO5321oWtb2fcR6pkzOfXq1UPLli2N7oYTV30SEZGuSqvyfQrSzBbQKQ3cxMOYanlqw5f5b7PSd+keaAa7Y8eOISkpCddeey3GjBmD06dPG9ofBmpERKQLXwO0YKFVwCb2StpknwM28l1mZiaWL1+OjRs3IicnBydOnECfPn3wyy+/GNYnDn0SERERAcjKynJ+3aVLF2RmZqJNmzZ47733MGnSJEP6xEDNIItHSq9qGpmWHcCeGCMUf8um0CW3ijEY/y8E43vSktJsm9z+oJ4wi6a9xo0bo127digpKTGsDxz6JCIivziGOLUa6jRDeQ5/yS0Y8JW/w6ik3oULF3D8+HEkJiYa1gdm1IiIgkRpVb6uQU6oZsp8LYDrKUjTes6aGDNp2nnkkUcwbNgwtGnTBmfPnsXcuXMRERGBe+65R3WblZWV2L59O9q3b4/09HSfzzc0o7ZgwQJkZGQgNjYWCQkJGDFiBIqLi72ed/78edhsNiQmJiI6Ohrt2rXDhg0bXI5ZunQpUlNTERMTg8zMTHz55Zcur/fr1w9hYWEufx588EFN3x8RERFZR2lpKe655x60b98ed999N5o2bYp9+/ahefPmitu4++678c9//hMA8Ouvv6JHjx64++670aVLF/znP//xuU+GZtQ+++wz2Gw2ZGRk4PLly3j88ccxaNAgfPXVV2jYsKHHc2pqajBw4EAkJCTggw8+QKtWrXDq1Ck0btzYeczq1asxc+ZMvPrqq8jMzMSSJUswePBgFBcXIyEhwXnc/fffj2eeecb5uEGDBrq9VyKiQHDPqjmyYP5m2gKZTdM7Mxgoeg5ZMoumj1WrVvndxs6dO/G3v/0NALBmzRoIgoDz589jxYoVePbZZ3HnnXf61J6hgdrGjRtdHi9fvhwJCQkoKChA3759PZ7z5ptvory8HHv27EHkb/t/paamuhzz0ksv4f7778eECRMAAK+++io+/vhjvPnmm5g9e7bzuAYNGpiqqB0RkZnIBWe9UYnd0G+fRK0CTCNwTlloq6ioQJMmTQDUxjl33nknGjRogNtvvx2PPvqoz+2Zao5aRUXtpq6ON+jJ+vXr0bNnT9hsNqxbtw7NmzfH6NGjkZ2djYiICNTU1KCgoABz5sxxnhMeHo4BAwZg7969Lm298847WLlyJVq2bIlhw4bhySefDFhWTW5lZ/Gg8ZKvFb7m+/i2EnL9UfubtF4r3fRo14hN4vX6ARSq84jMTO2/iZb/luIslXu7njJw7jydKz7PsUclgDoBnNR1rUDNBu2B4OgXM2vmk5KSgr1796JJkybYuHGjM0v3888/IyYmxuf2TBOo2e12TJ8+Hb169UKnTp0kj/vmm2+wfft2jBkzBhs2bEBJSQmmTJmCS5cuYe7cufjxxx9x5coVtGjRwuW8Fi1auGyqOnr0aLRp0wZJSUk4dOgQsrOzUVxcjA8//NDjdaurq1FdXe18XFlZ6ec7JiIiomAzffp0jBkzBo0aNUKbNm3Qr18/ALVDop07d/a5PdMEajabDUeOHMHu3btlj7Pb7UhISMCyZcsQERGB7t2748yZM3jhhRcwd+5cxdf761//6vy6c+fOSExMxK233orjx4+jbdu2dY5fsGABnn76aeVviIjIIFKZK1+f742rv5Ce/O1vR3bsJFyzaJ7OOxkz2uV59yyykgybUfPVApFJm5W+S9V11J5HgTFlyhRkZmbi9OnTGDhwIMLDa9dtXnvttXj22Wd9bs8UgdrUqVORn5+PnTt3Ijk5WfbYxMREREZGIiIiwvlceno6ysrKUFNTg2bNmiEiIgLnzp1zOe/cuXOy89EyMzMBACUlJR4DtTlz5mDmzJnOx5WVlUhJSVH0/oiIzCQ5ZmidIUzxY5cAzS3Y8kbp8WYcBlUS/KgZavTWrrhNT8d6Cswc54ifd++b1HVvO3jc5bF4g/aiVUken5c1r0LZcSHg0qVL6NChA/Lz8/GnP/3J5bXbb79dVZuGlucQBAFTp07FmjVrsH37dqSlpXk9p1evXigpKYHdbnc+d/ToUSQmJiIqKgpRUVHo3r07tm3b5nzdbrdj27Zt6Nmzp2S7hYWFACBZ1C46OhpxcXEuf4iIiIgcIiMjUVVVpWmbhmbUbDYb8vLysG7dOsTGxqKsrAwAEB8fj/r16wMAxo4di1atWmHBggUAgMmTJ+Of//wnpk2bhoceegjHjh3D/Pnz8fDDDzvbnTlzJsaNG4cePXrgpptuwpIlS3Dx4kXnKtDjx48jLy8Pt912G5o2bYpDhw5hxowZ6Nu3L7p06RLgu0BEpC1PQ4XiYcqTcJ3g757d8jWLJl48ILXYwFMflWbV/F0BqqRP4uzTyLRsrD6xyOV1fybtu2fExG25tyt1HU8ZNHfu13DP1Dkfu61JU5VFI0k2mw2LFi3Cv//9b9Sr53+YZWiglpNTu4TZMdHOITc3F+PHjwcAnD592jm+C9Supti0aRNmzJiBLl26oFWrVpg2bRqys6+uWhw5ciR++OEHPPXUUygrK8ONN96IjRs3OhcYREVFYevWrc4ALiUlBXfeeSeeeOIJfd8wEVEASA1jOrgEbb8FTL4GQaVV+ZCfUWyeemjuQak4CHMEL+KV71oGaVrzFtg5gjWpoVJPGJxpa//+/di2bRs2b96Mzp0716kLK7VoUUqYIAiClh0MFZWVlYiPj0dFRYWqYVC5TdlvfKDIn66p0n7z8oBfU06gN7E2W3kOM87fIfNyBGO7EVen1IbjsdTEf1+zZ75+NpUEar60qXXhXkdQNit9l/O11ScWmSo4U0su++bv+3Nk4bJGvIiTC5XPvVL6s9Nx3LN/GoSY32qmaqXq0iU8sWaz6p/f3jhG76Tk5ub61J4pFhMQERERBQNfAzFvGKgREVmc1A4BUtknX7NoDmoyvVoPf2q9Y4FjyLO06uq8tJFp2Vj828BGMGTWbjt43GV4c3FRH9nVot4UrUq62p628+aDxuXLl7Fjxw4cP34co0ePRmxsLM6ePYu4uDg0atTIp7YYqBERBRH3HQgcX7sPi+pJPBTr6IfSc8TnSbXnaFPN+5EaGi6tyhcFLLswMi3f+bVVSS0ecF9koDRocwx3ck6bvFOnTmHIkCE4ffo0qqurMXDgQMTGxmLRokWorq7Gq6++6lN7DNSIiCzOPfgQB0aevlYbsMmd52kOnNL9QN0XPHhaAOGpPaUrTMXHi1ebis9xP98MiyACQW3Q5lCbnWUdNbFp06ahR48eOHjwIJo2bep8/k9/+hPuv/9+n9tjoEZERESkkV27dmHPnj2IiopyeT41NRVnzpzxuT2fA7Vx48Zh0qRJ6Nu3r88XIyIibfia8dFqtaTU5uyOTJdUNkzObsSpOk8NqWxjsGTQxBkxxw4ESocqZ6XvQtGqJGzoWrs7j8tcNB/aCXV2ux1Xrlyp83xpaSliY2N9bs/nQK2iogIDBgxAmzZtMGHCBIwbNw6tWrXy+cLBTq78hjeFr6VLvqbXxNZtg8arOk+vsh7BUg5Dr2/+LO1Bnmg90V7uGlLPiYcme6NS0fCnFkGae7+U3gNPx7nPfzNLPThP5EpwOAIurFIeZKWPOgusuvqYxXB9N2jQICxZsgTLli0DAISFheHChQuYO3cubrvtNp/b8zlQW7t2LX744Qe8/fbbWLFiBebOnYsBAwZg0qRJGD58OCI1rndCRETKBeqXA6nASCpoU0uLNuR+eREHt1LHmTVIc+e+o4L7np5KSe39ycUEyixevBiDBw/GDTfcgKqqKowePRrHjh1Ds2bN8O677/rcnqo5as2bN8fMmTMxc+ZM/Pe//0Vubi7uu+8+NGrUCPfeey+mTJmC66+/Xk3TRERERACAQYdPoFFEhKZtXrhyBU8AyMjIQEREBGw2G2w2m2btJycn4+DBg1i1ahUOHTqECxcuYNKkSRgzZoxze0xf+LWY4LvvvsOWLVuwZcsWRERE4LbbbsPhw4dxww034Pnnn8eMGTP8aZ6IiHwQyMyP1LV82cNTit5ZNCmBGDLW+hquqzav1oVbfWKR4syXOGsGwKd5aalVeTipsK9ms3//fl12Jrh48SIaNmyIe++9V5P2fA7ULl26hPXr1yM3NxebN29Gly5dMH36dIwePdr5htesWYOJEycyUCMiIkV8Dc7c55BJPedLO3rS6zrizdZr/3Z8fXX+mqe5zS5bQI0a7fKct3lpqVV5qosmh4IWLVrg7rvvxsSJE9G7d2+/2/M5UEtMTITdbsc999yDL7/8EjfeeGOdY/r374/GjRv73TkiIrIWNZks9wUI7kGbp/lvahcP+HtOIMll4TwtIvC2Ebs4AMsa8WKd87NGvIhP1j7ifLyha1tsKGrrsS2pvWMJWLlyJZYvX44//OEPSE1NxcSJEzF27FgkJSV5P9mDcF9PePnll3H27FksXbrUY5AGAI0bN8aJEydUdYiIiIjIqkaMGIG1a9fizJkzePDBB5GXl4c2bdpg6NCh+PDDD3H58mWf2gsTBEHQqa9BrbKyEvHx8aioqPA4xr1te1vVbcuV53DMP/BVscryG3rRq6yHHL1KWujRrrff9FmCw1z0yszI/TubNRukZ2kdNasyrXgPAfn3Kh7udOepjtqGrm3xStpkr9c8GTNattyHVBsnF97utW0Hbz873Y/78rrrdVlMcFPJMa990NIrr7yCRx99FDU1NWjWrBkefPBBzJ49Gw0aNPB6LncmICIiVQL1C4O36/jaD6sEaFJz7mal75IMqFwWF+DqMQ+dyHF+7R5wOV4TH++JY16aeNjTlyAt1Jw7dw4rVqzA8uXLcerUKfz5z3/GpEmTUFpaikWLFmHfvn3YvHmz13YYqBERkc+Y1dWH0j1LR6bVfi2umwZ4XkBw28Hjslk1x/Oe5gaKA0LH1w8hR3QUAzV3H374IXJzc7Fp0ybccMMNmDJlCu69916Xufu33HIL0tOlR8/EGKgRERERaWTChAkYNWoUPv/8c2RkZHg8JikpCX/7298UtcdAjYiIFLN6Js3Mw55yxP0W16pz343AkUlzHxq97eBxvJLmuW33TJqjvVkyCZ9Zq639OdDTd99953XuWf369TF37lxF7TFQIyKyoEDs6+npelYhtXl8sJBaYHE1gLv63C8H/woAztIbWSNelKxbJw76JOfBMUiTJQ7SqqqqUFNT4/K6rwsYGKgZRI+VnVaSvFB+0qrcqtlbd/6o6ppmW9kpx2o/FOW4z6ERC4XPOqDvSkg9WflzKFUEN5iCNaD2/blmvq7OTXPcg9gRy1zO2S3TnnuGTvy8t+/bVOvixYvIzs7Ge++9h59++qnO61euXPGpPZ/rqBERERGRZ4899hi2b9+OnJwcREdH49///jeefvppJCUl4a233vK5PWbUiIjI0tkzOeIsWrBl09yJ/w1Xn1iEWem+b6klzqaJM97Mpin30Ucf4a233kK/fv0wYcIE9OnTB9dddx3atGmDd955B2PGjPGpPQZqREQhzipBWm3wId6E/GrwMDIt2+u8LXfBHLjVBllX75V4AYIUR5AWKlMS9FJeXo5rr70WQO18tPLycgBA7969MXmy98LD7hioERGFOPeARTy/S0kB1kBxr8Yvflxale1zn5Qcb6VgTu1cWrl5pMyk+e7aa6/FiRMn0Lp1a3To0AHvvfcebrrpJnz00UeIj4/3uT3OUSMiIiLSyIQJE3Dw4EEAwOzZs7F06VLExMRgxowZeOyxx3xujxk1IqIgoTSj5C3zoiSLZER2Tdw390yfuIo+h+5cefv3kbpfzKapM2PGDOfXAwYMwNdff42CggI0a9YMK1eu9Lk9BmoGkdpQF6hN4UuR21zdiI3O1fJn03rMq1B1WrHMNeXKpQDAyLTAllewypwhs9Lj3vrTZqCGz5TMQwK8b1Qu9bp7EGfE5/TqvLRFzgBjcVEfjEzLdtlWSU2wZqVhTm/8KkfEAE1Tbdq0QZs2bXDw4EG88cYbWLZsmfeTRDj0SUQURBzZJbVBh7cgzsxWn1jkDNIcX5NyyTFDGaSJLFy4EGFhYZg+fbqh/WCgRkRERCSyf/9+vPbaa+jSpYvRXeHQJxGRFWk97ChV2kLPayrhnsUTV+FfXOR63NXXdgHo43zevYyHkuuoEehtveQoHQZ3HEtXXbhwAWPGjMHrr7+OZ5991ujuMFAjIiLvtcbMOG9Sbq6v+DXH196CUF8DFrm5fIA1AiCXPqqc/xtsbDYbbr/9dgwYMMCnQO2OO+6Qff38+fOq+sNAjYiILMmRKZML2BwLDTwRLzqonc92NfPm3qZUbTmrYoDm2apVq/Df//4X+/fv9/lcbzXS4uPjMXbsWJ/bZaBGREREIe/bb7/FtGnTsGXLFsTExPh8fm5urg69YqBmmG19m8m8Oj5Q3bAkv0p7SLjxgSL5Azara9dKJTj06qsRNa30KMHhDyuvpHQwagh0cVEfyW2jpI4BxP2su/LTsRp0Vvoul3luDp4ydGYeAlZCMhPIbJpTQUEBvv/+e/zud79zPnflyhXs3LkT//znP1FdXY2IiIiA94uBGhGRBRkVOAS6jtrItGyPwRQgPeQp7pf7LwqBKNlhluDb/TPC4U55t956Kw4fPuzy3IQJE9ChQwdkZ2cbEqQBDNSIiCxNap/OQF9bSdZQ675JzVGTm0fmGrhJz22TIt4Y3irZNbMEjmYXGxuLTp06uTzXsGFDNG3atM7zgcQ6akREREQmxYwaEZGFqSkroeW1vRH3zZd+empber6jb5kxcT88tVlalS3ZV3H2zj1zZ5nMFYc9FduxY4fRXWCgRkRkReIAQc8hOKmaYHovkBAPl+pVpFZJcV9P71tt8Gk4BmiWxEBNJ2bbIN2f/shtBC/n1p0/Sr4mv+pVfbty/Lmm2nuAzdaYwwLo98Ne7eRtudpYfm04rcMPVn/aVBvweHotEAGbv22ouVee5rj58/59zQSKz7FUYCbGIM2yOEeNiIiIyKSYUSMiooCQWo3pLUvl7zwwf2sEijOBnJNGgcZAjYjI4sxWJsI9mPE2bOhpSFTNe5IqFyJ3fakAzP2cYNtCiqyDQ59EREREJsWMGhER6Ubp6lQts1T+tiXXZ/fXTD38ySHPoMBAjYiILMPfIVEtMUijQGCgRl6pLYchx1u5ELlyGP6U2VBLdUkQlWU9vN2fQG/27s/+iGo3ZS+tUr+Ze6B/gBpZLoTzpfwTdPePAVrQ4Rw1IiIiIpNioEZERCGltCo/+DJpALNpQYpDn0REFLSUluTwt021TL8ggQzHQI2IyIKCMiOkE6maaFq15y+/22MmLahx6JOIiIjIpJhRIyIiyar+cseJyW2tpNUuA0r7KHVtK2Qhfc6uMZsW9Bio6cSflPjioj6Sr6ktdeAPNd+0vfF63mbpa8qV7tCL3D2Q649cWQ+5MiPe3mPyH2S+Oc/eJfmS2jIbRnzu/Pk/pMdnVo4ve1Wahdr7IBWQybXn65BjoMvPqKXV/DJP98f9fda5DgO0kMFAjYjIgtRkl3xtW6921Z6n5f6f/tB6bpqSfURdAuSF0r/MB5txs+ohon6Epm1e+TUMmAxkZGQgIiICNpsNNptN02toiYEaERERhZz9+/cjLi7O6G54xUCNiMji5LJGemXeAlVSQst9O7Xi7ypNr8OaRCKGrvpcsGABMjIyEBsbi4SEBIwYMQLFxcVezzt//jxsNhsSExMRHR2Ndu3aYcOGDS7HLF26FKmpqYiJiUFmZia+/PJLl9erqqpgs9nQtGlTNGrUCHfeeSfOnTun6fsjIgo0qXljWg77OYbo9Cocq2fbZqbk/YbSsCfVMjSj9tlnn8FmsyEjIwOXL1/G448/jkGDBuGrr75Cw4YNPZ5TU1ODgQMHIiEhAR988AFatWqFU6dOoXHjxs5jVq9ejZkzZ+LVV19FZmYmlixZgsGDB6O4uBgJCQkAgBkzZuDjjz/G+++/j/j4eEydOhV33HEHPv/880C8dSIi3eixEMPT/Cmt52qFCvc5dwzQSI6hgdrGjRtdHi9fvhwJCQkoKChA3759PZ7z5ptvory8HHv27EFkZCQAIDU11eWYl156Cffffz8mTJgAAHj11Vfx8ccf480338Ts2bNRUVGBN954A3l5efjDH/4AAMjNzUV6ejr27duHm2++WeN3SkREROQ7U81Rq6ioXW7cpEkTyWPWr1+Pnj17wmazYd26dWjevDlGjx6N7OxsREREoKamBgUFBZgzZ47znPDwcAwYMAB79+4FABQUFODSpUsYMGCA85gOHTqgdevW2Lt3r8dArbq6GtXV1c7HlZWVfr9fKbPSpcsrLC6SPk+uhIK3sgx6lF/w57dk2d/UDSjdobZduRIccm79w3FV5wFe+vpauuRLcp8BvcpPaDXHR6tz9ZorpLbcRCD74+2eapVN81bew1s/9FqRGkg+lylhKY6QZppAzW63Y/r06ejVqxc6deokedw333yD7du3Y8yYMdiwYQNKSkowZcoUXLp0CXPnzsWPP/6IK1euoEWLFi7ntWjRAl9//TUAoKysDFFRUS7DpY5jysrKPF53wYIFePrpp/17k0REAeYpKJArThuoPrg/72vAKlfKwspc3isDNIKJAjWbzYYjR45g9+7dssfZ7XYkJCRg2bJliIiIQPfu3XHmzBm88MILmDt3rm79mzNnDmbOnOl8XFlZiZSUFN2uR0TkL6XBj14Bj1btKsmyBUPQxiCNPDFFoDZ16lTk5+dj586dSE5Olj02MTERkZGRiIi4WgAvPT0dZWVlqKmpQbNmzRAREVFnBee5c+fQsmVLAEDLli1RU1OD8+fPu2TVxMe4i46ORnR0tMp3SEREROQ7Q8tzCIKAqVOnYs2aNdi+fTvS0tK8ntOrVy+UlJTAbrc7nzt69CgSExMRFRWFqKgodO/eHdu2bXO+brfbsW3bNvTs2RMA0L17d0RGRrocU1xcjNOnTzuPISIKZmpLYHg7x4jSGkZm09S8V0eJE4/mVTCbRi4MDdRsNhtWrlyJvLw8xMbGoqysDGVlZfj111+dx4wdO9ZlYcDkyZNRXl6OadOm4ejRo/j4448xf/58l+0fZs6ciddffx0rVqxAUVERJk+ejIsXLzpXgcbHx2PSpEmYOXMmPv30UxQUFGDChAno2bMnV3wSUdAIZCFVs9Y90/Me+LvhO/fvJCUMHfrMyckBAPTr18/l+dzcXIwfPx4AcPr0aYSHX40nU1JSsGnTJsyYMQNdunRBq1atMG3aNGRnX12xNnLkSPzwww946qmnUFZWhhtvvBEbN250WWDw8ssvIzw8HHfeeSeqq6sxePBg/Otf/9LuzXn7DzcvXlWzcitCS6ukV+15W9UptypU7lwjvjGrXREqx4iN3uVs295Wl3bVruzUbQWvDL1WQ5oxmPCHp4UBgXiPZr+PVlodyhppJMfQQE0QBK/H7Nixo85zPXv2xL59+2TPmzp1KqZOnSr5ekxMDJYuXYqlS5d67QMRERGREUyxmICIiNSRKl3hYIWMkpX5m7ljNo28YaBGRERBJdBz8zw9p3QqgXydAyIGakRERJpSuvMDs2mkhKGrPomIiIhIGjNqRERBwpG1sdKKR70FatcC8XW8Db0yk0a+YKBmELWlB0LlG68e79Ofsh5mK99x684fJV+T2wg+kHN3/BVM/w/07q97+x6H2RT+21vt3gLegzG9Alf364qvI7Wgg0GaueXk5CAnJwcnT54EAHTs2BFPPfUUsrKyDOsTAzUiIgsL1H6agaYkuBIHQ0b8EiK1aMBT3xmgWUNycjIWLlyI66+/HoIgYMWKFRg+fDj+7//+Dx07djSkTwzUiIiIiAAMGzbM5fFzzz2HnJwc7Nu3j4EaEREppyQDFixD3Voc7zhHy8yhVHt1hkSZTbOkK1eu4P3338fFixcN3QecgRoREQV8AYLSQMt9rpeZgk9P89PEzzNAs6bDhw+jZ8+eqKqqQqNGjbBmzRrccMMNhvWHgRoRURAxUyDjoFWftGhHr1Wg7m0ySLOu9u3bo7CwEBUVFfjggw8wbtw4fPbZZ4YFawzUiIiIiH4TFRWF6667DgDQvXt37N+/H//4xz/w2muvGdIfBmomxNId6smV0SiGdNkKQPo8f7TfvFzVeWbLinjrj9xnT+3nWS9mu7dyfP0/bZb3ZpZ+GIXZtOBit9tRXV1t2PUZqBERWZyWgZGaoUGrBWa61VVjgGZ5c+bMQVZWFlq3bo1ffvkFeXl52LFjBzZt2mRYnxioERFZkJ7BkVSx1mCj5Xw1BmnB4fvvv8fYsWPx3XffIT4+Hl26dMGmTZswcOBAw/rEQI2IiIgIwBtvvGF0F+pgoEZERJKUDhMq3efSTMTlPtRm1phJI70xUCMiIhdKgxarb/4eqA3bifwRbnQHiIiIiMgzZtQMonZ4wIjf/lafWCT52si07AD2xDu5chj+DMmoLjFhwDDQrTt/lHxN9fCOl/ch9/q2vjJlUTar64/cZ9KbWemqT5Xkz/9LKw0VulP6vqUq+Fsdhz0pEBioERGRqmDT1/p6wRKkMUCjQGKgRkREquabeVpA4K34sdWDNQZpFGico0ZERERkUsyoERGFCD3nuPo6X0284tLMWTZHP5lJI6MwUCMiCgF6BGlaLdAJ9JCo1L3wNPzLII2MxkDNKPMqZF6Ll3xJr29mI9Okv4nLrbCz0opQvei1klIPctdUu7E64OVzUCX9OSgeNF7yNbnVq4D8D065z16pTH/0ova+q23T37Z9pcV1ApVd8xakOR8zOCOT4Bw1IiIiIpNiRo2IKEgEus6iHtfTI7Pmax1EZtPITBioERFZnF4BmtKyG2ajusCu3JQUIoMwUCMiIhdm2MPT38yakvNcVp4yi0YmxTlqRERERCbFjBoRkcVpkQEz6zCn0mFM9z4reQ8svUFWwECNvDKizIYe5QzM9MMHsNZG3v5sgi7X12JIb9gut5m7XMkPf/qjF7N99tzVKU1hgqFPT9zrrfnbPwZp5rfvVCniosM0bbOyWkA8gIyMDERERMBms8Fms2l6DS0xUCMisiC/gxQT7waghOr6cwzO6Df79+9HXFyc0d3winPUiIiIiEyKgRoRUYhRmk0zY9attCqf2TQKKRz6JCIKAWYMugKFARpZGQM1IqIg5W9wZrbFBGowSCOr49AnERERkUkxo2ZCqudf+PHbc6CHRby9R1/35tPzPH/P1YNe71OKPyVaSmVKaRS+pq7sR/s0tb0BFhdJZ1hmpe+SfM0q2SUt/i9b5b3KYSaNggUDNSIiiwvUBuaBovr9cK9OCkIc+iQisrBgWyTAII3IFQM1IiIiIpPi0CcRESnaU1OLYVFdMoDMplEQY6BGRGRBgZ6XZsq9aRmgUQgIEwRBMLoTVlRZWYn4+HhUVFRYYq8wzIuXfVntKkK9mGFCM5mXP5vE+7OCVS21/4cC9f9SLptm2j1FGaRZktKfnc7jZsfqsyn7wl8s8/Obc9SIiIiITIpDn0RE5JERNR29YiaNQgwDNSIicmG6qQcMziiEceiTiCiEOYKy5JihSI4ZqipIYwaNSD8M1IiIiIhMikOfREQhSOuaaJpn1ZhJIwMsWLAAH374Ib7++mvUr18ft9xyCxYtWoT27dsb1icGaqHCyze9ZNlztexIaNGjLIM/9NjQ3tu5xYPGS77WfvNy2XalGFFiQ44/QYoRpXHcr6nF51TTvjJII4N89tlnsNlsyMjIwOXLl/H4449j0KBB+Oqrr9CwYUND+sRAjYgoxPlSR033uooM0shAGzdudHm8fPlyJCQkoKCgAH379jWkT5yjRkRERORBRUXtLw5NmjQxrA/MqBERhRj31Z1Ks2R6bluVvLCPZm0TacFut2P69Ono1asXOnXqZFg/DM2oLViwABkZGYiNjUVCQgJGjBiB4uJi2XOWL1+OsLAwlz8xMTEux5w7dw7jx49HUlISGjRogCFDhuDYsWMux/Tr169OOw8++KDm75GIyOyUzInUKkgrrco3X502Ig9sNhuOHDmCVatWGdoPQzNqaiftxcXFuQR0YWFX9wETBAEjRoxAZGQk1q1bh7i4OLz00ksYMGBAnXbvv/9+PPPMM87HDRo00PgdEhGZk9RcNPfntQjQvAVmzKaR2UydOhX5+fnYuXMnkpNll9vpztBATe2kvbCwMLRs2dLja8eOHcO+fftw5MgRdOzYEQCQk5ODli1b4t1338Vf/vIX57ENGjSQbIeIiIhCiyAIeOihh7BmzRrs2LEDaWlpRnfJXHPUlE7au3DhAtq0aQO73Y7f/e53mD9/vjMoq66uBgCX4dDw8HBER0dj9+7dLoHaO++8g5UrV6Jly5YYNmwYnnzyScmsWnV1tbNtAKisrFT3Jq3IgFVYevz+Ujp7l+pzdV/pFiBGlIJQW4JDbSmRYKLm36u0Kl9VOZVAlQJxuSYzaWQyNpsNeXl5WLduHWJjY1FWVgYAiI+PR/369Q3pk2lWfSqdtNe+fXu8+eabWLduHVauXAm73Y5bbrkFpaWlAIAOHTqgdevWmDNnDn7++WfU1NRg0aJFKC0txXfffedsZ/To0Vi5ciU+/fRTzJkzB2+//TbuvfdeyesuWLAA8fHxzj8pKSnavXkiIj845n05giKpeWBSz4uDtEAFwQzSyIxycnJQUVGBfv36ITEx0fln9erVhvXJNBk1x6S93bt3yx7Xs2dP9OzZ0/n4lltuQXp6Ol577TX8/e9/R2RkJD788ENMmjQJTZo0QUREBAYMGICsrCwIguA8769//avz686dOyMxMRG33norjh8/jrZt29a57pw5czBz5kzn48rKSgZrREREQUQcJ5iFKQI1fybtRUZGolu3bigpKXE+1717dxQWFqKiogI1NTVo3rw5MjMz0aNHD8l2MjMzAQAlJSUeA7Xo6GhER0f71DciIr0oyXyJh0Hljhcfp3UJjjrtsaAtkU8MHfoUBAFTp07FmjVrsH37dlWT9q5cuYLDhw8jMTGxzmvx8fFo3rw5jh07hgMHDmD48OGS7RQWFgKAx3aIiKxKSTkMveanMUgj8p+hGTUlk/bGjh2LVq1aYcGCBQCAZ555BjfffDOuu+46nD9/Hi+88AJOnTrlskjg/fffR/PmzdG6dWscPnwY06ZNw4gRIzBo0CAAwPHjx5GXl4fbbrsNTZs2xaFDhzBjxgz07dsXXbp0CfBdICIyTkAWyjBAI1LN0EAtJycHQG3xWbHc3FyMHz8eAHD69GmEh19N/P3888+4//77UVZWhmuuuQbdu3fHnj17cMMNNziP+e677zBz5kycO3cOiYmJGDt2LJ588knn61FRUdi6dSuWLFmCixcvIiUlBXfeeSeeeOIJ/d4sERERkY/CBDPOnLOAyspKxMfHo6KiAnFxcUZ3hxQIpvIcalfmGfE+jOjr4iJ1KwpHpmWrOk9NOQwjBfRzwGwaiSj92ek8bnYs4qLDJI9T1YdqAfELf7HMz2/TlOcgIiLf+RJ0JccMZZBGZDGmWPVJRETqKM3WMUAjsiZm1IiIiIhMihk1IqIgZba5lUTkOwZqRERBxtAAjcOeRJpioEYhQ3ZvwXnxgeuIAnqtEjRiBabazdX9uQez0tX2V93KYDOt6jQsSGOARqQLzlEjIiIiMilm1IiILMhU88+YTSPSDQM1IiJShwEake449ElERL5jkEYUEAzUiIiIiEyKQ59ERORcuep17hszaUQBxUCNCP6VV1A7qdtMJR28sVJfg0mgFgyUVuUruxaDNAqwTlVvIFxooGmb9ur/AbgbGRkZiIiIgM1mg81m0/QaWmKgRkQU4hikUSjav38/4uLijO6GV5yjRkRERGRSzKgREZE0ZtKIDMWMGhFRiOMcRCLzYkaNiCjE1ZmjxiwakWkwo0ZERERkUsyoEQFIXthH/oB58YHpiIHkVv4ZMTRmqr0sYUwJl0By1lHz9n+BiAKKgRoRURBTEmAmL+yD5AD0hYh8x0CNiMjC1Gb6mDkjsgbOUSMiIiIyKWbUiIgsSE0mjVk0IuthRo2IKAQwSCOyJmbUiJSQqStVOnuX5GtGrPazwgpDvemxSlWv+6rniloGZ0TWx4waERERkUkxo0ZEFESYRSMKLgzUiIgsjsEZUfDi0CcRkYUxSCMKbgzUiIiIiADs3LkTw4YNQ1JSEsLCwrB27Vqju8RAjYjIipIX9mE2jUhjFy9eRNeuXbF06VKju+LEOWpEfpL9YTkvYN1wkiv3wNId1iL/7yVdMoaI1MnKykJWVpbR3XDBjBoRERGRSTFQIyIiIjIpBmpEREREJsVAjYiIiMikGKgRERERmRRXfRIREREBuHDhAkpKSpyPT5w4gcLCQjRp0gStW7c2pE8M1Ij0NE+6hEKyzGmls3dp3xeLMaLMiBHlS+RrobEEB1EgHThwAP3793c+njlzJgBg3LhxWL58uSF9YqBGREREBKBfv34QBMHobrjgHDUiIiIik2KgRkRERGRSDNSIiIiITIqBGhEREZFJMVAjIiIiMimu+iQyIfmSDfLkSnsYUfIiaMiUWiEi0gszakREREQmxUCNiIiIyKQYqBERERGZFAM1IiIiIpNioEZERERkUlz1SRRk1K8YVbeBvDHkV2Cq7y9XdhKRuTCjRkRERGRSDNSIiIiITIqBGhEREZFJMVAjIiIiMikuJlBJEAQAQGVlpcE9ISIisgbHz0zHz1Bv7NX/07wPerSppzBB6d0iF6WlpUhJSTG6G0RERJbz7bffIjlZen12VVUV0tLSUFZWpsv14+LikJiYiPDwcNhsNthsNl2uowUGairZ7XacPXsWsbGxCAsLC8g1KysrkZKSgm+//RZxcXEBuaaV8P7I4/2Rx/sjj/dHHu+PPMf9OX36NMLCwpCUlITwcPnZV1VVVaipqdGlP1FRUYiJidGlba1x6FOl8PBw2d8G9BQXF8dvBDJ4f+Tx/sjj/ZHH+yOP90defHy84vsTExNjmWBKT1xMQERERGRSDNSIiIiITIqBmoVER0dj7ty5iI6ONrorpsT7I4/3Rx7vjzzeH3m8P/J4f9TjYgIiIiIik2JGjYiIiMikGKgRERERmRQDNSIiIiKTYqCmsTNnzuDee+9F06ZNUb9+fXTu3BkHDhwAAFy6dAnZ2dno3LkzGjZsiKSkJIwdOxZnz551aaO8vBxjxoxBXFwcGjdujEmTJuHChQsuxxw6dAh9+vRBTEwMUlJS8Pzzz9fpy/vvv48OHTogJiYGnTt3xoYNG1xeFwQBTz31FBITE1G/fn0MGDAAx44d0/iOuNLi/qSmpiIsLMzlz8KFC12OCcb7AwDz5s1Dhw4d0LBhQ1xzzTUYMGAAvvjiC5c2QvXzAyi7P6H8+RF78MEHERYWhiVLlrg8H8qfHzGp+xPKn5/x48fXee9DhgxxaSOYPz+GEUgz5eXlQps2bYTx48cLX3zxhfDNN98ImzZtEkpKSgRBEITz588LAwYMEFavXi18/fXXwt69e4WbbrpJ6N69u0s7Q4YMEbp27Srs27dP2LVrl3DdddcJ99xzj/P1iooKoUWLFsKYMWOEI0eOCO+++65Qv3594bXXXnMe8/nnnwsRERHC888/L3z11VfCE088IURGRgqHDx92HrNw4UIhPj5eWLt2rXDw4EHhj3/8o5CWlib8+uuvpr4/bdq0EZ555hnhu+++c/65cOFC0N8fQRCEd955R9iyZYtw/Phx4ciRI8KkSZOEuLg44fvvv3ceE6qfH6X3J5Q/Pw4ffvih0LVrVyEpKUl4+eWXXV4L5c+Pg9z9CeXPz7hx44QhQ4a4vPfy8nKXdoL182MkBmoays7OFnr37u3TOV9++aUAQDh16pQgCILw1VdfCQCE/fv3O4/55JNPhLCwMOHMmTOCIAjCv/71L+Gaa64RqqurXa7dvn175+O7775buP32212ulZmZKTzwwAOCIAiC3W4XWrZsKbzwwgvO18+fPy9ER0cL7777rk/vQSkt7o8g1H6jdP/mKRZK96eiokIAIGzdulUQBH5+3LnfH0Hg56e0tFRo1aqVcOTIkTr3gp8f+fsjCKH9+Rk3bpwwfPhwydeD+fNjJA59amj9+vXo0aMH7rrrLiQkJKBbt254/fXXZc+pqKhAWFgYGjduDADYu3cvGjdujB49ejiPGTBgAMLDw51DOHv37kXfvn0RFRXlPGbw4MEoLi7Gzz//7DxmwIABLtcaPHgw9u7dCwA4ceIEysrKXI6Jj49HZmam8xitaXF/HBYuXIimTZuiW7dueOGFF3D58mXna6Fyf2pqarBs2TLEx8eja9euAPj5EfN0fxxC9fNjt9tx33334dFHH0XHjh3rtBHqnx9v98chVD8/ALBjxw4kJCSgffv2mDx5Mn766Sfna8H8+TESAzUNffPNN8jJycH111+PTZs2YfLkyXj44YexYsUKj8dXVVUhOzsb99xzj3Pvs7KyMiQkJLgcV69ePTRp0gRlZWXOY1q0aOFyjOOxt2PEr4vP83SM1rS4PwDw8MMPY9WqVfj000/xwAMPYP78+Xjsscecrwf7/cnPz0ejRo0QExODl19+GVu2bEGzZs2c/Q71z4/c/QFC+/OzaNEi1KtXDw8//LDHNkL98+Pt/gCh/fkZMmQI3nrrLWzbtg2LFi3CZ599hqysLFy5csXZ72D9/BiJm7JryG63o0ePHpg/fz4AoFu3bjhy5AheffVVjBs3zuXYS5cu4e6774YgCMjJyTGiuwGn1f2ZOXOm8+suXbogKioKDzzwABYsWGDpqtdK70///v1RWFiIH3/8Ea+//jruvvtufPHFF3W+QQYbre5PqH5+CgoK8I9//AP//e9/ERYWZnBvA0+r+xOqnx8AGDVqlPP4zp07o0uXLmjbti127NiBW2+91ZB+hwJm1DSUmJiIG264weW59PR0nD592uU5RxBy6tQpbNmyxSVb1LJlS3z//fcux1++fBnl5eVo2bKl85hz5865HON47O0Y8evi8zwdozUt7o8nmZmZuHz5Mk6ePAkg+O9Pw4YNcd111+Hmm2/GG2+8gXr16uGNN95w9jvUPz9y98eTUPn87Nq1C99//z1at26NevXqoV69ejh16hRmzZqF1NRUZ79D9fOj5P54EiqfH0+uvfZaNGvWDCUlJQCC+/NjJAZqGurVqxeKi4tdnjt69CjatGnjfOwIQo4dO4atW7eiadOmLsf37NkT58+fR0FBgfO57du3w263IzMz03nMzp07cenSJecxW7ZsQfv27XHNNdc4j9m2bZtL21u2bEHPnj0BAGlpaWjZsqXLMZWVlfjiiy+cx2hNi/vjSWFhIcLDw50Zk2C+P57Y7XZUV1cD4OfHE/H98SRUPj/33XcfDh06hMLCQuefpKQkPProo9i0aZPzfYXq50fJ/fEkVD4/npSWluKnn35CYmIigOD+/BjK6NUMweTLL78U6tWrJzz33HPCsWPHhHfeeUdo0KCBsHLlSkEQBKGmpkb44x//KCQnJwuFhYUuS5zFK2CGDBkidOvWTfjiiy+E3bt3C9dff73L8ubz588LLVq0EO677z7hyJEjwqpVq4QGDRrUWd5cr1494cUXXxSKioqEuXPnelze3LhxY2HdunXCoUOHhOHDh+u6vFmL+7Nnzx7h5ZdfFgoLC4Xjx48LK1euFJo3by6MHTs26O/PhQsXhDlz5gh79+4VTp48KRw4cECYMGGCEB0dLRw5csTZTqh+fpTcn1D+/HjiaQVjqH5+PHG/P6H8+fnll1+ERx55RNi7d69w4sQJYevWrcLvfvc74frrrxeqqqqc7QTr58dIDNQ09tFHHwmdOnUSoqOjhQ4dOgjLli1zvnbixAkBgMc/n376qfO4n376SbjnnnuERo0aCXFxccKECROEX375xeU6Bw8eFHr37i1ER0cLrVq1EhYuXFinL++9957Qrl07ISoqSujYsaPw8ccfu7xut9uFJ598UmjRooUQHR0t3HrrrUJxcbG2N8SNv/enoKBAyMzMFOLj44WYmBghPT1dmD9/vss3CkEIzvvz66+/Cn/605+EpKQkISoqSkhMTBT++Mc/Cl9++aVLG6H6+VFyf0L58+OJp0AtVD8/nrjfn1D+/Pzvf/8TBg0aJDRv3lyIjIwU2rRpI9x///1CWVmZSxvB/PkxSpggCIIxuTwiIiIiksM5akREREQmxUCNiIiIyKQYqBERERGZFAM1IiIiIpNioEZERERkUgzUiIiIiEyKgRoRERGRSTFQIyIiIjIpBmpEREREJsVAjYiIiMikGKgRERERmRQDNSIKCj/88ANatmyJ+fPnO5/bs2cPoqKisG3bNgN7RkSkHjdlJ6KgsWHDBowYMQJ79uxB+/btceONN2L48OF46aWXjO4aEZEqDNSIKKjYbDZs3boVPXr0wOHDh7F//35ER0cb3S0iIlUYqBFRUPn111/RqVMnfPvttygoKEDnzp2N7hIRkWqco0ZEQeX48eM4e/Ys7HY7Tp48aXR3iIj8wowaEQWNmpoa3HTTTbjxxhvRvn17LFmyBIcPH0ZCQoLRXSMiUoWBGhEFjUcffRQffPABDh48iEaNGuH3v/894uPjkZ+fb3TXiIhU4dAnEQWFHTt2YMmSJXj77bcRFxeH8PBwvP3229i1axdycnKM7h4RkSrMqBERERGZFDNqRERERCbFQI2IiIjIpBioEREREZkUAzUiIiIik2KgRkRERGRSDNSIiIiITIqBGhEREZFJMVAjIiIiMikGakREREQmxUCNiIiIyKQYqBERERGZFAM1IiIiIpP6/whjryUplk3ZAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# xarray version\n",
+    "toto = gm.assign_coords(surf, add_lay=False) # add lay false because it needs to be a variable to plot, not a dimension\n",
+    "gm.plot_outcrop(toto)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Get mask of active domain"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/manlaya/envs/gm/lib/python3.11/site-packages/gridmarthe/operasem/gis.py:58: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
+      "  if 'time' in ds.dims.keys():\n"
+     ]
+    }
+   ],
+   "source": [
+    "mask = gm.get_active_mask(grid) # return a geopandas geodataframe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "mask.boundary.plot(color='k')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Compute depths and thickness\n",
+    "\n",
+    "Users can get geometry attributes (depth, thickness, upper/lower altitudes) in a dataset:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1f1f1f;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 75MB\n",
+       "Dimensions:     (time: 1, zone: 1176480)\n",
+       "Coordinates:\n",
+       "  * time        (time) datetime64[ns] 8B 1850-01-01\n",
+       "  * zone        (zone) int32 5MB 1 2 3 4 5 ... 1176477 1176478 1176479 1176480\n",
+       "Data variables:\n",
+       "    h_topogr    (time, zone) float64 9MB 9.999e+03 9.999e+03 ... 9.999e+03\n",
+       "    x           (zone) float32 5MB 5.438e+05 5.442e+05 ... 7.362e+05 7.368e+05\n",
+       "    y           (zone) float32 5MB 2.678e+06 2.678e+06 ... 2.526e+06 2.526e+06\n",
+       "    dx          (zone) float32 5MB 500.0 500.0 500.0 500.0 ... 500.0 500.0 500.0\n",
+       "    dy          (zone) float32 5MB 500.0 500.0 500.0 500.0 ... 500.0 500.0 500.0\n",
+       "    z           (zone) int32 5MB 1 1 1 1 1 1 1 1 1 ... 10 10 10 10 10 10 10 10\n",
+       "    h_substrat  (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
+       "    h_upper     (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
+       "    thickness   (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
+       "    depth       (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
+       "Attributes: (12/17)\n",
+       "    conventions:          CF-1.10\n",
+       "    title:                \n",
+       "    marthe_grid_version:  9.0\n",
+       "    original_dimensions:  x,y,z [grids]: 387 304 10\n",
+       "    lon_resolution:       500.0\n",
+       "    lat_resolution:       500.0\n",
+       "    ...                   ...\n",
+       "    creation_date:        Created on 2025-03-26T13:41:08Z UTC\n",
+       "    institution:          BRGM, French Geological Survey, Orléans, France\n",
+       "    comment:              Hydrogeological model created with MARTHE code (Thi...\n",
+       "    resolution_units:     m\n",
+       "    projection:           epsg:27572\n",
+       "    domain:               FR-France</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6406bc72-1e19-43d7-9174-0cb81cd5d487' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6406bc72-1e19-43d7-9174-0cb81cd5d487' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>zone</span>: 1176480</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4503273c-06bb-4c58-b0d2-55dd3640a45d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4503273c-06bb-4c58-b0d2-55dd3640a45d' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1850-01-01</div><input id='attrs-0059bef2-82c3-4c7d-bafb-6beba9133db1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0059bef2-82c3-4c7d-bafb-6beba9133db1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5fe5eb1-f123-4e16-aa58-3598aa3cca48' class='xr-var-data-in' type='checkbox'><label for='data-e5fe5eb1-f123-4e16-aa58-3598aa3cca48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1850-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zone</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 1176478 1176479 1176480</div><input id='attrs-cf05c054-6234-49d2-ab24-3a64f86ac6cc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf05c054-6234-49d2-ab24-3a64f86ac6cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28c781b9-63c0-4033-8894-e0cfb500d14b' class='xr-var-data-in' type='checkbox'><label for='data-28c781b9-63c0-4033-8894-e0cfb500d14b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([      1,       2,       3, ..., 1176478, 1176479, 1176480],\n",
+       "      shape=(1176480,), dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aa36df7c-dc98-40a4-b690-984fcec0a9ef' class='xr-section-summary-in' type='checkbox'  checked><label for='section-aa36df7c-dc98-40a4-b690-984fcec0a9ef' class='xr-section-summary' >Data variables: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>h_topogr</span></div><div class='xr-var-dims'>(time, zone)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.999e+03 9.999e+03 ... 9.999e+03</div><input id='attrs-db5b14a7-278e-4381-9a90-000cd172c2c2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db5b14a7-278e-4381-9a90-000cd172c2c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32c26ee9-1170-4806-9431-e2506a777747' class='xr-var-data-in' type='checkbox'><label for='data-32c26ee9-1170-4806-9431-e2506a777747' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[9999., 9999., 9999., ..., 9999., 9999., 9999.]],\n",
+       "      shape=(1, 1176480))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.438e+05 5.442e+05 ... 7.368e+05</div><input id='attrs-f9be15cb-a998-436e-a049-2ecf45a2441f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9be15cb-a998-436e-a049-2ecf45a2441f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9e279a6-3b0d-4366-bd40-27956a80f8b1' class='xr-var-data-in' type='checkbox'><label for='data-a9e279a6-3b0d-4366-bd40-27956a80f8b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([543750., 544250., 544750., ..., 735750., 736250., 736750.],\n",
+       "      shape=(1176480,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.678e+06 2.678e+06 ... 2.526e+06</div><input id='attrs-b4c623b5-dd10-4481-96e4-d5200aa7d513' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4c623b5-dd10-4481-96e4-d5200aa7d513' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcc54329-20fc-47ee-822a-038c814b8e92' class='xr-var-data-in' type='checkbox'><label for='data-fcc54329-20fc-47ee-822a-038c814b8e92' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([2677850., 2677850., 2677850., ..., 2526350., 2526350., 2526350.],\n",
+       "      shape=(1176480,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dx</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>500.0 500.0 500.0 ... 500.0 500.0</div><input id='attrs-34611d81-6862-4121-a1df-80dcfc450e10' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-34611d81-6862-4121-a1df-80dcfc450e10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc2f2528-866c-4e2a-899c-b34f31e7d36a' class='xr-var-data-in' type='checkbox'><label for='data-bc2f2528-866c-4e2a-899c-b34f31e7d36a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([500., 500., 500., ..., 500., 500., 500.],\n",
+       "      shape=(1176480,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dy</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>500.0 500.0 500.0 ... 500.0 500.0</div><input id='attrs-5f349249-a338-4207-b90b-e3989e4cfc1c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5f349249-a338-4207-b90b-e3989e4cfc1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f67e1f85-c9e4-4d46-833f-74154a4d9c9d' class='xr-var-data-in' type='checkbox'><label for='data-f67e1f85-c9e4-4d46-833f-74154a4d9c9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([500., 500., 500., ..., 500., 500., 500.],\n",
+       "      shape=(1176480,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 ... 10 10 10 10 10 10</div><input id='attrs-b97cdf75-d70a-4710-926f-d1ee874c5e2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b97cdf75-d70a-4710-926f-d1ee874c5e2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2c096f4-2294-4b89-8da7-b737ea9be697' class='xr-var-data-in' type='checkbox'><label for='data-b2c096f4-2294-4b89-8da7-b737ea9be697' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>long_name :</span></dt><dd>aquifer_layer</dd></dl></div><div class='xr-var-data'><pre>array([ 1,  1,  1, ..., 10, 10, 10], shape=(1176480,), dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h_substrat</span></div><div class='xr-var-dims'>(time, zone)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ebe05482-3643-404a-bf35-11ecf4a66223' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ebe05482-3643-404a-bf35-11ecf4a66223' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b47a9199-cf07-4ba3-a9db-22b1ef520a6b' class='xr-var-data-in' type='checkbox'><label for='data-b47a9199-cf07-4ba3-a9db-22b1ef520a6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan]], shape=(1, 1176480))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h_upper</span></div><div class='xr-var-dims'>(time, zone)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-78007827-41c0-46ea-9102-d16c51129a6d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-78007827-41c0-46ea-9102-d16c51129a6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8740c41c-5300-48ff-b9f0-a3bca9a7acf1' class='xr-var-data-in' type='checkbox'><label for='data-8740c41c-5300-48ff-b9f0-a3bca9a7acf1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan]], shape=(1, 1176480))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thickness</span></div><div class='xr-var-dims'>(time, zone)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4fc053da-c53a-43cd-9980-89c8b63240f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4fc053da-c53a-43cd-9980-89c8b63240f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b30dfd80-38a1-41b0-acce-f63486743014' class='xr-var-data-in' type='checkbox'><label for='data-b30dfd80-38a1-41b0-acce-f63486743014' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan]], shape=(1, 1176480))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time, zone)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ed00b5ac-5474-4632-8e9c-fa30ded28592' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ed00b5ac-5474-4632-8e9c-fa30ded28592' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d062ce10-1736-41f1-b063-49ec54274d1a' class='xr-var-data-in' type='checkbox'><label for='data-d062ce10-1736-41f1-b063-49ec54274d1a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan]], shape=(1, 1176480))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-967c93eb-d4e4-4826-8816-38cd030343fb' class='xr-section-summary-in' type='checkbox'  ><label for='section-967c93eb-d4e4-4826-8816-38cd030343fb' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-6a0342fb-4c3e-4aac-8d8c-4187ceefa03d' class='xr-index-data-in' type='checkbox'/><label for='index-6a0342fb-4c3e-4aac-8d8c-4187ceefa03d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1850-01-01&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>zone</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-7c64203b-afbf-451d-b4ba-d193d779b6b3' class='xr-index-data-in' type='checkbox'/><label for='index-7c64203b-afbf-451d-b4ba-d193d779b6b3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([      1,       2,       3,       4,       5,       6,       7,       8,\n",
+       "             9,      10,\n",
+       "       ...\n",
+       "       1176471, 1176472, 1176473, 1176474, 1176475, 1176476, 1176477, 1176478,\n",
+       "       1176479, 1176480],\n",
+       "      dtype=&#x27;int32&#x27;, name=&#x27;zone&#x27;, length=1176480))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-de10b9c7-e350-4aa1-ab9f-77b48843dc9e' class='xr-section-summary-in' type='checkbox'  ><label for='section-de10b9c7-e350-4aa1-ab9f-77b48843dc9e' class='xr-section-summary' >Attributes: <span>(17)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conventions :</span></dt><dd>CF-1.10</dd><dt><span>title :</span></dt><dd></dd><dt><span>marthe_grid_version :</span></dt><dd>9.0</dd><dt><span>original_dimensions :</span></dt><dd>x,y,z [grids]: 387 304 10</dd><dt><span>lon_resolution :</span></dt><dd>500.0</dd><dt><span>lat_resolution :</span></dt><dd>500.0</dd><dt><span>scale_factor :</span></dt><dd>1.0</dd><dt><span>nested_grid :</span></dt><dd>False</dd><dt><span>extend :</span></dt><dd>xymin : 543750.0 2526350.0; xymax: 736750.0 2677850.0</dd><dt><span>period :</span></dt><dd>1850-1850</dd><dt><span>frequency :</span></dt><dd>nan day(s)</dd><dt><span>creation_date :</span></dt><dd>Created on 2025-03-26T13:41:08Z UTC</dd><dt><span>institution :</span></dt><dd>BRGM, French Geological Survey, Orléans, France</dd><dt><span>comment :</span></dt><dd>Hydrogeological model created with MARTHE code (Thiery, D. 2020. Guidelines for MARTHE v7.8 computer codefor hydro-systems modelling. report BRGM/RP-69660-FR).</dd><dt><span>resolution_units :</span></dt><dd>m</dd><dt><span>projection :</span></dt><dd>epsg:27572</dd><dt><span>domain :</span></dt><dd>FR-France</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 75MB\n",
+       "Dimensions:     (time: 1, zone: 1176480)\n",
+       "Coordinates:\n",
+       "  * time        (time) datetime64[ns] 8B 1850-01-01\n",
+       "  * zone        (zone) int32 5MB 1 2 3 4 5 ... 1176477 1176478 1176479 1176480\n",
+       "Data variables:\n",
+       "    h_topogr    (time, zone) float64 9MB 9.999e+03 9.999e+03 ... 9.999e+03\n",
+       "    x           (zone) float32 5MB 5.438e+05 5.442e+05 ... 7.362e+05 7.368e+05\n",
+       "    y           (zone) float32 5MB 2.678e+06 2.678e+06 ... 2.526e+06 2.526e+06\n",
+       "    dx          (zone) float32 5MB 500.0 500.0 500.0 500.0 ... 500.0 500.0 500.0\n",
+       "    dy          (zone) float32 5MB 500.0 500.0 500.0 500.0 ... 500.0 500.0 500.0\n",
+       "    z           (zone) int32 5MB 1 1 1 1 1 1 1 1 1 ... 10 10 10 10 10 10 10 10\n",
+       "    h_substrat  (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
+       "    h_upper     (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
+       "    thickness   (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
+       "    depth       (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
+       "Attributes: (12/17)\n",
+       "    conventions:          CF-1.10\n",
+       "    title:                \n",
+       "    marthe_grid_version:  9.0\n",
+       "    original_dimensions:  x,y,z [grids]: 387 304 10\n",
+       "    lon_resolution:       500.0\n",
+       "    lat_resolution:       500.0\n",
+       "    ...                   ...\n",
+       "    creation_date:        Created on 2025-03-26T13:41:08Z UTC\n",
+       "    institution:          BRGM, French Geological Survey, Orléans, France\n",
+       "    comment:              Hydrogeological model created with MARTHE code (Thi...\n",
+       "    resolution_units:     m\n",
+       "    projection:           epsg:27572\n",
+       "    domain:               FR-France"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "topo = gm.load_marthe_grid('./data/example.topog')\n",
+    "hsubs = gm.load_marthe_grid('./data/example.hsubs')\n",
+    "geom = gm.compute_geometry(topo, hsubs)\n",
+    "geom\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Interpolation, regridding, transformations"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Projection transformation\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Tutorial in construction"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "gm",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/docs/source/user_guide/index.rst b/docs/source/user_guide/index.rst
index 1401b21..de565f2 100644
--- a/docs/source/user_guide/index.rst
+++ b/docs/source/user_guide/index.rst
@@ -9,4 +9,6 @@ User Guide
 
     example/gm_example.ipynb
     example/cli.ipynb
-    example/gigogne.ipynb
\ No newline at end of file
+    example/gigogne.ipynb
+    example/preproc.ipynb
+    example/treatments.ipynb
\ No newline at end of file

From 7d3fd0e552a637855a4ecbcffe6da8d8a21cdcaa Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Wed, 26 Mar 2025 21:03:10 +0100
Subject: [PATCH 15/31] build+fix: modify meson build to allow several modules
 (future: ddr); minor fixes ; edit licence headers

---
 Makefile                             |   13 +-
 add_copyleft.sh                      |   43 +
 meson.build                          |   33 +-
 src/gridmarthe/gridmarthe.py         |    2 +-
 src/gridmarthe/lecsem/edsemigl.f90   |   20 +-
 src/gridmarthe/lecsem/lecsem.f90     |   18 +-
 src/gridmarthe/lecsem/meson.build    |   27 +
 src/gridmarthe/lecsem/scan_grid.f90  |    3 +-
 src/gridmarthe/plot.py               |   13 +-
 src/gridmarthe/scripts/cleanmgrid.py |  110 +-
 src/gridmarthe/scripts/ncmart.py     |    2 +-
 tests/data/craie_npc.hsubs           | 2730 ++++++++++++++++++++++++++
 tests/data/craie_npc.topog           |  595 ++++++
 tests/data/hallue.permh              |   84 +
 tests/test_geom.py                   |   17 +
 tests/test_lecsem.py                 |   23 +-
 tests/test_reproj.py                 |   85 +
 tests/test_surface_mask.py           |    7 +
 18 files changed, 3686 insertions(+), 139 deletions(-)
 create mode 100644 add_copyleft.sh
 create mode 100644 src/gridmarthe/lecsem/meson.build
 create mode 100644 tests/data/craie_npc.hsubs
 create mode 100644 tests/data/craie_npc.topog
 create mode 100644 tests/data/hallue.permh
 create mode 100644 tests/test_geom.py
 create mode 100644 tests/test_reproj.py

diff --git a/Makefile b/Makefile
index 197b459..7904bf5 100644
--- a/Makefile
+++ b/Makefile
@@ -33,12 +33,12 @@ F2PYOPT =--backend=meson --lower
 
 FFLAGS = -fdefault-real-8
 # already O3 in f2py, change it here
-FFLAGS +=-O2 
+FFLAGS += -O2 
 # Position-Independent Code, si shared library, utile
 # FFLAGS +=-fPIC -shared
-FFLAGS +=-ffree-line-length-none
+FFLAGS += -ffree-line-length-none
 # FFLAGS +=-fallow-argument-mismatch # only gfortran > 12.0
-FFLAGS +=-std=legacy
+# FFLAGS += -std=legacy  # not really necessary
 # FFLAGS +=-static # only windows // and not for dev
 
 COMPILE = CC=$(CC) FC=$(FC) FFLAGS="$(FFLAGS)" $(F2PY) -c $(F90FILES) -m lecsem $(F2PYOPT)
@@ -52,6 +52,7 @@ all: clean editm
 # only compile with f2py for develop purpose
 lib: lecsem.so
 
+
 doc:
 	cd docs; $(MAKE) html
 
@@ -68,8 +69,8 @@ requirements:
 	$(PY) -m pip install charset_normalizer numpy meson meson-python
 
 # install: requirements lecsem.pyf lecsem.so
-install: requirements lecsem.so setuptools
-	$(PY) -m pip install $(PIPFLAGS) .
+install: requirements lecsem.so setuptools bakup_pyproj
+	$(PY) -m pip install $(PIPFLAGS) . -vvv
 
 lecsem.pyf:
 	cd $(F90SRCDIR); echo "******** Generating signature ********"; \
@@ -85,7 +86,7 @@ lecsem.so:
 
 # meson editable for test
 editm: requirements
-	$(PY) -m pip install --no-build-isolation --editable . -vvv
+	$(PY) -m pip install --no-build-isolation --config-settings=editable-verbose=true --editable . -vvv
     # meson version of editable - for future replacement of setuptools
 
 wheel:
diff --git a/add_copyleft.sh b/add_copyleft.sh
new file mode 100644
index 0000000..13672c3
--- /dev/null
+++ b/add_copyleft.sh
@@ -0,0 +1,43 @@
+#!/bin/bash
+
+# get all possible args in var
+FILES=("$@")  # all args in an array
+
+# check if any
+if [ "$#" -eq 0 ]; then
+  echo "Usage: $0 <filename(s)>"
+  exit 1
+fi
+
+# loop over files in args
+for filename in "${FILES[@]}";do
+    # adapt header with original filename
+    header="! SPDX-License-Identifier: GPL-3.0-or-later
+! Copyright 2025, BRGM
+! 
+! This file is part of gridmarthe.
+! 
+! Gridmarthe is free software: you can redistribute it and/or modify it under the
+! terms of the GNU General Public License as published by the Free Software
+! Foundation, either version 3 of the License, or (at your option) any later
+! version.
+! 
+! Gridmarthe is distributed in the hope that it will be useful, but WITHOUT ANY
+! WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
+! PARTICULAR PURPOSE. See the GNU General Public License for more details.
+! 
+! You should have received a copy of the GNU General Public License along with
+! Gridmarthe. If not, see <https://www.gnu.org/licenses/>.
+!
+!
+! (from MARTHE, file : ${filename}, convert utf-8 )
+!
+! MARTHE, Copyright (c) 1990-2025 BRGM
+!
+"
+    # echo $filename
+    # echo $header
+    echo -e "$header$(cat $filename)" > "$filename.tmp" && mv "$filename.tmp" "$filename"
+done
+
+exit 0
diff --git a/meson.build b/meson.build
index e952f70..022997a 100644
--- a/meson.build
+++ b/meson.build
@@ -15,14 +15,6 @@ project('gridmarthe', ['fortran', 'c'],
 )
 
 # add_languages('fortran')
-# subdir('src/gridmarthe')
-fortran_sources = files([
-    'src/gridmarthe/lecsem/lecsem.f90',
-    'src/gridmarthe/lecsem/edsemigl.f90',
-    'src/gridmarthe/lecsem/scan_grid.f90'
-])
-lecsem_install_dir = 'gridmarthe/lecsem/' # in python_install_dir
-
 
 # ----- Get compiler and build options ------ #
 fc = meson.get_compiler('fortran')
@@ -83,7 +75,6 @@ python_install_dir = py.get_install_dir()
 
 deps += [py_dep]
 
-
 incdir_numpy = run_command(py,
   ['-c', 'import os; os.chdir(".."); import numpy; print(numpy.get_include())'],
   check : true
@@ -102,28 +93,12 @@ incdir_f2py = incdir_numpy / '..' / '..' / 'f2py' / 'src'
 inc_f2py = include_directories(incdir_f2py)
 fortranobject_c = incdir_f2py / 'fortranobject.c'
 
-# -------- Building interface ----------- #
-lecsem_interface = custom_target('lecsemmodule.c',
-  input : fortran_sources,
-  output : ['lecsemmodule.c', 'lecsem-f2pywrappers.f', 'lecsem-f2pywrappers2.f90'],
-  command : [py, '-m', 'numpy.f2py', '@INPUT@', '-m', 'lecsem', '--lower']
-)
-
-
 inc_dir += [inc_np,inc_f2py]
 
-py.extension_module('lecsem',
-  [
-    fortran_sources,
-    lecsem_interface,
-    fortranobject_c
-  ],
-  include_directories: inc_dir,
-  dependencies: deps,
-  install: true,
-  install_dir: python_install_dir / lecsem_install_dir,
-  # fortran_args : fortran_args
-)
 
+# --------   Compile sources   --------- #
+subdir('src/gridmarthe/lecsem')
+# subdir('src/gridmarthe/rivermod/draindir')
+# subdir('src/gridmarthe/rivermod/rivernet')
 # -------- Install pypackage ----------- #
 install_subdir('src/gridmarthe', install_dir : python_install_dir)
diff --git a/src/gridmarthe/gridmarthe.py b/src/gridmarthe/gridmarthe.py
index 4181d1f..179cf11 100644
--- a/src/gridmarthe/gridmarthe.py
+++ b/src/gridmarthe/gridmarthe.py
@@ -362,7 +362,7 @@ def load_marthe_grid(
     if drop_nan:
         if nanval is None:
             nanval = vattrs.get('missing_value', 9999.) # if no  user defined nanval, try to get corresponding val in dict then 9999. if not present
-        if varname == 'permeab' and is_nested:
+        if (varname == 'permeab' or filename.endswith("permh")) and is_nested:
             nanval = [nanval, -9999.]
         ds = dropna(ds, varname, nanval)
         
diff --git a/src/gridmarthe/lecsem/edsemigl.f90 b/src/gridmarthe/lecsem/edsemigl.f90
index f74452e..4f87236 100644
--- a/src/gridmarthe/lecsem/edsemigl.f90
+++ b/src/gridmarthe/lecsem/edsemigl.f90
@@ -1,6 +1,7 @@
+! SPDX-License-Identifier: GPL-3.0-or-later
 ! Copyright 2024, BRGM
 ! 
-! This file is part of Gridmarthe.
+! This file is part of gridmarthe.
 ! 
 ! Gridmarthe is free software: you can redistribute it and/or modify it under the
 ! terms of the GNU General Public License as published by the Free Software
@@ -15,24 +16,9 @@
 ! Gridmarthe. If not, see <https://www.gnu.org/licenses/>.
 !
 !
-! (Provenance MARTHE, file : edsemi.f90, convert utf-8 )
+! (from MARTHE, file : edsemi.f90, convert utf-8 )
 !
 ! MARTHE, Copyright (c) 1990-2024 BRGM
-!
-! Copyright (c) 1990-2025  BRGM
-
-! Permission is granted under the following conditions :
-! The User undertakes:
-! 1.  To use the software only at his own premises.
-! 2.  Not to use the software simultaneously on several computers or through a network or server.
-! 3.  To ensure that the Marthe software is not passed to any third party (subcontractor, client, etc.) and to take every precaution necessary to prevent illegal copying of the software.
-
-! The User is nevertheless permitted:
-! 1.  To make one or more backup copies of the software for his own use.
-! 2.  To install the software on several workstations at his premises (for instance a desktop and a lap top computer) provided that the software will be never used simultaneously on several computers.
-
-! Limitation of liability:
-! The greatest care was taken to the realization of this software, however BRGM will not be held liable for any direct or indirect damage (including lost profits, lost savings, costs, fees, or expenses of any kind) rising from the use or impossibility of using the software.
 !
       SUBROUTINE EDSEMI7_0(FONC, NKOL, NLIG, XCOL, YLIG, X0, Y0, INVY &
        ,TITSEM, IEREDI, IOUMAI, DXLU, DYLU)
diff --git a/src/gridmarthe/lecsem/lecsem.f90 b/src/gridmarthe/lecsem/lecsem.f90
index c9093d5..88c01b5 100644
--- a/src/gridmarthe/lecsem/lecsem.f90
+++ b/src/gridmarthe/lecsem/lecsem.f90
@@ -1,6 +1,7 @@
+! SPDX-License-Identifier: GPL-3.0-or-later
 ! Copyright 2024, BRGM
 ! 
-! This file is part of Gridmarthe.
+! This file is part of gridmarthe.
 ! 
 ! Gridmarthe is free software: you can redistribute it and/or modify it under the
 ! terms of the GNU General Public License as published by the Free Software
@@ -18,21 +19,6 @@
 ! (Provenance MARTHE, Fichier : lecsem.f90, convert utf-8 )
 !
 ! MARTHE, Copyright (c) 1990-2024 BRGM
-!
-! Copyright (c) 1990-2025  BRGM
-
-! Permission is granted under the following conditions :
-! The User undertakes:
-! 1.  To use the software only at his own premises.
-! 2.  Not to use the software simultaneously on several computers or through a network or server.
-! 3.  To ensure that the Marthe software is not passed to any third party (subcontractor, client, etc.) and to take every precaution necessary to prevent illegal copying of the software.
-
-! The User is nevertheless permitted:
-! 1.  To make one or more backup copies of the software for his own use.
-! 2.  To install the software on several workstations at his premises (for instance a desktop and a lap top computer) provided that the software will be never used simultaneously on several computers.
-
-! Limitation of liability:
-! The greatest care was taken to the realization of this software, however BRGM will not be held liable for any direct or indirect damage (including lost profits, lost savings, costs, fees, or expenses of any kind) rising from the use or impossibility of using the software.
 !
       SUBROUTINE LECSEM8_0(X0, Y0, FONC, XCOL, YLIG, NLIG, NKOL, INVERS, TITSEM &
        , IOUCON, LEC, IERLEC, NUMERR, NTOT &
diff --git a/src/gridmarthe/lecsem/meson.build b/src/gridmarthe/lecsem/meson.build
new file mode 100644
index 0000000..037b081
--- /dev/null
+++ b/src/gridmarthe/lecsem/meson.build
@@ -0,0 +1,27 @@
+lecsem_sources = files([
+    './lecsem.f90',
+    './edsemigl.f90',
+    './scan_grid.f90'
+])
+lecsem_install_dir = 'gridmarthe/lecsem/'  # in python_install_dir
+
+# -------- Building interface ----------- #
+lecsem_interface = custom_target('lecsemmodule.c',
+  input : lecsem_sources,
+  output : ['lecsemmodule.c', 'lecsem-f2pywrappers.f', 'lecsem-f2pywrappers2.f90'],
+  command : [py, '-m', 'numpy.f2py', '@INPUT@', '-m', 'lecsem', '--lower'],
+  #install_dir: python_install_dir / lecsem_install_dir
+)
+
+py.extension_module('lecsem',
+  [
+    lecsem_sources,
+    lecsem_interface,
+    fortranobject_c
+  ],
+  include_directories: inc_dir,
+  dependencies: deps,
+  install: true,
+  install_dir: python_install_dir / lecsem_install_dir,
+  # fortran_args : fortran_args
+)
diff --git a/src/gridmarthe/lecsem/scan_grid.f90 b/src/gridmarthe/lecsem/scan_grid.f90
index d33b937..7eb77c9 100644
--- a/src/gridmarthe/lecsem/scan_grid.f90
+++ b/src/gridmarthe/lecsem/scan_grid.f90
@@ -1,6 +1,7 @@
+! SPDX-License-Identifier: GPL-3.0-or-later
 ! Copyright 2024, BRGM
 ! 
-! This file is part of Gridmarthe.
+! This file is part of gridmarthe.
 ! 
 ! Gridmarthe is free software: you can redistribute it and/or modify it under the
 ! terms of the GNU General Public License as published by the Free Software
diff --git a/src/gridmarthe/plot.py b/src/gridmarthe/plot.py
index 71a2cd6..ebc90a0 100644
--- a/src/gridmarthe/plot.py
+++ b/src/gridmarthe/plot.py
@@ -25,6 +25,7 @@ def _set_map_lims(ax, xmin, ymin, xmax, ymax, perc=.05):
 
 def plot_nested_grid(da, ax=None, var='charge', **kwargs):
     """ Usefull function to plot nested grids, keeping heterogeneous resolution
+    
     TODO: remove var arg: should be a xr.DataArray with coords assigned, same as xarray API for plots
     
     Parameters
@@ -62,13 +63,20 @@ def plot_nested_grid(da, ax=None, var='charge', **kwargs):
     # plots nested then main
     for dx2, dy2 in zip(dx, dy):
         gig = da.where(da['dx'] == dx2, drop=True)
-        gig[var].plot.pcolormesh(x='x', y='y', ax=ax, vmin=vmin, vmax=vmax, add_colorbar=False, **{k:v for k,v in kwargs.items() if k != 'add_colorbar'})
+        gig[var].plot.pcolormesh(
+            x='x', y='y',
+            ax=ax, vmin=vmin, vmax=vmax,
+            add_colorbar=False,
+            **{k:v for k,v in kwargs.items() if k != 'add_colorbar'}
+        )
+    
     grid[var].plot.pcolormesh(x='x', y='y', ax=ax, vmin=vmin, vmax=vmax, cbar_kwargs=cbar_kwargs, **kwargs)
     
     _set_map_lims(ax, da.x.min().data, da.y.min().data, da.x.max().data, da.y.max().data)
     
     return ax
 
+
 def plot_mesh_time_serie(*arg, zone: int, varname='charge', show=False, figsize=(12,4), **kwargs):
     """ Usefull function to plot time serie from any dataset, by extracting a specific cell timeserie
     
@@ -105,6 +113,7 @@ def plot_mesh_time_serie(*arg, zone: int, varname='charge', show=False, figsize=
         plt.show(block=False)
     return ax
 
+
 def plot_outcrop(ds_outcrop, file_out=None, engine='xr', show=False):
     
     """ Usefull function to plot outcrop layers of a marthe (multilayer) grid
@@ -184,7 +193,7 @@ def plot_outcrop(ds_outcrop, file_out=None, engine='xr', show=False):
         label='Layers',
     )
     ax_cbar.ax.tick_params(size=0)
-    ax_cbar.set_ticklabels(ax_cbar.set_ticklabels(['{:.0f}'.format(x) for x in bounds]))
+    ax_cbar.set_ticklabels(['{:.0f}'.format(x) for x in bounds])
     
     if file_out is not None:
         plt.savefig(file_out, dpi=300)
diff --git a/src/gridmarthe/scripts/cleanmgrid.py b/src/gridmarthe/scripts/cleanmgrid.py
index 4661244..e5a6548 100644
--- a/src/gridmarthe/scripts/cleanmgrid.py
+++ b/src/gridmarthe/scripts/cleanmgrid.py
@@ -10,68 +10,62 @@
 
 from gridmarthe.__version__ import _copyleft
 
+
+# ext: VARIABLE_NAME in FRench
 MARTGRID_FILES = {
-    # ext: VARIABLE_NAME
-    'topog' : 'H_TOPOGR',
-    'hsubs' : 'H_SUBSTRAT',
-    'sepon' : 'SUBS_EPONTE',
-    'kepon' : 'PERM_EPONTE',
     'permh' : 'PERMEAB',
-    'poros' : 'POROSITE',
-    'press' : 'PRESSION',
-    'perm_r': 'PERM_LIT_RIVI',
-    'anisv' : 'ANISO_VERTI',
-    'anish' : 'ANISO_HORIZ',
-    'emmli' : 'EMMAG_LIBR',
+    'debit' : 'DEBIT',
+    'charg' : 'CHARGE',
     'emmca' : 'EMMAG_CAPT',
+    'emmli' : 'EMMAG_LIBR',
+    'zgeom' : 'ZONE_GEOM',
+    'hsubs' : 'H_SUBSTRAT',
+    'equip' : 'Z_EQUIPOT',
+    'topog' : 'H_TOPOGR',
+    'zonep' : 'ZONE_SOL',
+    'zonei' : 'ZONE_IRRIG',
     'idebo' : 'IND_DEBORD',
-    'charg' : 'CHARGE',
-    'debit' : 'DEBIT', 
+    'sepon' : 'SUBS_EPONTE',
+    'salini': 'SALINITE',
+    'poros' : 'POROSITE',
+    'satur' : 'SATURAT',
+    'salext': 'SALIN_EXT',
+    'conce' : 'CONCENTR',
+    'conex' : 'CONCEN_EXT',
+    'tempe' : 'TEMPERAT',
+    'temex' : 'TEMPER_EXT',
+    'mconc' : 'MASS_CONCEN',
+    'porfx' : 'PORO_FIX',
     'aff_r' : 'AFFLU_RIVI',
-    'flo_r' : 'DEBIT_RIVI',
-    'fon_r' : 'FOND_RIVI',
-    'hau_r' : 'HAUTEU_RIVI',
-    'lar_r' : 'LARG_RIVI',
-    'lon_r' : 'LONG_RIVI',
     'trc_r' : 'TRONC_RIVI',
+    'lon_r' : 'LONG_RIVI',
+    'lar_r' : 'LARG_RIVI',
+    'hau_r' : 'HAUTEU_RIVI',
+    'epai_r': 'EPAI_LIT_RIV',
+    'perm_r': 'PERM_LIT_RIVI',
     'qext_r': 'Q_EXTER_RIVI',
-    'd_ava' : 'DIRECT_AVAL',
-    # : 'Q_AMONT_RIVI',
-    # : 'EPAI_LIT_RIV',
-    # : 'RUGOS_RIVI',
-    # : 'PENTE_RIVI',
+    'flo_r' : 'DEBIT_RIVI',
+    'qamon' : 'Q_AMONT_RIVI',
+    'rug_r' : 'RUGOS_RIVI',
+    'pnt_r' : 'PENTE_RIVI',
+    'fon_r' : 'FOND_RIVI',
+    'conc_r': 'CONCEN_RIVI',
+    'cext_r': 'CONC_EXT_RIVI',
+    'qmas_r': 'QMASS_RIVI',
+    'mass_r': 'MASSE_RIVI',
+    'aff_d' : 'AFFLU_DRAIN',
+    'trc_d' : 'TRONC_DRAIN',
+    'lon_d' : 'LONG_DRAIN',
+    'z_dra' : 'ALTIT_DRAIN',
     'meteo' : 'ZONE_METEO',
-    'zonep' : 'ZONE_SOL',
-    'zgeom' : 'ZONE_GEOM',
-    'zoneg2': 'ZONE_2',
-    'zoneg3': 'ZONE_3',
-    'zonei' : 'ZONE_IRRIG'
+    'd_ava' : 'DIRECT_AVAL',
+    'v_rui' : 'VITESS_RUISS',
+    'ruiss' : 'RUISSEL',
+    'recha' : 'RECHARGE',
+    's_bvext' : 'SUPERF_BV_EXT',
+    'z_bvext' : 'NZON_RIV_EXT',
 }
 
-# legacy, switch to ArgumentParser
-# def print_help():
-    # msg = """ Usage: 
-    # `cleanmgrid PATH_TO_FILE`
-    
-    # PATH_TO_FILE can be a relative path, if it ends with '.rma' all grid file in rma project will be processed.
-
-    # Only works for marthe grid v9.0 (a check is performed and <v9 are skipped)
-    
-    # {}
-    # """.format(_copyleft)
-    # print(msg)
-
-# def parse_args():
-    # if len(sys.argv) < 2:
-        # print('cleanmgrid NO argument were passed')
-        # print_help()
-        # sys.exit(1)
-    # finputs  = sys.argv[1]
-    # if finputs in ['h', '-h', '--help']: # or not finputs.endswith('rma'):
-        # print_help()
-        # sys.exit(1)
-    # return finputs
-
 
 def parse_args():
     """ CLI program """
@@ -85,7 +79,7 @@ def parse_args():
     parser.add_argument('opt', metavar='PATH_TO_FILE', type=str, nargs=1, help='PATH_TO_FILE can be a relative path, if it ends with ".rma" all grid file in rma project will be processed.')
     parser.add_argument('--layer' , '-l', type=int, default=None, help='Number of layer. Only if PATH_TO_FILE is *NOT* a rma file. Otherwise, it will be parsed from Marthe\'s files.')
     parser.add_argument('--grid'  , '-g', type=int, default=None, help='Number of nested grid. Only if PATH_TO_FILE is *NOT* a rma file. Otherwise, it will be parsed from Marthe\'s files.')
-    parser.add_argument('--output', '-o', type=str, default=None, help='Output file. Only if PATH_TO_FILE is a single grid file and *NOT* a rma file. Otherwise, all files will be bakup and clean')
+    parser.add_argument('--output', '-o', type=str, default=None, help='Output file name (without subdir if any). Only if PATH_TO_FILE is a single grid file and *NOT* a rma file. Otherwise, all files will be bakup and clean')
     parser.add_argument(
         '--no_overwrite' , '-n',
         action="store_const", const=True, default=False,
@@ -101,12 +95,12 @@ def parse_args():
     return args
 
 
-
 def fread(file:str):
     with open(file, 'r', encoding='ISO-8859-1') as f:
         content = f.read()
     return content
 
+
 def scan_vers_semi(str_semi):
     if re.search(r'Marthe_Grid.*Version=9\.0', str_semi):
         version = 9.0
@@ -117,12 +111,14 @@ def scan_vers_semi(str_semi):
         version = 9999.
     return version
 
+
 def parse_geom(layer_str:str):
     layers = re.findall(r'Cou=\s*(\d+);', layer_str)
     ngrid  = re.findall(r'(\d+)=Nombre.*[g|G]igognes', layer_str)[0]
     # nlay = max(map(int, layers))
     return layers, ngrid
 
+
 def read_rma(frma):
     rma = fread(frma)
     files = re.finditer('(.*)  =\s+[A-z]', rma)
@@ -130,6 +126,7 @@ def read_rma(frma):
     files = [ x for x in files if len(x) > 0]
     return files
 
+
 def read_files_from_rma(frma):
     
     # root = os.path.dirname(frma)
@@ -150,14 +147,17 @@ def read_files_from_rma(frma):
     layers, ngrid = parse_geom(layer)
     return res, layers, ngrid
 
+
 def insert_str(string, index, insert_str):
     return string[:index] + insert_str + string[index:]
 
+
 def search_index(string, pattern):
     # get research start, match end, research pattern and result
     idx = [(m.start(0), m.end(1), m.group(0).replace(m.group(1), ''), m.group(1)) for m in re.finditer(pattern, string)]
     return idx
 
+
 def clean_grid_str(string: str, pattern: str, fillvalue: str|list, test=lambda x: len(x) < 1):
     """ Search for a pattern and replace with a unique or varying value
     if match satisfy a custom test
@@ -186,13 +186,13 @@ def clean_grid_str(string: str, pattern: str, fillvalue: str|list, test=lambda x
             new_str = re.sub(pattern, '{}{}'.format(matches[0][2], fillvalue), new_str)
     return new_str
 
+
 def write_res(string, fname):
     with open(f'{str(fname)}', 'w', encoding='ISO-8859-1') as f:
         f.write(string)
     return 0
 
 
-
 def main():
     """ CLEANMGRID """
     
diff --git a/src/gridmarthe/scripts/ncmart.py b/src/gridmarthe/scripts/ncmart.py
index b7d794e..e41b401 100644
--- a/src/gridmarthe/scripts/ncmart.py
+++ b/src/gridmarthe/scripts/ncmart.py
@@ -24,7 +24,7 @@ def parse_args():
     
     parser.add_argument('opt', metavar='grid timesteps', type=str, nargs='*', help='Paths to grid and timesteps files are expected') # nargs='+'
     parser.add_argument('--output'  , '-o', type=str, default=None, help='Output filename. Default is input.nc')
-    parser.add_argument('--variable', '-v', type=str, default=None, help='Variable (field) to read, default is None; i.e variable will be parsed from file and ONLY the first variable will be read.')
+    parser.add_argument('--variable', '-v', type=str, default=None, help='Variable (field) to read, default is None: i.e variable will be parsed from file and ONLY the first variable will be read. Pass \'all\' to get all variables.')
     parser.add_argument('--as2d'    , '-d', action="store_const", const=True, default=False, help='Store grid as 2D (or more), default is 1D for space dimension') #choices=('True','False'), dest='monnomdevariable'
     parser.add_argument('--xyfactor', '-x', type=float, default=1., help='Transformation factor for coordinates. Optionnal, default is 1 (no transformation).')
     # parser.add_argument('--show', type=str, default='', choices=('c', 'w'), help='Print licensing for warranty (w) and redistribution conditions (c)')
diff --git a/tests/data/craie_npc.hsubs b/tests/data/craie_npc.hsubs
new file mode 100644
index 0000000..8cf0cb6
--- /dev/null
+++ b/tests/data/craie_npc.hsubs
@@ -0,0 +1,2730 @@
+Marthe_Grid Version=9.0
+Title=                                                                       H_SUBSTRAT     1
+[Infos]
+Field=H_SUBSTRAT
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=1
+Max_Layer=10
+Nest_grid=0
+Max_NestG=0
+[Structure]
+X_Left_Corner=543500
+Y_Lower_Corner=2526100
+Ncolumn=387
+Nrows=304
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
+[Data]
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+Title=                                                                       H_SUBSTRAT     5
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+[Data_Descript]
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+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
+[Data]
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+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
+[Data]
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diff --git a/tests/data/craie_npc.topog b/tests/data/craie_npc.topog
new file mode 100644
index 0000000..18d9ccf
--- /dev/null
+++ b/tests/data/craie_npc.topog
@@ -0,0 +1,595 @@
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_TO   RH_TOPOGR       1
+[Infos]
+Field=H_TOPOGR
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=1
+Max_Layer=10
+Nest_grid=0
+Max_NestG=0
+[Structure]
+X_Left_Corner=543500
+Y_Lower_Corner=2526100
+Ncolumn=387
+Nrows=304
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+Title=Craie NPC                                                      H_TO   RH_TOPOGR       3
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+Title=Craie NPC                                                      H_TO   RH_TOPOGR       4
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+Title=Craie NPC                                                      H_TO   RH_TOPOGR       5
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_TO   RH_TOPOGR       6
+[Infos]
+Field=H_TOPOGR
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=6
+Max_Layer=10
+Nest_grid=0
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+[Constant_Data]
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_TO   RH_TOPOGR       7
+[Infos]
+Field=H_TOPOGR
+Type=
+Elem_Number=0
+Name=
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+[Constant_Data]
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_TO   RH_TOPOGR       8
+[Infos]
+Field=H_TOPOGR
+Type=
+Elem_Number=0
+Name=
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+[Constant_Data]
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_TO   RH_TOPOGR       9
+[Infos]
+Field=H_TOPOGR
+Type=
+Elem_Number=0
+Name=
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+[Constant_Data]
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_TO   RH_TOPOGR      10
+[Infos]
+Field=H_TOPOGR
+Type=
+Elem_Number=0
+Name=
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+Ncolumn=387
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+[Constant_Data]
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diff --git a/tests/data/hallue.permh b/tests/data/hallue.permh
new file mode 100644
index 0000000..4eccfb0
--- /dev/null
+++ b/tests/data/hallue.permh
@@ -0,0 +1,84 @@
+Marthe_Grid Version=9.0
+Title=Champ : Origine 'Travail'                                              PERMEAB        1
+[Infos]
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+Type=
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+Name=
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+43	2547.75	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3.20000E-04	3.20000E-04	3.20000E-04	3.20000E-04	8.00000E-04	2.40000E-03	3.54000E-03	2.36000E-03	8.00000E-04	6.22000E-04	6.22000E-04	6.22000E-04	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.5	
+44	2547.25	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3.20000E-04	3.20000E-04	3.20000E-04	8.00000E-04	8.00000E-04	3.38000E-03	3.56000E-03	8.00000E-04	8.00000E-04	8.00000E-04	6.22000E-04	8.00000E-04	2.40000E-03	3.46000E-03	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.5	
+45	2546.75	0	0	0	0	0	0	0	0	0	0	0	0	0	0	8.00000E-04	8.00000E-04	8.00000E-04	8.00000E-04	8.00000E-04	3.46000E-03	3.38000E-03	2.38000E-03	8.00000E-04	8.00000E-04	8.00000E-04	2.38000E-03	2.38000E-03	2.92000E-03	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.5	
+46	2546.25	0	0	0	0	0	0	0	0	0	0	0	0	0	0	8.00000E-04	8.00000E-04	8.00000E-04	8.00000E-04	8.00000E-04	8.00000E-04	3.46000E-03	3.46000E-03	8.00000E-04	8.00000E-04	5.36000E-03	5.80000E-03	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.5	
+47	2545.75	0	0	0	0	0	0	0	0	0	0	0	0	0	7.80000E-04	7.80000E-04	7.80000E-04	8.00000E-04	8.00000E-04	8.00000E-04	1.58000E-03	1.58000E-03	3.44000E-03	8.00000E-04	4.07000E-03	5.31160E-03	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.5	
+48	2545.25	0	0	0	0	0	0	0	0	0	0	0	0	0	3.20000E-04	8.00000E-04	8.00000E-04	8.00000E-04	8.00000E-04	8.00000E-04	8.00000E-04	8.00000E-04	3.46000E-03	3.58400E-03	2.90000E-03	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.5	
+49	2544.75	0	0	0	0	0	0	0	0	0	0	0	0	0	0	7.80000E-04	3.20000E-04	7.80000E-04	7.80000E-04	8.00000E-04	8.00000E-04	8.00000E-04	1.58000E-03	3.43480E-03	2.74000E-03	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.5	
+50	2544.25	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	8.00000E-04	3.20000E-04	3.20000E-04	8.00000E-04	8.00000E-04	1.44000E-03	2.89000E-03	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.5	
+51	2543.75	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	8.00000E-04	8.00000E-04	8.00000E-04	8.00000E-04	1.58000E-03	1.42200E-03	2.74000E-03	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.5	
+52	2543.25	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2.99160E-03	2.12400E-03	1.40400E-03	1.91880E-03	3.06720E-03	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.5	
+53	2542.75	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.5	
+54	2542.25	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.5	
+0	0	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	
+[End_Grid]
diff --git a/tests/test_geom.py b/tests/test_geom.py
new file mode 100644
index 0000000..58949a2
--- /dev/null
+++ b/tests/test_geom.py
@@ -0,0 +1,17 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import gridmarthe as gm
+
+# np.set_printoptions(threshold=np.inf)
+
+model_name = 'craie_npc'
+hsubs = gm.load_marthe_grid('../../mart_cabbalr_no_lay2_new_topo/{}.hsubs'.format(model_name))
+topo  = gm.load_marthe_grid('../../mart_cabbalr_no_lay2_new_topo/{}.topog'.format(model_name))
+permh = gm.load_marthe_grid('../../mart_cabbalr_no_lay2_new_topo/{}.permh'.format(model_name), varname='PERMEAB')
+mask = gm.get_mask_array(permh)['zone'].data
+
+geom = gm.compute_geometry(topo, hsubs, mask)
+geom = gm.compute_geometry(topo, hsubs)
+
+
diff --git a/tests/test_lecsem.py b/tests/test_lecsem.py
index 693d22a..e7556fc 100644
--- a/tests/test_lecsem.py
+++ b/tests/test_lecsem.py
@@ -8,6 +8,7 @@
 if __name__ == '__main__':
     import matplotlib.pyplot as plt
     
+    import os;os.chdir('./tests')
     print(gm.lecsem.__doc__)
     print(gm.lecsem.modgridmarthe.__doc__)
     
@@ -45,15 +46,15 @@
         masque = ds[varname.lower()].where(ds[varname.lower()] != 9999.).dropna(dim='zone') # drop nan_val
         ds = ds.sel(zone=masque['zone'])
 
-        if "z" in ds.keys():
-            first_lay = gm.get_min_layer(ds.isel(time=0))
-            gm.plot_outcrop(ds, engine='xr')
-            # plot_outcrop(ds, varname='permeab', nanval=0., engine='xr')
+        # if "z" in ds.keys():
+        #     first_lay = gm.get_min_layer(ds.isel(time=0))
+        #     gm.plot_outcrop(ds, engine='xr')
+        #     # plot_outcrop(ds, varname='permeab', nanval=0., engine='xr')
 
-            # dsbis = gm.assign_coords(ds)
-            # dsbis['charge'].plot.pcolormesh(x='x', y='y', row='z', col='time')
-            # Pour les gigognes, la grille irrégulière créée rend discontinu le graphique
-            # soit interpol, soit geopandas --> polyg.
-            # dsbis['charge'].sel(z=[6,9]).plot.pcolormesh(x='x', y='y', row='z', col='time')
-            plt.show()
-            plt.close()
+        #     # dsbis = gm.assign_coords(ds)
+        #     # dsbis['charge'].plot.pcolormesh(x='x', y='y', row='z', col='time')
+        #     # Pour les gigognes, la grille irrégulière créée rend discontinu le graphique
+        #     # soit interpol, soit geopandas --> polyg.
+        #     # dsbis['charge'].sel(z=[6,9]).plot.pcolormesh(x='x', y='y', row='z', col='time')
+        #     plt.show()
+        #     plt.close()
diff --git a/tests/test_reproj.py b/tests/test_reproj.py
new file mode 100644
index 0000000..54fabe2
--- /dev/null
+++ b/tests/test_reproj.py
@@ -0,0 +1,85 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import gridmarthe as gm
+import matplotlib.pyplot as plt
+import numpy as np
+
+from pyproj import Transformer
+
+import xarray as xr
+import rioxarray as rio
+# import rasterio
+
+def transf_proj(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154"):
+    """ Transform coordinates of a dataset using pyproj.
+    /!\ return more unique points than initial.
+    """
+    transformer = Transformer.from_crs(from_epsg, to_epsg, always_xy=True)
+    x_source, y_source = ds.x.data, ds.y.data
+    x_target, y_target = transformer.transform(x_source, y_source)
+    ds = ds.copy()
+    ds['x'].data = np.round(np.astype(x_target, np.float32))
+    ds['y'].data = np.round(np.astype(y_target, np.float32))
+    ds.attrs['projection'] = to_epsg
+    return ds
+
+def transf_proj2(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154"):
+    """ Transform coordinates of a dataset using pyproj.
+    /!\ recreate a regular grid in dest epsg
+    """
+    x, y = np.unique(ds['x'].data), np.unique(ds['y'].data)
+    nx, ny = len(x), len(y)
+    x0, y0 = np.nanmin(x), np.nanmin(y)
+    x1, y1 = np.nanmax(x), np.nanmax(y)
+    dx, dy = ds['dx'].data, ds['dy'].data
+
+    transformer = Transformer.from_crs(from_epsg, to_epsg, always_xy=True)
+    # Transformer uniquement les bornes de la grille
+    x0n, y0n = transformer.transform(x0, y0)
+    x1n, y1n = transformer.transform(x1, y1)
+    
+    # Recreate regular grid
+    x_reg = np.linspace(x0, x1, ds.x.size)
+    y_reg = np.linspace(y0, y1, ds.y.size)
+
+    ds = ds.copy()
+    ds['x'].data = np.round(np.astype(x_reg, np.float32), 2)
+    ds['y'].data = np.round(np.astype(y_reg, np.float32), 2)
+    ds.attrs['projection'] = to_epsg
+
+    # version meshgrid
+    xx, yy = np.meshgrid(x, y)
+    xx_transformed, yy_transformed = transformer.transform(xx, yy)
+
+    # Recréer la grille avec les nouvelles coordonnées
+    data_transformed = xr.DataArray(
+        gm.assign_coords(ds)['permeab'].data,
+        dims=["y", "x"],
+        coords={"y": yy_transformed[:, 0], "x": xx_transformed[0, :]}
+    )
+
+    return ds
+
+
+
+grid = gm.load_marthe_grid('./data/hallue.permh', xyfactor=1e3, drop_nan=True)
+grid = gm.load_marthe_grid('./data/Somme_V3_Surfex.permh', xyfactor=1e3, drop_nan=True, nanval=[-9999.,0.])
+grid = gm.load_marthe_grid('./data/craie_npc.permh', drop_nan=True)
+
+# grid_2154 = transf_proj2(grid, 'EPSG:27572', 'EPSG:2154')
+# len(np.unique(grid['x'].data))
+# len(np.unique(grid_2154['x'].data))
+
+g2d = gm.assign_coords(grid) #.where(grid['z']==6, drop=True)
+# rio
+g2d_2154 = g2d.rio.write_crs('EPSG:27572').isel(time=0).rio.reproject("EPSG:4326")
+# g2d_2154.to_netcdf('toto.nc', engine='h5netcdf')
+
+
+fig, ax = plt.subplots(ncols=2, figsize=(10,4))
+gm.plot_nested_grid(g2d.isel(time=0), var='permeab', ax=ax[0], add_colorbar=False)
+gm.plot_nested_grid(g2d_2154, var='permeab', ax=ax[1])
+plt.show()
+
+# np.unique(g2d_2154['dy'].data)
\ No newline at end of file
diff --git a/tests/test_surface_mask.py b/tests/test_surface_mask.py
index e0e5b8f..80abc28 100644
--- a/tests/test_surface_mask.py
+++ b/tests/test_surface_mask.py
@@ -1,7 +1,14 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
 # import modules
 import gridmarthe as gm
 import matplotlib.pyplot as plt
 
+
+import os;os.chdir('tests')
+
+
 grid = gm.load_marthe_grid('./data/craie_npc.permh', drop_nan=True)
 surf = gm.get_surface_layer(ds=grid)
 gdf = gm.to_geodataframe(surf)

From f37aef65dadbdc34c6b644be05e39c31985db073 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Wed, 26 Mar 2025 21:04:16 +0100
Subject: [PATCH 16/31] wip: add reproj func with rio, minor fixes in operasem

---
 src/gridmarthe/operasem/geometry.py | 21 ++++---
 src/gridmarthe/operasem/gis.py      | 93 +++++++++++++++++++++++++----
 src/gridmarthe/operasem/interp.py   |  4 ++
 3 files changed, 96 insertions(+), 22 deletions(-)

diff --git a/src/gridmarthe/operasem/geometry.py b/src/gridmarthe/operasem/geometry.py
index 07a34e5..79c4cc8 100644
--- a/src/gridmarthe/operasem/geometry.py
+++ b/src/gridmarthe/operasem/geometry.py
@@ -1,6 +1,9 @@
 #! /usr/bin/env python3
 # -*- coding: utf-8 -*-
 
+""" Module to manage geometry attributes of Marthe grids/domain
+"""
+
 import numpy as np
 import xarray as xr
 
@@ -91,21 +94,21 @@ def _get_depth(topo, h_upper):
 
 
 def compute_geometry(topo, hsubs, mask=None):
-    """_summary_
+    """ Compute geometry attributes of Marthe domain
 
     Parameters
     ----------
-    topo : _type_
-        _description_
-    hsubs : _type_
-        _description_
+    topo : xr.Dataset
+        Topgraphy of the domain
+    hsubs : xr.Dataset
+        altitude of all the lower boundary in the domain
     mask : numpy.array
         list of indices (`zone`) to keep, if None (default) not used.
 
     Returns
     -------
-    _type_
-        _description_
+    xr.Dataset
+        A new dataset with layer, depth, thickness, upper/lower altitude.
     """
 
     # compute elements of geometry
@@ -123,8 +126,8 @@ def compute_geometry(topo, hsubs, mask=None):
     # put values in xr.Dataset
     # ds = xr.combine_by_coords([ds, tmp])
     ds = xtopo.copy()
-    ds['h_substrat'] = (('time', 'zone'), tmp['h_substrat'].data)
-    ds['h_upper']    = (('time', 'zone'), tmp['h_upper'].data)
+    ds['z_lower']    = (('time', 'zone'), tmp['h_substrat'].data)
+    ds['z_upper']    = (('time', 'zone'), tmp['h_upper'].data)
     ds['thickness']  = (('time', 'zone'), thick)
     ds['depth']      = (('time', 'zone'), depth)
     return ds
diff --git a/src/gridmarthe/operasem/gis.py b/src/gridmarthe/operasem/gis.py
index 6b781cb..ec9badc 100644
--- a/src/gridmarthe/operasem/gis.py
+++ b/src/gridmarthe/operasem/gis.py
@@ -1,27 +1,20 @@
 #! /usr/bin/env python3
 # -*- coding: utf-8 -*-
 
+""" GIS utility for marthe grids
+"""
+
+
 import numpy as np
 
 from shapely.geometry import Polygon
 from pyproj import Transformer
 import geopandas as gpd
+import xarray as xr
 
 from ..utils import assign_coords
 
 
-def transf_proj(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154"):
-    """ Transform coordinates of a dataset using pyproj.
-    """
-    transformer = Transformer.from_crs(from_epsg, to_epsg, always_xy=True)
-    x_source, y_source = ds.x.data, ds.y.data
-    x_target, y_target = transformer.transform(x_source, y_source)
-    ds = ds.copy()
-    ds['x'].data, ds['y'].data = np.astype(x_target, np.float32), np.astype(y_target, np.float32)
-    ds.attrs['projection'] = to_epsg
-    return ds
-
-
 def _mk_cell_polygon(xleft, ylower, xright, yupper):
     return Polygon(
         (
@@ -33,6 +26,7 @@ def _mk_cell_polygon(xleft, ylower, xright, yupper):
         )
     )
 
+
 _polygonize = np.vectorize(_mk_cell_polygon)
 
 
@@ -48,7 +42,8 @@ def _build_polyg(ds):
 
 
 def to_geodataframe(ds, epsg='EPSG:27572', fmt='long'):
-    """ Convert marthegrid.Dataset to a geodataframe 
+    """ Convert marthegrid.Dataset to a geodataframe
+
     fmt must be long or wide, default is long
     """
     
@@ -78,12 +73,25 @@ def to_geodataframe(ds, epsg='EPSG:27572', fmt='long'):
     return gdf
 
 
+def _check_rioxarray():
+    try:
+        import rioxarray
+    except ModuleNotFoundError:
+        raise ModuleNotFoundError(
+            'rioxarray is not Found in python env.' + \
+            'Please install it or reinstall gridmarthe with optionnal dependancies: pip install gridmarthe[opt]'
+        )
+    return
+
+
 def clip_dataset(ds, gdf, crs=27572, engine='gdf'):
     """ Clip a xarray Dataset with a gpd.GeoDataFrame
+
     Needs rioxarray
     See: https://corteva.github.io/rioxarray/html/examples/clip_geom.html
     Todo: shapely version
     """
+    _check_rioxarray()
     shp = gdf.to_crs(crs)
     da  = assign_coords(ds.rio.write_crs("EPSG:{}".format(crs)))
     clipped_da = da.rio.clip(shp.geometry.values, shp.crs, drop=True)
@@ -93,6 +101,7 @@ def clip_dataset(ds, gdf, crs=27572, engine='gdf'):
 def subset_with_coords(da, dims=['x', 'y'], gdf=None, xmin=None, ymin=None, xmax=None, ymax=None):
     """
     subset DataArray or Dataset with gpd.GeoDataFrame or bounds
+
     TODO: real shp clip
     """
     if gdf is not None:
@@ -117,11 +126,69 @@ def subset_with_coords(da, dims=['x', 'y'], gdf=None, xmin=None, ymin=None, xmax
     return da.where(mask_lon & mask_lat, drop=True)
 
 
+def _transf_proj_xy(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154"):
+    """ Transform coordinates of a dataset using pyproj.
+
+    /!\ return more unique points than initial due to projection deformation
+    """
+    transformer = Transformer.from_crs(from_epsg, to_epsg, always_xy=True)
+    x_source, y_source = ds.x.data, ds.y.data
+    x_target, y_target = transformer.transform(x_source, y_source)
+    ds = ds.copy()
+    ds['x'].data, ds['y'].data = np.astype(x_target, np.float32), np.astype(y_target, np.float32)
+    ds.attrs['projection'] = to_epsg
+    return ds
+
+# def _transf_proj_regrid(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154"):
+    # """ Recreate a transformed grid based on dx,dy and x0,y0"
+    # transformer = Transformer.from_crs(from_epsg, to_epsg, always_xy=True)
+    # nx, ny = len(x), len(y)
+    # x0, y0 = np.nanmin(x), np.nanmin(y)
+    # x1, y1 = np.nanmax(x), np.nanmax(y)
+    # dx, dy = ds['dx'].data, ds['dy'].data
+    # return
+
+def _transf_proj_meshgrid(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154"):
+    """ Transform grid of a dataset using pyproj,
+    using meshgrid
+    """
+    x, y = np.unique(ds['x'].data), np.unique(ds['y'].data)
+    transformer = Transformer.from_crs(from_epsg, to_epsg, always_xy=True)
+    
+    xx, yy = np.meshgrid(x, y)
+    xx_transformed, yy_transformed = transformer.transform(xx, yy)
+    data_transformed = xr.DataArray(
+        assign_coords(ds)['permeab'].data,
+        dims=["y", "x"],
+        coords={"y": yy_transformed[:, 0], "x": xx_transformed[0, :]}
+    )
+    return data_transformed
+
+
+def transf_proj(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154", engine='rioxarray'):
+    """  Transform grid of a dataset using pyproj
+
+    engine: rioxarray, meshgrid, xy
+
+    Data (ds) needs to be a 2D array with xy as coords dimensions and time sliced.
+    If needed, use :py:func:`gridmarthe.assign_coords` first.
+    """ 
+    if engine == 'rioxarray':
+        _check_rioxarray()
+        ds_transf = ds.rio.write_crs(from_epsg).rio.reproject(to_epsg)
+    elif engine == 'meshgrid':
+        ds_transf = _transf_proj_meshgrid(ds, from_epsg, to_epsg)
+    elif engine == 'xy':
+        ds_transf = _transf_proj_xy(ds, from_epsg, to_epsg)
+    return ds_transf
+
 
 def write_raster_from_da(da, x_dim='x', y_dim='y', epsg=27572, fout='raster.tiff'):
     """ Write a xr.DataArray to a raster file
+    
     need xarray with rioxarray installed
     """
+    _check_rioxarray()
     da = da.copy().rio.write_crs('epsg:{}'.format(epsg))
     da = da.rio.set_spatial_dims(x_dim=x_dim, y_dim=y_dim)
     da.rio.to_raster(fout)
diff --git a/src/gridmarthe/operasem/interp.py b/src/gridmarthe/operasem/interp.py
index 0a556c6..50224dd 100644
--- a/src/gridmarthe/operasem/interp.py
+++ b/src/gridmarthe/operasem/interp.py
@@ -1,6 +1,10 @@
 #! /usr/bin/env python3
 # -*- coding: utf-8 -*-
 
+""" Interpolation and regridding module
+"""
+
+
 import numpy as np
 import xarray as xr #needs netcdf4, rioxarray
 

From 11701b827c2ac400a5ead0906eec6eeebde3b100 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Wed, 26 Mar 2025 21:12:01 +0100
Subject: [PATCH 17/31] clean docstring after rename func

---
 src/gridmarthe/operasem/geometry.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/gridmarthe/operasem/geometry.py b/src/gridmarthe/operasem/geometry.py
index 79c4cc8..30fe4f7 100644
--- a/src/gridmarthe/operasem/geometry.py
+++ b/src/gridmarthe/operasem/geometry.py
@@ -144,7 +144,7 @@ def get_surface_layer(ds, aquif_layers=None):
     
     Examples
     --------
-    >>>    mask = get_min_layer(ds, [6,8,9])
+    >>>    mask = get_surface_layer(ds, [6,8,9])
     >>>    ds_surf = ds.sel(zone=mask.zone.data)
         
     Parameters

From 30950750e05baadb40f35f13072da0ce92a8a17d Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Wed, 16 Apr 2025 17:48:13 +0200
Subject: [PATCH 18/31] fix build: revert to single meson.build file ; todo add
 subdir

---
 LICENSE => COPYING                |  0
 Makefile                          | 31 ++++++++++++----------
 README.md                         |  3 ++-
 meson.build                       | 44 +++++++++++++++++++++----------
 pyproject.toml                    |  2 +-
 src/gridmarthe/lecsem/meson.build | 27 -------------------
 tests/test_gridmarthe.py          |  5 ++--
 7 files changed, 52 insertions(+), 60 deletions(-)
 rename LICENSE => COPYING (100%)
 delete mode 100644 src/gridmarthe/lecsem/meson.build

diff --git a/LICENSE b/COPYING
similarity index 100%
rename from LICENSE
rename to COPYING
diff --git a/Makefile b/Makefile
index 7904bf5..31fb39f 100644
--- a/Makefile
+++ b/Makefile
@@ -48,7 +48,7 @@ COMPILE = CC=$(CC) FC=$(FC) FFLAGS="$(FFLAGS)" $(F2PY) -c $(F90FILES) -m lecsem
 
 .PHONY: all docs clean requirements wheel
 # all: clean install bakup_pyproj
-all: clean editm
+all: clean editable
 # only compile with f2py for develop purpose
 lib: lecsem.so
 
@@ -56,21 +56,20 @@ lib: lecsem.so
 doc:
 	cd docs; $(MAKE) html
 
-
-setuptools: pyproject.toml
-	cp pyproject.toml pyproject.bak ; sed -i '16s/# //' pyproject.toml ; sed -i '17s/^/# /' pyproject.toml
-    # change to setuptools for editable version
-
-bakup_pyproj: pyproject.toml
-	mv pyproject.bak pyproject.toml
-    # format pyproject.{toml,bak} non accepté par make ?
+# deprecated
+# setuptools: pyproject.toml
+# 	cp pyproject.toml pyproject.bak ; sed -i '16s/# //' pyproject.toml ; sed -i '17s/^/# /' pyproject.toml
+#     # change to setuptools for editable version
+# 
+# bakup_pyproj: pyproject.toml
+# 	mv pyproject.bak pyproject.toml
+#     # format pyproject.{toml,bak} non accepté par make ?
 
 requirements:
 	$(PY) -m pip install charset_normalizer numpy meson meson-python
 
-# install: requirements lecsem.pyf lecsem.so
-install: requirements lecsem.so setuptools bakup_pyproj
-	$(PY) -m pip install $(PIPFLAGS) . -vvv
+#install: requirements lecsem.so setuptools bakup_pyproj
+#	$(PY) -m pip install $(PIPFLAGS) . -vvv
 
 lecsem.pyf:
 	cd $(F90SRCDIR); echo "******** Generating signature ********"; \
@@ -85,13 +84,17 @@ lecsem.so:
 	# FC="$(FC)" FFLAGS="$(FFLAGS)" python -m numpy.f2py -c lecsem.pyf lecsem.f90 edsemigl.f90 scan_grid.f90 -m lecsem --backend=meson --lower
 
 # meson editable for test
-editm: requirements
+editable: requirements
 	$(PY) -m pip install --no-build-isolation --config-settings=editable-verbose=true --editable . -vvv
     # meson version of editable - for future replacement of setuptools
 
 wheel:
 	$(PY) -m pip install build
-	$(PY) -m build .
+	$(PY) -m build -w
+
+sdist:
+	$(PY) -m pip install build
+	$(PY) -m build -s
 
 clean:
 	cd $(F90SRCDIR); \
diff --git a/README.md b/README.md
index b913d5c..f4e5296 100644
--- a/README.md
+++ b/README.md
@@ -132,7 +132,8 @@ This program is free software and released under the terms of the
 
 
 ## Authors and acknowledgment
-J.P. Vergnes and A. Manlay
+
+A. Manlay and J.P. Vergnes, (c) BRGM
 
 
 ## References
diff --git a/meson.build b/meson.build
index 022997a..0e63f6f 100644
--- a/meson.build
+++ b/meson.build
@@ -7,7 +7,7 @@
 project('gridmarthe', ['fortran', 'c'],
   version : run_command('meson_get_version.py').stdout().strip(),
   license: 'GNU/GPL-V3',
-  meson_version: '>=0.64.0',
+  meson_version: '>=1.1.0',
   default_options : [
     'warning_level=1',
     'buildtype=release'
@@ -15,8 +15,15 @@ project('gridmarthe', ['fortran', 'c'],
 )
 
 # add_languages('fortran')
+lecsem_sources = files([
+    'src/gridmarthe/lecsem/lecsem.f90',
+    'src/gridmarthe/lecsem/edsemigl.f90',
+    'src/gridmarthe/lecsem/scan_grid.f90'
+])
+lecsem_install_dir = 'gridmarthe/lecsem/'  # in python_install_dir
 
-# ----- Get compiler and build options ------ #
+
+# ------ Get compiler and build options ------ #
 fc = meson.get_compiler('fortran')
 cc = meson.get_compiler('c')
 deps = []
@@ -24,7 +31,7 @@ inc_dir = []
 
 # Options de compilation Fortran
 fargs = []  # compile args
-largs = []  # arg de link
+largs = []  # link args
 
 if fc.get_id() == 'gcc'
   
@@ -80,12 +87,6 @@ incdir_numpy = run_command(py,
   check : true
 ).stdout().strip()
 
-# incdir_f2py = run_command(py,
-#     ['-c', 'import os; os.chdir(".."); import numpy.f2py; print(numpy.f2py.get_include())'],
-#     check : true
-# ).stdout().strip()
-
-# inc_np = include_directories(incdir_numpy, incdir_f2py)
 inc_np = include_directories(incdir_numpy)
 np_dep = declare_dependency(include_directories: inc_np)
 
@@ -95,10 +96,25 @@ fortranobject_c = incdir_f2py / 'fortranobject.c'
 
 inc_dir += [inc_np,inc_f2py]
 
+# ---- Building interface for LECSEM ---- #
+# subdir('src/gridmarthe/lecsem') # not functionnal yet, keep it here for now
+lecsem_interface = custom_target('lecsemmodule.c',
+  input : lecsem_sources,
+  output : ['lecsemmodule.c', 'lecsem-f2pywrappers.f', 'lecsem-f2pywrappers2.f90'],
+  command : [py, '-m', 'numpy.f2py', '@INPUT@', '-m', 'lecsem', '--lower']
+)
+
+py.extension_module('lecsem',
+  [
+    lecsem_sources,
+    lecsem_interface,
+    fortranobject_c
+  ],
+  include_directories: inc_dir,
+  dependencies: deps,
+  install: true,
+  install_dir: python_install_dir / lecsem_install_dir,
+)
 
-# --------   Compile sources   --------- #
-subdir('src/gridmarthe/lecsem')
-# subdir('src/gridmarthe/rivermod/draindir')
-# subdir('src/gridmarthe/rivermod/rivernet')
-# -------- Install pypackage ----------- #
+# --------- Install pypackage ----------- #
 install_subdir('src/gridmarthe', install_dir : python_install_dir)
diff --git a/pyproject.toml b/pyproject.toml
index 9185f89..931de9e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -26,7 +26,7 @@ authors = [
 
 description = "python package to read/write/manage Marthe Grids"
 readme = {file = "README.md", content-type = "text/markdown"}   
-license = {file = "LICENSE"}
+license = {file = "COPYING"}
 
 classifiers = [
     "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)",
diff --git a/src/gridmarthe/lecsem/meson.build b/src/gridmarthe/lecsem/meson.build
deleted file mode 100644
index 037b081..0000000
--- a/src/gridmarthe/lecsem/meson.build
+++ /dev/null
@@ -1,27 +0,0 @@
-lecsem_sources = files([
-    './lecsem.f90',
-    './edsemigl.f90',
-    './scan_grid.f90'
-])
-lecsem_install_dir = 'gridmarthe/lecsem/'  # in python_install_dir
-
-# -------- Building interface ----------- #
-lecsem_interface = custom_target('lecsemmodule.c',
-  input : lecsem_sources,
-  output : ['lecsemmodule.c', 'lecsem-f2pywrappers.f', 'lecsem-f2pywrappers2.f90'],
-  command : [py, '-m', 'numpy.f2py', '@INPUT@', '-m', 'lecsem', '--lower'],
-  #install_dir: python_install_dir / lecsem_install_dir
-)
-
-py.extension_module('lecsem',
-  [
-    lecsem_sources,
-    lecsem_interface,
-    fortranobject_c
-  ],
-  include_directories: inc_dir,
-  dependencies: deps,
-  install: true,
-  install_dir: python_install_dir / lecsem_install_dir,
-  # fortran_args : fortran_args
-)
diff --git a/tests/test_gridmarthe.py b/tests/test_gridmarthe.py
index d5ff0ad..f459f04 100644
--- a/tests/test_gridmarthe.py
+++ b/tests/test_gridmarthe.py
@@ -4,9 +4,8 @@
 inputs = './data/craie_npc.permh', "PERMEAB" # ajouter tests/data ici pour conda-forge ?
 
 
-toto = gm.load_marthe_grid(*inputs)
-# toto = gm.load_marthe_grid(*inputs, dropna=True)
-# toto = gm.load_marthe_grid(*inputs, dropna=True, nanval=0.)
+toto = gm.load_marthe_grid(*inputs, drop_nan=True)
+# toto = gm.load_marthe_grid(*inputs, drop_nan=True, nanval=0.)
 # toto = gm.load_marthe_grid(inputs[0], varname=None)
 # toto = gm.load_marthe_grid(inputs[0], varname='all')
 # toto = gm.load_marthe_grid(*inputs, keepligcol=True)

From 2821b8a0264851bc765b1a35755aa42af3cbe3d3 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Wed, 7 May 2025 11:30:41 +0200
Subject: [PATCH 19/31] change: reset zone if drop_nan option is used when
 loading a marthe grid file, improve aqui-fr compatibility

---
 src/gridmarthe/gridmarthe.py | 20 +++++++++++++++-----
 1 file changed, 15 insertions(+), 5 deletions(-)

diff --git a/src/gridmarthe/gridmarthe.py b/src/gridmarthe/gridmarthe.py
index 179cf11..68c4e88 100644
--- a/src/gridmarthe/gridmarthe.py
+++ b/src/gridmarthe/gridmarthe.py
@@ -303,7 +303,7 @@ def load_marthe_grid(
     xcols, dxlus = _transform_xcoords(zxcol, zylig, zdxlu, nlayer=dims[0][-1], factor=xyfactor)
     yligs, dylus = _transform_ycoords(zxcol, zylig, zdylu, nlayer=dims[0][-1], factor=xyfactor)
     
-    if varname == '': varname = 'variable' # security if force mode
+    if varname == '': varname = 'variable'  # security if force mode
     vattrs = VARS_ATTRS.get(varname.lower(), {})
     vattrs.update(var_attrs)
     dic_data = {
@@ -314,6 +314,10 @@ def load_marthe_grid(
         'dy' : ("zone", dylus)
     }
     
+    # dic_coords = {
+    #
+    # }
+    
     if keepligcol:
         if is_nested:
             add_id_grid = True # force to add id_grid if nested grid
@@ -348,10 +352,6 @@ def load_marthe_grid(
         coords={
             'time': dates,
             'zone': np.arange(1, zvar.shape[1] + 1, dtype=np.int32),
-            # 'xc': (['zone'], xcols), # TODO coordinates directly as coords depending on dims ?
-            # 'yc': (['zone'], yligs),
-            # 'domain_size': dims, # add non dimension coordinate for info
-            # 'domain_origin': [(x0, y0) for igig in grids], # add non dimension coordinate for info
         },
         attrs={
             **_parse_attrs(title, dims, xyfactor, dates, is_nested, dxlus, dylus, xcols, yligs),
@@ -359,12 +359,22 @@ def load_marthe_grid(
         }
     )
     
+    # add non-dimensionnal coordinates
+    # 'xc': (['zone'], xcols), # TODO coordinates directly as coords depending on dims ?
+    # 'yc': (['zone'], yligs),
+    # 'domain_size': dims, # add non dimension coordinate for info
+    # 'domain_origin': [(x0, y0) for igig in grids], # add non dimension coordinate for info
+    # ds = ds.assign_coords(
+        # dic_coords
+    # )
+    
     if drop_nan:
         if nanval is None:
             nanval = vattrs.get('missing_value', 9999.) # if no  user defined nanval, try to get corresponding val in dict then 9999. if not present
         if (varname == 'permeab' or filename.endswith("permh")) and is_nested:
             nanval = [nanval, -9999.]
         ds = dropna(ds, varname, nanval)
+        ds['zone'] = np.arange(1, np.size(ds['zone'].data) + 1, dtype=np.int32)  # rearange zone
         
     # FIXME better, prevent bug at write : https://github.com/pydata/xarray/issues/7722 // https://stackoverflow.com/questions/65019301/variable-has-conflicting-fillvalue-and-missing-value-cannot-encode-data-when
     # del ds[varname.lower()].encoding['missing_value']

From cb870f06b1a6a174ee8a44f091c8e9daad1a6a66 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Wed, 18 Jun 2025 09:43:19 +0200
Subject: [PATCH 20/31] fix: wrong nan value for subsurface flows

---
 src/gridmarthe/gridmarthe.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/gridmarthe/gridmarthe.py b/src/gridmarthe/gridmarthe.py
index 68c4e88..2bf573b 100644
--- a/src/gridmarthe/gridmarthe.py
+++ b/src/gridmarthe/gridmarthe.py
@@ -50,7 +50,7 @@
         'varname': 'CHARGE',
         'units': 'm',
         'missing_value': 9999.,
-        'standard_name': 'water_table_level',#depth
+        'standard_name': 'water_table_level',
         'long_name':
         'groundwater head'
     },
@@ -64,7 +64,7 @@
     'debit'  : {
         'varname': 'DEBIT',
         'units': 'm3/s',
-        'missing_value': 9999.,
+        'missing_value': 0.,
         'standard_name': '',
         'long_name': 'flow'
     },
@@ -370,8 +370,8 @@ def load_marthe_grid(
     
     if drop_nan:
         if nanval is None:
-            nanval = vattrs.get('missing_value', 9999.) # if no  user defined nanval, try to get corresponding val in dict then 9999. if not present
-        if (varname == 'permeab' or filename.endswith("permh")) and is_nested:
+            nanval = vattrs.get('missing_value', 9999.)  # if no  user defined nanval, try to get corresponding val in dict then 9999. if not present
+        if (varname.lower() == 'permeab' or filename.endswith("permh")) and is_nested:
             nanval = [nanval, -9999.]
         ds = dropna(ds, varname, nanval)
         ds['zone'] = np.arange(1, np.size(ds['zone'].data) + 1, dtype=np.int32)  # rearange zone

From 0fe87061535a0efa9d668b062cf24bef3df47ea4 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Wed, 18 Jun 2025 10:43:52 +0200
Subject: [PATCH 21/31] add: martshp script + minor modifs (doc, style)

---
 changelog.rst                              | 14 ++++
 meson.build                                |  2 +-
 pyproject.toml                             |  2 +
 src/gridmarthe/__init__.py                 |  2 +-
 src/gridmarthe/lecsem/_parse_gridmarthe.py |  8 +-
 src/gridmarthe/operasem/geometry.py        | 43 ++++++++--
 src/gridmarthe/plot.py                     |  2 +
 src/gridmarthe/scripts/__init__.py         |  2 +-
 src/gridmarthe/scripts/martshp.py          | 91 ++++++++++++++++++++++
 9 files changed, 151 insertions(+), 15 deletions(-)
 create mode 100644 src/gridmarthe/scripts/martshp.py

diff --git a/changelog.rst b/changelog.rst
index 2e81b82..0f7c711 100644
--- a/changelog.rst
+++ b/changelog.rst
@@ -1,3 +1,16 @@
+v0.1.3
+------
+
+Released on 2025-XX-XX
+
+* add geometry functions (get_mask_array, compute_geometry)
+* add reprojection functions (still experimental)
+* add `martshp` script to easily convert a marthe grid file into a shp/gpkg file in command line
+* code refactoring (lecsem module and global organization)
+* minor fixes in plot method
+* change: zone index is reset when the `drop_nan` option is used in `load_grid_marthe()`
+
+
 v0.1.2
 ------
 
@@ -7,6 +20,7 @@ Released on 2025-01-09
 * fix scripts 'ncmart' and 'cleanmgrid' paths
 * update write method
 
+
 v0.1.1
 ------
 
diff --git a/meson.build b/meson.build
index 0e63f6f..9e980f6 100644
--- a/meson.build
+++ b/meson.build
@@ -83,7 +83,7 @@ python_install_dir = py.get_install_dir()
 deps += [py_dep]
 
 incdir_numpy = run_command(py,
-  ['-c', 'import os; os.chdir(".."); import numpy; print(numpy.get_include())'],
+  ['-c', 'import os; import numpy; print(os.path.relpath(numpy.get_include()))'],
   check : true
 ).stdout().strip()
 
diff --git a/pyproject.toml b/pyproject.toml
index 931de9e..6effedb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -34,6 +34,7 @@ classifiers = [
     "Programming Language :: Python :: 3 :: Only",
     "Programming Language :: Python :: Implementation :: CPython",
     "Programming Language :: Fortran",
+    "Operating System :: Unix",
     "Operating System :: POSIX :: Linux",
     "Operating System :: MacOS",
     "Operating System :: Microsoft :: Windows",
@@ -67,6 +68,7 @@ doc = ['sphinx', 'pydata_sphinx_theme', 'sphinx-copybutton', 'sphinx_design', 's
 [project.scripts]
 ncmart = "gridmarthe:scripts.ncmart.main"
 cleanmgrid = "gridmarthe:scripts.cleanmgrid.main"
+martshp = "gridmarthe:scripts.martshp.main"
 
 
 [project.urls]
diff --git a/src/gridmarthe/__init__.py b/src/gridmarthe/__init__.py
index 9264373..47d7b5f 100644
--- a/src/gridmarthe/__init__.py
+++ b/src/gridmarthe/__init__.py
@@ -79,4 +79,4 @@ def subset_coords(self, dims=['x', 'y'], gdf=None, xmin=None, ymin=None, xmax=No
     def dropna(self, varname='charge', nanval=9999.):
         ds = self.obj.copy()
         masque = ds[varname].where(ds[varname] != nanval).dropna(dim='zone') # drop nanval
-        return ds.sel(zone=masque['zone'])
\ No newline at end of file
+        return ds.sel(zone=masque['zone'])
diff --git a/src/gridmarthe/lecsem/_parse_gridmarthe.py b/src/gridmarthe/lecsem/_parse_gridmarthe.py
index 035ea0c..e20fe4f 100644
--- a/src/gridmarthe/lecsem/_parse_gridmarthe.py
+++ b/src/gridmarthe/lecsem/_parse_gridmarthe.py
@@ -10,9 +10,9 @@
 
 def scan_var(xfile):
     """ List all variables stored in a Marthe grid file """
-    var = modgridmarthe.scan_typevar(xfile) # get a list of unique type_var that are in xfile
-    var = np.char.strip(np.char.decode(var, 'ISO-8859-1')) # decode byte array provided by f2py
-    var = var[var != ''] # get rid of empty element provided by fortran code
+    var = modgridmarthe.scan_typevar(xfile)  # get a list of unique type_var that are in xfile
+    var = np.char.strip(np.char.decode(var, 'ISO-8859-1'))  # decode byte array provided by f2py
+    var = var[var != '']  # get rid of empty element provided by fortran code
     return var
 
 
@@ -163,6 +163,7 @@ def _parse_dims_from_xr_attrs(str_dims):
     else:
         return [list(map(int, x.split(' '))) for x in str_dims.strip('x, y, z [grids]: ').split('; ')]
 
+
 # def sort_data(ds):
     # TODO:
     # s'assurer de l'ordre si ds a été retravaillé :
@@ -179,7 +180,6 @@ def _extract_zvar_from_ds(ds, varname):
     zylig   = ds.y.data
     zdxlu   = ds.dx.data
     zdylu   = ds.dy.data
-    # from pymarthe : dx, dy = map(abs, map(np.gradient, [xcc,ycc])) # Using the absolute gradient TODO
     ztitle  = ds.attrs.get('title')
     izdates = _datetime64_to_float(zdates)
 
diff --git a/src/gridmarthe/operasem/geometry.py b/src/gridmarthe/operasem/geometry.py
index 30fe4f7..7aa85cf 100644
--- a/src/gridmarthe/operasem/geometry.py
+++ b/src/gridmarthe/operasem/geometry.py
@@ -11,26 +11,53 @@
 from ..utils import _nearest_node, subset
 
 
-def get_mask_array(ds, varname: str='permeab', nanval: list=[-9999., 0.]):
+def _get_mask_array(ds, varname: str='permeab', nanval: list=[-9999., 0.]):
     """ Get mask array of active domain, from permh file (hydraulic conductivity)
     """
     return ds.where(~ds[varname].isin(nanval), drop=True)
 
 
-def get_active_mask(ds, varname: str='permeab', nanval: list=[-9999., 0.], fileout=None):
+def get_active_mask(ds, varname: str='permeab', nanval: list=[-9999., 0.], as_array=False, shp_file=None):
     """ Filter dataset on non-nan values, and dissolve results to get a mask shape 
     input ds should be the permh dataset (read from permh file, ie Horizontal hydraulic conductivity)
+    
+    Parameters
+    ----------
+    
+    ds : xr.Dataset
+    
+    varname: str, optional
+        default is 'permeab'
+    
+    nanval: float or list, optional.
+        default are 'permeab' nan values : 0,-9999.
+    
+    as_array: bool, optional.
+        default is False. Option to get result as a xr.Dataset and not geodataframe.
+        
+    shp_file: str, optional.
+        if set (and not `as_array`), used to stored result in a file.
+    
+    Returns
+    -------
+    either a xr.Dataset filter to mask array or a
+    gpd.GeoDataFrame with active domain.
     """
-    mask = get_mask_array(ds, varname, nanval)
+    mask = _get_mask_array(ds, varname, nanval)
     mask = ds.sel(zone=mask['zone'])
-    gdf  = to_geodataframe(mask)
-    gdf  = gdf.dissolve()
-    if fileout is not None:
-        gdf.to_file(fileout)
+    if not as_array:
+        gdf  = to_geodataframe(mask)
+        gdf  = gdf.dissolve()
+        if shp_file is not None:
+            gdf.to_file(shp_file)
     return gdf
 
 
 def _get_true_topo(topo, key='h_topogr'):
+    # in Marthe, topography is stored in the first layer,
+    # for the whole domain, avoiding duplicates data.
+    # Here, this function tile topography to all layers
+    # to allow vectorized operations.
     ds = topo.copy()
     if 'z' not in list(topo.dims) + list(topo.keys()):
         zdim = 1
@@ -99,7 +126,7 @@ def compute_geometry(topo, hsubs, mask=None):
     Parameters
     ----------
     topo : xr.Dataset
-        Topgraphy of the domain
+        Topgraphy of the domain (stored in the first layer, in Marthe Conventions).
     hsubs : xr.Dataset
         altitude of all the lower boundary in the domain
     mask : numpy.array
diff --git a/src/gridmarthe/plot.py b/src/gridmarthe/plot.py
index ebc90a0..d76d1af 100644
--- a/src/gridmarthe/plot.py
+++ b/src/gridmarthe/plot.py
@@ -50,6 +50,8 @@ def plot_nested_grid(da, ax=None, var='charge', **kwargs):
     
     vmin, vmax = da[var].min(), da[var].max()
     vmin, vmax = kwargs.pop('vmin', vmin), kwargs.pop('vmax', vmax) # replace with user defined, if defined
+    if kwargs.get('norm') is not None:
+        vmin, vmax = None, None  # if user set a norm, vmin and vmax are not allowed
     cbar_kwargs = kwargs.pop('cbar_kwargs', {})
     
     # split grids
diff --git a/src/gridmarthe/scripts/__init__.py b/src/gridmarthe/scripts/__init__.py
index 72081ec..de72657 100644
--- a/src/gridmarthe/scripts/__init__.py
+++ b/src/gridmarthe/scripts/__init__.py
@@ -1 +1 @@
-from . import ncmart, cleanmgrid
+from . import ncmart, cleanmgrid, martshp
diff --git a/src/gridmarthe/scripts/martshp.py b/src/gridmarthe/scripts/martshp.py
new file mode 100644
index 0000000..e904c61
--- /dev/null
+++ b/src/gridmarthe/scripts/martshp.py
@@ -0,0 +1,91 @@
+#!/usr/bin/env python3
+# -*- coding:utf-8 -*-
+
+#    gridmarthe is a python library to manage grid files for 
+#    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
+#    Copyright (C) 2024  BRGM
+#    Released under the GNU/GPL-v3 (or later) license <https://www.gnu.org/licenses/gpl-3.0.txt>
+
+import os, sys, textwrap
+from argparse import ArgumentParser, RawDescriptionHelpFormatter
+import gridmarthe as gm
+from gridmarthe.__version__ import _copyleft
+
+
+def parse_args():
+    """ CLI program """
+    parser = ArgumentParser(
+        prog='martshp',
+        formatter_class=RawDescriptionHelpFormatter,
+        description="Convert a Marthe GridFile to shapefile format.",
+        epilog=textwrap.dedent(_copyleft)
+    )
+    
+    parser.add_argument('opt', metavar='grid timesteps', type=str, nargs='*', help='Paths to grid [and timesteps if result] files are expected') # nargs='+'
+    parser.add_argument('--output'  , '-o', type=str, default=None, help='Output filename. Default is input.nc')
+    parser.add_argument('--variable', '-v', type=str, default=None, help='Variable (field) to read, default is None: i.e variable will be parsed from file and ONLY the first variable will be read. Pass \'all\' to get all variables.')
+    parser.add_argument('--xyfactor', '-x', type=float, default=1., help='Transformation factor for coordinates. Optionnal, default is 1 (no transformation).')
+    parser.add_argument('--gpkg', '-g', action="store_const", const=True, default=False, help='Use GPKG format instead of shapefile')
+    parser.add_argument('--mask', '-m', action="store_const", const=True, default=False, help='Only get a mask of active domain')
+    parser.add_argument('--version', '-V', action="store_const", const=True, default=False, help='Show version and exit')
+    parser.add_argument('--wide_fmt', '-w', action="store_const", const=True, default=False, help='Use wide format (columns) for time')
+    
+    args = parser.parse_args()
+    
+    if args.version:
+        print('gridmarthe {}'.format(gm.__version__))
+        print(_copyleft)
+        sys.exit(0)
+    
+    if args.output is not None:
+        dirout = os.path.dirname(args.output)
+        if dirout != '':
+            os.makedirs(dirout, exist_ok=True)
+    else:
+        fname, ext = os.path.splitext(args.opt[0])
+        args.output = '{}.shp'.format(fname)
+    
+    if args.gpkg:
+        fname, ext = os.path.splitext(args.output)
+        args.output = '{}.gpkg'.format(fname)
+    
+    if os.path.exists(args.output):
+        os.remove(args.output)
+
+    if args.variable is not None:
+        args.variable = args.variable.upper()
+
+    return args
+
+
+def main():
+    """
+    Convert a Marthe Grid file to NetCDF format, using gridmarthe pymodule
+    """
+    args   = parse_args()
+    fpastp = args.opt[1] if len(args.opt) > 1 else None
+    
+    ds = gm.load_marthe_grid(
+        args.opt[0],
+        fpastp=fpastp,
+        drop_nan=True,
+        varname=args.variable,
+        xyfactor=args.xyfactor
+    )
+    
+    if args.mask:
+        mask = gm.get_active_mask(ds)
+        mask.to_file(args.output)
+        sys.exit(0)
+
+    #ds = gm.assign_coords(ds)
+    gdf = gm.to_geodataframe(ds, fmt='long' if not args.wide_fmt else 'wide')
+    gdf.to_file(args.output)
+    return 0
+    
+    
+if __name__ == "__main__":
+    
+    status = main()
+    sys.exit(status)
+   

From f21ee75ef0db5ac51e6b26a0ceed7c4d9b2cb7fc Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Wed, 18 Jun 2025 11:22:06 +0200
Subject: [PATCH 22/31] fix: bug with list of nan values in load_grid_marthe()

---
 src/gridmarthe/gridmarthe.py | 14 +++++++++++---
 src/gridmarthe/utils.py      |  4 +++-
 2 files changed, 14 insertions(+), 4 deletions(-)

diff --git a/src/gridmarthe/gridmarthe.py b/src/gridmarthe/gridmarthe.py
index 2bf573b..34c090c 100644
--- a/src/gridmarthe/gridmarthe.py
+++ b/src/gridmarthe/gridmarthe.py
@@ -165,7 +165,7 @@ def load_marthe_grid(
     The gridfile is read as a sequence: the variable for all layer
     for main grid, then all layer for nested grids, is stored in
     a 1D vector for every timestep. A single spatial identifier
-    `zone` is used to map spatial coordinates.
+    ``zone`` is used to map spatial coordinates.
 
     Before plot operations, user can assign coordinates (set x,y
     as dimension coordinates and drop zone) to get 2-D arrays (or
@@ -179,7 +179,7 @@ def load_marthe_grid(
             A path to marthegrid file (*.permh, *.out, etc.)
         
         varname : str, Optionnal
-            variable to access in martgrid file, e.g `CHARGE` for groundwater head. See marthegrid file content.
+            variable to access in martgrid file, e.g ``CHARGE`` for groundwater head. See marthegrid file content.
             if None  is passed (default), function will scan all varnames in filename and keep first only
             if 'all' is passed,  function will scan all varnames in filename and keep all. 
             All datavars are added to dataset, using recursive call to func
@@ -371,8 +371,16 @@ def load_marthe_grid(
     if drop_nan:
         if nanval is None:
             nanval = vattrs.get('missing_value', 9999.)  # if no  user defined nanval, try to get corresponding val in dict then 9999. if not present
+        
+        if not isinstance(nanval, (list, tuple)):
+            nanval = [nanval]
+        elif isinstance(nanval, tuple):
+            nanval = list(nanval)
+        
         if (varname.lower() == 'permeab' or filename.endswith("permh")) and is_nested:
-            nanval = [nanval, -9999.]
+            if -9999. not in nanval:
+                nanval += [-9999.]
+        
         ds = dropna(ds, varname, nanval)
         ds['zone'] = np.arange(1, np.size(ds['zone'].data) + 1, dtype=np.int32)  # rearange zone
         
diff --git a/src/gridmarthe/utils.py b/src/gridmarthe/utils.py
index 58135d3..144d4d2 100644
--- a/src/gridmarthe/utils.py
+++ b/src/gridmarthe/utils.py
@@ -92,7 +92,9 @@ def dropna(ds, varname: str, nanval: Union[list, float]):
     """
     if isinstance(nanval, (float, int, str)):
         nanval = [nanval]
-    nanval = nanval + [1e+20]
+    elif isinstance(nanval, tuple):
+        nanval = list(nanval)  # convert to list to be mutated
+    nanval += [1.e+20]
     mask = ds[varname.lower()].where(~ds[varname.lower()].isin(nanval)).dropna(dim='zone') # drop nanval
     ds_no_nan = ds.sel(zone=mask['zone'])
     return ds_no_nan

From 24a5915f40676edbea080d356ff7e507986a0f06 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Wed, 18 Jun 2025 13:46:35 +0200
Subject: [PATCH 23/31] doc: general update for sphinx doc and py docstrings

---
 docs/source/_static/custom.css                |  87 ++++
 docs/source/_static/switcher.json             |  12 +
 docs/source/_templates/brgm-logo-en.html      |   4 +
 docs/source/conf.py                           |  50 +-
 docs/source/index.rst                         |   1 +
 docs/source/references.rst                    |   5 +
 docs/source/switcher.json                     |   7 -
 docs/source/user_guide/example/gis.ipynb      |  89 ++++
 .../user_guide/example/treatments.ipynb       | 473 +-----------------
 docs/source/user_guide/index.rst              |   7 +-
 src/gridmarthe/__init__.py                    |   6 +-
 src/gridmarthe/gridmarthe.py                  |  12 +-
 src/gridmarthe/operasem/gis.py                |  82 ++-
 13 files changed, 327 insertions(+), 508 deletions(-)
 create mode 100644 docs/source/_static/custom.css
 create mode 100644 docs/source/_static/switcher.json
 create mode 100644 docs/source/_templates/brgm-logo-en.html
 delete mode 100644 docs/source/switcher.json
 create mode 100644 docs/source/user_guide/example/gis.ipynb

diff --git a/docs/source/_static/custom.css b/docs/source/_static/custom.css
new file mode 100644
index 0000000..a3a122a
--- /dev/null
+++ b/docs/source/_static/custom.css
@@ -0,0 +1,87 @@
+/* Main index page overview cards */
+.sd-card-img-top {
+  width: 33% !important;
+  display: block;
+  margin-left: auto;
+  margin-right: auto;
+  margin-top: 10px;
+}
+
+/* customise nbsphinx ----------------------------------------------- */
+div.nbinput.container div.prompt pre,
+div.nbinput.container div.prompt pre > code {
+  color: var(--pst-color-primary);
+}
+
+div.nboutput.container div.prompt pre,
+div.nboutput.container div.prompt pre > code {
+  color: var(--pst-color-secondary);
+}
+
+div.nbinput.container div.input_area {
+    border: 1px solid var(--pst-color-border);
+}
+
+div.rendered_html table {
+    color: var(--pst-color-text-base);
+}
+
+div.rendered_html thead {
+    border-bottom: 1px solid var(--pst-color-border);
+}
+
+div.rendered_html tbody tr:nth-child(odd) {
+    background: var(--pst-color-surface);
+}
+
+div.rendered_html tbody tr:hover {
+    background: var(--pst-color-accent-bg);
+}
+
+html[data-theme="dark"] .bd-content .nboutput .output_area.rendered_html {
+    background-color: transparent;
+}
+
+/* customise footer ------------------------------------------------- */
+.bd-footer .footer-items__end, .bd-footer .footer-items__start {
+    gap: 0;
+}
+
+.navbar-corporate img {
+    margin-bottom: 0;
+    height: 77px;
+}
+
+.navbar-corporate img {
+    margin-bottom: 0;
+    height: 77px;
+}
+a.navbar-corporate, a.navbar-corporate:hover {
+    border-bottom: hidden;
+}
+
+/* customise header ------------------------------------------------- */
+/* Change font size in header */
+.navbar-brand {
+    font-size: 20px;
+}
+
+/* Change elements size (eg switcher) */
+.navbar-nav .nav-item {
+    font-size: 14px;
+}
+
+/* Change link size in navbar */
+.navbar-nav .nav-link {
+    font-size: 16px;
+}
+
+/* Force navbar to use full width */
+.navbar {
+    width: 100%;
+}
+
+/* reduce margin */
+.navbar-nav {
+    margin: 0;
+}
\ No newline at end of file
diff --git a/docs/source/_static/switcher.json b/docs/source/_static/switcher.json
new file mode 100644
index 0000000..5c72e10
--- /dev/null
+++ b/docs/source/_static/switcher.json
@@ -0,0 +1,12 @@
+[
+    {
+        "name": "dev",
+        "version": "latest",
+        "url": "https://gridmarthe.readthedocs.io/en/dev/"
+    },
+    {
+        "name": "0.1.2 (stable)",
+        "version": "v0.1.2",
+        "url": "https://gridmarthe.readthedocs.io/en/stable/"
+    }
+]
diff --git a/docs/source/_templates/brgm-logo-en.html b/docs/source/_templates/brgm-logo-en.html
new file mode 100644
index 0000000..556e039
--- /dev/null
+++ b/docs/source/_templates/brgm-logo-en.html
@@ -0,0 +1,4 @@
+<a class="navbar-corporate" href="https://www.brgm.fr/" rel="noopener" target="_blank">
+    <img src="https://www.brgm.fr/sites/default/files/logos/2020-07/logo-brgm-etat-en-couleurs.svg" class="logo__image only-light" alt="Marianne+BRGM logo">
+    <img src="https://www.brgm.fr/sites/default/files/logos/2023-06/logo-brgm-etat-en-blanc.svg" class="logo__image only-dark" alt="Marianne+BRGM logo">
+</a>
diff --git a/docs/source/conf.py b/docs/source/conf.py
index d6b7b74..df4ba41 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -1,5 +1,6 @@
 # Configuration file for the Sphinx documentation builder.
-#
+# Disclaimer: this doc configuration is heavily inspired by rameau's documentation.
+
 # For the full list of built-in configuration values, see the documentation:
 # https://www.sphinx-doc.org/en/master/usage/configuration.html
 
@@ -16,6 +17,7 @@
 copyright = '2024,  BRGM'
 
 release = __version__
+language = 'en'
 
 html_short_title = project
 html_title = project
@@ -56,37 +58,47 @@
 
 # html_theme = 'furo'
 html_theme = 'pydata_sphinx_theme'
-# html_static_path = ['_static']
-# html_css_files = ['custom.css']
-
-# adapted from gardenia/ramo doc:
+html_static_path = ['_static']
+html_css_files = ['custom.css']
+
+# version switcher
+json_url = html_baseurl + language + '/latest/_static/switcher.json'
+version_match = os.environ.get("READTHEDOCS_VERSION")
+
+# If READTHEDOCS_VERSION doesn't exist, we're not on RTD
+# If it is an integer, we're in a PR build and the version isn't correct.
+# If it's "latest" → change to "dev" (that's what we want the switcher to call it)
+if not version_match or version_match.isdigit() or version_match in ["latest", "dev"]:
+    # For local development, infer the version to match from the package.
+    version_match = "dev"
+    json_url = "_static/switcher.json"
+elif version_match == "stable":
+    version_match = f"v{release}"
+
+# adapted from gardenia/rameau doc:
 html_permalinks_icon = '<span class="fa fa-link">'
 html_theme_options = {
-    # "logo": {
-    #     "text": 'aquida'
-    # },
     "icon_links": [
         {
             "name": "GitLab",
-            "url": f"https://gitlab.com/brgm/hydrogeological-modelling/marthe-tools/gridmarthe.git",
+            "url" : "https://gitlab.com/brgm/hydrogeological-modelling/marthe-tools/gridmarthe.git",
             "icon": "fa-brands fa-gitlab",
             "type": "fontawesome",
         }
     ],
-    "show_prev_next": False,
-    "show_toc_level": 1,
-    "show_nav_level": 1,
     "navbar_align": "content",
     "navbar_start": ["navbar-logo"],
-    #"navbar_end": ["version-switcher","theme-switcher", "navbar-icon-links"],
-    "navbar_end": ["theme-switcher", "navbar-icon-links"],
+    "navbar_end": ["version-switcher", "theme-switcher", "navbar-icon-links"],
     "footer_start": ["copyright", "sphinx-version", "last-updated"],
-    # "footer_end": ["corporate-logo"],
+    "footer_end": ["brgm-logo-{}".format(language)],
+    "show_toc_level": 1,
+    "show_nav_level": 1,
     "header_links_before_dropdown": 6,
-    # "switcher": {
-    #     "json_url": f"{html_baseurl}/en/latest/_static/switcher.json",
-    #     "version_match": release
-    # },
+    "show_prev_next": False,
+     "switcher": {
+        "json_url": json_url,
+        "version_match": version_match,
+    },
 }
 
 html_last_updated_fmt = '%b %d, %Y'
diff --git a/docs/source/index.rst b/docs/source/index.rst
index cd5113a..299a47e 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -31,6 +31,7 @@ This library is open-source and released under the GNU General Public License (v
    This documentation and the library itself are under heavy developpement
 
 .. grid:: 1 1 2 2 
+   :gutter: 1
    
    .. grid-item-card:: Getting started
       :link: getting_started/index
diff --git a/docs/source/references.rst b/docs/source/references.rst
index caeb74a..bd72a60 100644
--- a/docs/source/references.rst
+++ b/docs/source/references.rst
@@ -7,6 +7,11 @@ About
 
 The MARTHE software is available at <https://www.brgm.fr/en/software/marthe-modelling-software-groundwater-flows>
 
+``gridmarthe`` was developped with the hope it will be useful, but without any warranty
+(see the term of GNU Public Licence v3).
+For any bug, please report it on the project repository
+<https://gitlab.com/brgm/hydrogeological-modelling/marthe-tools/gridmarthe/-/issues>.
+
 
 Bibliography
 ------------
diff --git a/docs/source/switcher.json b/docs/source/switcher.json
deleted file mode 100644
index 5e5f814..0000000
--- a/docs/source/switcher.json
+++ /dev/null
@@ -1,7 +0,0 @@
-[
-    {
-        "name": "v0.1.1 (dev)",
-        "version": "0.1.1",
-        "url": "https://gridmarthe.readthedocs.io/en/latest/"
-    }
-]
diff --git a/docs/source/user_guide/example/gis.ipynb b/docs/source/user_guide/example/gis.ipynb
new file mode 100644
index 0000000..c10d6b7
--- /dev/null
+++ b/docs/source/user_guide/example/gis.ipynb
@@ -0,0 +1,89 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# GIS interoperability and export (shapefile)\n",
+    "This notebook shows how to export gridmarthe features to common GIS format.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Script API"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# import modules\n",
+    "import numpy as np\n",
+    "import gridmarthe as gm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds = gm.load_marthe_grid('./data/chasim_hallue.out', 'CHARGE', fpastp='./data/chasim_hallue.pastp').isel(time=-1)\n",
+    "ds.mart.to_geodataframe()  # or gm.to_geodataframe(ds)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "help(gm.to_raster())  # function doc to write a raster file\n",
+    "# wrapper with time dimension : ds.mart.to_raster('chasim_hallue.tif')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## CLI for gis transformation\n",
+    "\n",
+    "A command line script is also provided to transform a marthe grid file to shapefile or geopackage."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!martshp -h"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "gm",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/docs/source/user_guide/example/treatments.ipynb b/docs/source/user_guide/example/treatments.ipynb
index d407c2e..6b9b3bd 100644
--- a/docs/source/user_guide/example/treatments.ipynb
+++ b/docs/source/user_guide/example/treatments.ipynb
@@ -1022,13 +1022,6 @@
     "## Get mask of active domain"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## "
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 7,
@@ -1079,466 +1072,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/html": [
-       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
-       "<defs>\n",
-       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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-       "\n",
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-       "\n",
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-       "  display: inline-block;\n",
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-       "\n",
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-       "  list-style: none;\n",
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-       ".xr-dim-list li {\n",
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-       "\n",
-       ".xr-dim-list:before {\n",
-       "  content: \"(\";\n",
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-       "\n",
-       ".xr-dim-list:after {\n",
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-       ".xr-var-list,\n",
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-       ".xr-var-list > li:nth-child(odd) > div,\n",
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-       "\n",
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-       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
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-       "\n",
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-       "\n",
-       ".xr-var-name span,\n",
-       ".xr-var-data,\n",
-       ".xr-index-name div,\n",
-       ".xr-index-data,\n",
-       ".xr-attrs {\n",
-       "  padding-left: 25px !important;\n",
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-       "\n",
-       ".xr-attrs,\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  grid-column: 1 / -1;\n",
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-       "\n",
-       "dl.xr-attrs {\n",
-       "  padding: 0;\n",
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-       "\n",
-       ".xr-attrs dt,\n",
-       ".xr-attrs dd {\n",
-       "  padding: 0;\n",
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-       "  float: left;\n",
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-       "\n",
-       ".xr-attrs dt {\n",
-       "  font-weight: normal;\n",
-       "  grid-column: 1;\n",
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-       "\n",
-       ".xr-attrs dt:hover span {\n",
-       "  display: inline-block;\n",
-       "  background: var(--xr-background-color);\n",
-       "  padding-right: 10px;\n",
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-       "\n",
-       ".xr-attrs dd {\n",
-       "  grid-column: 2;\n",
-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2,\n",
-       ".xr-no-icon {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
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-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 75MB\n",
-       "Dimensions:     (time: 1, zone: 1176480)\n",
-       "Coordinates:\n",
-       "  * time        (time) datetime64[ns] 8B 1850-01-01\n",
-       "  * zone        (zone) int32 5MB 1 2 3 4 5 ... 1176477 1176478 1176479 1176480\n",
-       "Data variables:\n",
-       "    h_topogr    (time, zone) float64 9MB 9.999e+03 9.999e+03 ... 9.999e+03\n",
-       "    x           (zone) float32 5MB 5.438e+05 5.442e+05 ... 7.362e+05 7.368e+05\n",
-       "    y           (zone) float32 5MB 2.678e+06 2.678e+06 ... 2.526e+06 2.526e+06\n",
-       "    dx          (zone) float32 5MB 500.0 500.0 500.0 500.0 ... 500.0 500.0 500.0\n",
-       "    dy          (zone) float32 5MB 500.0 500.0 500.0 500.0 ... 500.0 500.0 500.0\n",
-       "    z           (zone) int32 5MB 1 1 1 1 1 1 1 1 1 ... 10 10 10 10 10 10 10 10\n",
-       "    h_substrat  (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
-       "    h_upper     (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
-       "    thickness   (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
-       "    depth       (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
-       "Attributes: (12/17)\n",
-       "    conventions:          CF-1.10\n",
-       "    title:                \n",
-       "    marthe_grid_version:  9.0\n",
-       "    original_dimensions:  x,y,z [grids]: 387 304 10\n",
-       "    lon_resolution:       500.0\n",
-       "    lat_resolution:       500.0\n",
-       "    ...                   ...\n",
-       "    creation_date:        Created on 2025-03-26T13:41:08Z UTC\n",
-       "    institution:          BRGM, French Geological Survey, Orléans, France\n",
-       "    comment:              Hydrogeological model created with MARTHE code (Thi...\n",
-       "    resolution_units:     m\n",
-       "    projection:           epsg:27572\n",
-       "    domain:               FR-France</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6406bc72-1e19-43d7-9174-0cb81cd5d487' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6406bc72-1e19-43d7-9174-0cb81cd5d487' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>zone</span>: 1176480</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4503273c-06bb-4c58-b0d2-55dd3640a45d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4503273c-06bb-4c58-b0d2-55dd3640a45d' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1850-01-01</div><input id='attrs-0059bef2-82c3-4c7d-bafb-6beba9133db1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0059bef2-82c3-4c7d-bafb-6beba9133db1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5fe5eb1-f123-4e16-aa58-3598aa3cca48' class='xr-var-data-in' type='checkbox'><label for='data-e5fe5eb1-f123-4e16-aa58-3598aa3cca48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1850-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zone</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 1176478 1176479 1176480</div><input id='attrs-cf05c054-6234-49d2-ab24-3a64f86ac6cc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf05c054-6234-49d2-ab24-3a64f86ac6cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28c781b9-63c0-4033-8894-e0cfb500d14b' class='xr-var-data-in' type='checkbox'><label for='data-28c781b9-63c0-4033-8894-e0cfb500d14b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([      1,       2,       3, ..., 1176478, 1176479, 1176480],\n",
-       "      shape=(1176480,), dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aa36df7c-dc98-40a4-b690-984fcec0a9ef' class='xr-section-summary-in' type='checkbox'  checked><label for='section-aa36df7c-dc98-40a4-b690-984fcec0a9ef' class='xr-section-summary' >Data variables: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>h_topogr</span></div><div class='xr-var-dims'>(time, zone)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.999e+03 9.999e+03 ... 9.999e+03</div><input id='attrs-db5b14a7-278e-4381-9a90-000cd172c2c2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db5b14a7-278e-4381-9a90-000cd172c2c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32c26ee9-1170-4806-9431-e2506a777747' class='xr-var-data-in' type='checkbox'><label for='data-32c26ee9-1170-4806-9431-e2506a777747' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[9999., 9999., 9999., ..., 9999., 9999., 9999.]],\n",
-       "      shape=(1, 1176480))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.438e+05 5.442e+05 ... 7.368e+05</div><input id='attrs-f9be15cb-a998-436e-a049-2ecf45a2441f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9be15cb-a998-436e-a049-2ecf45a2441f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9e279a6-3b0d-4366-bd40-27956a80f8b1' class='xr-var-data-in' type='checkbox'><label for='data-a9e279a6-3b0d-4366-bd40-27956a80f8b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([543750., 544250., 544750., ..., 735750., 736250., 736750.],\n",
-       "      shape=(1176480,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.678e+06 2.678e+06 ... 2.526e+06</div><input id='attrs-b4c623b5-dd10-4481-96e4-d5200aa7d513' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4c623b5-dd10-4481-96e4-d5200aa7d513' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcc54329-20fc-47ee-822a-038c814b8e92' class='xr-var-data-in' type='checkbox'><label for='data-fcc54329-20fc-47ee-822a-038c814b8e92' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([2677850., 2677850., 2677850., ..., 2526350., 2526350., 2526350.],\n",
-       "      shape=(1176480,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dx</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>500.0 500.0 500.0 ... 500.0 500.0</div><input id='attrs-34611d81-6862-4121-a1df-80dcfc450e10' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-34611d81-6862-4121-a1df-80dcfc450e10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc2f2528-866c-4e2a-899c-b34f31e7d36a' class='xr-var-data-in' type='checkbox'><label for='data-bc2f2528-866c-4e2a-899c-b34f31e7d36a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([500., 500., 500., ..., 500., 500., 500.],\n",
-       "      shape=(1176480,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dy</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>500.0 500.0 500.0 ... 500.0 500.0</div><input id='attrs-5f349249-a338-4207-b90b-e3989e4cfc1c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5f349249-a338-4207-b90b-e3989e4cfc1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f67e1f85-c9e4-4d46-833f-74154a4d9c9d' class='xr-var-data-in' type='checkbox'><label for='data-f67e1f85-c9e4-4d46-833f-74154a4d9c9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([500., 500., 500., ..., 500., 500., 500.],\n",
-       "      shape=(1176480,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>(zone)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 ... 10 10 10 10 10 10</div><input id='attrs-b97cdf75-d70a-4710-926f-d1ee874c5e2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b97cdf75-d70a-4710-926f-d1ee874c5e2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2c096f4-2294-4b89-8da7-b737ea9be697' class='xr-var-data-in' type='checkbox'><label for='data-b2c096f4-2294-4b89-8da7-b737ea9be697' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>long_name :</span></dt><dd>aquifer_layer</dd></dl></div><div class='xr-var-data'><pre>array([ 1,  1,  1, ..., 10, 10, 10], shape=(1176480,), dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h_substrat</span></div><div class='xr-var-dims'>(time, zone)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ebe05482-3643-404a-bf35-11ecf4a66223' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ebe05482-3643-404a-bf35-11ecf4a66223' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b47a9199-cf07-4ba3-a9db-22b1ef520a6b' class='xr-var-data-in' type='checkbox'><label for='data-b47a9199-cf07-4ba3-a9db-22b1ef520a6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan]], shape=(1, 1176480))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h_upper</span></div><div class='xr-var-dims'>(time, zone)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-78007827-41c0-46ea-9102-d16c51129a6d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-78007827-41c0-46ea-9102-d16c51129a6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8740c41c-5300-48ff-b9f0-a3bca9a7acf1' class='xr-var-data-in' type='checkbox'><label for='data-8740c41c-5300-48ff-b9f0-a3bca9a7acf1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan]], shape=(1, 1176480))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thickness</span></div><div class='xr-var-dims'>(time, zone)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4fc053da-c53a-43cd-9980-89c8b63240f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4fc053da-c53a-43cd-9980-89c8b63240f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b30dfd80-38a1-41b0-acce-f63486743014' class='xr-var-data-in' type='checkbox'><label for='data-b30dfd80-38a1-41b0-acce-f63486743014' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan]], shape=(1, 1176480))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time, zone)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ed00b5ac-5474-4632-8e9c-fa30ded28592' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ed00b5ac-5474-4632-8e9c-fa30ded28592' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d062ce10-1736-41f1-b063-49ec54274d1a' class='xr-var-data-in' type='checkbox'><label for='data-d062ce10-1736-41f1-b063-49ec54274d1a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan]], shape=(1, 1176480))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-967c93eb-d4e4-4826-8816-38cd030343fb' class='xr-section-summary-in' type='checkbox'  ><label for='section-967c93eb-d4e4-4826-8816-38cd030343fb' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-6a0342fb-4c3e-4aac-8d8c-4187ceefa03d' class='xr-index-data-in' type='checkbox'/><label for='index-6a0342fb-4c3e-4aac-8d8c-4187ceefa03d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1850-01-01&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>zone</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-7c64203b-afbf-451d-b4ba-d193d779b6b3' class='xr-index-data-in' type='checkbox'/><label for='index-7c64203b-afbf-451d-b4ba-d193d779b6b3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([      1,       2,       3,       4,       5,       6,       7,       8,\n",
-       "             9,      10,\n",
-       "       ...\n",
-       "       1176471, 1176472, 1176473, 1176474, 1176475, 1176476, 1176477, 1176478,\n",
-       "       1176479, 1176480],\n",
-       "      dtype=&#x27;int32&#x27;, name=&#x27;zone&#x27;, length=1176480))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-de10b9c7-e350-4aa1-ab9f-77b48843dc9e' class='xr-section-summary-in' type='checkbox'  ><label for='section-de10b9c7-e350-4aa1-ab9f-77b48843dc9e' class='xr-section-summary' >Attributes: <span>(17)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conventions :</span></dt><dd>CF-1.10</dd><dt><span>title :</span></dt><dd></dd><dt><span>marthe_grid_version :</span></dt><dd>9.0</dd><dt><span>original_dimensions :</span></dt><dd>x,y,z [grids]: 387 304 10</dd><dt><span>lon_resolution :</span></dt><dd>500.0</dd><dt><span>lat_resolution :</span></dt><dd>500.0</dd><dt><span>scale_factor :</span></dt><dd>1.0</dd><dt><span>nested_grid :</span></dt><dd>False</dd><dt><span>extend :</span></dt><dd>xymin : 543750.0 2526350.0; xymax: 736750.0 2677850.0</dd><dt><span>period :</span></dt><dd>1850-1850</dd><dt><span>frequency :</span></dt><dd>nan day(s)</dd><dt><span>creation_date :</span></dt><dd>Created on 2025-03-26T13:41:08Z UTC</dd><dt><span>institution :</span></dt><dd>BRGM, French Geological Survey, Orléans, France</dd><dt><span>comment :</span></dt><dd>Hydrogeological model created with MARTHE code (Thiery, D. 2020. Guidelines for MARTHE v7.8 computer codefor hydro-systems modelling. report BRGM/RP-69660-FR).</dd><dt><span>resolution_units :</span></dt><dd>m</dd><dt><span>projection :</span></dt><dd>epsg:27572</dd><dt><span>domain :</span></dt><dd>FR-France</dd></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset> Size: 75MB\n",
-       "Dimensions:     (time: 1, zone: 1176480)\n",
-       "Coordinates:\n",
-       "  * time        (time) datetime64[ns] 8B 1850-01-01\n",
-       "  * zone        (zone) int32 5MB 1 2 3 4 5 ... 1176477 1176478 1176479 1176480\n",
-       "Data variables:\n",
-       "    h_topogr    (time, zone) float64 9MB 9.999e+03 9.999e+03 ... 9.999e+03\n",
-       "    x           (zone) float32 5MB 5.438e+05 5.442e+05 ... 7.362e+05 7.368e+05\n",
-       "    y           (zone) float32 5MB 2.678e+06 2.678e+06 ... 2.526e+06 2.526e+06\n",
-       "    dx          (zone) float32 5MB 500.0 500.0 500.0 500.0 ... 500.0 500.0 500.0\n",
-       "    dy          (zone) float32 5MB 500.0 500.0 500.0 500.0 ... 500.0 500.0 500.0\n",
-       "    z           (zone) int32 5MB 1 1 1 1 1 1 1 1 1 ... 10 10 10 10 10 10 10 10\n",
-       "    h_substrat  (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
-       "    h_upper     (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
-       "    thickness   (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
-       "    depth       (time, zone) float64 9MB nan nan nan nan nan ... nan nan nan nan\n",
-       "Attributes: (12/17)\n",
-       "    conventions:          CF-1.10\n",
-       "    title:                \n",
-       "    marthe_grid_version:  9.0\n",
-       "    original_dimensions:  x,y,z [grids]: 387 304 10\n",
-       "    lon_resolution:       500.0\n",
-       "    lat_resolution:       500.0\n",
-       "    ...                   ...\n",
-       "    creation_date:        Created on 2025-03-26T13:41:08Z UTC\n",
-       "    institution:          BRGM, French Geological Survey, Orléans, France\n",
-       "    comment:              Hydrogeological model created with MARTHE code (Thi...\n",
-       "    resolution_units:     m\n",
-       "    projection:           epsg:27572\n",
-       "    domain:               FR-France"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
+     "ename": "NameError",
+     "evalue": "name 'gm' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m topo \u001b[38;5;241m=\u001b[39m \u001b[43mgm\u001b[49m\u001b[38;5;241m.\u001b[39mload_marthe_grid(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m./data/example.topog\u001b[39m\u001b[38;5;124m'\u001b[39m, drop_nan\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, nanval\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m9999.\u001b[39m)\n\u001b[1;32m      2\u001b[0m hsubs \u001b[38;5;241m=\u001b[39m gm\u001b[38;5;241m.\u001b[39mload_marthe_grid(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m./data/example.hsubs\u001b[39m\u001b[38;5;124m'\u001b[39m, drop_nan\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, nanval\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m9999\u001b[39m)\n\u001b[1;32m      3\u001b[0m geom \u001b[38;5;241m=\u001b[39m gm\u001b[38;5;241m.\u001b[39mcompute_geometry(topo, hsubs)\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'gm' is not defined"
+     ]
     }
    ],
    "source": [
-    "topo = gm.load_marthe_grid('./data/example.topog')\n",
-    "hsubs = gm.load_marthe_grid('./data/example.hsubs')\n",
+    "topo = gm.load_marthe_grid('./data/example.topog')   # be careful with nan here, topography can be set outside of active area\n",
+    "hsubs = gm.load_marthe_grid('./data/example.hsubs')  # same here, hsubs can be set outside of active area\n",
     "geom = gm.compute_geometry(topo, hsubs)\n",
+    "# print(geom.where(~geom['depth'].isnull(), drop=True))\n",
     "geom\n"
    ]
   },
diff --git a/docs/source/user_guide/index.rst b/docs/source/user_guide/index.rst
index de565f2..4859250 100644
--- a/docs/source/user_guide/index.rst
+++ b/docs/source/user_guide/index.rst
@@ -8,7 +8,8 @@ User Guide
     :maxdepth: 1
 
     example/gm_example.ipynb
-    example/cli.ipynb
     example/gigogne.ipynb
-    example/preproc.ipynb
-    example/treatments.ipynb
\ No newline at end of file
+    example/treatments.ipynb
+    example/gis.ipynb
+    example/cli.ipynb
+    example/preproc.ipynb
\ No newline at end of file
diff --git a/src/gridmarthe/__init__.py b/src/gridmarthe/__init__.py
index 47d7b5f..5a413a7 100644
--- a/src/gridmarthe/__init__.py
+++ b/src/gridmarthe/__init__.py
@@ -64,12 +64,12 @@ def to_raster(self, x_dim='x', y_dim='y', time=None, epsg=27572, fout_template='
         Warning, only functionnal for regular grids
         """
         if time is None:
-            time = self.obj.times # if not defined, get all available times
-        if isinstance(time, str): # make sure to get a iterable for slicing
+            time = self.obj.times  # if not defined, get all available times
+        if isinstance(time, str):  # make sure to get a iterable for slicing
             time = [time]
         
         for t in time:
-            write_raster_from_da(self.obj.sel(time=slice(t)), x_dim, y_dim, epsg, "{}_{}.tiff".format(fout_template, t))
+            to_raster(self.obj.sel(time=slice(t)), x_dim, y_dim, epsg, "{}_{}.tiff".format(fout_template, t))
         
         return None
     
diff --git a/src/gridmarthe/gridmarthe.py b/src/gridmarthe/gridmarthe.py
index 34c090c..24e524d 100644
--- a/src/gridmarthe/gridmarthe.py
+++ b/src/gridmarthe/gridmarthe.py
@@ -171,12 +171,10 @@ def load_marthe_grid(
     as dimension coordinates and drop zone) to get 2-D arrays (or
     3D arrays if multilayer) for every timesteps.
 
-    
     Parameters
     ----------
-    
         filename: str
-            A path to marthegrid file (*.permh, *.out, etc.)
+            A path to marthegrid file (.permh, .out, etc.)
         
         varname : str, Optionnal
             variable to access in martgrid file, e.g ``CHARGE`` for groundwater head. See marthegrid file content.
@@ -234,7 +232,6 @@ def load_marthe_grid(
             Another option is 'numpy', which return a list of numpy arrays :
             [zvar, zdates, isteps, zxcol, zylig, zdxlu, zdylu, ztitle, dims]
 
-
         verbose: bool, Optionnal
             Print some information about execution in stdout.
             Default is False.
@@ -243,7 +240,6 @@ def load_marthe_grid(
     -------
         ds: xr.Dataset
             A xarray.Dataset object containing values and attributes read from Marthe grid file.
-    
     """
     
     # Fortran error cause sys exit. To avoid this, we add a test on file first
@@ -455,8 +451,8 @@ def write_marthe_grid(ds, fileout='grid.out', varname='charge', file_permh: str
     """ Write Dataset as MartheGrid v9 file
     
     ds should contain x, y, dx, dy, attrs[['title', 'original_dimensions']]
-    in case of error, please use :py:func:`gm.reset_geometry` first.
-    When providing a path to `file_permh` argument, :py:func:`gm.reset_geometry` is called automatically.
+    in case of error, please use :py:func:`gridmarthe.reset_geometry` first.
+    When providing a path to ``file_permh`` argument, :py:func:`gridmarthe.reset_geometry` is called automatically.
     
     A good pratice is to provide the permh file when writing dataset to marthegrid format.
     
@@ -496,7 +492,7 @@ def write_marthe_grid(ds, fileout='grid.out', varname='charge', file_permh: str
         if only main grid : `[[x,y,z]]`
         if None (default, dims will be parsed from ds.attrs['original_dimensions'] which is added
         when read with :py:func:`gridmarthe.load_marthe_grid`. If not present (lost in some computation for example),
-        please use py:func:`gridmarthe.reset_geometry(ds)` or provide list of dims manually.
+        please use py:func:`gridmarthe.reset_geometry` or provide list of dims manually.
     
     debug: bool, Optionnal (default is False).
     
diff --git a/src/gridmarthe/operasem/gis.py b/src/gridmarthe/operasem/gis.py
index ec9badc..28086a7 100644
--- a/src/gridmarthe/operasem/gis.py
+++ b/src/gridmarthe/operasem/gis.py
@@ -44,7 +44,19 @@ def _build_polyg(ds):
 def to_geodataframe(ds, epsg='EPSG:27572', fmt='long'):
     """ Convert marthegrid.Dataset to a geodataframe
 
-    fmt must be long or wide, default is long
+    Parameters
+    ----------
+    ds : xarray.Dataset
+        The dataset to convert.
+    epsg : str, optional
+        The EPSG code for the coordinate reference system, by default 'EPSG:27572'.
+    fmt : str, optional
+        The format of the output GeoDataFrame, either 'long' or 'wide', by default 'long'.
+    
+    Returns
+    -------
+    geopandas.GeoDataFrame
+        The converted GeoDataFrame.
     """
     
     polygons = _build_polyg(ds) # .isel(time=0) # x,y does not vary in time
@@ -87,9 +99,27 @@ def _check_rioxarray():
 def clip_dataset(ds, gdf, crs=27572, engine='gdf'):
     """ Clip a xarray Dataset with a gpd.GeoDataFrame
 
-    Needs rioxarray
+    Needs rioxarray. If not installed, raise ModuleNotFoundError
+    please install it or reinstall gridmarthe with optionnal dependancies: pip install gridmarthe[opt]
+
     See: https://corteva.github.io/rioxarray/html/examples/clip_geom.html
     Todo: shapely version
+
+    Parameters
+    ----------
+    ds : xarray.Dataset
+        The dataset to clip.
+    gdf : geopandas.GeoDataFrame
+        The GeoDataFrame containing the geometry to clip with.
+    crs : int, optional
+        The coordinate reference system to use for the clipping, by default 27572.
+    engine : str, optional
+        The engine to use for clipping, by default 'gdf'.
+    
+    Returns
+    -------
+    xarray.DataArray or xarray.Dataset
+        The clipped dataset.
     """
     _check_rioxarray()
     shp = gdf.to_crs(crs)
@@ -99,10 +129,23 @@ def clip_dataset(ds, gdf, crs=27572, engine='gdf'):
 
 
 def subset_with_coords(da, dims=['x', 'y'], gdf=None, xmin=None, ymin=None, xmax=None, ymax=None):
-    """
-    subset DataArray or Dataset with gpd.GeoDataFrame or bounds
-
-    TODO: real shp clip
+    """ subset DataArray or Dataset on rectangular shape, with gpd.GeoDataFrame or bounds
+
+    Parameters
+    ----------
+    da : xarray.DataArray or xarray.Dataset
+        The data to subset.
+    dims : list of str, optional
+        The dimensions to use for subsetting, by default ['x', 'y'].
+    gdf : geopandas.GeoDataFrame, optional
+        A GeoDataFrame containing the geometry to use for subsetting, by default None.
+    xmin, ymin, xmax, ymax : float, optional
+        The manual bounds to use for subsetting, by default None.
+    
+    Returns
+    -------
+    xarray.DataArray or xarray.Dataset
+        The subsetted data.
     """
     if gdf is not None:
         # edit, one line with total_bounds attribute instead of bounds
@@ -172,6 +215,8 @@ def transf_proj(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154", engine='rioxarr
 
     Data (ds) needs to be a 2D array with xy as coords dimensions and time sliced.
     If needed, use :py:func:`gridmarthe.assign_coords` first.
+
+    Warning: IN DEVELOPMENT, not tested yet // USE WITH CAUTION
     """ 
     if engine == 'rioxarray':
         _check_rioxarray()
@@ -183,10 +228,31 @@ def transf_proj(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154", engine='rioxarr
     return ds_transf
 
 
-def write_raster_from_da(da, x_dim='x', y_dim='y', epsg=27572, fout='raster.tiff'):
+def to_raster(da, x_dim='x', y_dim='y', epsg=27572, fout='raster.tiff'):
     """ Write a xr.DataArray to a raster file
     
-    need xarray with rioxarray installed
+    need xarray with rioxarray installed.
+    Only for regular grids.
+    TODO: add support for irregular grids, using PostMARTHE QGIS plugin code.
+
+    Parameters
+    ----------
+    da : xarray.DataArray
+        The DataArray to write to a raster file (only 2D, i.e. no time dimension, select
+        a variable and timestep before).
+    x_dim : str, optional
+        The name of the x dimension, by default 'x'.
+    y_dim : str, optional
+        The name of the y dimension, by default 'y'.
+    epsg : int, optional
+        The EPSG code for the coordinate reference system, by default 27572.
+    fout : str, optional
+        The output file path for the raster file, by default 'raster.tiff'.
+    
+    Returns
+    -------
+    None
+        The function writes the raster file and returns None.
     """
     _check_rioxarray()
     da = da.copy().rio.write_crs('epsg:{}'.format(epsg))

From cc4eea4b4833326913caea943006c3dc20950f9d Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Wed, 18 Jun 2025 13:57:35 +0200
Subject: [PATCH 24/31] fix: active mask return; update changelog

---
 changelog.rst => changelog.md       |  1 +
 src/gridmarthe/operasem/geometry.py |  3 ++-
 tests/test_geom.py                  | 13 ++++++-------
 3 files changed, 9 insertions(+), 8 deletions(-)
 rename changelog.rst => changelog.md (86%)

diff --git a/changelog.rst b/changelog.md
similarity index 86%
rename from changelog.rst
rename to changelog.md
index 0f7c711..f915536 100644
--- a/changelog.rst
+++ b/changelog.md
@@ -9,6 +9,7 @@ Released on 2025-XX-XX
 * code refactoring (lecsem module and global organization)
 * minor fixes in plot method
 * change: zone index is reset when the `drop_nan` option is used in `load_grid_marthe()`
+* change: rename function to write raster: `to_raster()` instead of `write_raster_from_da()` 
 
 
 v0.1.2
diff --git a/src/gridmarthe/operasem/geometry.py b/src/gridmarthe/operasem/geometry.py
index 7aa85cf..dc70143 100644
--- a/src/gridmarthe/operasem/geometry.py
+++ b/src/gridmarthe/operasem/geometry.py
@@ -50,7 +50,8 @@ def get_active_mask(ds, varname: str='permeab', nanval: list=[-9999., 0.], as_ar
         gdf  = gdf.dissolve()
         if shp_file is not None:
             gdf.to_file(shp_file)
-    return gdf
+        return gdf
+    return mask
 
 
 def _get_true_topo(topo, key='h_topogr'):
diff --git a/tests/test_geom.py b/tests/test_geom.py
index 58949a2..25b37ae 100644
--- a/tests/test_geom.py
+++ b/tests/test_geom.py
@@ -6,12 +6,11 @@
 # np.set_printoptions(threshold=np.inf)
 
 model_name = 'craie_npc'
-hsubs = gm.load_marthe_grid('../../mart_cabbalr_no_lay2_new_topo/{}.hsubs'.format(model_name))
-topo  = gm.load_marthe_grid('../../mart_cabbalr_no_lay2_new_topo/{}.topog'.format(model_name))
-permh = gm.load_marthe_grid('../../mart_cabbalr_no_lay2_new_topo/{}.permh'.format(model_name), varname='PERMEAB')
-mask = gm.get_mask_array(permh)['zone'].data
-
-geom = gm.compute_geometry(topo, hsubs, mask)
-geom = gm.compute_geometry(topo, hsubs)
+hsubs = gm.load_marthe_grid('./tests/data/{}.hsubs'.format(model_name))
+topo  = gm.load_marthe_grid('./tests/data/{}.topog'.format(model_name))
+permh = gm.load_marthe_grid('./tests/data/{}_nogig.permh'.format(model_name), varname='PERMEAB')
+mask = gm.get_active_mask(permh, as_array=True)['zone'].data
 
+geom = gm.compute_geometry(topo, hsubs, mask)  # ok
+geom = gm.compute_geometry(topo, hsubs)  # ok
 

From 0848126d0cf98aa5c5952c6354e6f3c6fbb5e190 Mon Sep 17 00:00:00 2001
From: manlaya <a.manlay@brgm.fr>
Date: Wed, 18 Jun 2025 13:59:59 +0200
Subject: [PATCH 25/31] update test/doc data

---
 .../user_guide/example/data/chasim_hallue.nc  |   Bin 1112692 -> 1112692 bytes
 .../user_guide/example/data/chasim_hallue.out | 17220 ++++++++++++++++
 tests/data/craie_npc_nogig.permh              |  3340 +++
 3 files changed, 20560 insertions(+)
 create mode 100644 docs/source/user_guide/example/data/chasim_hallue.out
 create mode 100644 tests/data/craie_npc_nogig.permh

diff --git a/docs/source/user_guide/example/data/chasim_hallue.nc b/docs/source/user_guide/example/data/chasim_hallue.nc
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diff --git a/docs/source/user_guide/example/data/chasim_hallue.out b/docs/source/user_guide/example/data/chasim_hallue.out
new file mode 100644
index 0000000..d553013
--- /dev/null
+++ b/docs/source/user_guide/example/data/chasim_hallue.out
@@ -0,0 +1,17220 @@
+Marthe_Grid Version=9.0
+Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas       0;    CHARGE  1                    <> CHARGE 1
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+Name=
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+[Structure]
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+[Data_Descript]
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+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
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+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+Marthe_Grid Version=9.0
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    1189;    CHARGE  1                    <> CHARGE 1
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+Marthe_Grid Version=9.0
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+[End_Grid]
+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+[End_Grid]
+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
+Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    2040;    CHARGE  1                    <> CHARGE 1
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    3927;    CHARGE  1                    <> CHARGE 1
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+Marthe_Grid Version=9.0
+Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4019;    CHARGE  1                    <> CHARGE 1
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    4111;    CHARGE  1                    <> CHARGE 1
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
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+Marthe_Grid Version=9.0
+Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas    5906;    CHARGE  1                    <> CHARGE 1
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+Marthe_Grid Version=9.0
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+[End_Grid]
diff --git a/tests/data/craie_npc_nogig.permh b/tests/data/craie_npc_nogig.permh
new file mode 100644
index 0000000..2d38f45
--- /dev/null
+++ b/tests/data/craie_npc_nogig.permh
@@ -0,0 +1,3340 @@
+Marthe_Grid Version=9.0
+Title=Craie NPC                                                      H_SU   RPERMEAB        1
+[Infos]
+Field=PERMEAB
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=1
+Max_Layer=10
+Nest_grid=0
+Max_NestG=0
+[Structure]
+X_Left_Corner=543500
+Y_Lower_Corner=2526100
+Ncolumn=387
+Nrows=304
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
+[Data]
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+Title=Craie NPC                                                      H_SU   RPERMEAB        2
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+Title=Craie NPC                                                      H_SU   RPERMEAB        3
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+Title=Craie NPC                                                      H_SU   RPERMEAB        4
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+Title=Craie NPC                                                      H_SU   RPERMEAB        5
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+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+Title=Craie NPC                                                      H_SU   RPERMEAB        6
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+Title=Craie NPC                                                      H_SU   RPERMEAB        7
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+Title=Craie NPC                                                      H_SU   RPERMEAB        8
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+[End_Grid]

From 11dafd259d7c73993fad30a7aa54769ce736aef2 Mon Sep 17 00:00:00 2001
From: Adrien Manlay <a.manlay@brgm.fr>
Date: Mon, 1 Sep 2025 19:40:49 +0200
Subject: [PATCH 26/31] tests: add automatic tests for read/write/geom/scripts

---
 tests/chasim2nc.py                     |  31 ---
 tests/data/chasim_hallue_2var.out      | 168 +++++++++++++++++
 tests/data/hallue.gpkg                 | Bin 0 -> 98304 bytes
 tests/data/hallue_multilayer.hsubs     | 252 +++++++++++++++++++++++++
 tests/data/hallue_multilayer.permh     | 252 +++++++++++++++++++++++++
 tests/data/hallue_multilayer.topog     | 142 ++++++++++++++
 tests/data/hallue_multilayer_depth.sem | 252 +++++++++++++++++++++++++
 tests/data/hallue_multilayer_thick.sem | 252 +++++++++++++++++++++++++
 tests/res/.gitignore                   |   4 +
 tests/test_all_var.py                  |   9 -
 tests/test_cleanm.sh                   |   7 +-
 tests/test_convert.sh                  |  10 +-
 tests/test_edsemi.py                   |  79 ++++----
 tests/test_geom.py                     |  37 +++-
 tests/test_gridmarthe.py               | 103 ++++++++--
 tests/test_lecsem.py                   | 104 +++++-----
 tests/test_reproj.py                   |  85 ---------
 tests/test_scan.py                     |  20 --
 tests/test_surface_mask.py             |  59 +-----
 19 files changed, 1551 insertions(+), 315 deletions(-)
 delete mode 100644 tests/chasim2nc.py
 create mode 100644 tests/data/chasim_hallue_2var.out
 create mode 100644 tests/data/hallue.gpkg
 create mode 100644 tests/data/hallue_multilayer.hsubs
 create mode 100644 tests/data/hallue_multilayer.permh
 create mode 100644 tests/data/hallue_multilayer.topog
 create mode 100644 tests/data/hallue_multilayer_depth.sem
 create mode 100644 tests/data/hallue_multilayer_thick.sem
 create mode 100644 tests/res/.gitignore
 delete mode 100644 tests/test_all_var.py
 delete mode 100644 tests/test_reproj.py
 delete mode 100644 tests/test_scan.py

diff --git a/tests/chasim2nc.py b/tests/chasim2nc.py
deleted file mode 100644
index 2c1c399..0000000
--- a/tests/chasim2nc.py
+++ /dev/null
@@ -1,31 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding:utf-8 -*-
-
-import gridmarthe as gm
-
-# needs, xarray, netcdf4, h5netcdf
-
-def main(fchasim, fpastp, fnc):
-    ds = gm.load_marthe_grid(fchasim, fpastp=fpastp, dropna=True, varname='CHARGE')
-    encode = {'charge': {'zlib': True, 'complevel': 7}}
-    ds.to_netcdf(fnc, engine='h5netcdf', encoding=encode)
-    return 0
-    
-    
-if __name__ == "__main__":
-    
-    import os, sys
-    from pathlib import Path
-    
-    os.makedirs('nc', exist_ok=True)
-    
-    # chasim = sys.argv[1]
-    # pastp = sys.argv[2]
-
-    chasim='./data/chasim_hallue.out'
-    pastp='./data/hallue.pastp'
-    nc = Path('nc', os.path.basename(chasim.replace("out", "nc")))
-
-    status = main(chasim, pastp, nc)
-    sys.exit(status)
-   
diff --git a/tests/data/chasim_hallue_2var.out b/tests/data/chasim_hallue_2var.out
new file mode 100644
index 0000000..fc6953c
--- /dev/null
+++ b/tests/data/chasim_hallue_2var.out
@@ -0,0 +1,168 @@
+Marthe_Grid Version=9.0
+Title=Mod�lisation du bassin de la SOMME Nappe_Libre         Pas       4;    CHARGE  1                    <> CHARGE 1
+[Infos]
+Field=CHARGE
+Type=
+Elem_Number=0
+Name=
+Time_Step=4
+Time=216
+Layer=1
+Max_Layer=1
+Nest_grid=0
+Max_NestG=0
+[Structure]
+X_Left_Corner=596.5
+Y_Lower_Corner=2542
+Ncolumn=53
+Nrows=54
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
+[Data]
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+[End_Grid]
diff --git a/tests/data/hallue.gpkg b/tests/data/hallue.gpkg
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literal 0
HcmV?d00001

diff --git a/tests/data/hallue_multilayer.hsubs b/tests/data/hallue_multilayer.hsubs
new file mode 100644
index 0000000..42a1421
--- /dev/null
+++ b/tests/data/hallue_multilayer.hsubs
@@ -0,0 +1,252 @@
+Marthe_Grid Version=9.0
+Title=Bidon                                                                  H_SUBSTRAT  1
+[Infos]
+Field=H_SUBSTRAT
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=1
+Max_Layer=3
+Nest_grid=0
+Max_NestG=0
+[Structure]
+X_Left_Corner=596.5
+Y_Lower_Corner=2542
+Ncolumn=53
+Nrows=54
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
+[Data]
+0	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	27	28	29	30	31	32	33	34	35	36	37	38	39	40	41	42	43	44	45	46	47	48	49	50	51	52	53	
+0	0	596.75	597.25	597.75	598.25	598.75	599.25	599.75	600.25	600.75	601.25	601.75	602.25	602.75	603.25	603.75	604.25	604.75	605.25	605.75	606.25	606.75	607.25	607.75	608.25	608.75	609.25	609.75	610.25	610.75	611.25	611.75	612.25	612.75	613.25	613.75	614.25	614.75	615.25	615.75	616.25	616.75	617.25	617.75	618.25	618.75	619.25	619.75	620.25	620.75	621.25	621.75	622.25	622.75	
+1	2568.75	51.58	48.94	45.8	44.4	43.14	42.65	42.05	41.88	40.95	40.07	39.1	39.18	40.37	41.48	42.47	42.64	42.34	42.09	42	41.95	41.95	41.96	42.17	42.97	46.16	48.97	53.44	55.89	58.2	59.33	60.21	60.89	62.05	63.14	65.53	67.51	70.84	72.77	75.04	76.43	78.3	79.46	80.9	81.59	82.35	82.6	82.38	81.81	80.39	79.12	76.76	75.09	0	0.5	
+2	2568.25	58.03	54.75	50.89	48.84	46.35	45.07	43.25	42.46	42.02	41.93	42.14	43.04	44.68	45.23	44.85	43.71	42.4	42.09	42	42	42	42.07	42.53	43.67	46.81	49.82	54.46	56.85	59.16	60.15	60.92	61.22	61.8	62.52	64.72	66.99	70.62	72.87	75.5	76.99	79.22	80.33	80.87	80.73	80.29	80.18	79.9	79.34	77.88	76.57	74.51	73.4	72.3	0.5	
+3	2567.75	62.17	58.71	54.12	51.87	48.69	47.2	44.97	43.73	42.48	42.33	43.04	44.28	46.01	46.33	45.41	43.93	42.4	42.09	42	42	42.08	42.31	43.32	44.69	47.95	50.82	54.96	57.13	59.47	60.61	61.62	61.85	62.02	62.41	64.25	66.36	69.78	72.18	75.15	76.75	79.28	80.37	80.5	79.98	78.98	78.57	78.09	77.58	76.33	75.16	73.46	72.62	71.77	0.5	
+4	2567.25	66.1	62.9	58.12	55.81	52.42	50.41	48.05	46.58	44.48	43.46	42.98	43.88	45.63	46.06	45.24	43.91	42.5	42.16	42.14	42.26	42.67	43.37	45.07	46.74	50.07	52.43	55.59	57.43	60.09	61.7	63.05	63.17	62.63	62.41	63.32	65	68.1	70.67	73.98	75.72	78.1	79.01	79.07	78.32	76.8	76.19	75.81	75.64	74.95	74	72.36	71.48	70.39	0.5	
+5	2566.75	67.37	64.49	59.76	57.36	54.5	52.69	50.04	48.64	46.42	45.06	43.59	43.62	45	45.63	45.18	44.15	42.88	42.51	42.63	43.01	43.71	44.57	46.44	48.17	51.33	53.29	56.02	57.69	60.37	62.12	63.57	63.69	62.87	62.35	62.64	63.86	66.72	69.24	72.38	74.17	76.24	76.86	77.15	76.51	75.25	74.75	74.67	74.9	74.56	73.76	71.81	70.57	69.1	0.5	
+6	2566.25	69.16	66.87	62.44	59.81	57.24	55.83	53.82	52.49	50.14	48.37	46.08	45.47	46.13	47.04	47.28	46.46	44.82	44.11	44.46	45.07	46.15	47.13	48.85	50.43	53.08	54.47	56.72	58.08	60.53	62.27	63.66	63.68	62.8	62.25	62.13	62.69	64.6	66.54	69.07	70.49	72.35	73.03	73.65	73.51	72.98	72.75	73.16	73.75	73.6	72.81	70.55	68.87	66.91	0.5	
+7	2565.75	70.22	68.41	64.44	61.69	59.15	57.89	56.35	55.47	53.59	51.83	49.38	48.56	49.04	49.71	50.05	49.18	47.27	46.36	46.29	46.79	48.05	49.01	50.4	51.75	54.14	55.54	57.45	58.67	60.72	62.15	63.29	63.24	62.58	62.26	62.24	62.56	63.71	65.05	66.92	67.92	69.63	70.48	71.54	71.64	71.45	71.42	72.06	72.75	72.59	71.69	69.29	67.54	65.3	0.5	
+8	2565.25	69.48	68.65	65.93	64.06	62.63	62.02	61.01	60.12	58.59	57.27	55.33	54.6	54.51	54.62	54.11	52.99	50.87	49.68	48.95	49.26	50.52	51.25	52.25	53.31	55.71	57.36	59.09	60.06	61.37	62.08	62.58	62.56	62.39	62.48	62.81	62.95	63.09	63.24	63.83	64.48	66.13	67.36	68.87	69.28	69.3	69.63	70.22	70.55	70.3	68.96	66.37	64.57	62.04	0.5	
+9	2564.75	67.88	67.63	66.23	65.23	65.29	65.31	64.9	64.17	62.5	61.12	59.06	58.17	57.71	57.28	55.97	54.59	52.46	51.09	49.76	49.77	50.64	51.26	52.54	53.77	56.37	58.2	60.14	61.03	62.07	62.42	62.4	62.34	62.39	62.68	63.19	63.25	63.04	62.74	62.68	63.15	64.77	65.97	67.47	67.96	68.14	68.55	68.86	68.7	67.72	66.12	63.62	61.81	59.11	0.5	
+10	2564.25	64.35	64.8	65.38	66.13	67.98	69.04	69.02	68.58	67.4	66.16	63.99	62.5	60.38	58.74	56.15	54.6	52.85	51.48	49.46	48.71	48.84	49.38	50.94	52.59	55.74	57.76	60.22	61.37	62.31	62.5	61.96	61.79	62.14	62.69	63.41	63.47	62.98	62.41	61.94	62.08	62.89	63.56	64.47	65.03	65.41	65.6	65.36	64.64	62.79	61.04	58.56	56.57	53.9	0.5	
+11	2563.75	61.86	62.86	64.71	66.43	69.33	70.95	71.19	70.81	69.67	68.47	66.04	64.25	60.94	58.48	55.57	53.93	52.27	50.93	48.53	47.24	46.88	47.33	49.01	51.17	54.98	56.93	58.96	59.85	60.74	61.06	60.85	60.83	61.51	62.14	62.91	63.04	62.5	61.9	61.33	61.11	60.93	61.08	61.59	62.04	62.53	62.49	61.61	60.68	58.85	57.4	55.13	53.27	50.87	0.5	
+12	2563.25	59.25	60.84	63.5	65.72	69.12	71.07	71.99	72	71.78	71.08	68.41	65.75	60.89	57.58	54.51	53.06	51.81	50.51	47.59	45.62	44.13	44.28	46.42	49.24	53.08	54.54	55.11	55.08	55.77	56.53	57.72	58.55	59.78	60.3	60.57	60.63	60.39	60.04	59.24	58.4	57.16	56.45	55.75	55.56	55.9	55.99	55.31	54.53	53.29	52.61	51.28	49.86	47.64	0.5	
+13	2562.75	57.56	59.31	62.03	64.5	67.94	70.09	71.72	71.91	71.99	71.79	69.17	66.07	60.39	56.78	53.68	52.57	51.92	50.65	47.66	45.42	43.3	43.19	45.25	47.85	50.79	51.59	51.25	50.68	51.22	52.23	54.42	55.96	57.58	57.78	57.54	57.53	57.32	56.93	56.13	55.33	53.93	52.76	51.47	51.07	50.99	51.06	50.81	50.54	50	49.89	49.1	48	45.93	0.5	
+14	2562.25	54.79	56.7	59.43	61.97	65.7	67.9	70.37	71.24	71.89	71.78	69.19	65.31	58.88	55.01	52.08	51.59	51.49	50.41	47.47	45.27	42.72	42.27	43.38	45	46.47	46.28	44.76	43.79	44.29	45.76	48.92	50.91	52.38	52.28	51.95	51.87	51.84	51.44	50.51	50.01	48.87	47.62	46.09	45.27	44.63	44.74	45.14	45.58	46.38	46.73	46.22	45.57	43.94	0.5	
+15	2561.75	52.94	54.99	57.99	60.34	63.88	66.09	68.82	70.15	71.45	71.53	68.6	64.4	57.38	53.31	50.56	50.25	50.28	49.36	46.49	44.3	41.82	41.32	41.62	42.22	42.78	42.18	40.52	39.8	40.37	41.92	45.15	46.91	47.87	47.55	47.21	46.93	47.11	47.19	46.78	46.74	46.3	45.4	43.59	42.17	40.91	41.04	41.8	42.62	43.94	44.51	44.06	43.45	42.21	0.5	
+16	2561.25	49.82	52.06	55.55	57.81	60.78	62.62	65.4	67.26	69.74	70.39	67.45	62.95	54.87	50.36	47.58	47.25	47.05	46.18	43.22	41.1	39.05	38.76	38.74	38.55	37.93	37.12	36.03	35.9	36.59	37.7	39.81	40.78	40.78	40.34	40.21	40.14	40.58	41.07	41.9	42.91	43.55	42.95	40.81	39.04	37.19	36.92	37.92	38.97	40.37	40.92	40.72	40.07	39.17	0.5	
+17	2560.75	47.77	50.06	53.75	56.1	58.57	60.05	62.54	64.63	67.6	68.46	65.49	61	52.94	48.49	45.61	45.13	44.67	43.59	40.65	38.81	37.01	36.79	36.97	36.8	36.09	35.3	34.4	34.29	34.96	35.87	37.09	37.48	37.1	36.51	36.4	36.63	37.22	37.93	39.7	41.22	42.3	41.83	39.61	37.76	35.66	35.24	36.23	37.39	38.77	39.11	38.68	37.94	36.99	0.5	
+18	2560.25	44.36	46.82	50.73	53.14	55.42	56.39	58.33	60.06	62.74	63.61	61.37	57.64	50.65	46.63	43.46	42.67	41.71	40.26	37.28	35.61	34.26	34.23	34.74	34.73	34.34	33.89	33.17	33.09	33.54	33.96	34.34	34.25	33.59	33.14	32.79	32.84	33.38	34.39	37.01	38.85	40.37	40.18	38.24	36.57	34.66	34.29	35.03	35.82	36.58	36.4	35.54	34.59	33.18	0.5	
+19	2559.75	42.64	44.88	48.73	51.12	53.34	54.21	55.71	57.1	59.08	59.82	58.66	55.88	49.99	46.37	42.94	41.84	40.13	38.48	35.52	33.99	32.84	32.83	33.24	33.29	33.16	32.91	32.41	32.43	32.63	32.65	32.76	32.73	32.35	32.22	32.1	32.12	32.5	33.42	35.81	37.61	39.22	39.17	37.64	36.31	34.73	34.35	34.75	35.18	35.3	34.83	33.81	32.81	31.21	0.5	
+20	2559.25	41.38	43.32	46.74	48.72	50.79	51.65	52.67	53.46	54.52	54.81	54.48	52.77	49	46.25	42.59	40.98	38.43	36.58	33.68	32.16	30.75	30.04	29.46	29.22	29.56	29.99	30.19	30.31	30.23	30.19	30.34	30.53	31.06	31.44	31.76	31.93	32.29	32.99	34.81	36.19	37.5	37.64	36.79	35.89	34.64	34.14	34	33.95	33.4	32.61	31.32	30.42	29.1	0.5	
+21	2558.75	40.72	42.56	45.77	47.48	49.35	50.17	50.95	51.44	52.02	52.17	52.07	50.84	47.96	45.48	42.08	40.45	37.72	35.75	32.63	30.94	29.03	27.68	25.44	24.94	25.84	27.17	28.6	28.69	28.47	28.5	28.81	29.18	30.2	30.79	31.37	31.7	32.25	32.9	34.45	35.57	36.6	36.7	35.86	34.98	33.82	33.35	33.06	32.77	31.91	30.99	29.73	29.04	28.11	0.5	
+22	2558.25	39.16	41.17	44.37	45.85	47.32	47.85	48.36	48.56	48.9	49.32	49.43	48.48	45.29	42.97	40.47	39.34	37.03	35	31.63	29.7	26.98	24.58	20.57	19.89	21.03	22.92	26.03	26.53	26.39	26.49	26.93	27.51	28.8	29.66	30.74	31.33	32.07	32.65	33.78	34.45	34.81	34.58	33.4	32.41	31.14	30.62	30.31	30.08	29.26	28.44	27.26	26.7	26.26	0.5	
+23	2557.75	38.04	40.17	43.42	44.8	46.14	46.53	46.76	46.69	47.02	47.57	47.22	46.17	42.87	40.74	39.05	38.16	36.29	34.37	31.05	29.03	25.93	23.39	19.2	18.42	19.61	21.6	24.92	25.5	25.68	25.89	26.32	26.84	28.13	29.11	30.66	31.39	32.11	32.51	33.19	33.57	33.48	32.89	31.25	30.03	28.72	28.23	28.07	27.93	27.33	26.7	25.71	25.14	24.69	0.5	
+24	2557.25	36.61	38.85	42.05	43.23	44.19	44.41	44.25	43.97	44.18	44.58	43.61	42.29	38.83	36.95	35.86	35.46	34.42	32.87	29.99	28	24.99	23.13	20	19.07	20.29	21.95	24.21	24.63	25.14	25.37	25.92	26.56	28.23	29.46	31.16	31.81	31.99	32.09	32.41	32.42	31.63	30.38	27.85	26.35	25.02	24.73	24.83	24.89	24.75	24.44	23.69	23.11	22.53	0.5	
+25	2556.75	36.18	38.27	41.05	42.07	42.86	43.06	42.93	42.6	42.34	42.41	41.08	39.38	35.92	34.33	33.87	33.94	33.09	31.68	29.04	27.04	24.27	22.91	21.05	20.53	21.5	22.37	23.78	24.33	25.01	25.49	26.81	28.03	30.38	31.56	32.46	32.46	31.64	31.46	31.56	31.39	30.28	28.77	26.13	24.67	23.38	23.12	23.24	23.39	23.46	23.18	22.4	21.77	21.22	0.5	
+26	2556.25	35.95	37.61	39.54	40.33	41.17	41.57	41.74	41.28	39.71	38.61	36.12	34.02	31.33	30.62	31.02	31.42	31.26	29.81	27.1	25.08	22.46	21.32	20.47	20.55	21.18	21.69	25	26	25.18	29	32	35.77	39.84	40.04	36.85	33.91	30.12	28.97	28.64	28.51	27.58	26.12	24	23.03	22.22	22.17	22.31	22.46	22.3	21.78	20.77	20.13	19.78	0.5	
+27	2555.75	35.39	37.03	38.75	39.52	40.83	41.58	41.65	40.79	38.31	36.44	33.37	31.29	29.04	28.73	29.25	29.77	29.85	28.49	25.46	23.31	20.7	19.72	19.24	19.45	20.14	20.84	24	23.11	25.33	28.46	37.16	43.72	49.61	48.69	40.46	33.96	27.35	25.41	24.9	24.89	24.37	23.44	22.45	22.18	22.01	22.01	22.06	22.1	21.76	21.05	19.86	19.17	18.92	0.5	
+28	2555.25	33.4	35.26	37.42	38.97	43.36	45.62	44.21	41.06	35.6	33.48	30.75	29.07	27.29	26.72	27.32	27.61	27.26	25.55	22.25	20.11	18.12	17.64	17.56	17.68	18.4	19.47	21.21	22.25	25.14	29.45	41.92	51.72	59.24	56.17	42.18	31.51	21.72	19.17	18.46	18.55	18.58	18.76	19.64	20.55	21.68	21.88	21.69	21.4	20.57	19.63	18.25	17.56	17.38	0.5	
+29	2554.75	31.17	33.09	35.91	38.54	45.99	47.27	43.39	39.35	32.25	31.28	29.48	28.22	26.55	25.71	25.65	25.81	25.04	23.35	20.14	18.21	16.71	16.49	16.54	16.72	17.56	18.77	20.75	21.89	24.21	28.48	41.02	50.78	57.39	53.16	38.12	27.46	17.7	15.32	14.9	15	15.27	15.86	17.65	19.12	20.98	21.43	21.08	20.42	19.24	18.3	20	19	16.46	0.5	
+30	2554.25	26.92	28.6	31.78	35.53	43.99	43.45	39.43	35.03	27.34	27.93	27.99	27.23	25.86	24.76	23.76	23.27	21.74	19.96	17.14	15.7	15.14	15.27	15.36	18	16.44	17.85	20.25	21.5	22.54	25.18	33.31	39.42	43.39	39.27	27.24	19.24	13.26	12.23	12.19	12.25	12.49	13.08	15.08	16.76	18.98	19.78	19.27	18.38	16.96	16.17	18	15.21	15.19	0.5	
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+Marthe_Grid Version=9.0
+Title=Bidon                                                                  H_SUBSTRAT  2
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+5	2566.75	57.37	54.49	49.76	47.36	44.5	42.69	40.04	38.64	36.42	35.06	33.59	33.62	35	35.63	35.18	34.15	32.88	32.51	32.63	33.01	33.71	34.57	36.44	38.17	41.33	43.29	46.02	47.69	50.37	52.12	53.57	53.69	52.87	52.35	52.64	53.86	56.72	59.24	62.38	64.17	66.24	66.86	67.15	66.51	65.25	64.75	64.67	64.9	64.56	63.76	61.81	60.57	59.1	0.5	
+6	2566.25	59.16	56.87	52.44	49.81	47.24	45.83	43.82	42.49	40.14	38.37	36.08	35.47	36.13	37.04	37.28	36.46	34.82	34.11	34.46	35.07	36.15	37.13	38.85	40.43	43.08	44.47	46.72	48.08	50.53	52.27	53.66	53.68	52.8	52.25	52.13	52.69	54.6	56.54	59.07	60.49	62.35	63.03	63.65	63.51	62.98	62.75	63.16	63.75	63.6	62.81	60.55	58.87	56.91	0.5	
+7	2565.75	60.22	58.41	54.44	51.69	49.15	47.89	46.35	45.47	43.59	41.83	39.38	38.56	39.04	39.71	40.05	39.18	37.27	36.36	36.29	36.79	38.05	39.01	40.4	41.75	44.14	45.54	47.45	48.67	50.72	52.15	53.29	53.24	52.58	52.26	52.24	52.56	53.71	55.05	56.92	57.92	59.63	60.48	61.54	61.64	61.45	61.42	62.06	62.75	62.59	61.69	59.29	57.54	55.3	0.5	
+8	2565.25	59.48	58.65	55.93	54.06	52.63	52.02	51.01	50.12	48.59	47.27	45.33	44.6	44.51	44.62	44.11	42.99	40.87	39.68	38.95	39.26	40.52	41.25	42.25	43.31	45.71	47.36	49.09	50.06	51.37	52.08	52.58	52.56	52.39	52.48	52.81	52.95	53.09	53.24	53.83	54.48	56.13	57.36	58.87	59.28	59.3	59.63	60.22	60.55	60.3	58.96	56.37	54.57	52.04	0.5	
+9	2564.75	57.88	57.63	56.23	55.23	55.29	55.31	54.9	54.17	52.5	51.12	49.06	48.17	47.71	47.28	45.97	44.59	42.46	41.09	39.76	39.77	40.64	41.26	42.54	43.77	46.37	48.2	50.14	51.03	52.07	52.42	52.4	52.34	52.39	52.68	53.19	53.25	53.04	52.74	52.68	53.15	54.77	55.97	57.47	57.96	58.14	58.55	58.86	58.7	57.72	56.12	53.62	51.81	49.11	0.5	
+10	2564.25	54.35	54.8	55.38	56.13	57.98	59.04	59.02	58.58	57.4	56.16	53.99	52.5	50.38	48.74	46.15	44.6	42.85	41.48	39.46	38.71	38.84	39.38	40.94	42.59	45.74	47.76	50.22	51.37	52.31	52.5	51.96	51.79	52.14	52.69	53.41	53.47	52.98	52.41	51.94	52.08	52.89	53.56	54.47	55.03	55.41	55.6	55.36	54.64	52.79	51.04	48.56	46.57	43.9	0.5	
+11	2563.75	51.86	52.86	54.71	56.43	59.33	60.95	61.19	60.81	59.67	58.47	56.04	54.25	50.94	48.48	45.57	43.93	42.27	40.93	38.53	37.24	36.88	37.33	39.01	41.17	44.98	46.93	48.96	49.85	50.74	51.06	50.85	50.83	51.51	52.14	52.91	53.04	52.5	51.9	51.33	51.11	50.93	51.08	51.59	52.04	52.53	52.49	51.61	50.68	48.85	47.4	45.13	43.27	40.87	0.5	
+12	2563.25	49.25	50.84	53.5	55.72	59.12	61.07	61.99	62	61.78	61.08	58.41	55.75	50.89	47.58	44.51	43.06	41.81	40.51	37.59	35.62	34.13	34.28	36.42	39.24	43.08	44.54	45.11	45.08	45.77	46.53	47.72	48.55	49.78	50.3	50.57	50.63	50.39	50.04	49.24	48.4	47.16	46.45	45.75	45.56	45.9	45.99	45.31	44.53	43.29	42.61	41.28	39.86	37.64	0.5	
+13	2562.75	47.56	49.31	52.03	54.5	57.94	60.09	61.72	61.91	61.99	61.79	59.17	56.07	50.39	46.78	43.68	42.57	41.92	40.65	37.66	35.42	33.3	33.19	35.25	37.85	40.79	41.59	41.25	40.68	41.22	42.23	44.42	45.96	47.58	47.78	47.54	47.53	47.32	46.93	46.13	45.33	43.93	42.76	41.47	41.07	40.99	41.06	40.81	40.54	40	39.89	39.1	38	35.93	0.5	
+14	2562.25	44.79	46.7	49.43	51.97	55.7	57.9	60.37	61.24	61.89	61.78	59.19	55.31	48.88	45.01	42.08	41.59	41.49	40.41	37.47	35.27	32.72	32.27	33.38	35	36.47	36.28	34.76	33.79	34.29	35.76	38.92	40.91	42.38	42.28	41.95	41.87	41.84	41.44	40.51	40.01	38.87	37.62	36.09	35.27	34.63	34.74	35.14	35.58	36.38	36.73	36.22	35.57	33.94	0.5	
+15	2561.75	42.94	44.99	47.99	50.34	53.88	56.09	58.82	60.15	61.45	61.53	58.6	54.4	47.38	43.31	40.56	40.25	40.28	39.36	36.49	34.3	31.82	31.32	31.62	32.22	32.78	32.18	30.52	29.8	30.37	31.92	35.15	36.91	37.87	37.55	37.21	36.93	37.11	37.19	36.78	36.74	36.3	35.4	33.59	32.17	30.91	31.04	31.8	32.62	33.94	34.51	34.06	33.45	32.21	0.5	
+16	2561.25	39.82	42.06	45.55	47.81	50.78	52.62	55.4	57.26	59.74	60.39	57.45	52.95	44.87	40.36	37.58	37.25	37.05	36.18	33.22	31.1	29.05	28.76	28.74	28.55	27.93	27.12	26.03	25.9	26.59	27.7	29.81	30.78	30.78	30.34	30.21	30.14	30.58	31.07	31.9	32.91	33.55	32.95	30.81	29.04	27.19	26.92	27.92	28.97	30.37	30.92	30.72	30.07	29.17	0.5	
+17	2560.75	37.77	40.06	43.75	46.1	48.57	50.05	52.54	54.63	57.6	58.46	55.49	51	42.94	38.49	35.61	35.13	34.67	33.59	30.65	28.81	27.01	26.79	26.97	26.8	26.09	25.3	24.4	24.29	24.96	25.87	27.09	27.48	27.1	26.51	26.4	26.63	27.22	27.93	29.7	31.22	32.3	31.83	29.61	27.76	25.66	25.24	26.23	27.39	28.77	29.11	28.68	27.94	26.99	0.5	
+18	2560.25	34.36	36.82	40.73	43.14	45.42	46.39	48.33	50.06	52.74	53.61	51.37	47.64	40.65	36.63	33.46	32.67	31.71	30.26	27.28	25.61	24.26	24.23	24.74	24.73	24.34	23.89	23.17	23.09	23.54	23.96	24.34	24.25	23.59	23.14	22.79	22.84	23.38	24.39	27.01	28.85	30.37	30.18	28.24	26.57	24.66	24.29	25.03	25.82	26.58	26.4	25.54	24.59	23.18	0.5	
+19	2559.75	32.64	34.88	38.73	41.12	43.34	44.21	45.71	47.1	49.08	49.82	48.66	45.88	39.99	36.37	32.94	31.84	30.13	28.48	25.52	23.99	22.84	22.83	23.24	23.29	23.16	22.91	22.41	22.43	22.63	22.65	22.76	22.73	22.35	22.22	22.1	22.12	22.5	23.42	25.81	27.61	29.22	29.17	27.64	26.31	24.73	24.35	24.75	25.18	25.3	24.83	23.81	22.81	21.21	0.5	
+20	2559.25	31.38	33.32	36.74	38.72	40.79	41.65	42.67	43.46	44.52	44.81	44.48	42.77	39	36.25	32.59	30.98	28.43	26.58	23.68	22.16	20.75	20.04	19.46	19.22	19.56	19.99	20.19	20.31	20.23	20.19	20.34	20.53	21.06	21.44	21.76	21.93	22.29	22.99	24.81	26.19	27.5	27.64	26.79	25.89	24.64	24.14	24	23.95	23.4	22.61	21.32	20.42	19.1	0.5	
+21	2558.75	30.72	32.56	35.77	37.48	39.35	40.17	40.95	41.44	42.02	42.17	42.07	40.84	37.96	35.48	32.08	30.45	27.72	25.75	22.63	20.94	19.03	17.68	15.44	14.94	15.84	17.17	18.6	18.69	18.47	18.5	18.81	19.18	20.2	20.79	21.37	21.7	22.25	22.9	24.45	25.57	26.6	26.7	25.86	24.98	23.82	23.35	23.06	22.77	21.91	20.99	19.73	19.04	18.11	0.5	
+22	2558.25	29.16	31.17	34.37	35.85	37.32	37.85	38.36	38.56	38.9	39.32	39.43	38.48	35.29	32.97	30.47	29.34	27.03	25	21.63	19.7	16.98	14.58	10.57	9.89	11.03	12.92	16.03	16.53	16.39	16.49	16.93	17.51	18.8	19.66	20.74	21.33	22.07	22.65	23.78	24.45	24.81	24.58	23.4	22.41	21.14	20.62	20.31	20.08	19.26	18.44	17.26	16.7	16.26	0.5	
+23	2557.75	28.04	30.17	33.42	34.8	36.14	36.53	36.76	36.69	37.02	37.57	37.22	36.17	32.87	30.74	29.05	28.16	26.29	24.37	21.05	19.03	15.93	13.39	9.2	8.42	9.61	11.6	14.92	15.5	15.68	15.89	16.32	16.84	18.13	19.11	20.66	21.39	22.11	22.51	23.19	23.57	23.48	22.89	21.25	20.03	18.72	18.23	18.07	17.93	17.33	16.7	15.71	15.14	14.69	0.5	
+24	2557.25	26.61	28.85	32.05	33.23	34.19	34.41	34.25	33.97	34.18	34.58	33.61	32.29	28.83	26.95	25.86	25.46	24.42	22.87	19.99	18	14.99	13.13	10	9.07	10.29	11.95	14.21	14.63	15.14	15.37	15.92	16.56	18.23	19.46	21.16	21.81	21.99	22.09	22.41	22.42	21.63	20.38	17.85	16.35	15.02	14.73	14.83	14.89	14.75	14.44	13.69	13.11	12.53	0.5	
+25	2556.75	26.18	28.27	31.05	32.07	32.86	33.06	32.93	32.6	32.34	32.41	31.08	29.38	25.92	24.33	23.87	23.94	23.09	21.68	19.04	17.04	14.27	12.91	11.05	10.53	11.5	12.37	13.78	14.33	15.01	15.49	16.81	18.03	20.38	21.56	22.46	22.46	21.64	21.46	21.56	21.39	20.28	18.77	16.13	14.67	13.38	13.12	13.24	13.39	13.46	13.18	12.4	11.77	11.22	0.5	
+26	2556.25	25.95	27.61	29.54	30.33	31.17	31.57	31.74	31.28	29.71	28.61	26.12	24.02	21.33	20.62	21.02	21.42	21.26	19.81	17.1	15.08	12.46	11.32	10.47	10.55	11.18	11.69	15	16	15.18	19	22	25.77	29.84	30.04	26.85	23.91	20.12	18.97	18.64	18.51	17.58	16.12	14	13.03	12.22	12.17	12.31	12.46	12.3	11.78	10.77	10.13	9.78	0.5	
+27	2555.75	25.39	27.03	28.75	29.52	30.83	31.58	31.65	30.79	28.31	26.44	23.37	21.29	19.04	18.73	19.25	19.77	19.85	18.49	15.46	13.31	10.7	9.72	9.24	9.45	10.14	10.84	14	13.11	15.33	18.46	27.16	33.72	39.61	38.69	30.46	23.96	17.35	15.41	14.9	14.89	14.37	13.44	12.45	12.18	12.01	12.01	12.06	12.1	11.76	11.05	9.86	9.17	8.92	0.5	
+28	2555.25	23.4	25.26	27.42	28.97	33.36	35.62	34.21	31.06	25.6	23.48	20.75	19.07	17.29	16.72	17.32	17.61	17.26	15.55	12.25	10.11	8.12	7.64	7.56	7.68	8.4	9.47	11.21	12.25	15.14	19.45	31.92	41.72	49.24	46.17	32.18	21.51	11.72	9.17	8.46	8.55	8.58	8.76	9.64	10.55	11.68	11.88	11.69	11.4	10.57	9.63	8.25	7.56	7.38	0.5	
+29	2554.75	21.17	23.09	25.91	28.54	35.99	37.27	33.39	29.35	22.25	21.28	19.48	18.22	16.55	15.71	15.65	15.81	15.04	13.35	10.14	8.21	6.71	6.49	6.54	6.72	7.56	8.77	10.75	11.89	14.21	18.48	31.02	40.78	47.39	43.16	28.12	17.46	7.7	5.32	4.9	5	5.27	5.86	7.65	9.12	10.98	11.43	11.08	10.42	9.24	8.3	10	9	6.46	0.5	
+30	2554.25	16.92	18.6	21.78	25.53	33.99	33.45	29.43	25.03	17.34	17.93	17.99	17.23	15.86	14.76	13.76	13.27	11.74	9.96	7.14	5.7	5.14	5.27	5.36	8	6.44	7.85	10.25	11.5	12.54	15.18	23.31	29.42	33.39	29.27	17.24	9.24	3.26	2.23	2.19	2.25	2.49	3.08	5.08	6.76	8.98	9.78	9.27	8.38	6.96	6.17	8	5.21	5.19	0.5	
+31	2553.75	13.51	15.03	17.98	21.51	29.26	29.19	25.54	21.21	14.84	16.48	17.21	16.76	15.26	13.96	12.37	11.4	9.37	7.59	5.25	4.23	4.17	4.41	7	4.54	5.66	7.33	10.01	11.44	11.95	12.95	16.92	19.72	20.9	17.87	9.68	5.02	2.16	1.92	1.91	1.93	2.04	2.35	3.73	5.1	7.25	8.09	7.75	6.93	5.52	4.8	4.45	7	4.49	0.5	
+32	2553.25	9.02	10.31	12.41	14.62	18.86	19.49	17.44	15.43	15.64	16.67	16.46	15.5	13.44	11.95	9.61	8.2	5.95	4.51	3.02	2.64	2.77	2.86	3.15	3.3	4.71	6.55	9.55	11.11	11.41	10.63	9.81	9.4	8.01	6.28	3.6	2.3	1.57	1.45	1.44	1.56	1.74	1.81	2.23	2.94	4.4	5.08	5.02	4.45	3.54	3.2	3.26	3.34	3.61	0.5	
+33	2552.75	6.69	7.68	9.1	10.5	13.24	14.55	15.08	15.58	16.45	16.64	15.79	14.28	11.7	9.89	7.3	5.82	3.93	2.88	1.98	1.82	1.93	2.02	2.28	2.56	3.96	5.86	8.83	10.33	10.41	9.03	6.47	5.17	3.5	2.69	1.87	1.42	1.02	0.93	0.95	1.11	1.38	1.45	1.55	1.86	2.63	3.11	3.32	3.11	2.73	2.6	2.66	2.72	3.02	0.5	
+34	2552.25	3.54	4.27	4.91	5.77	7.61	9.23	11.86	13.73	15	14.91	13.69	11.63	8.58	6.56	3.97	2.9	1.82	1.36	1.11	1.16	1	1.05	1.33	1.57	2.83	4.39	6.66	7.92	7.99	6.51	3.37	1.36	-0.44	-0.66	-0.68	-0.72	-0.7	-0.57	-0.3	-7.0000E-02	0.34	0.43	0.42	0.39	0.6	3	2	2	1.94	1.97	2.1	2.14	2.34	0.5	
+35	2551.75	1.83	2.49	2.91	3.48	4.92	6.69	9.78	11.76	13.33	13.07	11.26	9.4	6.52	4.61	2.45	1.67	1.06	0.85	0.87	0.97	0.64	0.65	0.8	1.03	1.88	2.88	4.4	5.38	5.66	4.44	1.59	-0.37	-2.26	-2.55	-2.69	-2.6	-2.3	-2.05	-1.59	-1.13	2	2	2	2	2	2	0.74	1.13	1.65	1.81	1.97	1.98	2.11	0.5	
+36	2551.25	-0.65	-8.0000E-02	0.32	0.9	2.37	4.01	6.87	8.05	9.27	9.05	7.65	6.5	4.32	2.84	1.22	0.66	0.29	0.22	0.29	0.35	0.16	2	2.00000E-02	0.12	0.19	0.35	0.78	1.36	1.65	1.06	-0.86	-2.54	-4.43	-5.14	-5.56	-5.43	-4.83	-4.27	-1	-1	-1.01	2	-0.61	-0.89	-0.86	-0.44	0.53	1.1	1.53	1.63	1.75	1.81	1.94	0.5	
+37	2550.75	-1.88	-1.29	-0.88	-0.25	1.32	2.75	5.36	6.27	7.1	7	5.97	5.2	3.57	2.32	0.8	0.24	-0.18	-0.26	-0.31	-0.31	-0.45	2	-0.58	-0.59	-0.86	-1.1	-1.22	-1	-0.93	-1.25	-2.65	-4.06	-5.75	-6.43	-6.91	-6.84	-6.13	-3	-3	-1	1	-0.24	-0.44	-0.68	-0.68	-0.31	0.68	1.1	1.28	1.37	1.53	1.69	1.88	0.5	
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+13	2562.75	37.56	39.31	42.03	44.5	47.94	50.09	51.72	51.91	51.99	51.79	49.17	46.07	40.39	36.78	33.68	32.57	31.92	30.65	27.66	25.42	23.3	23.19	25.25	27.85	30.79	31.59	31.25	30.68	31.22	32.23	34.42	35.96	37.58	37.78	37.54	37.53	37.32	36.93	36.13	35.33	33.93	32.76	31.47	31.07	30.99	31.06	30.81	30.54	30	29.89	29.1	28	25.93	0.5	
+14	2562.25	34.79	36.7	39.43	41.97	45.7	47.9	50.37	51.24	51.89	51.78	49.19	45.31	38.88	35.01	32.08	31.59	31.49	30.41	27.47	25.27	22.72	22.27	23.38	25	26.47	26.28	24.76	23.79	24.29	25.76	28.92	30.91	32.38	32.28	31.95	31.87	31.84	31.44	30.51	30.01	28.87	27.62	26.09	25.27	24.63	24.74	25.14	25.58	26.38	26.73	26.22	25.57	23.94	0.5	
+15	2561.75	32.94	34.99	37.99	40.34	43.88	46.09	48.82	50.15	51.45	51.53	48.6	44.4	37.38	33.31	30.56	30.25	30.28	29.36	26.49	24.3	21.82	21.32	21.62	22.22	22.78	22.18	20.52	19.8	20.37	21.92	25.15	26.91	27.87	27.55	27.21	26.93	27.11	27.19	26.78	26.74	26.3	25.4	23.59	22.17	20.91	21.04	21.8	22.62	23.94	24.51	24.06	23.45	22.21	0.5	
+16	2561.25	29.82	32.06	35.55	37.81	40.78	42.62	45.4	47.26	49.74	50.39	47.45	42.95	34.87	30.36	27.58	27.25	27.05	26.18	23.22	21.1	19.05	18.76	18.74	18.55	17.93	17.12	16.03	15.9	16.59	17.7	19.81	20.78	20.78	20.34	20.21	20.14	20.58	21.07	21.9	22.91	23.55	22.95	20.81	19.04	17.19	16.92	17.92	18.97	20.37	20.92	20.72	20.07	19.17	0.5	
+17	2560.75	27.77	30.06	33.75	36.1	38.57	40.05	42.54	44.63	47.6	48.46	45.49	41	32.94	28.49	25.61	25.13	24.67	23.59	20.65	18.81	17.01	16.79	16.97	16.8	16.09	15.3	14.4	14.29	14.96	15.87	17.09	17.48	17.1	16.51	16.4	16.63	17.22	17.93	19.7	21.22	22.3	21.83	19.61	17.76	15.66	15.24	16.23	17.39	18.77	19.11	18.68	17.94	16.99	0.5	
+18	2560.25	24.36	26.82	30.73	33.14	35.42	36.39	38.33	40.06	42.74	43.61	41.37	37.64	30.65	26.63	23.46	22.67	21.71	20.26	17.28	15.61	14.26	14.23	14.74	14.73	14.34	13.89	13.17	13.09	13.54	13.96	14.34	14.25	13.59	13.14	12.79	12.84	13.38	14.39	17.01	18.85	20.37	20.18	18.24	16.57	14.66	14.29	15.03	15.82	16.58	16.4	15.54	14.59	13.18	0.5	
+19	2559.75	22.64	24.88	28.73	31.12	33.34	34.21	35.71	37.1	39.08	39.82	38.66	35.88	29.99	26.37	22.94	21.84	20.13	18.48	15.52	13.99	12.84	12.83	13.24	13.29	13.16	12.91	12.41	12.43	12.63	12.65	12.76	12.73	12.35	12.22	12.1	12.12	12.5	13.42	15.81	17.61	19.22	19.17	17.64	16.31	14.73	14.35	14.75	15.18	15.3	14.83	13.81	12.81	11.21	0.5	
+20	2559.25	21.38	23.32	26.74	28.72	30.79	31.65	32.67	33.46	34.52	34.81	34.48	32.77	29	26.25	22.59	20.98	18.43	16.58	13.68	12.16	10.75	10.04	9.46	9.22	9.56	9.99	10.19	10.31	10.23	10.19	10.34	10.53	11.06	11.44	11.76	11.93	12.29	12.99	14.81	16.19	17.5	17.64	16.79	15.89	14.64	14.14	14	13.95	13.4	12.61	11.32	10.42	9.1	0.5	
+21	2558.75	20.72	22.56	25.77	27.48	29.35	30.17	30.95	31.44	32.02	32.17	32.07	30.84	27.96	25.48	22.08	20.45	17.72	15.75	12.63	10.94	9.03	7.68	5.44	4.94	5.84	7.17	8.6	8.69	8.47	8.5	8.81	9.18	10.2	10.79	11.37	11.7	12.25	12.9	14.45	15.57	16.6	16.7	15.86	14.98	13.82	13.35	13.06	12.77	11.91	10.99	9.73	9.04	8.11	0.5	
+22	2558.25	19.16	21.17	24.37	25.85	27.32	27.85	28.36	28.56	28.9	29.32	29.43	28.48	25.29	22.97	20.47	19.34	17.03	15	11.63	9.7	6.98	4.58	0.57	-0.11	1.03	2.92	6.03	6.53	6.39	6.49	6.93	7.51	8.8	9.66	10.74	11.33	12.07	12.65	13.78	14.45	14.81	14.58	13.4	12.41	11.14	10.62	10.31	10.08	9.26	8.44	7.26	6.7	6.26	0.5	
+23	2557.75	18.04	20.17	23.42	24.8	26.14	26.53	26.76	26.69	27.02	27.57	27.22	26.17	22.87	20.74	19.05	18.16	16.29	14.37	11.05	9.03	5.93	3.39	-0.8	-1.58	-0.39	1.6	4.92	5.5	5.68	5.89	6.32	6.84	8.13	9.11	10.66	11.39	12.11	12.51	13.19	13.57	13.48	12.89	11.25	10.03	8.72	8.23	8.07	7.93	7.33	6.7	5.71	5.14	4.69	0.5	
+24	2557.25	16.61	18.85	22.05	23.23	24.19	24.41	24.25	23.97	24.18	24.58	23.61	22.29	18.83	16.95	15.86	15.46	14.42	12.87	9.99	8	4.99	3.13	0	-0.93	0.29	1.95	4.21	4.63	5.14	5.37	5.92	6.56	8.23	9.46	11.16	11.81	11.99	12.09	12.41	12.42	11.63	10.38	7.85	6.35	5.02	4.73	4.83	4.89	4.75	4.44	3.69	3.11	2.53	0.5	
+25	2556.75	16.18	18.27	21.05	22.07	22.86	23.06	22.93	22.6	22.34	22.41	21.08	19.38	15.92	14.33	13.87	13.94	13.09	11.68	9.04	7.04	4.27	2.91	1.05	0.53	1.5	2.37	3.78	4.33	5.01	5.49	6.81	8.03	10.38	11.56	12.46	12.46	11.64	11.46	11.56	11.39	10.28	8.77	6.13	4.67	3.38	3.12	3.24	3.39	3.46	3.18	2.4	1.77	1.22	0.5	
+26	2556.25	15.95	17.61	19.54	20.33	21.17	21.57	21.74	21.28	19.71	18.61	16.12	14.02	11.33	10.62	11.02	11.42	11.26	9.81	7.1	5.08	2.46	1.32	0.47	0.55	1.18	1.69	5	6	5.18	9	12	15.77	19.84	20.04	16.85	13.91	10.12	8.97	8.64	8.51	7.58	6.12	4	3.03	2.22	2.17	2.31	2.46	2.3	1.78	0.77	0.13	-0.22	0.5	
+27	2555.75	15.39	17.03	18.75	19.52	20.83	21.58	21.65	20.79	18.31	16.44	13.37	11.29	9.04	8.73	9.25	9.77	9.85	8.49	5.46	3.31	0.7	-0.28	-0.76	-0.55	0.14	0.84	4	3.11	5.33	8.46	17.16	23.72	29.61	28.69	20.46	13.96	7.35	5.41	4.9	4.89	4.37	3.44	2.45	2.18	2.01	2.01	2.06	2.1	1.76	1.05	-0.14	-0.83	-1.08	0.5	
+28	2555.25	13.4	15.26	17.42	18.97	23.36	25.62	24.21	21.06	15.6	13.48	10.75	9.07	7.29	6.72	7.32	7.61	7.26	5.55	2.25	0.11	-1.88	-2.36	-2.44	-2.32	-1.6	-0.53	1.21	2.25	5.14	9.45	21.92	31.72	39.24	36.17	22.18	11.51	1.72	-0.83	-1.54	-1.45	-1.42	-1.24	-0.36	0.55	1.68	1.88	1.69	1.4	0.57	-0.37	-1.75	-2.44	-2.62	0.5	
+29	2554.75	11.17	13.09	15.91	18.54	25.99	27.27	23.39	19.35	12.25	11.28	9.48	8.22	6.55	5.71	5.65	5.81	5.04	3.35	0.14	-1.79	-3.29	-3.51	-3.46	-3.28	-2.44	-1.23	0.75	1.89	4.21	8.48	21.02	30.78	37.39	33.16	18.12	7.46	-2.3	-4.68	-5.1	-5	-4.73	-4.14	-2.35	-0.88	0.98	1.43	1.08	0.42	-0.76	-1.7	0	-1	-3.54	0.5	
+30	2554.25	6.92	8.6	11.78	15.53	23.99	23.45	19.43	15.03	7.34	7.93	7.99	7.23	5.86	4.76	3.76	3.27	1.74	-4.0000E-02	-2.86	-4.3	-4.86	-4.73	-4.64	-2	-3.56	-2.15	0.25	1.5	2.54	5.18	13.31	19.42	23.39	19.27	7.24	-0.76	-6.74	-7.77	-7.81	-7.75	-7.51	-6.92	-4.92	-3.24	-1.02	-0.22	-0.73	-1.62	-3.04	-3.83	-2	-4.79	-4.81	0.5	
+31	2553.75	3.51	5.03	7.98	11.51	19.26	19.19	15.54	11.21	4.84	6.48	7.21	6.76	5.26	3.96	2.37	1.4	-0.63	-2.41	-4.75	-5.77	-5.83	-5.59	-3	-5.46	-4.34	-2.67	1.00000E-02	1.44	1.95	2.95	6.92	9.72	10.9	7.87	-0.32	-4.98	-7.84	-8.08	-8.09	-8.07	-7.96	-7.65	-6.27	-4.9	-2.75	-1.91	-2.25	-3.07	-4.48	-5.2	-5.55	-3	-5.51	0.5	
+32	2553.25	-0.98	0.31	2.41	4.62	8.86	9.49	7.44	5.43	5.64	6.67	6.46	5.5	3.44	1.95	-0.39	-1.8	-4.05	-5.49	-6.98	-7.36	-7.23	-7.14	-6.85	-6.7	-5.29	-3.45	-0.45	1.11	1.41	0.63	-0.19	-0.6	-1.99	-3.72	-6.4	-7.7	-8.43	-8.55	-8.56	-8.44	-8.26	-8.19	-7.77	-7.06	-5.6	-4.92	-4.98	-5.55	-6.46	-6.8	-6.74	-6.66	-6.39	0.5	
+33	2552.75	-3.31	-2.32	-0.9	0.5	3.24	4.55	5.08	5.58	6.45	6.64	5.79	4.28	1.7	-0.11	-2.7	-4.18	-6.07	-7.12	-8.02	-8.18	-8.07	-7.98	-7.72	-7.44	-6.04	-4.14	-1.17	0.33	0.41	-0.97	-3.53	-4.83	-6.5	-7.31	-8.13	-8.58	-8.98	-9.07	-9.05	-8.89	-8.62	-8.55	-8.45	-8.14	-7.37	-6.89	-6.68	-6.89	-7.27	-7.4	-7.34	-7.28	-6.98	0.5	
+34	2552.25	-6.46	-5.73	-5.09	-4.23	-2.39	-0.77	1.86	3.73	5	4.91	3.69	1.63	-1.42	-3.44	-6.03	-7.1	-8.18	-8.64	-8.89	-8.84	-9	-8.95	-8.67	-8.43	-7.17	-5.61	-3.34	-2.08	-2.01	-3.49	-6.63	-8.64	-10.44	-10.66	-10.68	-10.72	-10.7	-10.57	-10.3	-10.07	-9.66	-9.57	-9.58	-9.61	-9.4	-7	-8	-8	-8.06	-8.03	-7.9	-7.86	-7.66	0.5	
+35	2551.75	-8.17	-7.51	-7.09	-6.52	-5.08	-3.31	-0.22	1.76	3.33	3.07	1.26	-0.6	-3.48	-5.39	-7.55	-8.33	-8.94	-9.15	-9.13	-9.03	-9.36	-9.35	-9.2	-8.97	-8.12	-7.12	-5.6	-4.62	-4.34	-5.56	-8.41	-10.37	-12.26	-12.55	-12.69	-12.6	-12.3	-12.05	-11.59	-11.13	-8	-8	-8	-8	-8	-8	-9.26	-8.87	-8.35	-8.19	-8.03	-8.02	-7.89	0.5	
+36	2551.25	-10.65	-10.08	-9.68	-9.1	-7.63	-5.99	-3.13	-1.95	-0.73	-0.95	-2.35	-3.5	-5.68	-7.16	-8.78	-9.34	-9.71	-9.78	-9.71	-9.65	-9.84	-8	-9.98	-9.88	-9.81	-9.65	-9.22	-8.64	-8.35	-8.94	-10.86	-12.54	-14.43	-15.14	-15.56	-15.43	-14.83	-14.27	-11	-11	-11.01	-8	-10.61	-10.89	-10.86	-10.44	-9.47	-8.9	-8.47	-8.37	-8.25	-8.19	-8.06	0.5	
+37	2550.75	-11.88	-11.29	-10.88	-10.25	-8.68	-7.25	-4.64	-3.73	-2.9	-3	-4.03	-4.8	-6.43	-7.68	-9.2	-9.76	-10.18	-10.26	-10.31	-10.31	-10.45	-8	-10.58	-10.59	-10.86	-11.1	-11.22	-11	-10.93	-11.25	-12.65	-14.06	-15.75	-16.43	-16.91	-16.84	-16.13	-13	-13	-11	-9	-10.24	-10.44	-10.68	-10.68	-10.31	-9.32	-8.9	-8.72	-8.63	-8.47	-8.31	-8.12	0.5	
+38	2550.25	-13.64	-12.92	-12.06	-11.37	-9.92	-8.92	-6.69	-5.75	-5.03	-4.99	-5.56	-6.06	-7.32	-8.44	-9.9	-10.53	-10.97	-11.14	-11.33	-11.34	-11.39	-11.4	-11.52	-11.62	-12.08	-12.56	-13.24	-13.49	-13.77	-14.06	-15.11	-16.02	-17.06	-17.51	-17.8	-17.75	-17.13	-16.21	-14.03	-12.31	-10	-9.28	-9.52	-9.84	-9.93	-9.68	-9.01	-8.84	-8.77	-8.72	-8.59	-8.39	-8.11	0.5	
+39	2549.75	-15	-14.22	-12.96	-12.12	-10.62	-9.76	-8.01	-7.15	-6.26	-5.98	-6.23	-6.68	-7.95	-8.99	-10.41	-11.06	-11.54	-11.74	-11.97	-12.12	-12.35	-12.3	-12.41	-12.42	-12.78	-13.23	-13.96	-14.38	-14.93	-15.32	-16.07	-16.63	-17.31	-17.65	-17.91	-17.91	-17.4	-16.51	-14.15	-12.19	-9.69	-8.8	-8.92	-9.17	-9.24	-9.04	-8.66	-8.65	-8.72	-8.7	-8.55	-8.31	-8.07	0.5	
+40	2549.25	-17.77	-16.81	-14.68	-13.48	-11.95	-11.11	-9.87	-9	-7.86	-7.43	-7.41	-7.83	-9.01	-9.94	-11.24	-11.83	-12.15	-12.28	-12.38	-12.73	-13.32	-11	-13.51	-13.51	-13.87	-14.3	-15.06	-15.57	-16.18	-16.44	-16.78	-17.05	-17.47	-17.74	-17.94	-17.96	-17.72	-17.17	-15.17	-13.28	-10.57	-9.23	-8.32	-8.25	-8.26	-8.23	-8.2	-8.23	-8.31	-8.33	-8.22	-8.13	-8.1	0.5	
+41	2548.75	-20.31	-19.05	-16.41	-14.78	-13.02	-12.28	-11.34	-10.61	-9.4	-8.78	-8.45	-8.69	-9.66	-10.44	-11.69	-12.38	-12.66	-12.46	-12.51	-12.89	-13.6	-13	-14.24	-14.2	-14.62	-15.14	-15.91	-16.32	-16.72	-16.86	-17.07	-17.27	-17.57	-17.79	-17.97	-18	-17.91	-17.64	-16.18	-14.56	-11.94	-10.36	-8.92	-8.39	-8.06	-8.04	-8.05	-8.07	-8.1	-8.11	-8.2	-8.33	-8.59	0.5	
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+[End_Grid]
diff --git a/tests/data/hallue_multilayer.permh b/tests/data/hallue_multilayer.permh
new file mode 100644
index 0000000..6202b89
--- /dev/null
+++ b/tests/data/hallue_multilayer.permh
@@ -0,0 +1,252 @@
+Marthe_Grid Version=9.0
+Title=Champ : Origine 'Travail'                                              PERMEAB  1
+[Infos]
+Field=PERMEAB
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=1
+Max_Layer=3
+Nest_grid=0
+Max_NestG=0
+[Structure]
+X_Left_Corner=596.5
+Y_Lower_Corner=2542
+Ncolumn=53
+Nrows=54
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+[End_Grid]
diff --git a/tests/data/hallue_multilayer.topog b/tests/data/hallue_multilayer.topog
new file mode 100644
index 0000000..5ff7bd0
--- /dev/null
+++ b/tests/data/hallue_multilayer.topog
@@ -0,0 +1,142 @@
+Marthe_Grid Version=9.0
+Title=modelisation du bassin de la somme                                     H_TOPOGR  1
+[Infos]
+Field=H_TOPOGR
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=1
+Max_Layer=3
+Nest_grid=0
+Max_NestG=0
+[Structure]
+X_Left_Corner=596.5
+Y_Lower_Corner=2542
+Ncolumn=53
+Nrows=54
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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diff --git a/tests/data/hallue_multilayer_depth.sem b/tests/data/hallue_multilayer_depth.sem
new file mode 100644
index 0000000..9c92ae3
--- /dev/null
+++ b/tests/data/hallue_multilayer_depth.sem
@@ -0,0 +1,252 @@
+Marthe_Grid Version=9.0
+Title=Travail                                                                TRAVA          1
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+Title=Travail                                                                TRAVA          2
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+Marthe_Grid Version=9.0
+Title=Travail                                                                TRAVA          3
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+[End_Grid]
diff --git a/tests/data/hallue_multilayer_thick.sem b/tests/data/hallue_multilayer_thick.sem
new file mode 100644
index 0000000..9025e64
--- /dev/null
+++ b/tests/data/hallue_multilayer_thick.sem
@@ -0,0 +1,252 @@
+Marthe_Grid Version=9.0
+Title=Travail                                                                TRAVA          1
+[Infos]
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+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
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+[Structure]
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+Y_Lower_Corner=2542
+Ncolumn=53
+Nrows=54
+[Data_Descript]
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+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Travail                                                                TRAVA          2
+[Infos]
+Field=TRAVA
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=2
+Max_Layer=3
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+Max_NestG=0
+[Structure]
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+Y_Lower_Corner=2542
+Ncolumn=53
+Nrows=54
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+[End_Grid]
+Marthe_Grid Version=9.0
+Title=Travail                                                                TRAVA          3
+[Infos]
+Field=TRAVA
+Type=
+Elem_Number=0
+Name=
+Time_Step=-9999
+Time=0
+Layer=3
+Max_Layer=3
+Nest_grid=0
+Max_NestG=0
+[Structure]
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+Y_Lower_Corner=2542
+Ncolumn=53
+Nrows=54
+[Data_Descript]
+! Line 1       :   0   ,     0          , <   1 , 2 , 3 , Ncolumn   >
+! Line 2       :   0   ,     0          , < X_Center_of_all_Columns >
+! Line 2+1     :   1   , Y_of_Row_1     , < Field_Values_of_all_Columns > , Dy_of_Row_1
+! Line 2+2     :   2   , Y_of_Row_2     , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 2+Nrows : Nrows , Y_of_Row_Nrows , < Field_Values_of_all_Columns > , Dy_of_Row_2
+! Line 3+Nrows :   0   ,     0          , <     Dx_of_all_Columns   >
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+46	2546.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	10	10	10	10	10	10	9.999999	10	10	10	10	10	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
+47	2545.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	10	10	10	10	10	10	10	10	10	10	10	10	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
+48	2545.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	10	9.999999	10	10	9.999999	10	10	10	10	9.999999	10	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
+49	2544.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9.999999	10	9.999999	10	10	10	10	10	10	10	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
+50	2544.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9.999999	10	10	9.999999	10	10	10	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
+51	2543.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	10	10	10	9.999999	10	10	10	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
+52	2543.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	10	10	10	10	10	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
+53	2542.75	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
+54	2542.25	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	9999	0.5	
+0	0	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	
+[End_Grid]
diff --git a/tests/res/.gitignore b/tests/res/.gitignore
new file mode 100644
index 0000000..5e7d273
--- /dev/null
+++ b/tests/res/.gitignore
@@ -0,0 +1,4 @@
+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore
diff --git a/tests/test_all_var.py b/tests/test_all_var.py
deleted file mode 100644
index ae39304..0000000
--- a/tests/test_all_var.py
+++ /dev/null
@@ -1,9 +0,0 @@
-import gridmarthe as gm
-
-
-ds = gm.load_marthe_grid(
-    'Jordan_aquifers.out', 
-    'all', 
-    fpastp='Jordan_aquifers.pastp',
-    drop_nan=True
-)
diff --git a/tests/test_cleanm.sh b/tests/test_cleanm.sh
index ee8793f..9c7c384 100644
--- a/tests/test_cleanm.sh
+++ b/tests/test_cleanm.sh
@@ -1,3 +1,8 @@
 #!/bin/bash
 
-cleanmgrid data/grid_wrong_attrs.hsubs -l 1 -g 3
\ No newline at end of file
+cleanmgrid -h
+cleanmgrid data/grid_wrong_attrs.hsubs -l 1 -g 3
+if [[ $? -ne 0 ]]; then
+    echo "Test for cleanmgrid script failed"
+    exit 1
+fi
diff --git a/tests/test_convert.sh b/tests/test_convert.sh
index 2c223a7..a7d7ec7 100644
--- a/tests/test_convert.sh
+++ b/tests/test_convert.sh
@@ -5,8 +5,10 @@
 
 mkdir -p nc
 # ncmart -h
-# ncmart ./data/chasim_hallue.out ./data/hallue.pastp
-# ncmart ./data/chasim_hallue.out ./data/hallue.pastp -o hallue.nc
-ncmart ./data/chasim_hallue.out ./data/hallue.pastp -o nc/hallue.nc
+# ncmart ./data/chasim_hallue.out ./data/hallue.pastp -o nc/hallue.nc
 ncmart ./data/chasim_hallue.out ./data/hallue.pastp -o nc/hallue.nc -x 1000
-ncmart ./data/chasim_hallue.out ./data/hallue.pastp -o nc/hallue.nc -x 1000 -v all
+# ncmart ./data/chasim_hallue.out ./data/hallue.pastp -o nc/hallue.nc -x 1000 -v all
+if [[ $? -ne 0 ]]; then
+    echo "Test for ncmart script failed"
+    exit 1
+fi
\ No newline at end of file
diff --git a/tests/test_edsemi.py b/tests/test_edsemi.py
index 51129bb..21ef8ff 100644
--- a/tests/test_edsemi.py
+++ b/tests/test_edsemi.py
@@ -1,47 +1,47 @@
 
-import gridmarthe as gm
-from gridmarthe.lecsem import _extract_zvar_from_ds, _parse_dims_from_xr_attrs, modgridmarthe
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
 import numpy as np
+import gridmarthe as gm
+# from gridmarthe.lecsem import _extract_zvar_from_ds, _parse_dims_from_xr_attrs, modgridmarthe
 
 
-if __name__ == "__main__":
-    
-    import os;os.chdir('./tests')
+def test_write_marthe_grid():
     
-    martfile = './data/craie_npc.permh'   # multilayer
-    martfile = './data/Somme_V3_Surfex.permh'  # nested
-    martfile = './data/hallue.permh'  # simple, single layer
+    # martfile = './tests/data/craie_npc.permh'   # multilayer
+    # martfile = './tests/data/hallue.permh'      # simple, single layer
+    martfile = './tests/data/Somme_V3_Surfex.permh'  # nested
     varname  = 'PERMEAB'
+    fout = './tests/res/grid.out'
     
+    # ds = gm.load_marthe_grid(martfile, varname)
+    # dims = _parse_dims_from_xr_attrs(ds.attrs.get('original_dimensions'))
+    # (
+    #     zvar, zdates,
+    #     zxcol, zylig, zdxlu, zdylu,
+    #     ztitle, izdates
+    # ) = _extract_zvar_from_ds(ds, varname.lower())
     
-    ds = gm.load_marthe_grid(martfile, varname)
-
-    dims = _parse_dims_from_xr_attrs(ds.attrs.get('original_dimensions'))
-    (
-        zvar, zdates,
-        zxcol, zylig, zdxlu, zdylu,
-        ztitle, izdates
-    ) = _extract_zvar_from_ds(ds, varname.lower())
-    
-    np.prod(np.array(dims), axis=1).sum() == np.size(zvar)
+    # np.prod(np.array(dims), axis=1).sum() == np.size(zvar)
     
     # help(gm.lecsem.modgridmarthe.write_grid)
-    modgridmarthe.write_grid(
-        zvar=zvar,
-        xcol=zxcol,
-        ylig=zylig,
-        dxlu=zdxlu.round(2),
-        dylu=zdylu.round(2),
-        typ_don=varname.upper(),
-        titsem='ztitle',
-        n_dims=dims,
-        nval=len(zvar[0]),
-        ngrid=len(dims),
-        nsteps=len(zdates),
-        dates=izdates,
-        debug=True,
-        xfile='test.out'
-    )
+    # modgridmarthe.write_grid(
+    #     zvar=zvar,
+    #     xcol=zxcol,
+    #     ylig=zylig,
+    #     dxlu=zdxlu.round(2),
+    #     dylu=zdylu.round(2),
+    #     typ_don=varname.upper(),
+    #     titsem='ztitle',
+    #     n_dims=dims,
+    #     nval=len(zvar[0]),
+    #     ngrid=len(dims),
+    #     nsteps=len(zdates),
+    #     dates=izdates,
+    #     debug=True,
+    #     xfile='test.out'
+    # )
 
     # t = np.arange(1, 2862)
     # t2 = np.arange(1, 2862, dtype=np.int32)
@@ -50,4 +50,13 @@
     # np.allclose(t, t2)
 
     ds2 = gm.load_marthe_grid(martfile, varname, drop_nan=True, nanval=[0.,-9999.])
-    gm.write_marthe_grid(ds2, varname='permeab', file_permh=martfile)
+    status = gm.write_marthe_grid(ds2, fout, varname='permeab', file_permh=martfile)
+    assert status == 0, "write_marthe_grid test failed"
+
+    # also test reading the written file
+    ds3 = gm.load_marthe_grid(fout, varname, drop_nan=True, nanval=[0.,-9999.])
+    assert 'permeab' in ds3.data_vars, "re-read written file failed"
+    assert ds3.permeab.shape == ds2.permeab.shape, "re-read written file shape mismatch"
+    assert np.allclose(ds3.permeab.values, ds2.permeab.values, equal_nan=True), "re-read written file values mismatch"
+    print("write_marthe_grid test passed")
+
diff --git a/tests/test_geom.py b/tests/test_geom.py
index 25b37ae..fb3ab36 100644
--- a/tests/test_geom.py
+++ b/tests/test_geom.py
@@ -1,16 +1,39 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
+import numpy as np
 import gridmarthe as gm
 
+
 # np.set_printoptions(threshold=np.inf)
 
-model_name = 'craie_npc'
-hsubs = gm.load_marthe_grid('./tests/data/{}.hsubs'.format(model_name))
-topo  = gm.load_marthe_grid('./tests/data/{}.topog'.format(model_name))
-permh = gm.load_marthe_grid('./tests/data/{}_nogig.permh'.format(model_name), varname='PERMEAB')
-mask = gm.get_active_mask(permh, as_array=True)['zone'].data
+def test_compute_geometry():
+    
+    model_name = 'hallue_multilayer'
+    hsubs = gm.load_marthe_grid('./tests/data/{}.hsubs'.format(model_name))
+    topo  = gm.load_marthe_grid('./tests/data/{}.topog'.format(model_name))
+    permh = gm.load_marthe_grid('./tests/data/{}.permh'.format(model_name), varname='PERMEAB')
+
+    mask = gm.get_active_mask(permh, as_array=True)['zone'].data
+
+    # geom = gm.compute_geometry(topo, hsubs, mask)  # ok
+    geom = gm.compute_geometry(topo, hsubs)  # ok
+
+    # add tests
+    # pour ça il faut un vrai topo et hsubs, (réalisé avec Winmarthe)
+    # puis lire le résultat et comparer aux résultats de compute_geometry
+    true_depth = gm.load_marthe_grid('./tests/data/{}_depth.sem'.format(model_name), varname='TRAVA')
+    true_thick = gm.load_marthe_grid('./tests/data/{}_thick.sem'.format(model_name), varname='TRAVA')
+
+    assert np.allclose(
+        geom['depth'].sel(zone=mask),
+        true_depth['trava'].sel(zone=mask)
+    ), "depth does not match"
+
+    assert np.allclose(
+        geom['thickness'].sel(zone=mask), 
+        true_thick['trava'].sel(zone=mask)
+    ), "thickness does not match"
 
-geom = gm.compute_geometry(topo, hsubs, mask)  # ok
-geom = gm.compute_geometry(topo, hsubs)  # ok
+    print("test_compute_geometry passed")
 
diff --git a/tests/test_gridmarthe.py b/tests/test_gridmarthe.py
index f459f04..e0eabde 100644
--- a/tests/test_gridmarthe.py
+++ b/tests/test_gridmarthe.py
@@ -1,29 +1,98 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+
+import numpy as np
+import xarray as xr
+import pytest
 
 import gridmarthe as gm
 
-inputs = './data/craie_npc.permh', "PERMEAB" # ajouter tests/data ici pour conda-forge ?
 
+DATA_PATH = './tests/data/chasim_hallue_2var.out'
+VAR = "CHARGE"
 
-toto = gm.load_marthe_grid(*inputs, drop_nan=True)
-# toto = gm.load_marthe_grid(*inputs, drop_nan=True, nanval=0.)
-# toto = gm.load_marthe_grid(inputs[0], varname=None)
-# toto = gm.load_marthe_grid(inputs[0], varname='all')
-# toto = gm.load_marthe_grid(*inputs, keepligcol=True)
-# toto = gm.load_marthe_grid(*inputs, add_id_grid=True)
 
-print(toto.attrs)
+def test_load_valid_grid_returns_xarray():
+    ds = gm.load_marthe_grid(DATA_PATH, VAR)
+    assert isinstance(ds, xr.Dataset)
+    assert VAR.lower() in ds.data_vars
+
+
+def test_load_with_varname_none_picks_first():
+    ds = gm.load_marthe_grid(DATA_PATH, varname=None)
+    assert isinstance(ds, xr.Dataset)
+    # assert len(ds.data_vars) > 0
+    assert VAR.lower() in ds.data_vars  # here we know the first var is CHARGE
+
+
+def test_load_with_varname_all_returns_multiple():
+    ds = gm.load_marthe_grid(DATA_PATH, varname='all')
+    assert isinstance(ds, xr.Dataset)
+    data_vars = [ x for x in list(ds.data_vars) if not x in ['x', 'y', 'z', 'dx', 'dy']]
+    assert len(data_vars) >= 1
+
+
+def test_load_with_drop_nan_removes_nan():
+    ds = gm.load_marthe_grid(DATA_PATH, VAR, drop_nan=True)
+    arr = ds[VAR.lower()].values
+    assert not np.any(np.isnan(arr))
+    assert not np.any(arr == 9999.)  # here 9999. is the default nanval
 
-# for pymarthe compat'
-# to recarray
-# df=  toto.to_dataframe()
-# df.to_records()
 
-toto2 = toto.mart.assign_coords()
-toto3 = toto.mart.to_recarray()
+def test_load_with_custom_nanval():
+    ds = gm.load_marthe_grid(DATA_PATH, VAR, drop_nan=True, nanval=0.)
+    arr = ds[VAR.lower()].values
+    assert not np.any(arr == 0.)
 
 
-# import matplotlib.pyplot as plt
-# toto2.permeab.sel(z=6).isel(time=0).plot.pcolormesh()
-# plt.show()
+def test_load_with_keepligcol_adds_col_lig():
+    ds = gm.load_marthe_grid(DATA_PATH, VAR, keepligcol=True)
+    assert 'col' in ds.data_vars
+    assert 'lig' in ds.data_vars
 
 
+def test_load_with_add_id_grid_adds_id_grid():
+    ds = gm.load_marthe_grid(DATA_PATH, VAR, add_id_grid=True)
+    assert 'id_grid' in ds.data_vars
+
+
+def test_load_nonexistent_file_raises():
+    with pytest.raises(FileNotFoundError):
+        gm.load_marthe_grid('not_a_file.permh', VAR)
+
+
+def test_load_invalid_varname_raises():
+    with pytest.raises(ValueError):
+        gm.load_marthe_grid(DATA_PATH, varname='INVALIDVAR')
+
+
+def test_load_grid_attrs_present():
+    ds = gm.load_marthe_grid(DATA_PATH, VAR)
+    assert 'title' in ds.attrs
+    assert 'marthe_grid_version' in ds.attrs
+    assert 'original_dimensions' in ds.attrs
+
+
+# MY TESTS
+# inputs = './tests/data/craie_npc.permh', "PERMEAB" # ajouter tests/data ici pour conda-forge ?
+# 
+# toto = gm.load_marthe_grid(*inputs, drop_nan=True)
+# # toto = gm.load_marthe_grid(*inputs, drop_nan=True, nanval=0.)
+# # toto = gm.load_marthe_grid(inputs[0], varname=None)
+# # toto = gm.load_marthe_grid(inputs[0], varname='all')
+# # toto = gm.load_marthe_grid(*inputs, keepligcol=True)
+# # toto = gm.load_marthe_grid(*inputs, add_id_grid=True)
+# 
+# test = toto.set_coords(['time', 'zone', 'x', 'y', 'z', 'dx', 'dy'])
+# print(toto.attrs)
+# test.mart.assign_coords()
+# 
+# # for pymarthe compat'
+# # to recarray
+# df = toto.to_dataframe()
+# df.to_records()
+# 
+# toto2 = toto.mart.assign_coords()
+# toto3 = toto.mart.to_recarray()
+# 
\ No newline at end of file
diff --git a/tests/test_lecsem.py b/tests/test_lecsem.py
index e7556fc..ce377a4 100644
--- a/tests/test_lecsem.py
+++ b/tests/test_lecsem.py
@@ -1,60 +1,56 @@
-#! /usr/bin/env python3
+#!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-import pandas as pd
-import gridmarthe as gm
+import numpy as np
+from gridmarthe import lecsem
 
 
-if __name__ == '__main__':
-    import matplotlib.pyplot as plt
-    
-    import os;os.chdir('./tests')
-    print(gm.lecsem.__doc__)
-    print(gm.lecsem.modgridmarthe.__doc__)
+XFILE, VAR = './tests/data/chasim_hallue_2var.out', "CHARGE"
+
+
+def test_lecsem_scan_dim():
+
+    nu_zoomx = lecsem.modgridmarthe.scan_nu_zoomx(XFILE) # scan nb of nested grids (gig)
+    dims, nbsteps = lecsem.modgridmarthe.scan_dim(XFILE, VAR, nu_zoomx)
     
-    xfiles = [
-        ('hallue', './data/chasim_hallue.out', 'CHARGE'),
-        # ('hallue', './data/chasim_hallue_multilay.out', 'CHARGE'),
-        # ('hallue', './data/chasim_hallue_2fields.out', 'CHARGE'),
-        # ('mart-npc', './data/chasim_npc_gig_1_layer.out', 'CHARGE'),
-        # ('mart-npc', './data/chasim_npc_gig.out', 'CHARGE'),
-        ('mart-npc2', './data/craie_npc.permh', 'PERMEAB')
-                                        
-    ]
+    assert isinstance(dims, np.ndarray)
+    assert dims.shape[0] == nu_zoomx + 1
+    assert dims.shape[1] == 3  # x, y, z
+    assert isinstance(nbsteps, int)
+    assert nbsteps > 0
+    print("test_lecsem_scan_dim passed")
+
+
+def test_lecsem_scan_typevar():
+
+    var = lecsem.modgridmarthe.scan_typevar(XFILE)
+    var = np.char.strip(np.char.decode(var, 'utf-8'))
+    var = var[var != '']
+
+    assert isinstance(var, np.ndarray)
+    assert var.size > 0
+    assert all(isinstance(v, str) for v in var)
+    print("test_lecsem_scan_typevar passed")
+
+
+def test_lecsem_read_marthe_grid():
+
+    (
+        zvar, zdates, isteps, zxcol,
+        zylig, zdxlu, zdylu, ztitle, dims
+    ) = lecsem._read_marthe_grid(XFILE, VAR, shallow_only=False)
     
-    date_range = {
-        'hallue'  : pd.DatetimeIndex(gm.read_dates_from_pastp('./data/hallue.pastp')['Date']),
-        'mart-npc': pd.date_range('2020-12-01', '2020-12-31', freq='M'),# fake dates for testing
-        'mart-npc2': None,# fake dates for testing
-    }
-
-    for modele, filename, varname in xfiles:
-        # modele, filename = xfiles[-1] # testing
-        # modele, filename = xfiles[1] # testing
-        dates = date_range[modele]
-        
-        ds = gm.load_marthe_grid(
-            filename,
-            varname,
-            dates,
-            # xyfactor=1000,
-            # ajouter les unités si besoin
-            # idealement, ajouter la réf du model, la projection
-            model_attrs={'projection': 'epsg:27572', "references": "Manlay et al., 2023"}
-        )
-        
-        masque = ds[varname.lower()].where(ds[varname.lower()] != 9999.).dropna(dim='zone') # drop nan_val
-        ds = ds.sel(zone=masque['zone'])
-
-        # if "z" in ds.keys():
-        #     first_lay = gm.get_min_layer(ds.isel(time=0))
-        #     gm.plot_outcrop(ds, engine='xr')
-        #     # plot_outcrop(ds, varname='permeab', nanval=0., engine='xr')
-
-        #     # dsbis = gm.assign_coords(ds)
-        #     # dsbis['charge'].plot.pcolormesh(x='x', y='y', row='z', col='time')
-        #     # Pour les gigognes, la grille irrégulière créée rend discontinu le graphique
-        #     # soit interpol, soit geopandas --> polyg.
-        #     # dsbis['charge'].sel(z=[6,9]).plot.pcolormesh(x='x', y='y', row='z', col='time')
-        #     plt.show()
-        #     plt.close()
+    assert isinstance(zvar, np.ndarray)
+    assert np.prod(dims, axis=1).sum() == np.size(zvar)
+
+    assert np.size(zxcol[zxcol != 1e+20]) == dims[:,0].sum()
+    assert np.size(zylig[zylig != 1e+20]) == dims[:,1].sum()
+    assert np.size(zdxlu[zdxlu != 1e+20]) == np.size(zxcol[zxcol != 1e+20])
+    assert np.size(zdylu[zdylu != 1e+20]) == np.size(zylig[zylig != 1e+20])
+
+    print("test_lecsem_read_marthe_grid passed")
+
+
+def test_lecsem_transform_coords():
+    # TODO
+    pass
diff --git a/tests/test_reproj.py b/tests/test_reproj.py
deleted file mode 100644
index 54fabe2..0000000
--- a/tests/test_reproj.py
+++ /dev/null
@@ -1,85 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-
-import gridmarthe as gm
-import matplotlib.pyplot as plt
-import numpy as np
-
-from pyproj import Transformer
-
-import xarray as xr
-import rioxarray as rio
-# import rasterio
-
-def transf_proj(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154"):
-    """ Transform coordinates of a dataset using pyproj.
-    /!\ return more unique points than initial.
-    """
-    transformer = Transformer.from_crs(from_epsg, to_epsg, always_xy=True)
-    x_source, y_source = ds.x.data, ds.y.data
-    x_target, y_target = transformer.transform(x_source, y_source)
-    ds = ds.copy()
-    ds['x'].data = np.round(np.astype(x_target, np.float32))
-    ds['y'].data = np.round(np.astype(y_target, np.float32))
-    ds.attrs['projection'] = to_epsg
-    return ds
-
-def transf_proj2(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154"):
-    """ Transform coordinates of a dataset using pyproj.
-    /!\ recreate a regular grid in dest epsg
-    """
-    x, y = np.unique(ds['x'].data), np.unique(ds['y'].data)
-    nx, ny = len(x), len(y)
-    x0, y0 = np.nanmin(x), np.nanmin(y)
-    x1, y1 = np.nanmax(x), np.nanmax(y)
-    dx, dy = ds['dx'].data, ds['dy'].data
-
-    transformer = Transformer.from_crs(from_epsg, to_epsg, always_xy=True)
-    # Transformer uniquement les bornes de la grille
-    x0n, y0n = transformer.transform(x0, y0)
-    x1n, y1n = transformer.transform(x1, y1)
-    
-    # Recreate regular grid
-    x_reg = np.linspace(x0, x1, ds.x.size)
-    y_reg = np.linspace(y0, y1, ds.y.size)
-
-    ds = ds.copy()
-    ds['x'].data = np.round(np.astype(x_reg, np.float32), 2)
-    ds['y'].data = np.round(np.astype(y_reg, np.float32), 2)
-    ds.attrs['projection'] = to_epsg
-
-    # version meshgrid
-    xx, yy = np.meshgrid(x, y)
-    xx_transformed, yy_transformed = transformer.transform(xx, yy)
-
-    # Recréer la grille avec les nouvelles coordonnées
-    data_transformed = xr.DataArray(
-        gm.assign_coords(ds)['permeab'].data,
-        dims=["y", "x"],
-        coords={"y": yy_transformed[:, 0], "x": xx_transformed[0, :]}
-    )
-
-    return ds
-
-
-
-grid = gm.load_marthe_grid('./data/hallue.permh', xyfactor=1e3, drop_nan=True)
-grid = gm.load_marthe_grid('./data/Somme_V3_Surfex.permh', xyfactor=1e3, drop_nan=True, nanval=[-9999.,0.])
-grid = gm.load_marthe_grid('./data/craie_npc.permh', drop_nan=True)
-
-# grid_2154 = transf_proj2(grid, 'EPSG:27572', 'EPSG:2154')
-# len(np.unique(grid['x'].data))
-# len(np.unique(grid_2154['x'].data))
-
-g2d = gm.assign_coords(grid) #.where(grid['z']==6, drop=True)
-# rio
-g2d_2154 = g2d.rio.write_crs('EPSG:27572').isel(time=0).rio.reproject("EPSG:4326")
-# g2d_2154.to_netcdf('toto.nc', engine='h5netcdf')
-
-
-fig, ax = plt.subplots(ncols=2, figsize=(10,4))
-gm.plot_nested_grid(g2d.isel(time=0), var='permeab', ax=ax[0], add_colorbar=False)
-gm.plot_nested_grid(g2d_2154, var='permeab', ax=ax[1])
-plt.show()
-
-# np.unique(g2d_2154['dy'].data)
\ No newline at end of file
diff --git a/tests/test_scan.py b/tests/test_scan.py
deleted file mode 100644
index fd80bfa..0000000
--- a/tests/test_scan.py
+++ /dev/null
@@ -1,20 +0,0 @@
-
-import numpy as np
-from gridmarthe import lecsem
-# inputs = './data/craie_npc.permh', "PERMEAB"
-inputs = './data/craie_npc.permh', "KKKK"
-xfile = inputs[0]
-varname = inputs[1]
-
-var = lecsem.modgridmarthe.scan_typevar(inputs[0])
-var = np.char.strip(np.char.decode(var, 'utf-8'))
-var = var[var != '']
-# var[0]
-print(var)
-len(var)
-
-varname = var[0]
-nu_zoomx = lecsem.modgridmarthe.scan_nu_zoomx(xfile) # scan nb of nested grids (gig)
-dims, nbsteps = lecsem.modgridmarthe.scan_dim(xfile, varname, nu_zoomx)
-np.prod(dims, axis=1).sum()
-
diff --git a/tests/test_surface_mask.py b/tests/test_surface_mask.py
index 80abc28..4bad8d7 100644
--- a/tests/test_surface_mask.py
+++ b/tests/test_surface_mask.py
@@ -1,68 +1,23 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-# import modules
-import gridmarthe as gm
+# import os;os.chdir('tests')
 import matplotlib.pyplot as plt
 
-
-import os;os.chdir('tests')
+import gridmarthe as gm
 
 
-grid = gm.load_marthe_grid('./data/craie_npc.permh', drop_nan=True)
+grid = gm.load_marthe_grid('./tests/data/craie_npc.permh', drop_nan=True)
 surf = gm.get_surface_layer(ds=grid)
+
+# Plot with geopandas
 gdf = gm.to_geodataframe(surf)
 gm.plot_outcrop(gdf, engine='gpd')
 plt.show()
 
+# Plot with xarray
 toto = gm.assign_coords(surf, add_lay=False)
 # gm.plot_nested_grid(toto, var='z')
 gm.plot_outcrop(toto)
 plt.show()
-
-
-# from matplotlib import pyplot as plt
-# from mpl_toolkits.axes_grid1 import make_axes_locatable
-# from matplotlib import (colors, cm)
-
-# import numpy as np
-# import xarray as xr
-# import geopandas as gpd
-
-# ds_outcrop=toto.copy()
-# ds_outcrop['z'] = ds_outcrop['z']
-# assert 'z' in ds_outcrop.keys(), "No `z` dimension. Outcrop plot is not possible."
-# maxn = np.nanmax(ds_outcrop['z'].data)
-
-# # custom cbar to force categories
-# cmap = cm.tab10 if maxn <= 10 else cm.tab20
-# cmap = colors.ListedColormap(cmap.colors[:int(maxn)]) # subset on number of colors, if not wrong legend
-# bounds = np.arange(1, maxn+1)
-# if len(bounds) == 1:
-#     bounds = np.append(bounds, [maxn+1])
-# norm = colors.BoundaryNorm(bounds, cmap.N+1,)  # set bins to custom values
-# cbar = plt.cm.ScalarMappable(norm=norm, cmap=cmap)
-
-# fig, ax = plt.subplots(1, 1)
-# divider = make_axes_locatable(ax)
-# cax = divider.append_axes("right", size="5%", pad=0.1)
-
-# # the_plot = ds_outcrop['z'].plot.pcolormesh(
-# the_plot = gm.plot_nested_grid(
-#     # x='x', y='y',
-#     ds_outcrop, var='z',
-#     ax=ax,
-#     cmap=cmap,
-#     levels=bounds,
-#     # add_colorbar=False,
-# )
-
-# ax_cbar = fig.colorbar(
-#     cbar, ax=ax, cax=cax,
-#     orientation='vertical',
-#     ticks=[x+0.5 for x in bounds], # set labels in the middle of class
-#     label='Layers',
-# )
-# ax_cbar.ax.tick_params(size=0)
-# ax_cbar.set_ticklabels(ax_cbar.set_ticklabels(['{:.0f}'.format(x) for x in bounds]))
-# plt.show()
\ No newline at end of file
+# plt.close('all')
\ No newline at end of file

From d4eae80deab42e55a07c73858090216413ce741b Mon Sep 17 00:00:00 2001
From: Adrien Manlay <a.manlay@brgm.fr>
Date: Mon, 1 Sep 2025 19:51:52 +0200
Subject: [PATCH 27/31] edit headers to GPL-3 compliant

---
 src/gridmarthe/__init__.py                 |  5 +-
 src/gridmarthe/__version__.py              | 23 ++++++++-
 src/gridmarthe/gridmarthe.py               | 60 ++++++++++++++++++----
 src/gridmarthe/lecsem/_parse_gridmarthe.py | 24 ++++++++-
 src/gridmarthe/operasem/geometry.py        | 45 +++++++++++++++-
 src/gridmarthe/operasem/gis.py             | 27 ++++++++--
 src/gridmarthe/operasem/interp.py          | 24 ++++++++-
 src/gridmarthe/plot.py                     | 42 ++++++++++++---
 src/gridmarthe/scripts/cleanmgrid.py       | 23 ++++++++-
 src/gridmarthe/scripts/martshp.py          | 25 +++++++--
 src/gridmarthe/scripts/ncmart.py           | 23 +++++++--
 src/gridmarthe/utils.py                    | 21 ++++++++
 12 files changed, 302 insertions(+), 40 deletions(-)

diff --git a/src/gridmarthe/__init__.py b/src/gridmarthe/__init__.py
index 5a413a7..464a67b 100644
--- a/src/gridmarthe/__init__.py
+++ b/src/gridmarthe/__init__.py
@@ -1,5 +1,6 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
+# SPDX-License-Identifier: GPL-3.0-or-later
 #
 #    This file is part of gridmarthe.
 #
@@ -59,7 +60,7 @@ def to_recarray(self):
         df = self.obj.to_dataframe()
         return df.to_records()
     
-    def to_raster(self, x_dim='x', y_dim='y', time=None, epsg=27572, fout_template='raster'):
+    def to_raster(self, x_dim='x', y_dim='y', time=None, epsg=27572, filename_tpl='raster'):
         """ Write raster file for a specific timestep (or all) from dataset 
         Warning, only functionnal for regular grids
         """
@@ -69,7 +70,7 @@ def to_raster(self, x_dim='x', y_dim='y', time=None, epsg=27572, fout_template='
             time = [time]
         
         for t in time:
-            to_raster(self.obj.sel(time=slice(t)), x_dim, y_dim, epsg, "{}_{}.tiff".format(fout_template, t))
+            to_raster(self.obj.sel(time=slice(t)), x_dim, y_dim, epsg, "{}_{}.tiff".format(filename_tpl, t))
         
         return None
     
diff --git a/src/gridmarthe/__version__.py b/src/gridmarthe/__version__.py
index 16accd6..c41139c 100644
--- a/src/gridmarthe/__version__.py
+++ b/src/gridmarthe/__version__.py
@@ -1,5 +1,26 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+#    This file is part of gridmarthe.
+#
+#    gridmarthe is a python library to manage grid files for 
+#    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
+#    Copyright (C) 2024  BRGM
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+#
 
 __version__ = '0.1.3'
 
@@ -7,7 +28,7 @@
     {program}  Copyright (C) {year}  {name_of_author}.
     This program comes with ABSOLUTELY NO WARRANTY.
     This is free software, see GNU General Public Lisence v3 for copying.
-""".format(program='gridmarthe', year=2024, name_of_author='BRGM') #(A. Manlay, J.P. Vergnes)
+""".format(program='gridmarthe', year=2025, name_of_author='BRGM')
 
 
 # def _show_c():
diff --git a/src/gridmarthe/gridmarthe.py b/src/gridmarthe/gridmarthe.py
index 24e524d..593b375 100644
--- a/src/gridmarthe/gridmarthe.py
+++ b/src/gridmarthe/gridmarthe.py
@@ -1,5 +1,26 @@
 #! /usr/bin/env python3
 # -*- coding: utf-8 -*-
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+#    This file is part of gridmarthe.
+#
+#    gridmarthe is a python library to manage grid files for 
+#    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
+#    Copyright (C) 2024  BRGM
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+#
 
 import os
 from datetime import datetime
@@ -129,7 +150,7 @@ def _parse_attrs(
     
     epilogue = {
         'creation_date' : 'Created on {}'.format(datetime.utcnow().strftime('%Y-%m-%dT%H:%M:%SZ UTC')),
-        'institution'   : 'BRGM, French Geological Survey, Orléans, France',
+        'institution'   : 'BRGM, French Geological Survey, Orléans, France',  # TODO: make it optional
         'comment'       : 'Hydrogeological model created with MARTHE code '\
                           '(Thiery, D. 2020. Guidelines for MARTHE v7.8 computer code'\
                           'for hydro-systems modelling. report BRGM/RP-69660-FR).'
@@ -221,11 +242,12 @@ def load_marthe_grid(
         model_attrs: dict, Optionnal
             Dictionnary of attributes to add to Dataset.
             by default, gis attrs are added and can be modified
+            
             >>> {
-            >>>    'resolution_units': 'm',
-            >>>    'projection'      : 'epsg:27572',
-            >>>    'domain'          : 'FR-France'
-            >>> }
+    ...    'resolution_units': 'm',
+    ...    'projection'      : 'epsg:27572',
+    ...    'domain'          : 'FR-France'
+    ... }
         
         engine: str, Optionnal
             Engine to use for returned object. Default is 'xarray', which return xarray.Dataset object.
@@ -360,7 +382,7 @@ def load_marthe_grid(
     # 'yc': (['zone'], yligs),
     # 'domain_size': dims, # add non dimension coordinate for info
     # 'domain_origin': [(x0, y0) for igig in grids], # add non dimension coordinate for info
-    # ds = ds.assign_coords(
+    # ds = ds.assign_coords(  # or toto.set_coords(['time', 'zone', 'x', 'y', 'z', 'dx', 'dy'])
         # dic_coords
     # )
     
@@ -378,6 +400,7 @@ def load_marthe_grid(
                 nanval += [-9999.]
         
         ds = dropna(ds, varname, nanval)
+        ds['zone_all'] = ('zone', ds['zone'].data)  # keep old zone as variable for write method // memo: remove tuple to keep as dim
         ds['zone'] = np.arange(1, np.size(ds['zone'].data) + 1, dtype=np.int32)  # rearange zone
         
     # FIXME better, prevent bug at write : https://github.com/pydata/xarray/issues/7722 // https://stackoverflow.com/questions/65019301/variable-has-conflicting-fillvalue-and-missing-value-cannot-encode-data-when
@@ -387,11 +410,20 @@ def load_marthe_grid(
 
 def reset_geometry(ds, path_to_permh: str, variable='permeab', fillna=False):
     """ Reset a Marthe grid geometry based on permh dataset
-    All values (nan, nested grid margins) should be included in
-    permh dataset.
+
+    This function is useful/used, to reconstruct the geometry of the dataset
+    (if NaN were dropped for example), before writting marthe grid, where the full
+    domain is needed (including non active cells).
+    
+    Note
+    ----
+    
     Join is performed with xy[z] (if xy are present in coords) or zone
-    to get zone back in full domain (if dropped, or nan were dropped, etc.)
-    Useful before writting marthe grid (full domain is needed)
+    to get zone back in full domain (if dropped, or nan were dropped, etc.).
+
+    If nan were dropped during :py:func:`gridmarthe.load_grid_marthe()`, 'zone_all'
+    was added and will be used (this variable store the zone index before the reindexing
+    during :py:func:`gridmarthe.dropna`).
     
     Parameters
     ----------
@@ -413,11 +445,17 @@ def reset_geometry(ds, path_to_permh: str, variable='permeab', fillna=False):
         xr.Dataset containing original variables and geometry read from permh file
     """
     da = ds.copy()
+    # All values (nan, nested grid margins) should be included in permh dataset.
     permh = load_marthe_grid(path_to_permh, drop_nan=False, add_id_grid=True, keepligcol=True, verbose=False)
-
+    
+    
     if 'x' in da.coords.keys():
         da = stack_coords(da, dropna=True)
         coords = [x for x in da.coords.keys() if x in ['x', 'y', 'z']] # if xy assert only existing coords in xyz
+    elif 'zone_all' in da.keys():
+        da['zone'] = da['zone_all'].data  # restore zone_all (zone before reorder after dropnan) for merge
+        da = da.drop('zone_all')
+        coords = ['zone']
     else:
         coords = ['zone']
 
diff --git a/src/gridmarthe/lecsem/_parse_gridmarthe.py b/src/gridmarthe/lecsem/_parse_gridmarthe.py
index e20fe4f..55dfe50 100644
--- a/src/gridmarthe/lecsem/_parse_gridmarthe.py
+++ b/src/gridmarthe/lecsem/_parse_gridmarthe.py
@@ -1,6 +1,26 @@
-#! /usr/bin/env python3
+#!/usr/bin/env python3
 # -*- coding: utf-8 -*-
-
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+#    This file is part of gridmarthe.
+#
+#    gridmarthe is a python library to manage grid files for 
+#    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
+#    Copyright (C) 2024  BRGM
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+#
 import re
 import numpy as np
 
diff --git a/src/gridmarthe/operasem/geometry.py b/src/gridmarthe/operasem/geometry.py
index dc70143..f895e43 100644
--- a/src/gridmarthe/operasem/geometry.py
+++ b/src/gridmarthe/operasem/geometry.py
@@ -1,5 +1,26 @@
-#! /usr/bin/env python3
+#!/usr/bin/env python3
 # -*- coding: utf-8 -*-
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+#    This file is part of gridmarthe.
+#
+#    gridmarthe is a python library to manage grid files for 
+#    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
+#    Copyright (C) 2024  BRGM
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+#
 
 """ Module to manage geometry attributes of Marthe grids/domain
 """
@@ -206,6 +227,28 @@ def search_zone(ds, i=None, j=None, x=None, y=None, z=None):
     if ds is multilayered, you need to provide the layer you want (int)
     ds should contains dx and dy
     ds should not have assigned coords (x and y are variables, zone is the dimension coordinates (with time))
+
+    Parameters
+    ----------
+    ds : xr.Dataset
+        dataset with zone, x, y, dx, dy variables.
+    i : int, optional
+        column index to search zone.
+    j : int, optional
+        row index to search zone.
+    x : float, optional
+        x coordinate to search zone.
+    y : float, optional
+        y coordinate to search zone.
+    z : int, optional
+        layer index to search zone. If not provided, all layers are considered.
+    
+    Returns
+    -------
+    zone : xr.Dataset
+        dataset with zone variable, containing the zone number(s) corresponding to the provided coordinates.
+        If no zone is found, an empty dataset is returned.
+    If multiple zones are found, all of them are returned.
     """
     ds_search = ds.copy()
     
diff --git a/src/gridmarthe/operasem/gis.py b/src/gridmarthe/operasem/gis.py
index 28086a7..390b85a 100644
--- a/src/gridmarthe/operasem/gis.py
+++ b/src/gridmarthe/operasem/gis.py
@@ -1,6 +1,26 @@
-#! /usr/bin/env python3
+#!/usr/bin/env python3
 # -*- coding: utf-8 -*-
-
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+#    This file is part of gridmarthe.
+#
+#    gridmarthe is a python library to manage grid files for 
+#    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
+#    Copyright (C) 2024-2025  BRGM
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+#
 """ GIS utility for marthe grids
 """
 
@@ -172,7 +192,7 @@ def subset_with_coords(da, dims=['x', 'y'], gdf=None, xmin=None, ymin=None, xmax
 def _transf_proj_xy(ds, from_epsg="EPSG:27572", to_epsg="EPSG:2154"):
     """ Transform coordinates of a dataset using pyproj.
 
-    /!\ return more unique points than initial due to projection deformation
+    **!** return more unique points than initial due to projection deformation
     """
     transformer = Transformer.from_crs(from_epsg, to_epsg, always_xy=True)
     x_source, y_source = ds.x.data, ds.y.data
@@ -233,6 +253,7 @@ def to_raster(da, x_dim='x', y_dim='y', epsg=27572, fout='raster.tiff'):
     
     need xarray with rioxarray installed.
     Only for regular grids.
+    
     TODO: add support for irregular grids, using PostMARTHE QGIS plugin code.
 
     Parameters
diff --git a/src/gridmarthe/operasem/interp.py b/src/gridmarthe/operasem/interp.py
index 50224dd..0c928f1 100644
--- a/src/gridmarthe/operasem/interp.py
+++ b/src/gridmarthe/operasem/interp.py
@@ -1,6 +1,26 @@
-#! /usr/bin/env python3
+#!/usr/bin/env python3
 # -*- coding: utf-8 -*-
-
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+#    This file is part of gridmarthe.
+#
+#    gridmarthe is a python library to manage grid files for 
+#    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
+#    Copyright (C) 2024  BRGM
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+#
 """ Interpolation and regridding module
 """
 
diff --git a/src/gridmarthe/plot.py b/src/gridmarthe/plot.py
index d76d1af..d3abdd0 100644
--- a/src/gridmarthe/plot.py
+++ b/src/gridmarthe/plot.py
@@ -1,3 +1,27 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+#    This file is part of gridmarthe.
+#
+#    gridmarthe is a python library to manage grid files for 
+#    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
+#    Copyright (C) 2024  BRGM
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+#
+
 from matplotlib import pyplot as plt
 from mpl_toolkits.axes_grid1 import make_axes_locatable
 from matplotlib import (colors, cm)
@@ -23,21 +47,19 @@ def _set_map_lims(ax, xmin, ymin, xmax, ymax, perc=.05):
     return None
 
 
-def plot_nested_grid(da, ax=None, var='charge', **kwargs):
+def plot_nested_grid(ds, ax=None, varname='charge', **kwargs):
     """ Usefull function to plot nested grids, keeping heterogeneous resolution
     
-    TODO: remove var arg: should be a xr.DataArray with coords assigned, same as xarray API for plots
-    
     Parameters
     ----------
-    da: xr.Dataset
+    ds: xr.Dataset
         the dataset MUST be a 2D array, with dims = x,y.
         In other words, you may need to sel z and time before plot, and you need to apply `assign_coord()`
     
     ax: matplotlib axe, Optionnal.
         if provided, data are plotted on this axis, otherwise fig, ax instances will be created.
     
-    var: str, Optionnal
+    varname: str, Optionnal
         the variable to plot in dataset. Default is 'charge'.
     
     kwargs: optionnal.
@@ -47,8 +69,12 @@ def plot_nested_grid(da, ax=None, var='charge', **kwargs):
     -------
     ax: matplotlib axis.
     """
+    da = ds.copy()
+    if 'var' in kwargs.keys():
+        # legacy, previous arg name was only var, harmonize between functions/methods
+        varname = kwargs.pop('var')
     
-    vmin, vmax = da[var].min(), da[var].max()
+    vmin, vmax = da[varname].min(), da[varname].max()
     vmin, vmax = kwargs.pop('vmin', vmin), kwargs.pop('vmax', vmax) # replace with user defined, if defined
     if kwargs.get('norm') is not None:
         vmin, vmax = None, None  # if user set a norm, vmin and vmax are not allowed
@@ -65,14 +91,14 @@ def plot_nested_grid(da, ax=None, var='charge', **kwargs):
     # plots nested then main
     for dx2, dy2 in zip(dx, dy):
         gig = da.where(da['dx'] == dx2, drop=True)
-        gig[var].plot.pcolormesh(
+        gig[varname].plot.pcolormesh(
             x='x', y='y',
             ax=ax, vmin=vmin, vmax=vmax,
             add_colorbar=False,
             **{k:v for k,v in kwargs.items() if k != 'add_colorbar'}
         )
     
-    grid[var].plot.pcolormesh(x='x', y='y', ax=ax, vmin=vmin, vmax=vmax, cbar_kwargs=cbar_kwargs, **kwargs)
+    grid[varname].plot.pcolormesh(x='x', y='y', ax=ax, vmin=vmin, vmax=vmax, cbar_kwargs=cbar_kwargs, **kwargs)
     
     _set_map_lims(ax, da.x.min().data, da.y.min().data, da.x.max().data, da.y.max().data)
     
diff --git a/src/gridmarthe/scripts/cleanmgrid.py b/src/gridmarthe/scripts/cleanmgrid.py
index e5a6548..78d0ce8 100644
--- a/src/gridmarthe/scripts/cleanmgrid.py
+++ b/src/gridmarthe/scripts/cleanmgrid.py
@@ -1,5 +1,26 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+#    This file is part of gridmarthe.
+#
+#    gridmarthe is a python library to manage grid files for 
+#    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
+#    Copyright (C) 2024  BRGM
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+#
 
 # objectif, lire l'ensemble des fichiers maillés et les corriger.
 # sinon, a minima le permh
@@ -121,7 +142,7 @@ def parse_geom(layer_str:str):
 
 def read_rma(frma):
     rma = fread(frma)
-    files = re.finditer('(.*)  =\s+[A-z]', rma)
+    files = re.finditer(r'(.*)  =\s+[A-z]', rma)
     files = [ x.group(1).strip().replace('=', '') for x in files]
     files = [ x for x in files if len(x) > 0]
     return files
diff --git a/src/gridmarthe/scripts/martshp.py b/src/gridmarthe/scripts/martshp.py
index e904c61..9a91805 100644
--- a/src/gridmarthe/scripts/martshp.py
+++ b/src/gridmarthe/scripts/martshp.py
@@ -1,11 +1,26 @@
 #!/usr/bin/env python3
-# -*- coding:utf-8 -*-
-
+# -*- coding: utf-8 -*-
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+#    This file is part of gridmarthe.
+#
 #    gridmarthe is a python library to manage grid files for 
 #    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
-#    Copyright (C) 2024  BRGM
-#    Released under the GNU/GPL-v3 (or later) license <https://www.gnu.org/licenses/gpl-3.0.txt>
-
+#    Copyright (C) 2025  BRGM
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+#
 import os, sys, textwrap
 from argparse import ArgumentParser, RawDescriptionHelpFormatter
 import gridmarthe as gm
diff --git a/src/gridmarthe/scripts/ncmart.py b/src/gridmarthe/scripts/ncmart.py
index e41b401..c7b40fd 100644
--- a/src/gridmarthe/scripts/ncmart.py
+++ b/src/gridmarthe/scripts/ncmart.py
@@ -1,11 +1,26 @@
 #!/usr/bin/env python3
-# -*- coding:utf-8 -*-
-
+# -*- coding: utf-8 -*-
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+#    This file is part of gridmarthe.
+#
 #    gridmarthe is a python library to manage grid files for 
 #    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
 #    Copyright (C) 2024  BRGM
-#    Released under the GNU/GPL-v3 (or later) license <https://www.gnu.org/licenses/gpl-3.0.txt>
-
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+#
 import os, sys, textwrap
 from argparse import ArgumentParser, RawDescriptionHelpFormatter
 import gridmarthe as gm
diff --git a/src/gridmarthe/utils.py b/src/gridmarthe/utils.py
index 144d4d2..e8986bd 100644
--- a/src/gridmarthe/utils.py
+++ b/src/gridmarthe/utils.py
@@ -1,5 +1,26 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+#    This file is part of gridmarthe.
+#
+#    gridmarthe is a python library to manage grid files for 
+#    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
+#    Copyright (C) 2024  BRGM
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+#
 
 import re
 from datetime import datetime

From c7ab0e50bf6620e666366aaad54b3cbf1c0eb847 Mon Sep 17 00:00:00 2001
From: Adrien Manlay <a.manlay@brgm.fr>
Date: Mon, 1 Sep 2025 20:36:37 +0200
Subject: [PATCH 28/31] doc: add linkcode mode from scikit-learn + general
 update

---
 docs/source/conf.py                           |  60 +++-
 docs/source/getting_started/install.rst       |  25 +-
 docs/source/getting_started/nutshell.rst      |   4 +-
 docs/source/index.rst                         |  25 +-
 docs/source/sphinxext/COPYING                 |  29 ++
 docs/source/sphinxext/git_link.py             |  94 +++++++
 docs/source/user_guide/example/cli.ipynb      |   4 +-
 .../user_guide/example/data/chasim_hallue.nc  | Bin 1112692 -> 1125055 bytes
 docs/source/user_guide/example/gigogne.ipynb  |   4 +-
 docs/source/user_guide/example/gis.ipynb      | 258 +++++++++++++++++-
 docs/source/user_guide/example/preproc.ipynb  |   4 +-
 .../user_guide/example/treatments.ipynb       | 110 +++-----
 src/gridmarthe/gridmarthe.py                  |   8 +-
 13 files changed, 508 insertions(+), 117 deletions(-)
 create mode 100644 docs/source/sphinxext/COPYING
 create mode 100644 docs/source/sphinxext/git_link.py

diff --git a/docs/source/conf.py b/docs/source/conf.py
index df4ba41..cb17421 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -1,5 +1,29 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+#    This file is part of gridmarthe.
+#
+#    gridmarthe is a python library to manage grid files for 
+#    MARTHE hydrogeological computer code from French Geological Survey (BRGM).
+#    Copyright (C) 2025  BRGM
+#
+#    This program is free software: you can redistribute it and/or modify
+#    it under the terms of the GNU General Public License as published by
+#    the Free Software Foundation, either version 3 of the License, or
+#    (at your option) any later version.
+#
+#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU General Public License for more details.
+#
+#    You should have received a copy of the GNU General Public License
+#    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+#
 # Configuration file for the Sphinx documentation builder.
-# Disclaimer: this doc configuration is heavily inspired by rameau's documentation.
+# Disclaimer: this doc configuration is heavily inspired by rameau's documentation,
+# and pandas, pastas, scikit-learn. Huge thanks are due to all their contributors.
 
 # For the full list of built-in configuration values, see the documentation:
 # https://www.sphinx-doc.org/en/master/usage/configuration.html
@@ -8,13 +32,17 @@
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information
 
 import os, sys
-# sys.path.insert(0, '../../src')
+
+sys.path.insert(0, os.path.abspath("."))
+sys.path.insert(0, os.path.abspath("sphinxext"))
+
+from sphinxext.git_link import make_linkcode_resolve
 from gridmarthe import __version__
 
 project = 'gridmarthe'
-authors = 'Jean-Pierre Vergnes, Adrien Manlay'
+authors = 'Adrien Manlay, Jean-Pierre Vergnes'
 # copyright = '2024,  BRGM.\nAuthors: {}'.format(authors)
-copyright = '2024,  BRGM'
+copyright = '2024-2025,  BRGM'
 
 release = __version__
 language = 'en'
@@ -22,6 +50,7 @@
 html_short_title = project
 html_title = project
 
+git_repo_url = "https://gitlab.com/brgm/hydrogeological-modelling/marthe-tools/gridmarthe/"
 html_baseurl = 'https://gridmarthe.readthedocs.io/'
 
 # -- General configuration ---------------------------------------------------
@@ -36,7 +65,8 @@
     'sphinx.ext.autosummary',       # Create neat summary tables, by importing code. autoapi just parse the code
     'sphinx.ext.mathjax',
     'sphinx.ext.doctest',
-    'sphinx.ext.viewcode',
+    # 'sphinx.ext.viewcode',        # view source code in doc
+    'sphinx.ext.linkcode',          # link source code (file:Line in git repo)
     'sphinx.ext.napoleon',          # allow different style of docstrings
     'sphinx.ext.intersphinx',
     'sphinx_design',                # grid layout
@@ -72,6 +102,11 @@
     # For local development, infer the version to match from the package.
     version_match = "dev"
     json_url = "_static/switcher.json"
+    # -------------------------------- #
+    # *** TMP for dev/faster build *** #
+    # comment before release/CI
+    # nbsphinx_execute = 'never'
+    # -------------------------------- #
 elif version_match == "stable":
     version_match = f"v{release}"
 
@@ -99,6 +134,8 @@
         "json_url": json_url,
         "version_match": version_match,
     },
+    "show_version_warning_banner": True,
+    "announcement": None,
 }
 
 html_last_updated_fmt = '%b %d, %Y'
@@ -140,6 +177,19 @@
 bibtex_bibfiles = ['refs.bib']
 bibtex_reference_style = 'author_year'
 
+# ----------------------------------------------------------------------
+# Options for *linkcode* extension - from scikit-learn doc
+# ----------------------------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/extensions/linkcode.html#module-sphinx.ext.linkcode
+# CREDITS: https://github.com/scikit-learn/scikit-learn/blob/c5497b7f7eacfaff061cf68e09bcd48aa93d4d6b/doc/sphinxext/github_link.py
+linkcode_resolve = make_linkcode_resolve(
+    "gridmarthe",
+    (
+        git_repo_url +
+        "-/blob/{revision}/"
+        "src/{package}/{path}#L{lineno}"
+    ),
+)
 
 # ----------------------------------------------------------------------
 # Options for *sphinx.ext.intersphinx* extension
diff --git a/docs/source/getting_started/install.rst b/docs/source/getting_started/install.rst
index d3f92d7..c489ee8 100644
--- a/docs/source/getting_started/install.rst
+++ b/docs/source/getting_started/install.rst
@@ -4,7 +4,8 @@ Installation
 From pip
 ~~~~~~~~
 
-`gridmarthe` is available on PyPi and can be installed with:
+``gridmarthe`` is available on `PyPi <https://pypi.org/project/gridmarthe/>`_
+and can be installed with:
 
 .. code-block:: bash
     
@@ -14,7 +15,8 @@ From pip
 From conda-forge (with conda or mamba)
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-`gridmarthe` is also available in the `conda-forge` channel. Conda users can install it with:
+``gridmarthe`` is also available in the `conda-forge <https://anaconda.org/conda-forge/gridmarthe>`_ channel.
+Conda users can install it with:
 
 .. code-block:: bash
     
@@ -41,15 +43,16 @@ Get the sources:
     cd gridmarthe
 
 Gridmarthe uses `Fortran` sources for efficient I/O operations on Marthe grid files.
-These sources need to be compiled in order to use the `lecsem` module in `gridmarthe`.
-The F90 sources are compiled with `f2py` (so make sure to have a compiler [`gfortran` 
-for example] and `make` installed on your system/python environment).
+These sources need to be compiled in order to use the `lecsem` module in ``gridmarthe``.
+The F90 sources are compiled with ``f2py`` (so make sure to have a compiler [``gfortran`` 
+for example] and ``make`` installed on your system/python environment).
 
 
 With pip
 ^^^^^^^^
 
-Then, for **developper mode** (ie *with editable flag*) just use the Makefile provided to do the compilation process and python installation.
+Then, for **developper mode** (ie *with editable flag*) just use the Makefile provided to do
+the compilation process and python installation.
 
 .. code-block:: bash
     
@@ -74,20 +77,16 @@ Alternatively, you can use a conda environment. For example with miniforge/mamba
     mamba activate gm
     pip install --no-deps .
 
-For the editable/developper mode, one can add the `-e` flag in pip command, or use `conda-build`:
+For the editable/developper mode, one can add the `-e` flag in pip command, or use ``conda-build``:
 
 .. code-block:: bash
 
     mamba env create -n gm -f environment.yml
     mamba activate gm
     mamba install conda-build
-    ## Compile lecsem lib
-    ## manual compilation
-    # cd src/gridmarthe/lecsem
-    # f2py -c lecsem.f90 edsemigl.f90 scan_grid.f90 -m lecsem --backend=meson --lower
-    # cd ../../../
-    ## or just use the makefile
+    # Compile lecsem lib
     make lib
+    # add develop path
     conda develop src/
 
 
diff --git a/docs/source/getting_started/nutshell.rst b/docs/source/getting_started/nutshell.rst
index 9b7cb45..1df4f28 100644
--- a/docs/source/getting_started/nutshell.rst
+++ b/docs/source/getting_started/nutshell.rst
@@ -12,4 +12,6 @@ and can be manage with `xarray <https://docs.xarray.dev/en/stable/>`_ (or `numpy
 functions as with "utils" functions provided by ``gridmarthe``.
 
 The package also install a command line tool, ``ncmart`` to convert Marthe Grid to netCDF format.
-Help can be found with ``ncmart -h``. A tutorial is available in the :ref:`userguide` section.
\ No newline at end of file
+Help can be found with ``ncmart -h``.
+
+Tutorials are available in the :ref:`userguide` section.
\ No newline at end of file
diff --git a/docs/source/index.rst b/docs/source/index.rst
index 299a47e..51c5b94 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -1,3 +1,5 @@
+.. SPDX-License-Identifier: GPL-3.0-or-later
+
 .. gridmarthe documentation master file, created by
    sphinx-quickstart on Mon Dec  2 15:02:14 2024.
    You can adapt this file completely to your liking, but it should at least
@@ -7,6 +9,27 @@
    `reStructuredText <https://www.sphinx-doc.org/en/master/usage/restructuredtext/index.html>`_
    documentation for details.
 
+
+   ..  This file is part of gridmarthe.
+
+   ..  gridmarthe is a python library to manage grid files for 
+   ..  MARTHE hydrogeological computer code from French Geological Survey (BRGM).
+   ..  Copyright (C) 2024  BRGM
+
+   ..  This program is free software: you can redistribute it and/or modify
+   ..  it under the terms of the GNU General Public License as published by
+   ..  the Free Software Foundation, either version 3 of the License, or
+   ..  (at your option) any later version.
+
+   ..  This program is distributed in the hope that it will be useful,
+   ..  but WITHOUT ANY WARRANTY; without even the implied warranty of
+   ..  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+   ..  GNU General Public License for more details.
+
+   ..  You should have received a copy of the GNU General Public License
+   ..  along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+
 ==========
 gridmarthe
 ==========
@@ -27,8 +50,6 @@ This library is open-source and released under the GNU General Public License (v
    
  ..  to add image => :img-top: _static/index_getting_started.svg
 
-.. warning::
-   This documentation and the library itself are under heavy developpement
 
 .. grid:: 1 1 2 2 
    :gutter: 1
diff --git a/docs/source/sphinxext/COPYING b/docs/source/sphinxext/COPYING
new file mode 100644
index 0000000..e1cd01d
--- /dev/null
+++ b/docs/source/sphinxext/COPYING
@@ -0,0 +1,29 @@
+BSD 3-Clause License
+
+Copyright (c) 2007-2024 The scikit-learn developers.
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+* Redistributions of source code must retain the above copyright notice, this
+  list of conditions and the following disclaimer.
+
+* Redistributions in binary form must reproduce the above copyright notice,
+  this list of conditions and the following disclaimer in the documentation
+  and/or other materials provided with the distribution.
+
+* Neither the name of the copyright holder nor the names of its
+  contributors may be used to endorse or promote products derived from
+  this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/docs/source/sphinxext/git_link.py b/docs/source/sphinxext/git_link.py
new file mode 100644
index 0000000..7b0b663
--- /dev/null
+++ b/docs/source/sphinxext/git_link.py
@@ -0,0 +1,94 @@
+# SPDX-License-Identifier: BSD-3-Clause
+#
+# DISCLAIMER: This module is taken from scikit-learn sources
+# all credits to the sklearn authors and contributors.
+# and huge thanks to them.
+# source: https://github.com/scikit-learn/scikit-learn/blob/c5497b7f7eacfaff061cf68e09bcd48aa93d4d6b/doc/sphinxext/github_link.py
+# License: BSD-3 Clause
+# See the COPYING file from this directory: ./COPYING
+
+
+import inspect
+import os
+import subprocess
+import sys
+from functools import partial
+from operator import attrgetter
+
+REVISION_CMD = "git rev-parse --short HEAD"
+
+
+def _get_git_revision():
+    try:
+        revision = subprocess.check_output(REVISION_CMD.split()).strip()
+    except (subprocess.CalledProcessError, OSError):
+        print("Failed to execute git to get revision")
+        return None
+    return revision.decode("utf-8")
+
+
+def _linkcode_resolve(domain, info, package, url_fmt, revision):
+    """Determine a link to online source for a class/method/function
+
+    This is called by sphinx.ext.linkcode
+
+    An example with a long-untouched module that everyone has
+    >>> _linkcode_resolve('py', {'module': 'tty',
+    ...                          'fullname': 'setraw'},
+    ...                   package='tty',
+    ...                   url_fmt='https://hg.python.org/cpython/file/'
+    ...                           '{revision}/Lib/{package}/{path}#L{lineno}',
+    ...                   revision='xxxx')
+    'https://hg.python.org/cpython/file/xxxx/Lib/tty/tty.py#L18'
+    """
+
+    if revision is None:
+        return
+    if domain not in ("py", "pyx"):
+        return
+    if not info.get("module") or not info.get("fullname"):
+        return
+
+    class_name = info["fullname"].split(".")[0]
+    module = __import__(info["module"], fromlist=[class_name])
+    obj = attrgetter(info["fullname"])(module)
+
+    # Unwrap the object to get the correct source
+    # file in case that is wrapped by a decorator
+    obj = inspect.unwrap(obj)
+
+    try:
+        fn = inspect.getsourcefile(obj)
+    except Exception:
+        fn = None
+    if not fn:
+        try:
+            fn = inspect.getsourcefile(sys.modules[obj.__module__])
+        except Exception:
+            fn = None
+    if not fn:
+        return
+
+    fn = os.path.relpath(fn, start=os.path.dirname(__import__(package).__file__))
+    try:
+        lineno = inspect.getsourcelines(obj)[1]
+    except Exception:
+        lineno = ""
+    return url_fmt.format(revision=revision, package=package, path=fn, lineno=lineno)
+
+
+def make_linkcode_resolve(package, url_fmt):
+    """Returns a linkcode_resolve function for the given URL format
+
+    revision is a git commit reference (hash or name)
+
+    package is the name of the root module of the package
+
+    url_fmt is along the lines of ('https://github.com/USER/PROJECT/'
+                                   'blob/{revision}/{package}/'
+                                   '{path}#L{lineno}')
+    """
+    revision = _get_git_revision()
+    return partial(
+        _linkcode_resolve, revision=revision, package=package, url_fmt=url_fmt
+    )
diff --git a/docs/source/user_guide/example/cli.ipynb b/docs/source/user_guide/example/cli.ipynb
index 1b206e1..304a365 100644
--- a/docs/source/user_guide/example/cli.ipynb
+++ b/docs/source/user_guide/example/cli.ipynb
@@ -78,7 +78,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
     "vscode": {
      "languageId": "shellscript"
@@ -143,7 +143,7 @@
     }
    ],
    "source": [
-    "# print variables headers and dimensions with nco tools\n",
+    "# print variables headers and dimensions with netcdf/nco tools\n",
     "!ncdump -h ./data/chasim_hallue.nc"
    ]
   }
diff --git a/docs/source/user_guide/example/data/chasim_hallue.nc b/docs/source/user_guide/example/data/chasim_hallue.nc
index d821003b59148206d7338bd6639b319ff653b5c3..efebfe3ffc8fa02dc8bd3a5583ce2c74a4077feb 100644
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diff --git a/docs/source/user_guide/example/gigogne.ipynb b/docs/source/user_guide/example/gigogne.ipynb
index 114c845..50b563b 100644
--- a/docs/source/user_guide/example/gigogne.ipynb
+++ b/docs/source/user_guide/example/gigogne.ipynb
@@ -91,7 +91,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -106,7 +106,7 @@
     }
    ],
    "source": [
-    "gm.plot_nested_grid(ds2d, var='permeab')\n",
+    "gm.plot_nested_grid(ds2d, varname='permeab')\n",
     "plt.show()"
    ]
   }
diff --git a/docs/source/user_guide/example/gis.ipynb b/docs/source/user_guide/example/gis.ipynb
index c10d6b7..5bde7f7 100644
--- a/docs/source/user_guide/example/gis.ipynb
+++ b/docs/source/user_guide/example/gis.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# GIS interoperability and export (shapefile)\n",
+    "# GIS interoperability and export (shapefile, raster)\n",
     "This notebook shows how to export gridmarthe features to common GIS format.\n"
    ]
   },
@@ -17,7 +17,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -26,23 +26,227 @@
     "import gridmarthe as gm"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Shapefile, step 1: conversion\n",
+    "\n",
+    "``gridmarthe`` use the ``geopandas`` API to convert grids to a geodataframe object."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/mnt/d/home/gridmarthe/src/gridmarthe/operasem/gis.py:65: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
+      "  if 'time' in ds.dims.keys():\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>charge</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "      <th>dx</th>\n",
+       "      <th>dy</th>\n",
+       "      <th>time</th>\n",
+       "      <th>geometry</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>zone</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>9999.0</td>\n",
+       "      <td>596.75</td>\n",
+       "      <td>2568.75</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>2012-07-01</td>\n",
+       "      <td>POLYGON ((596.5 2568.5, 597 2568.5, 597 2569, ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>9999.0</td>\n",
+       "      <td>597.25</td>\n",
+       "      <td>2568.75</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>2012-07-01</td>\n",
+       "      <td>POLYGON ((597 2568.5, 597.5 2568.5, 597.5 2569...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>9999.0</td>\n",
+       "      <td>597.75</td>\n",
+       "      <td>2568.75</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>2012-07-01</td>\n",
+       "      <td>POLYGON ((597.5 2568.5, 598 2568.5, 598 2569, ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>9999.0</td>\n",
+       "      <td>598.25</td>\n",
+       "      <td>2568.75</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>2012-07-01</td>\n",
+       "      <td>POLYGON ((598 2568.5, 598.5 2568.5, 598.5 2569...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>9999.0</td>\n",
+       "      <td>598.75</td>\n",
+       "      <td>2568.75</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>2012-07-01</td>\n",
+       "      <td>POLYGON ((598.5 2568.5, 599 2568.5, 599 2569, ...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      charge       x        y   dx   dy       time  \\\n",
+       "zone                                                 \n",
+       "1     9999.0  596.75  2568.75  0.5  0.5 2012-07-01   \n",
+       "2     9999.0  597.25  2568.75  0.5  0.5 2012-07-01   \n",
+       "3     9999.0  597.75  2568.75  0.5  0.5 2012-07-01   \n",
+       "4     9999.0  598.25  2568.75  0.5  0.5 2012-07-01   \n",
+       "5     9999.0  598.75  2568.75  0.5  0.5 2012-07-01   \n",
+       "\n",
+       "                                               geometry  \n",
+       "zone                                                     \n",
+       "1     POLYGON ((596.5 2568.5, 597 2568.5, 597 2569, ...  \n",
+       "2     POLYGON ((597 2568.5, 597.5 2568.5, 597.5 2569...  \n",
+       "3     POLYGON ((597.5 2568.5, 598 2568.5, 598 2569, ...  \n",
+       "4     POLYGON ((598 2568.5, 598.5 2568.5, 598.5 2569...  \n",
+       "5     POLYGON ((598.5 2568.5, 599 2568.5, 599 2569, ...  "
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "path_to_data = './data'\n",
+    "ds = gm.load_marthe_grid(f'{path_to_data}/chasim_hallue.out', 'CHARGE', fpastp=f'{path_to_data}/hallue.pastp').isel(time=-1)\n",
+    "gdf = ds.mart.to_geodataframe()  # equivalent to: gm.to_geodataframe(ds)\n",
+    "gdf.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Shapefile, step 2: export"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "ds = gm.load_marthe_grid('./data/chasim_hallue.out', 'CHARGE', fpastp='./data/chasim_hallue.pastp').isel(time=-1)\n",
-    "ds.mart.to_geodataframe()  # or gm.to_geodataframe(ds)"
+    "# gdf.to_file('chasim.shp')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Export to raster\n",
+    "\n",
+    "For one time step, user can export a regular grid as a TIFF file with function ``glm.to_raster``\n",
+    "For all time steps at once, use ``ds.mart.to_raster(filename_tpl='chasim_hallue')``, the filename template\n",
+    "argument must not contain any extension.\n",
+    "\n",
+    "CAUTION: this is only for regular grids. For irregular/nested grids,\n",
+    "the QGIS plugin PostMARTHE is preferable to save chasim as .tiff\n",
+    "It will save the results in raster file with the smallest resolution\n",
+    "available in all nested grids."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on function to_raster in module gridmarthe.operasem.gis:\n",
+      "\n",
+      "to_raster(da, x_dim='x', y_dim='y', epsg=27572, fout='raster.tiff')\n",
+      "    Write a xr.DataArray to a raster file\n",
+      "    \n",
+      "    need xarray with rioxarray installed.\n",
+      "    Only for regular grids.\n",
+      "    TODO: add support for irregular grids, using PostMARTHE QGIS plugin code.\n",
+      "    \n",
+      "    Parameters\n",
+      "    ----------\n",
+      "    da : xarray.DataArray\n",
+      "        The DataArray to write to a raster file (only 2D, i.e. no time dimension, select\n",
+      "        a variable and timestep before).\n",
+      "    x_dim : str, optional\n",
+      "        The name of the x dimension, by default 'x'.\n",
+      "    y_dim : str, optional\n",
+      "        The name of the y dimension, by default 'y'.\n",
+      "    epsg : int, optional\n",
+      "        The EPSG code for the coordinate reference system, by default 27572.\n",
+      "    fout : str, optional\n",
+      "        The output file path for the raster file, by default 'raster.tiff'.\n",
+      "    \n",
+      "    Returns\n",
+      "    -------\n",
+      "    None\n",
+      "        The function writes the raster file and returns None.\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
-    "help(gm.to_raster())  # function doc to write a raster file\n",
+    "help(gm.to_raster)  # function doc to write a raster file\n",
     "# wrapper with time dimension : ds.mart.to_raster('chasim_hallue.tif')"
    ]
   },
@@ -57,9 +261,47 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "usage: martshp [-h] [--output OUTPUT] [--variable VARIABLE]\n",
+      "               [--xyfactor XYFACTOR] [--gpkg] [--mask] [--version]\n",
+      "               [--wide_fmt]\n",
+      "               [grid timesteps ...]\n",
+      "\n",
+      "Convert a Marthe GridFile to shapefile format.\n",
+      "\n",
+      "positional arguments:\n",
+      "  grid timesteps        Paths to grid [and timesteps if result] files are\n",
+      "                        expected\n",
+      "\n",
+      "options:\n",
+      "  -h, --help            show this help message and exit\n",
+      "  --output OUTPUT, -o OUTPUT\n",
+      "                        Output filename. Default is input.nc\n",
+      "  --variable VARIABLE, -v VARIABLE\n",
+      "                        Variable (field) to read, default is None: i.e\n",
+      "                        variable will be parsed from file and ONLY the first\n",
+      "                        variable will be read. Pass 'all' to get all\n",
+      "                        variables.\n",
+      "  --xyfactor XYFACTOR, -x XYFACTOR\n",
+      "                        Transformation factor for coordinates. Optionnal,\n",
+      "                        default is 1 (no transformation).\n",
+      "  --gpkg, -g            Use GPKG format instead of shapefile\n",
+      "  --mask, -m            Only get a mask of active domain\n",
+      "  --version, -V         Show version and exit\n",
+      "  --wide_fmt, -w        Use wide format (columns) for time\n",
+      "\n",
+      "gridmarthe  Copyright (C) 2024  BRGM.\n",
+      "This program comes with ABSOLUTELY NO WARRANTY.\n",
+      "This is free software, see GNU General Public Lisence v3 for copying.\n"
+     ]
+    }
+   ],
    "source": [
     "!martshp -h"
    ]
diff --git a/docs/source/user_guide/example/preproc.ipynb b/docs/source/user_guide/example/preproc.ipynb
index e4c9475..0545f68 100644
--- a/docs/source/user_guide/example/preproc.ipynb
+++ b/docs/source/user_guide/example/preproc.ipynb
@@ -6,8 +6,8 @@
    "source": [
     "# Command line executable to fix marthe fmt\n",
     "\n",
-    "In some older version of MARTHE, grid attributes were miswritten.\n",
-    "A fix scripts is included in `gridmarthe` if users need to read such file.\n",
+    "In some older versions of MARTHE, grid attributes were miswritten.\n",
+    "A fix script is included in `gridmarthe` if users need to read such file.\n",
     "This example show how to use this script, called `cleanmgrid`. All kind of gridfiles may not be included. Please make an issue if you appear to lack a treatment.\n",
     "\n",
     "\n",
diff --git a/docs/source/user_guide/example/treatments.ipynb b/docs/source/user_guide/example/treatments.ipynb
index 6b9b3bd..251ae47 100644
--- a/docs/source/user_guide/example/treatments.ipynb
+++ b/docs/source/user_guide/example/treatments.ipynb
@@ -916,69 +916,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "              time       permeab         x          y     dx     dy  z  \\\n",
-      "zone                                                                     \n",
-      "178171  1850-01-01  1.000000e-06  618750.0  2599850.0  500.0  500.0  2   \n",
-      "177784  1850-01-01  1.000000e-06  618750.0  2600350.0  500.0  500.0  2   \n",
-      "647989  1850-01-01  3.067630e-03  618750.0  2600850.0  500.0  500.0  6   \n",
-      "647602  1850-01-01  2.484310e-03  618750.0  2601350.0  500.0  500.0  6   \n",
-      "882511  1850-01-01  1.770000e-07  618750.0  2601850.0  500.0  500.0  8   \n",
-      "...            ...           ...       ...        ...    ...    ... ..   \n",
-      "1389960 1850-01-01  1.000000e-06  649350.0  2605850.0  100.0  100.0  2   \n",
-      "1389653 1850-01-01  1.000000e-06  649350.0  2605950.0  100.0  100.0  2   \n",
-      "1389346 1850-01-01  1.000000e-06  649350.0  2606050.0  100.0  100.0  2   \n",
-      "1660427 1850-01-01  2.000000e-05  649350.0  2606150.0  100.0  100.0  4   \n",
-      "1660120 1850-01-01  2.000000e-05  649350.0  2606250.0  100.0  100.0  4   \n",
-      "\n",
-      "                                                  geometry  \n",
-      "zone                                                        \n",
-      "178171   POLYGON ((618500 2599600, 619000 2599600, 6190...  \n",
-      "177784   POLYGON ((618500 2600100, 619000 2600100, 6190...  \n",
-      "647989   POLYGON ((618500 2600600, 619000 2600600, 6190...  \n",
-      "647602   POLYGON ((618500 2601100, 619000 2601100, 6190...  \n",
-      "882511   POLYGON ((618500 2601600, 619000 2601600, 6190...  \n",
-      "...                                                    ...  \n",
-      "1389960  POLYGON ((649300 2605800, 649400 2605800, 6494...  \n",
-      "1389653  POLYGON ((649300 2605900, 649400 2605900, 6494...  \n",
-      "1389346  POLYGON ((649300 2606000, 649400 2606000, 6494...  \n",
-      "1660427  POLYGON ((649300 2606100, 649400 2606100, 6494...  \n",
-      "1660120  POLYGON ((649300 2606200, 649400 2606200, 6494...  \n",
-      "\n",
-      "[21025 rows x 8 columns]\n",
-      "<class 'geopandas.geodataframe.GeoDataFrame'>\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/manlaya/envs/gm/lib/python3.11/site-packages/gridmarthe/operasem/gis.py:58: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
-      "  if 'time' in ds.dims.keys():\n"
-     ]
-    }
-   ],
-   "source": [
-    "# transform to geodataframe (not necessary, just for example) \n",
-    "gdf = gm.to_geodataframe(surf)\n",
-    "print(gdf)\n",
-    "print(type(gdf))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -988,31 +931,30 @@
     }
    ],
    "source": [
-    "gm.plot_outcrop(gdf, engine='gpd')\n",
+    "# xarray version\n",
+    "toto = gm.assign_coords(surf, add_lay=False) # add lay false because it needs to be a variable to plot, not a dimension\n",
+    "gm.plot_outcrop(toto)\n",
     "plt.show()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This function also allow user to get the value of a variable in the surface layer,\n",
+    "or a subset of aquifer layers.\n",
+    "\n",
+    "For example, to get the value of your variable (groundwater head for example) in\n",
+    "the first layer encountered between 3 layers:"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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HpWrmtWmKc9fIR5yjRkRERGRSzKgREYUIcQZTyVBmIHcC0JLUezPNe+EwKPmAgRoRkcWJh9i1niOm9R6aRtJ83pm/OAxKCjBQIyKyIEfQIV5leTJmdJ3AytfFAIEU6L6ZJkATY7BGXnCOGhEREZFJMaNGRGRBnuqVeavwbzZm7ltAcc4ayWCgZjGLi/pIv9hV+qXbDh6XbddbeQEp/pTgkDMrfZfka7L3QIZcOQxvbcr1R47cfCH+kNKP3L2NHSF9nmxZDwPK3wTDZvf+bpCuJdMvjuAwKHnAoU8iIgvajThDisv6wlPxXPEfqeP0ZHSw6NW8eC/1MinUMFAjIiIiMikOfRIRWZinrJpzBwIDMm5qsmN6ZrlMPdQph8OghkhNTcWpU6fqPD9lyhQsXbrUgB4xUCMiIj+ZLTgLGlxkEHD79+/HlStXnI+PHDmCgQMH4q677jKsTxz6JCKyoN6o9LjyE7g6f038utSx/nCfa6ZEaVV+QIO0oAgIOWctYJo3b46WLVs6/+Tn56Nt27b4/e9/b1ifGKgRERERuampqcHKlSsxceJEhIWFGdYPDn2a0OKR6uZUeCvBoZbakiByRqZle7mmunbVUlt+wyiWnXfjRu59+JMJ0eP+xI5YJvOq/PXEWzz5Qq5cCFS0qeXcNat8Bq3ST684DBpwa9euxfnz5zF+/HhD+8FAjYjIghx1AZUGtGqDMy23eTJiGNL0tdPItN544w1kZWUhKSnwNRTFGKgREVnQ1Syd69wzM9dWS44Zqkuwple7psTVoAFx6tQpbN26FR9++KHRXeEcNSIiIiKx3NxcJCQk4Pbbbze6K8yoEREFE61Xd4ozVWbNXJmxT2Rddrsdubm5GDduHOrVMz5MMr4HREQUcO7zttwDMqXn+UJtQCWeJ+fp+iEXqHH4U1dbt27F6dOnMXHiRKO7AoCBGv1G7Ubnaq0+sUj2dblVod7O1YPcDwIjJiqbrT9mo9c8KLXX261Lu/5lztwDs0B8btRm5Bzn8LNNgTBo0CAIgmB0N5w4R42IiIjIpJhRIyKyIMfqTrk5aeLdCdxXgyrJThlV2kJ8zZAb1lSKddVCBgM1IiLyyKihRvfgjEOeFMoYqBERWZA4U+brSk8jAx89smWOuW+e2va0aEKv9y/1fpJjhqJole9FU9NHnfV+EBcWBD3OUSMiIiIyKWbUiIgsrDcqndtJqd1T1J2RqyzVXlN8Xu0qdsfq8D4ue/muPrEII9OUlSLxRW3G7K+eXxx19csNXdvqti8zBScGahaj9j/4hq5tNe6Jf7xtyq7PudIbr/szBONvbSgt2/RGj756a1euNIWVJoobURJFtl1RUCYXoHnaUkquZlog/00CFQiKyw/5871HTvqosy7Dm+KArGhVkuz3YMdr7t/fHe15HQLlwoKgxkCNiMjiHBk1wPesmlxgpnRSv9km/89K3+UMzsTZtNKqfA91GD3XkHScV7QqSdlcMVwNqBwBljg4k/slW+o1pdel4MY5akREREQmxYwaEZGFibNppVX5OBmgGmRGD1ur2U3Fl11NnO13BdLhe2ZLnCVTO/VEPPQpHlZlpi20MFAjIrIgcYAWKEqCMz2GPcXDmEoCNPFxgd4eT0wcoEnNQ1NCcWkPluoIShz6JCIiIjIpBmpEREHC6En8gP9Dop4yYLPSdzkn94u/1qsPSvokxzE06egry3GQPzj0aTFycxOMTPFbgdFzatxZqQSH2e6dEcwQBIk5Vnd6GwJ19Fvvf0Ol90fcD8ecMW9Dmr4OffoyF00p8XW9BYpA3e/VWgVrjvlq4vZdhkZXpdce93WRJtcj4zFQIyKyICPmqLnzNXh1DxYdNc1Kq7IxMq32udUnFkkGY2b4ZVRJkOZOvBjAfWGAL20AnsuFuJcFoeDCoU8iIiIik2JGjYgoiOk15OlLNs2XPsjtHKDHkKZSr6RNBgDMktnhRK6Ehvix+2veMmHuWThxVk3q3KIO6Rz+DBIM1IiIglig5qgFE0dQBgAPnchxeSwmHorVc8GAp2AsVIY5x1b9HrFCQ03b/KX6IhZiITIyMhAREQGbzQabzabpNbTEQI2IKIhpHaD5Oy/NH+JsW6Cya+5BWmpVHh46keN8LBWguQdScgvB5OafSbUnJrlXaAcuLJCzf/9+xMXV3QvXbDhHjYiIiMikmFGzGCNWPcnNGaHgwaExCgXuGTJxdszTEKfc0KdSvm7q7vNrji2u0l2fD5Xh0WDHQI2IKEglxwzVNABffWIRZqV7P85Bz+B/ZFq2JsOf3oIwT6/7Oh9NbkhTT85rcmspS+PQJxFRkBIHSr1R6Xd7vtYQM3KVpif+ZsYcska8iKwRL2rSFrNe5I2hgdqCBQuQkZGB2NhYJCQkYMSIESguLvZ63vnz52Gz2ZCYmIjo6Gi0a9cOGzZscL6+c+dODBs2DElJSQgLC8PatWvrtCEIAp566ikkJiaifv36GDBgAI4dO6bl2yMiIiLyi6FDn5999hlsNhsyMjJw+fJlPP744xg0aBC++uorNGzoeTluTU0NBg4ciISEBHzwwQdo1aoVTp06hcaNGzuPuXjxIrp27YqJEyfijjvu8NjO888/j//3//4fVqxYgbS0NDz55JMYPHgwvvrqK8TExOjxdomIAk6LTJqvHHNp5ea3aj0sa4SsES/ik7WPKDpWKnOmZJWnJsOmHP60LEMDtY0bN7o8Xr58ORISElBQUIC+fft6POfNN99EeXk59uzZg8jISABAamqqyzFZWVnIysqSvK4gCFiyZAmeeOIJDB8+HADw1ltvoUWLFli7di1GjRrlx7siIjInR9C2G/qVJFC64Km0Kt+l1IevQZsWw6q7EedzIKs0MJPiLejiUCi5M9VigoqK2mi/SZMmksesX78ePXv2hM1mw7p169C8eXOMHj0a2dnZiIiIUHSdEydOoKysDAMGDHA+Fx8fj8zMTOzdu9fwQM1slbm5WTeFCrNtvO4vrbNp7sGVr+TO9bUwr9IN2sXfT0ei7j1xBK3u31ul5rP5kkUTU5MVU1JfjYKfaQI1u92O6dOno1evXujUqZPkcd988w22b9+OMWPGYMOGDSgpKcGUKVNw6dIlzJ07V9G1ysrKAAAtWrRweb5FixbO19xVV1ejurra+biyMvDDCURERBRaTBOo2Ww2HDlyBLt375Y9zm63IyEhAcuWLUNERAS6d++OM2fO4IUXXlAcqKmxYMECPP3007q1T0SkB62HOR0ZL18ya75m4ZRk8Wv/9j7CsPrEIpesmtL74aiv5sisBSKL5j7s6XisWTZtXvxvf3OumpWYIlCbOnUq8vPzsXPnTiQnJ8sem5iYiMjISJdhzvT0dJSVlaGmpgZRUVFer9eyZUsAwLlz55CYmOh8/ty5c7jxxhs9njNnzhzMnDnT+biyshIpKSler0VEFIzEQ5TJMUM9DkPW1l3zraSHpyBNTXDo3g9AXfFutXPS0keddd4TX+8BkZihgZogCHjooYewZs0a7NixA2lpaV7P6dWrF/Ly8mC32xEeXltd5OjRo0hMTFQUpAFAWloaWrZsiW3btjkDs8rKSnzxxReYPNnzvITo6GhER0cre2NERCZwMmZ0QOaRllblY+Rv377FGSyt5vyJ23FtU9nCBSUBmi/7iDpqqMkFcUWrkoCuV79WkhVLH3VW+9WennAFqKUYWkfNZrNh5cqVyMvLQ2xsLMrKylBWVoZff/3VeczYsWMxZ84c5+PJkyejvLwc06ZNw9GjR/Hxxx9j/vz5sNlszmMuXLiAwsJCFBYWAqhdPFBYWIjTp08DAMLCwjB9+nQ8++yzWL9+PQ4fPoyxY8ciKSkJI0aMCMh7JyIiIvLG0IxaTk7tHIB+/fq5PJ+bm4vx48cDAE6fPu3MnAFASkoKNm3ahBkzZqBLly5o1aoVpk2bhuzsq78NHThwAP3793c+dgxZjhs3DsuXLwcAPPbYY7h48SL++te/4vz58+jduzc2btzIGmpEFDSMWJUtzkz5u0pUji/7HoszZFquqve2AtSx1ZQvmTGu7iR3hg99erNjx446z/Xs2RP79u2TPKdfv35e2w4LC8MzzzyDZ555xmsfzETtBunevgHJt8v5FURGSK3Kk3ztZMzoAPYkeCgNxnzdz9MTUwddXFhgGaZYTEBERNoLhur/UpTWUdODI4smteen2iA6IPPTyHK4KTsRERHRb86cOYN7770XTZs2Rf369dG5c2ccOHDAsP4wo0ZERLrRc56a0T5Z+4hLRs3f4WhDsmhcAeri559/Rq9evdC/f3988sknaN68OY4dO4ZrrrnGsD4xUCMiIl2511wzKy3mpZG1LVq0CCkpKcjNzXU+p6R0mJ449ElEFMSSY4aaKjgqrcoP2nlzVlS0KglFHdJR1CHd6K6Ywvr169GjRw/cddddSEhIQLdu3fD6668b2icGakRERESo3U88JycH119/PTZt2oTJkyfj4YcfxooVKwzrU5igpEYG1VFZWYn4+HhUVFQgLk7bvfTklM6WLpXhz2/NZvsNV+17Mdv7IGvRK/Mk97kMVLbLjP83pN67r0OlWq/+VDoEKp6f9snaR1zmmLmXVjFbORX3fUUBIP3rIt2vq/Rnp+O4r6Z/gtjohpr24Zfqi7hhSZbHPkRFRaFHjx7Ys2eP87mHH34Y+/fvx969ezXth1Kco0ZERD7rjUq/N3w3QwCrlHjbKPcAzZ0VgzQAKOqQHpBgzcwSExNxww03uDyXnp6O//znPwb1iIEaEVFICOaaaloRZ9I81UfzxGXVJ2oDMrMFZg5SARpd1atXLxQXF7s8d/ToUbRp08agHnGOGhEREREAYMaMGdi3bx/mz5+PkpIS5OXlYdmyZS77iQcaM2pERCTJMQRp5myc1rsUuGfT3Ic3xY+VZt7IGjIyMrBmzRrMmTMHzzzzDNLS0rBkyRKMGTPGsD4xUCMiIq8cQ6e9UQkAfs9P88YRGLrPVZN6XotgzdvcM0/Huxw3yq/LmwLnqQFDhw7F0KHmmSPJQI38YsSEXzP/Zk/Wptdny2wT4+VI9TW1Kg8nY4YCMhvFS/EnuJP6N/G2MnRWeu0KeXHwNjItW3ZT9odO5Di/3tC1LYDaeWuOrx0cc9nkgjnxggKzzlkja+AcNSIiIiKTYkaNiIi8zkXb/dtru31o05FJ05ujzyNFO/2kVk0GAOxOc83ijUzLdn69+sQivJI22WObjuyaI5smPu6V366jZHi0ti95psiqOeq8eVv96dilINSHQM2CgRoRUQhQWrNM/LV7PTB3juBDPHcN0H/+mhLiPoiHXsVDn1JBmvi1q8FYTp3X6sxREzkZM9rl/nm6l4EM3sTBWfqosyzVYSEM1IiIgkRpVb7k5Hsp3ubPOYIJR6DhKbhIdpu7JpVJ0zqYE7d3Mma0y3uVutYraZOd2bKHTuTIBmtAbTDmfpzj/FfSJjsXIHi6L+73zv35QBIHZwzSrIVz1IiIiIhMihk1IiKLU7IyUg2lmR9vQ6Ri3jJpchk+9/cjzlilVuV5nT/nyLJ5y6KJV38Ctas8Pc9Lu5pp8zQPzZf7EghK56g5sFSHOTBQI6+sVFqAyAje/o/oUfZDavK/r9fyNFzqiVzQJn7NW3Aini+mppiup746hj0dr9UGbXEu13NwD8KUENdXq1tr7eowqNx7N8NiArImDn0SERERmRQDNSIiCyqtyg948WclQ3neMke7EefMpjmGLJNjhjr/yJF73X1hQW9Uqs6muZbikB4mVbp9lJWzaUUd0p3lOsgYHPokIgpxSoc/tSC+jpYBjHs5DMfQ5+oTi4Dfaqd525nAQclqUE/nOHZDAMxTO82haFWSc44ay3NYCwM1IiJSRIvAQ67Mh1bEbY9Mc806+hKsAd4XHjhed8/WmSlIc2BwZk0c+iQiIiIyKWbUiIhCnNbDnkZlk5RcV0k2TUzNMGgwYqkO4zBQM6HS2bu8HxTkAj1JmsgfZv28JscMVdS3QM5RC5RA/5vcdvA4FqMPAGBW+i7N56hpPWTsmK8GcEjU7Dj0SUREhqwitQolq0XFgY/76li5QEhuJa1jVaz7nqG+FtJlIGZtDNSIiIiITIpDn0REQUKL4Uv3rJoVh0T1yAyKs2rilZ63HTwOAChCEtD16rHiUh3ibJuYt2yaHE+v+zIsqibL5qinFsi5ah+eehkxkZGatll16RIAICMjAxEREbDZbLDZbJpeQ0sM1IiILMyKgZRePAVo4vvjeH3kb3XV3CldaCAO2jZ0bQugNnhz7APqeE5qXpl7kCU+Ts3+oEoDNF/3+gx2+/fvR1yc/N6zZsBAjYjIgnzZvDwUiN+z+70RvyYVpGlNKuBSmkUTB19Fq5IU74LgCQvcWhvnqBERERGZFDNqFqN2mMOf37DlzjWiP0Tkmdb/r8w+rKp0Pp3jeW/3R5xtU1NvzTHkWTtv7Wr9NV+GMx3DqovRxzn/TY7e89I8tsOaagHFQI2IyOJC6Rcfb/PQ5HirK+cIztQOjzoCs1fSlG8ALw60UqvyXBYh4Le90ItWJTnnvzmGQB2PMUpVV8lCGKgREVmQnsGZWTNpcvPQlFJSBNjXbJoUb/uFnowZ7bJZulR2TLxq9CRqjylCbXZMfL4Y56QFD85RIyIiIjIpZtSIiEKYWbNnDnrUdfM0Zy05ZihmpV89ZnFRH5/adM+avZI2WfHwp7+MyJ4ZUVMtVDFQIyIKYWbd51McRPVGpfPrkxpeQ+37Fhe8dZDbvN39NccQp6cAy1PtNamyHcDVmm2eOBYjbOjaFrcdPO7X/p4s8WEcBmpBxJ/VmVzZSRT8zBiQeVJale8SnIlpvTm5FMekfk+ZNW9zzxw8BXTA1ffwCR6pc47jfXmrw+bpXF9oVvx2Xjwwr8K/NkgW56gRERERmRQzakREQcwqWTQHx1DsSaM7oiHxfDVPWThHVstldaeX7aQcZTqUzINTUo9NCU9ZuKJVSUifp0nzJIGBGhERGSoUpkmIh0EdX7vXRBMHQOmjznodBvXGtQCvf8RlQDhfLbAYqBERBRkrZNGCITiTW0AgxX016Ctpk+sWsUXt3DiX4rceru2Ne4CmJLhyX3DgqUab+LiiVUncqUBnnKNGREREZFLMqBERWZwVMmhW42sdNV9IrQYFXMttOPpwMt1zqQ5vxG3ddvC45FCo1ApQqWya+zEcBtVXmCAIgtGdsKLKykrEx8ejoqICcXFxmrZdOls63W0EPcpz+FMuhChUBGMApvT/tpHvXU2Q5usQKOC5zIe4xppUjTTx8XJDoErnpikJyLxSWKJD6c9Ox3HP/mkQYiIj/e+fSNWlS3hizWZdfn7rgRk1IiIyFTMEqOL5YUoCN1/mq4kDtIdO5Lg8VlInzdf5ad72AnVfxBDK5s2bh6efftrlufbt2+Prr782qEcM1IiIiIicOnbsiK1btzof16tnbKjEQI2IiALCKlMa5FZbakHJVlOOlaCO5321oWtb2fcR6pkzOfXq1UPLli2N7oYTV30SEZGuSqvyfQrSzBbQKQ3cxMOYanlqw5f5b7PSd+keaAa7Y8eOISkpCddeey3GjBmD06dPG9ofBmpERKQLXwO0YKFVwCb2StpknwM28l1mZiaWL1+OjRs3IicnBydOnECfPn3wyy+/GNYnDn0SERERAcjKynJ+3aVLF2RmZqJNmzZ47733MGnSJEP6xEDNIItHSq9qGpmWHcCeGCMUf8um0CW3ijEY/y8E43vSktJsm9z+oJ4wi6a9xo0bo127digpKTGsDxz6JCIivziGOLUa6jRDeQ5/yS0Y8JW/w6ik3oULF3D8+HEkJiYa1gdm1IiIgkRpVb6uQU6oZsp8LYDrKUjTes6aGDNp2nnkkUcwbNgwtGnTBmfPnsXcuXMRERGBe+65R3WblZWV2L59O9q3b4/09HSfzzc0o7ZgwQJkZGQgNjYWCQkJGDFiBIqLi72ed/78edhsNiQmJiI6Ohrt2rXDhg0bXI5ZunQpUlNTERMTg8zMTHz55Zcur/fr1w9hYWEufx588EFN3x8RERFZR2lpKe655x60b98ed999N5o2bYp9+/ahefPmitu4++678c9//hMA8Ouvv6JHjx64++670aVLF/znP//xuU+GZtQ+++wz2Gw2ZGRk4PLly3j88ccxaNAgfPXVV2jYsKHHc2pqajBw4EAkJCTggw8+QKtWrXDq1Ck0btzYeczq1asxc+ZMvPrqq8jMzMSSJUswePBgFBcXIyEhwXnc/fffj2eeecb5uEGDBrq9VyKiQHDPqjmyYP5m2gKZTdM7Mxgoeg5ZMoumj1WrVvndxs6dO/G3v/0NALBmzRoIgoDz589jxYoVePbZZ3HnnXf61J6hgdrGjRtdHi9fvhwJCQkoKChA3759PZ7z5ptvory8HHv27EHkb/t/paamuhzz0ksv4f7778eECRMAAK+++io+/vhjvPnmm5g9e7bzuAYNGpiqqB0RkZnIBWe9UYnd0G+fRK0CTCNwTlloq6ioQJMmTQDUxjl33nknGjRogNtvvx2PPvqoz+2Zao5aRUXtpq6ON+jJ+vXr0bNnT9hsNqxbtw7NmzfH6NGjkZ2djYiICNTU1KCgoABz5sxxnhMeHo4BAwZg7969Lm298847WLlyJVq2bIlhw4bhySefDFhWTW5lZ/Gg8ZKvFb7m+/i2EnL9UfubtF4r3fRo14hN4vX6ARSq84jMTO2/iZb/luIslXu7njJw7jydKz7PsUclgDoBnNR1rUDNBu2B4OgXM2vmk5KSgr1796JJkybYuHGjM0v3888/IyYmxuf2TBOo2e12TJ8+Hb169UKnTp0kj/vmm2+wfft2jBkzBhs2bEBJSQmmTJmCS5cuYe7cufjxxx9x5coVtGjRwuW8Fi1auGyqOnr0aLRp0wZJSUk4dOgQsrOzUVxcjA8//NDjdaurq1FdXe18XFlZ6ec7JiIiomAzffp0jBkzBo0aNUKbNm3Qr18/ALVDop07d/a5PdMEajabDUeOHMHu3btlj7Pb7UhISMCyZcsQERGB7t2748yZM3jhhRcwd+5cxdf761//6vy6c+fOSExMxK233orjx4+jbdu2dY5fsGABnn76aeVviIjIIFKZK1+f742rv5Ce/O1vR3bsJFyzaJ7OOxkz2uV59yyykgybUfPVApFJm5W+S9V11J5HgTFlyhRkZmbi9OnTGDhwIMLDa9dtXnvttXj22Wd9bs8UgdrUqVORn5+PnTt3Ijk5WfbYxMREREZGIiIiwvlceno6ysrKUFNTg2bNmiEiIgLnzp1zOe/cuXOy89EyMzMBACUlJR4DtTlz5mDmzJnOx5WVlUhJSVH0/oiIzCQ5ZmidIUzxY5cAzS3Y8kbp8WYcBlUS/KgZavTWrrhNT8d6Cswc54ifd++b1HVvO3jc5bF4g/aiVUken5c1r0LZcSHg0qVL6NChA/Lz8/GnP/3J5bXbb79dVZuGlucQBAFTp07FmjVrsH37dqSlpXk9p1evXigpKYHdbnc+d/ToUSQmJiIqKgpRUVHo3r07tm3b5nzdbrdj27Zt6Nmzp2S7hYWFACBZ1C46OhpxcXEuf4iIiIgcIiMjUVVVpWmbhmbUbDYb8vLysG7dOsTGxqKsrAwAEB8fj/r16wMAxo4di1atWmHBggUAgMmTJ+Of//wnpk2bhoceegjHjh3D/Pnz8fDDDzvbnTlzJsaNG4cePXrgpptuwpIlS3Dx4kXnKtDjx48jLy8Pt912G5o2bYpDhw5hxowZ6Nu3L7p06RLgu0BEpC1PQ4XiYcqTcJ3g757d8jWLJl48ILXYwFMflWbV/F0BqqRP4uzTyLRsrD6xyOV1fybtu2fExG25tyt1HU8ZNHfu13DP1Dkfu61JU5VFI0k2mw2LFi3Cv//9b9Sr53+YZWiglpNTu4TZMdHOITc3F+PHjwcAnD592jm+C9Supti0aRNmzJiBLl26oFWrVpg2bRqys6+uWhw5ciR++OEHPPXUUygrK8ONN96IjRs3OhcYREVFYevWrc4ALiUlBXfeeSeeeOIJfd8wEVEASA1jOrgEbb8FTL4GQaVV+ZCfUWyeemjuQak4CHMEL+KV71oGaVrzFtg5gjWpoVJPGJxpa//+/di2bRs2b96Mzp0716kLK7VoUUqYIAiClh0MFZWVlYiPj0dFRYWqYVC5TdlvfKDIn66p0n7z8oBfU06gN7E2W3kOM87fIfNyBGO7EVen1IbjsdTEf1+zZ75+NpUEar60qXXhXkdQNit9l/O11ScWmSo4U0su++bv+3Nk4bJGvIiTC5XPvVL6s9Nx3LN/GoSY32qmaqXq0iU8sWaz6p/f3jhG76Tk5ub61J4pFhMQERERBQNfAzFvGKgREVmc1A4BUtknX7NoDmoyvVoPf2q9Y4FjyLO06uq8tJFp2Vj828BGMGTWbjt43GV4c3FRH9nVot4UrUq62p628+aDxuXLl7Fjxw4cP34co0ePRmxsLM6ePYu4uDg0atTIp7YYqBERBRH3HQgcX7sPi+pJPBTr6IfSc8TnSbXnaFPN+5EaGi6tyhcFLLswMi3f+bVVSS0ecF9koDRocwx3ck6bvFOnTmHIkCE4ffo0qqurMXDgQMTGxmLRokWorq7Gq6++6lN7DNSIiCzOPfgQB0aevlYbsMmd52kOnNL9QN0XPHhaAOGpPaUrTMXHi1ebis9xP98MiyACQW3Q5lCbnWUdNbFp06ahR48eOHjwIJo2bep8/k9/+hPuv/9+n9tjoEZERESkkV27dmHPnj2IiopyeT41NRVnzpzxuT2fA7Vx48Zh0qRJ6Nu3r88XIyIibfia8dFqtaTU5uyOTJdUNkzObsSpOk8NqWxjsGTQxBkxxw4ESocqZ6XvQtGqJGzoWrs7j8tcNB/aCXV2ux1Xrlyp83xpaSliY2N9bs/nQK2iogIDBgxAmzZtMGHCBIwbNw6tWrXy+cLBTq78hjeFr6VLvqbXxNZtg8arOk+vsh7BUg5Dr2/+LO1Bnmg90V7uGlLPiYcme6NS0fCnFkGae7+U3gNPx7nPfzNLPThP5EpwOAIurFIeZKWPOgusuvqYxXB9N2jQICxZsgTLli0DAISFheHChQuYO3cubrvtNp/b8zlQW7t2LX744Qe8/fbbWLFiBebOnYsBAwZg0qRJGD58OCI1rndCRETKBeqXA6nASCpoU0uLNuR+eREHt1LHmTVIc+e+o4L7np5KSe39ycUEyixevBiDBw/GDTfcgKqqKowePRrHjh1Ds2bN8O677/rcnqo5as2bN8fMmTMxc+ZM/Pe//0Vubi7uu+8+NGrUCPfeey+mTJmC66+/Xk3TRERERACAQYdPoFFEhKZtXrhyBU8AyMjIQEREBGw2G2w2m2btJycn4+DBg1i1ahUOHTqECxcuYNKkSRgzZoxze0xf+LWY4LvvvsOWLVuwZcsWRERE4LbbbsPhw4dxww034Pnnn8eMGTP8aZ6IiHwQyMyP1LV82cNTit5ZNCmBGDLW+hquqzav1oVbfWKR4syXOGsGwKd5aalVeTipsK9ms3//fl12Jrh48SIaNmyIe++9V5P2fA7ULl26hPXr1yM3NxebN29Gly5dMH36dIwePdr5htesWYOJEycyUCMiIkV8Dc7c55BJPedLO3rS6zrizdZr/3Z8fXX+mqe5zS5bQI0a7fKct3lpqVV5qosmh4IWLVrg7rvvxsSJE9G7d2+/2/M5UEtMTITdbsc999yDL7/8EjfeeGOdY/r374/GjRv73TkiIrIWNZks9wUI7kGbp/lvahcP+HtOIMll4TwtIvC2Ebs4AMsa8WKd87NGvIhP1j7ifLyha1tsKGrrsS2pvWMJWLlyJZYvX44//OEPSE1NxcSJEzF27FgkJSV5P9mDcF9PePnll3H27FksXbrUY5AGAI0bN8aJEydUdYiIiIjIqkaMGIG1a9fizJkzePDBB5GXl4c2bdpg6NCh+PDDD3H58mWf2gsTBEHQqa9BrbKyEvHx8aioqPA4xr1te1vVbcuV53DMP/BVscryG3rRq6yHHL1KWujRrrff9FmCw1z0yszI/TubNRukZ2kdNasyrXgPAfn3Kh7udOepjtqGrm3xStpkr9c8GTNattyHVBsnF97utW0Hbz873Y/78rrrdVlMcFPJMa990NIrr7yCRx99FDU1NWjWrBkefPBBzJ49Gw0aNPB6LncmICIiVQL1C4O36/jaD6sEaFJz7mal75IMqFwWF+DqMQ+dyHF+7R5wOV4TH++JY16aeNjTlyAt1Jw7dw4rVqzA8uXLcerUKfz5z3/GpEmTUFpaikWLFmHfvn3YvHmz13YYqBERkc+Y1dWH0j1LR6bVfi2umwZ4XkBw28Hjslk1x/Oe5gaKA0LH1w8hR3QUAzV3H374IXJzc7Fp0ybccMMNmDJlCu69916Xufu33HIL0tOlR8/EGKgRERERaWTChAkYNWoUPv/8c2RkZHg8JikpCX/7298UtcdAjYiIFLN6Js3Mw55yxP0W16pz343AkUlzHxq97eBxvJLmuW33TJqjvVkyCZ9Zq639OdDTd99953XuWf369TF37lxF7TFQIyKyoEDs6+npelYhtXl8sJBaYHE1gLv63C8H/woAztIbWSNelKxbJw76JOfBMUiTJQ7SqqqqUFNT4/K6rwsYGKgZRI+VnVaSvFB+0qrcqtlbd/6o6ppmW9kpx2o/FOW4z6ERC4XPOqDvSkg9WflzKFUEN5iCNaD2/blmvq7OTXPcg9gRy1zO2S3TnnuGTvy8t+/bVOvixYvIzs7Ge++9h59++qnO61euXPGpPZ/rqBERERGRZ4899hi2b9+OnJwcREdH49///jeefvppJCUl4a233vK5PWbUiIjI0tkzOeIsWrBl09yJ/w1Xn1iEWem+b6klzqaJM97Mpin30Ucf4a233kK/fv0wYcIE9OnTB9dddx3atGmDd955B2PGjPGpPQZqREQhzipBWm3wId6E/GrwMDIt2+u8LXfBHLjVBllX75V4AYIUR5AWKlMS9FJeXo5rr70WQO18tPLycgBA7969MXmy98LD7hioERGFOPeARTy/S0kB1kBxr8Yvflxale1zn5Qcb6VgTu1cWrl5pMyk+e7aa6/FiRMn0Lp1a3To0AHvvfcebrrpJnz00UeIj4/3uT3OUSMiIiLSyIQJE3Dw4EEAwOzZs7F06VLExMRgxowZeOyxx3xujxk1IqIgoTSj5C3zoiSLZER2Tdw390yfuIo+h+5cefv3kbpfzKapM2PGDOfXAwYMwNdff42CggI0a9YMK1eu9Lk9BmoGkdpQF6hN4UuR21zdiI3O1fJn03rMq1B1WrHMNeXKpQDAyLTAllewypwhs9Lj3vrTZqCGz5TMQwK8b1Qu9bp7EGfE5/TqvLRFzgBjcVEfjEzLdtlWSU2wZqVhTm/8KkfEAE1Tbdq0QZs2bXDw4EG88cYbWLZsmfeTRDj0SUQURBzZJbVBh7cgzsxWn1jkDNIcX5NyyTFDGaSJLFy4EGFhYZg+fbqh/WCgRkRERCSyf/9+vPbaa+jSpYvRXeHQJxGRFWk97ChV2kLPayrhnsUTV+FfXOR63NXXdgHo43zevYyHkuuoEehtveQoHQZ3HEtXXbhwAWPGjMHrr7+OZ5991ujuMFAjIiLvtcbMOG9Sbq6v+DXH196CUF8DFrm5fIA1AiCXPqqc/xtsbDYbbr/9dgwYMMCnQO2OO+6Qff38+fOq+sNAjYiILMmRKZML2BwLDTwRLzqonc92NfPm3qZUbTmrYoDm2apVq/Df//4X+/fv9/lcbzXS4uPjMXbsWJ/bZaBGREREIe/bb7/FtGnTsGXLFsTExPh8fm5urg69YqBmmG19m8m8Oj5Q3bAkv0p7SLjxgSL5Azara9dKJTj06qsRNa30KMHhDyuvpHQwagh0cVEfyW2jpI4BxP2su/LTsRp0Vvoul3luDp4ydGYeAlZCMhPIbJpTQUEBvv/+e/zud79zPnflyhXs3LkT//znP1FdXY2IiIiA94uBGhGRBRkVOAS6jtrItGyPwRQgPeQp7pf7LwqBKNlhluDb/TPC4U55t956Kw4fPuzy3IQJE9ChQwdkZ2cbEqQBDNSIiCxNap/OQF9bSdZQ675JzVGTm0fmGrhJz22TIt4Y3irZNbMEjmYXGxuLTp06uTzXsGFDNG3atM7zgcQ6akREREQmxYwaEZGFqSkroeW1vRH3zZd+empber6jb5kxcT88tVlalS3ZV3H2zj1zZ5nMFYc9FduxY4fRXWCgRkRkReIAQc8hOKmaYHovkBAPl+pVpFZJcV9P71tt8Gk4BmiWxEBNJ2bbIN2f/shtBC/n1p0/Sr4mv+pVfbty/Lmm2nuAzdaYwwLo98Ne7eRtudpYfm04rcMPVn/aVBvweHotEAGbv22ouVee5rj58/59zQSKz7FUYCbGIM2yOEeNiIiIyKSYUSMiooCQWo3pLUvl7zwwf2sEijOBnJNGgcZAjYjI4sxWJsI9mPE2bOhpSFTNe5IqFyJ3fakAzP2cYNtCiqyDQ59EREREJsWMGhER6Ubp6lQts1T+tiXXZ/fXTD38ySHPoMBAjYiILMPfIVEtMUijQGCgRl6pLYchx1u5ELlyGP6U2VBLdUkQlWU9vN2fQG/27s/+iGo3ZS+tUr+Ze6B/gBpZLoTzpfwTdPePAVrQ4Rw1IiIiIpNioEZERCGltCo/+DJpALNpQYpDn0REFLSUluTwt021TL8ggQzHQI2IyIKCMiOkE6maaFq15y+/22MmLahx6JOIiIjIpJhRIyIiyar+cseJyW2tpNUuA0r7KHVtK2Qhfc6uMZsW9Bio6cSflPjioj6Sr6ktdeAPNd+0vfF63mbpa8qV7tCL3D2Q649cWQ+5MiPe3mPyH2S+Oc/eJfmS2jIbRnzu/Pk/pMdnVo4ve1Wahdr7IBWQybXn65BjoMvPqKXV/DJP98f9fda5DgO0kMFAjYjIgtRkl3xtW6921Z6n5f6f/tB6bpqSfURdAuSF0r/MB5txs+ohon6Epm1e+TUMmAxkZGQgIiICNpsNNptN02toiYEaERERhZz9+/cjLi7O6G54xUCNiMji5LJGemXeAlVSQst9O7Xi7ypNr8OaRCKGrvpcsGABMjIyEBsbi4SEBIwYMQLFxcVezzt//jxsNhsSExMRHR2Ndu3aYcOGDS7HLF26FKmpqYiJiUFmZia+/PJLl9erqqpgs9nQtGlTNGrUCHfeeSfOnTun6fsjIgo0qXljWg77OYbo9Cocq2fbZqbk/YbSsCfVMjSj9tlnn8FmsyEjIwOXL1/G448/jkGDBuGrr75Cw4YNPZ5TU1ODgQMHIiEhAR988AFatWqFU6dOoXHjxs5jVq9ejZkzZ+LVV19FZmYmlixZgsGDB6O4uBgJCQkAgBkzZuDjjz/G+++/j/j4eEydOhV33HEHPv/880C8dSIi3eixEMPT/Cmt52qFCvc5dwzQSI6hgdrGjRtdHi9fvhwJCQkoKChA3759PZ7z5ptvory8HHv27EFkZCQAIDU11eWYl156Cffffz8mTJgAAHj11Vfx8ccf480338Ts2bNRUVGBN954A3l5efjDH/4AAMjNzUV6ejr27duHm2++WeN3SkREROQ7U81Rq6ioXW7cpEkTyWPWr1+Pnj17wmazYd26dWjevDlGjx6N7OxsREREoKamBgUFBZgzZ47znPDwcAwYMAB79+4FABQUFODSpUsYMGCA85gOHTqgdevW2Lt3r8dArbq6GtXV1c7HlZWVfr9fKbPSpcsrLC6SPk+uhIK3sgx6lF/w57dk2d/UDSjdobZduRIccm79w3FV5wFe+vpauuRLcp8BvcpPaDXHR6tz9ZorpLbcRCD74+2eapVN81bew1s/9FqRGkg+lylhKY6QZppAzW63Y/r06ejVqxc6deokedw333yD7du3Y8yYMdiwYQNKSkowZcoUXLp0CXPnzsWPP/6IK1euoEWLFi7ntWjRAl9//TUAoKysDFFRUS7DpY5jysrKPF53wYIFePrpp/17k0REAeYpKJArThuoPrg/72vAKlfKwspc3isDNIKJAjWbzYYjR45g9+7dssfZ7XYkJCRg2bJliIiIQPfu3XHmzBm88MILmDt3rm79mzNnDmbOnOl8XFlZiZSUFN2uR0TkL6XBj14Bj1btKsmyBUPQxiCNPDFFoDZ16lTk5+dj586dSE5Olj02MTERkZGRiIi4WgAvPT0dZWVlqKmpQbNmzRAREVFnBee5c+fQsmVLAEDLli1RU1OD8+fPu2TVxMe4i46ORnR0tMp3SEREROQ7Q8tzCIKAqVOnYs2aNdi+fTvS0tK8ntOrVy+UlJTAbrc7nzt69CgSExMRFRWFqKgodO/eHdu2bXO+brfbsW3bNvTs2RMA0L17d0RGRrocU1xcjNOnTzuPISIKZmpLYHg7x4jSGkZm09S8V0eJE4/mVTCbRi4MDdRsNhtWrlyJvLw8xMbGoqysDGVlZfj111+dx4wdO9ZlYcDkyZNRXl6OadOm4ejRo/j4448xf/58l+0fZs6ciddffx0rVqxAUVERJk+ejIsXLzpXgcbHx2PSpEmYOXMmPv30UxQUFGDChAno2bMnV3wSUdAIZCFVs9Y90/Me+LvhO/fvJCUMHfrMyckBAPTr18/l+dzcXIwfPx4AcPr0aYSHX40nU1JSsGnTJsyYMQNdunRBq1atMG3aNGRnX12xNnLkSPzwww946qmnUFZWhhtvvBEbN250WWDw8ssvIzw8HHfeeSeqq6sxePBg/Otf/9LuzXn7DzcvXlWzcitCS6ukV+15W9UptypU7lwjvjGrXREqx4iN3uVs295Wl3bVruzUbQWvDL1WQ5oxmPCHp4UBgXiPZr+PVlodyhppJMfQQE0QBK/H7Nixo85zPXv2xL59+2TPmzp1KqZOnSr5ekxMDJYuXYqlS5d67QMRERGREUyxmICIiNSRKl3hYIWMkpX5m7ljNo28YaBGRERBJdBz8zw9p3QqgXydAyIGakRERJpSuvMDs2mkhKGrPomIiIhIGjNqRERBwpG1sdKKR70FatcC8XW8Db0yk0a+YKBmELWlB0LlG68e79Ofsh5mK99x684fJV+T2wg+kHN3/BVM/w/07q97+x6H2RT+21vt3gLegzG9Alf364qvI7Wgg0GaueXk5CAnJwcnT54EAHTs2BFPPfUUsrKyDOsTAzUiIgsL1H6agaYkuBIHQ0b8EiK1aMBT3xmgWUNycjIWLlyI66+/HoIgYMWKFRg+fDj+7//+Dx07djSkTwzUiIiIiAAMGzbM5fFzzz2HnJwc7Nu3j4EaEREppyQDFixD3Voc7zhHy8yhVHt1hkSZTbOkK1eu4P3338fFixcN3QecgRoREQV8AYLSQMt9rpeZgk9P89PEzzNAs6bDhw+jZ8+eqKqqQqNGjbBmzRrccMMNhvWHgRoRURAxUyDjoFWftGhHr1Wg7m0ySLOu9u3bo7CwEBUVFfjggw8wbtw4fPbZZ4YFawzUiIiIiH4TFRWF6667DgDQvXt37N+/H//4xz/w2muvGdIfBmomxNId6smV0SiGdNkKQPo8f7TfvFzVeWbLinjrj9xnT+3nWS9mu7dyfP0/bZb3ZpZ+GIXZtOBit9tRXV1t2PUZqBERWZyWgZGaoUGrBWa61VVjgGZ5c+bMQVZWFlq3bo1ffvkFeXl52LFjBzZt2mRYnxioERFZkJ7BkVSx1mCj5Xw1BmnB4fvvv8fYsWPx3XffIT4+Hl26dMGmTZswcOBAw/rEQI2IiIgIwBtvvGF0F+pgoEZERJKUDhMq3efSTMTlPtRm1phJI70xUCMiIhdKgxarb/4eqA3bifwRbnQHiIiIiMgzZtQMonZ4wIjf/lafWCT52si07AD2xDu5chj+DMmoLjFhwDDQrTt/lHxN9fCOl/ch9/q2vjJlUTar64/cZ9KbWemqT5Xkz/9LKw0VulP6vqUq+Fsdhz0pEBioERGRqmDT1/p6wRKkMUCjQGKgRkREquabeVpA4K34sdWDNQZpFGico0ZERERkUsyoERGFCD3nuPo6X0284tLMWTZHP5lJI6MwUCMiCgF6BGlaLdAJ9JCo1L3wNPzLII2MxkDNKPMqZF6Ll3xJr29mI9Okv4nLrbCz0opQvei1klIPctdUu7E64OVzUCX9OSgeNF7yNbnVq4D8D065z16pTH/0ova+q23T37Z9pcV1ApVd8xakOR8zOCOT4Bw1IiIiIpNiRo2IKEgEus6iHtfTI7Pmax1EZtPITBioERFZnF4BmtKyG2ajusCu3JQUIoMwUCMiIhdm2MPT38yakvNcVp4yi0YmxTlqRERERCbFjBoRkcVpkQEz6zCn0mFM9z4reQ8svUFWwECNvDKizIYe5QzM9MMHsNZG3v5sgi7X12JIb9gut5m7XMkPf/qjF7N99tzVKU1hgqFPT9zrrfnbPwZp5rfvVCniosM0bbOyWkA8gIyMDERERMBms8Fms2l6DS0xUCMisiC/gxQT7waghOr6cwzO6Df79+9HXFyc0d3winPUiIiIiEyKgRoRUYhRmk0zY9attCqf2TQKKRz6JCIKAWYMugKFARpZGQM1IqIg5W9wZrbFBGowSCOr49AnERERkUkxo2ZCqudf+PHbc6CHRby9R1/35tPzPH/P1YNe71OKPyVaSmVKaRS+pq7sR/s0tb0BFhdJZ1hmpe+SfM0q2SUt/i9b5b3KYSaNggUDNSIiiwvUBuaBovr9cK9OCkIc+iQisrBgWyTAII3IFQM1IiIiIpPi0CcRESnaU1OLYVFdMoDMplEQY6BGRGRBgZ6XZsq9aRmgUQgIEwRBMLoTVlRZWYn4+HhUVFRYYq8wzIuXfVntKkK9mGFCM5mXP5vE+7OCVS21/4cC9f9SLptm2j1FGaRZktKfnc7jZsfqsyn7wl8s8/Obc9SIiIiITIpDn0RE5JERNR29YiaNQgwDNSIicmG6qQcMziiEceiTiCiEOYKy5JihSI4ZqipIYwaNSD8M1IiIiIhMikOfREQhSOuaaJpn1ZhJIwMsWLAAH374Ib7++mvUr18ft9xyCxYtWoT27dsb1icGaqHCyze9ZNlztexIaNGjLIM/9NjQ3tu5xYPGS77WfvNy2XalGFFiQ44/QYoRpXHcr6nF51TTvjJII4N89tlnsNlsyMjIwOXLl/H4449j0KBB+Oqrr9CwYUND+sRAjYgoxPlSR033uooM0shAGzdudHm8fPlyJCQkoKCgAH379jWkT5yjRkRERORBRUXtLw5NmjQxrA/MqBERhRj31Z1Ks2R6bluVvLCPZm0TacFut2P69Ono1asXOnXqZFg/DM2oLViwABkZGYiNjUVCQgJGjBiB4uJi2XOWL1+OsLAwlz8xMTEux5w7dw7jx49HUlISGjRogCFDhuDYsWMux/Tr169OOw8++KDm75GIyOyUzInUKkgrrco3X502Ig9sNhuOHDmCVatWGdoPQzNqaiftxcXFuQR0YWFX9wETBAEjRoxAZGQk1q1bh7i4OLz00ksYMGBAnXbvv/9+PPPMM87HDRo00PgdEhGZk9RcNPfntQjQvAVmzKaR2UydOhX5+fnYuXMnkpNll9vpztBATe2kvbCwMLRs2dLja8eOHcO+fftw5MgRdOzYEQCQk5ODli1b4t1338Vf/vIX57ENGjSQbIeIiIhCiyAIeOihh7BmzRrs2LEDaWlpRnfJXHPUlE7au3DhAtq0aQO73Y7f/e53mD9/vjMoq66uBgCX4dDw8HBER0dj9+7dLoHaO++8g5UrV6Jly5YYNmwYnnzyScmsWnV1tbNtAKisrFT3Jq3IgFVYevz+Ujp7l+pzdV/pFiBGlIJQW4JDbSmRYKLm36u0Kl9VOZVAlQJxuSYzaWQyNpsNeXl5WLduHWJjY1FWVgYAiI+PR/369Q3pk2lWfSqdtNe+fXu8+eabWLduHVauXAm73Y5bbrkFpaWlAIAOHTqgdevWmDNnDn7++WfU1NRg0aJFKC0txXfffedsZ/To0Vi5ciU+/fRTzJkzB2+//TbuvfdeyesuWLAA8fHxzj8pKSnavXkiIj845n05giKpeWBSz4uDtEAFwQzSyIxycnJQUVGBfv36ITEx0fln9erVhvXJNBk1x6S93bt3yx7Xs2dP9OzZ0/n4lltuQXp6Ol577TX8/e9/R2RkJD788ENMmjQJTZo0QUREBAYMGICsrCwIguA8769//avz686dOyMxMRG33norjh8/jrZt29a57pw5czBz5kzn48rKSgZrREREQUQcJ5iFKQI1fybtRUZGolu3bigpKXE+1717dxQWFqKiogI1NTVo3rw5MjMz0aNHD8l2MjMzAQAlJSUeA7Xo6GhER0f71DciIr0oyXyJh0Hljhcfp3UJjjrtsaAtkU8MHfoUBAFTp07FmjVrsH37dlWT9q5cuYLDhw8jMTGxzmvx8fFo3rw5jh07hgMHDmD48OGS7RQWFgKAx3aIiKxKSTkMveanMUgj8p+hGTUlk/bGjh2LVq1aYcGCBQCAZ555BjfffDOuu+46nD9/Hi+88AJOnTrlskjg/fffR/PmzdG6dWscPnwY06ZNw4gRIzBo0CAAwPHjx5GXl4fbbrsNTZs2xaFDhzBjxgz07dsXXbp0CfBdICIyTkAWyjBAI1LN0EAtJycHQG3xWbHc3FyMHz8eAHD69GmEh19N/P3888+4//77UVZWhmuuuQbdu3fHnj17cMMNNziP+e677zBz5kycO3cOiYmJGDt2LJ588knn61FRUdi6dSuWLFmCixcvIiUlBXfeeSeeeOIJ/d4sERERkY/CBDPOnLOAyspKxMfHo6KiAnFxcUZ3hxQIpvIcalfmGfE+jOjr4iJ1KwpHpmWrOk9NOQwjBfRzwGwaiSj92ek8bnYs4qLDJI9T1YdqAfELf7HMz2/TlOcgIiLf+RJ0JccMZZBGZDGmWPVJRETqKM3WMUAjsiZm1IiIiIhMihk1IqIgZba5lUTkOwZqRERBxtAAjcOeRJpioEYhQ3ZvwXnxgeuIAnqtEjRiBabazdX9uQez0tX2V93KYDOt6jQsSGOARqQLzlEjIiIiMilm1IiILMhU88+YTSPSDQM1IiJShwEake449ElERL5jkEYUEAzUiIiIiEyKQ59ERORcuep17hszaUQBxUCNCP6VV1A7qdtMJR28sVJfg0mgFgyUVuUruxaDNAqwTlVvIFxooGmb9ur/AbgbGRkZiIiIgM1mg81m0/QaWmKgRkQU4hikUSjav38/4uLijO6GV5yjRkRERGRSzKgREZE0ZtKIDMWMGhFRiOMcRCLzYkaNiCjE1ZmjxiwakWkwo0ZERERkUsyoEQFIXthH/oB58YHpiIHkVv4ZMTRmqr0sYUwJl0By1lHz9n+BiAKKgRoRURBTEmAmL+yD5AD0hYh8x0CNiMjC1Gb6mDkjsgbOUSMiIiIyKWbUiIgsSE0mjVk0IuthRo2IKAQwSCOyJmbUiJSQqStVOnuX5GtGrPazwgpDvemxSlWv+6rniloGZ0TWx4waERERkUkxo0ZEFESYRSMKLgzUiIgsjsEZUfDi0CcRkYUxSCMKbgzUiIiIiADs3LkTw4YNQ1JSEsLCwrB27Vqju8RAjYjIipIX9mE2jUhjFy9eRNeuXbF06VKju+LEOWpEfpL9YTkvYN1wkiv3wNId1iL/7yVdMoaI1MnKykJWVpbR3XDBjBoRERGRSTFQIyIiIjIpBmpEREREJsVAjYiIiMikGKgRERERmRRXfRIREREBuHDhAkpKSpyPT5w4gcLCQjRp0gStW7c2pE8M1Ij0NE+6hEKyzGmls3dp3xeLMaLMiBHlS+RrobEEB1EgHThwAP3793c+njlzJgBg3LhxWL58uSF9YqBGREREBKBfv34QBMHobrjgHDUiIiIik2KgRkRERGRSDNSIiIiITIqBGhEREZFJMVAjIiIiMimu+iQyIfmSDfLkSnsYUfIiaMiUWiEi0gszakREREQmxUCNiIiIyKQYqBERERGZFAM1IiIiIpNioEZERERkUlz1SRRk1K8YVbeBvDHkV2Cq7y9XdhKRuTCjRkRERGRSDNSIiIiITIqBGhEREZFJMVAjIiIiMikuJlBJEAQAQGVlpcE9ISIisgbHz0zHz1Bv7NX/07wPerSppzBB6d0iF6WlpUhJSTG6G0RERJbz7bffIjlZen12VVUV0tLSUFZWpsv14+LikJiYiPDwcNhsNthsNl2uowUGairZ7XacPXsWsbGxCAsLC8g1KysrkZKSgm+//RZxcXEBuaaV8P7I4/2Rx/sjj/dHHu+PPMf9OX36NMLCwpCUlITwcPnZV1VVVaipqdGlP1FRUYiJidGlba1x6FOl8PBw2d8G9BQXF8dvBDJ4f+Tx/sjj/ZHH+yOP90defHy84vsTExNjmWBKT1xMQERERGRSDNSIiIiITIqBmoVER0dj7ty5iI6ONrorpsT7I4/3Rx7vjzzeH3m8P/J4f9TjYgIiIiIik2JGjYiIiMikGKgRERERmRQDNSIiIiKTYqCmsTNnzuDee+9F06ZNUb9+fXTu3BkHDhwAAFy6dAnZ2dno3LkzGjZsiKSkJIwdOxZnz551aaO8vBxjxoxBXFwcGjdujEmTJuHChQsuxxw6dAh9+vRBTEwMUlJS8Pzzz9fpy/vvv48OHTogJiYGnTt3xoYNG1xeFwQBTz31FBITE1G/fn0MGDAAx44d0/iOuNLi/qSmpiIsLMzlz8KFC12OCcb7AwDz5s1Dhw4d0LBhQ1xzzTUYMGAAvvjiC5c2QvXzAyi7P6H8+RF78MEHERYWhiVLlrg8H8qfHzGp+xPKn5/x48fXee9DhgxxaSOYPz+GEUgz5eXlQps2bYTx48cLX3zxhfDNN98ImzZtEkpKSgRBEITz588LAwYMEFavXi18/fXXwt69e4WbbrpJ6N69u0s7Q4YMEbp27Srs27dP2LVrl3DdddcJ99xzj/P1iooKoUWLFsKYMWOEI0eOCO+++65Qv3594bXXXnMe8/nnnwsRERHC888/L3z11VfCE088IURGRgqHDx92HrNw4UIhPj5eWLt2rXDw4EHhj3/8o5CWlib8+uuvpr4/bdq0EZ555hnhu+++c/65cOFC0N8fQRCEd955R9iyZYtw/Phx4ciRI8KkSZOEuLg44fvvv3ceE6qfH6X3J5Q/Pw4ffvih0LVrVyEpKUl4+eWXXV4L5c+Pg9z9CeXPz7hx44QhQ4a4vPfy8nKXdoL182MkBmoays7OFnr37u3TOV9++aUAQDh16pQgCILw1VdfCQCE/fv3O4/55JNPhLCwMOHMmTOCIAjCv/71L+Gaa64RqqurXa7dvn175+O7775buP32212ulZmZKTzwwAOCIAiC3W4XWrZsKbzwwgvO18+fPy9ER0cL7777rk/vQSkt7o8g1H6jdP/mKRZK96eiokIAIGzdulUQBH5+3LnfH0Hg56e0tFRo1aqVcOTIkTr3gp8f+fsjCKH9+Rk3bpwwfPhwydeD+fNjJA59amj9+vXo0aMH7rrrLiQkJKBbt254/fXXZc+pqKhAWFgYGjduDADYu3cvGjdujB49ejiPGTBgAMLDw51DOHv37kXfvn0RFRXlPGbw4MEoLi7Gzz//7DxmwIABLtcaPHgw9u7dCwA4ceIEysrKXI6Jj49HZmam8xitaXF/HBYuXIimTZuiW7dueOGFF3D58mXna6Fyf2pqarBs2TLEx8eja9euAPj5EfN0fxxC9fNjt9tx33334dFHH0XHjh3rtBHqnx9v98chVD8/ALBjxw4kJCSgffv2mDx5Mn766Sfna8H8+TESAzUNffPNN8jJycH111+PTZs2YfLkyXj44YexYsUKj8dXVVUhOzsb99xzj3Pvs7KyMiQkJLgcV69ePTRp0gRlZWXOY1q0aOFyjOOxt2PEr4vP83SM1rS4PwDw8MMPY9WqVfj000/xwAMPYP78+Xjsscecrwf7/cnPz0ejRo0QExODl19+GVu2bEGzZs2c/Q71z4/c/QFC+/OzaNEi1KtXDw8//LDHNkL98+Pt/gCh/fkZMmQI3nrrLWzbtg2LFi3CZ599hqysLFy5csXZ72D9/BiJm7JryG63o0ePHpg/fz4AoFu3bjhy5AheffVVjBs3zuXYS5cu4e6774YgCMjJyTGiuwGn1f2ZOXOm8+suXbogKioKDzzwABYsWGDpqtdK70///v1RWFiIH3/8Ea+//jruvvtufPHFF3W+QQYbre5PqH5+CgoK8I9//AP//e9/ERYWZnBvA0+r+xOqnx8AGDVqlPP4zp07o0uXLmjbti127NiBW2+91ZB+hwJm1DSUmJiIG264weW59PR0nD592uU5RxBy6tQpbNmyxSVb1LJlS3z//fcux1++fBnl5eVo2bKl85hz5865HON47O0Y8evi8zwdozUt7o8nmZmZuHz5Mk6ePAkg+O9Pw4YNcd111+Hmm2/GG2+8gXr16uGNN95w9jvUPz9y98eTUPn87Nq1C99//z1at26NevXqoV69ejh16hRmzZqF1NRUZ79D9fOj5P54EiqfH0+uvfZaNGvWDCUlJQCC+/NjJAZqGurVqxeKi4tdnjt69CjatGnjfOwIQo4dO4atW7eiadOmLsf37NkT58+fR0FBgfO57du3w263IzMz03nMzp07cenSJecxW7ZsQfv27XHNNdc4j9m2bZtL21u2bEHPnj0BAGlpaWjZsqXLMZWVlfjiiy+cx2hNi/vjSWFhIcLDw50Zk2C+P57Y7XZUV1cD4OfHE/H98SRUPj/33XcfDh06hMLCQuefpKQkPProo9i0aZPzfYXq50fJ/fEkVD4/npSWluKnn35CYmIigOD+/BjK6NUMweTLL78U6tWrJzz33HPCsWPHhHfeeUdo0KCBsHLlSkEQBKGmpkb44x//KCQnJwuFhYUuS5zFK2CGDBkidOvWTfjiiy+E3bt3C9dff73L8ubz588LLVq0EO677z7hyJEjwqpVq4QGDRrUWd5cr1494cUXXxSKioqEuXPnelze3LhxY2HdunXCoUOHhOHDh+u6vFmL+7Nnzx7h5ZdfFgoLC4Xjx48LK1euFJo3by6MHTs26O/PhQsXhDlz5gh79+4VTp48KRw4cECYMGGCEB0dLRw5csTZTqh+fpTcn1D+/HjiaQVjqH5+PHG/P6H8+fnll1+ERx55RNi7d69w4sQJYevWrcLvfvc74frrrxeqqqqc7QTr58dIDNQ09tFHHwmdOnUSoqOjhQ4dOgjLli1zvnbixAkBgMc/n376qfO4n376SbjnnnuERo0aCXFxccKECROEX375xeU6Bw8eFHr37i1ER0cLrVq1EhYuXFinL++9957Qrl07ISoqSujYsaPw8ccfu7xut9uFJ598UmjRooUQHR0t3HrrrUJxcbG2N8SNv/enoKBAyMzMFOLj44WYmBghPT1dmD9/vss3CkEIzvvz66+/Cn/605+EpKQkISoqSkhMTBT++Mc/Cl9++aVLG6H6+VFyf0L58+OJp0AtVD8/nrjfn1D+/Pzvf/8TBg0aJDRv3lyIjIwU2rRpI9x///1CWVmZSxvB/PkxSpggCIIxuTwiIiIiksM5akREREQmxUCNiIiIyKQYqBERERGZFAM1IiIiIpNioEZERERkUgzUiIiIiEyKgRoRERGRSTFQIyIiIjIpBmpEREREJsVAjYiIiMikGKgRERERmRQDNSIKCj/88ANatmyJ+fPnO5/bs2cPoqKisG3bNgN7RkSkHjdlJ6KgsWHDBowYMQJ79uxB+/btceONN2L48OF46aWXjO4aEZEqDNSIKKjYbDZs3boVPXr0wOHDh7F//35ER0cb3S0iIlUYqBFRUPn111/RqVMnfPvttygoKEDnzp2N7hIRkWqco0ZEQeX48eM4e/Ys7HY7Tp48aXR3iIj8wowaEQWNmpoa3HTTTbjxxhvRvn17LFmyBIcPH0ZCQoLRXSMiUoWBGhEFjUcffRQffPABDh48iEaNGuH3v/894uPjkZ+fb3TXiIhU4dAnEQWFHTt2YMmSJXj77bcRFxeH8PBwvP3229i1axdycnKM7h4RkSrMqBERERGZFDNqRERERCbFQI2IiIjIpBioEREREZkUAzUiIiIik2KgRkRERGRSDNSIiIiITIqBGhEREZFJMVAjIiIiMikGakREREQmxUCNiIiIyKQYqBERERGZFAM1IiIiIpP6/whjryUplk3ZAAAAAElFTkSuQmCC",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "# xarray version\n",
-    "toto = gm.assign_coords(surf, add_lay=False) # add lay false because it needs to be a variable to plot, not a dimension\n",
-    "gm.plot_outcrop(toto)\n",
-    "plt.show()"
+    "head_surf = gm.get_surface_layer(grid, aquif_layers=[6,8,9])  # get the values in the first layer between layers 6, 8 and 9"
    ]
   },
   {
@@ -1106,7 +1048,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Projection transformation\n"
+    "### Regrid (coarse/refine resolution)"
    ]
   },
   {
@@ -1117,6 +1059,18 @@
    "source": [
     "# Tutorial in construction"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Projection transformation\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
   }
  ],
  "metadata": {
diff --git a/src/gridmarthe/gridmarthe.py b/src/gridmarthe/gridmarthe.py
index 593b375..11f87e9 100644
--- a/src/gridmarthe/gridmarthe.py
+++ b/src/gridmarthe/gridmarthe.py
@@ -244,10 +244,10 @@ def load_marthe_grid(
             by default, gis attrs are added and can be modified
             
             >>> {
-    ...    'resolution_units': 'm',
-    ...    'projection'      : 'epsg:27572',
-    ...    'domain'          : 'FR-France'
-    ... }
+            ...    'resolution_units': 'm',
+            ...    'projection'      : 'epsg:27572',
+            ...    'domain'          : 'FR-France'
+            ... }
         
         engine: str, Optionnal
             Engine to use for returned object. Default is 'xarray', which return xarray.Dataset object.

From 38102ef52da52fa59ac34841e712a732113e9ccb Mon Sep 17 00:00:00 2001
From: Adrien Manlay <a.manlay@brgm.fr>
Date: Mon, 1 Sep 2025 20:44:10 +0200
Subject: [PATCH 29/31] update readme and changelog

---
 README.md                                | 25 +++++++++++-------------
 changelog.md                             | 22 ++++++++++++++++++---
 docs/source/getting_started/nutshell.rst | 12 ++++++------
 3 files changed, 36 insertions(+), 23 deletions(-)

diff --git a/README.md b/README.md
index f4e5296..9844c58 100644
--- a/README.md
+++ b/README.md
@@ -4,26 +4,26 @@
 
 # Gridmarthe
 
-Python project for (fast) Marthe grid operations.
-MARTHE is a hydrogeological modelling code developped at BRGM, French Geological Survey [[1]](#1),
-and is available at https://www.brgm.fr/en/software/marthe-modelling-software-groundwater-flows
+`gridmarthe` is a Python project for (fast) Marthe grid operations.
 
-
-**THIS IS A BETA VERSION, under development.**
+MARTHE is a hydrogeological modelling code developped at BRGM, French Geological
+Survey [(Thiery, 2020)](#references), and is available at
+https://www.brgm.fr/en/software/marthe-modelling-software-groundwater-flows
 
 
 ## gridmarthe in a nutshell
 
 `gridmarthe` allow users to read/write efficiently Marthe Grids (v9, v8, constant_data, etc.)
-for any MARTHE variable.
+with python, for any MARTHE variable.
 
 With the `gridmarthe` API, data are stored in a `xarray` dataset, and can be manage with
-`xarray` (or `numpy`) functions as with "utils" functions provided by `gridmarthe`.
+`xarray` functions (or `numpy`). Specific treatments/functions are also provided by `gridmarthe`.
+
+The package also install different command line tools: `ncmart` to convert Marthe Grid to netCDF format,
+`martshp` to convert in shapefile/geopackage, `cleanmgrid` to fix marthe grid format.
 
-The package also install a command line tool, `ncmart` to convert Marthe Grid to netCDF format.
-Help can be found with `ncmart -h`.
+Full documentation and tutorials can be founded at https://gridmarthe.readthedocs.io
 
-Full documentation can be founded at https://gridmarthe.readthedocs.io
 
 ## Installation
 
@@ -33,7 +33,7 @@ Full documentation can be founded at https://gridmarthe.readthedocs.io
 On pip, `gridmarthe` is available for GNU/Linux, macOS and Windows for python >=3.10.
 Users can install it with:
 
-```
+```bash
 pip install gridmarthe
 ```
 
@@ -138,9 +138,6 @@ A. Manlay and J.P. Vergnes, (c) BRGM
 
 ## References
 
-<a id="1">[1]</a> 
 Thiery, D. (2020). Guidelines for MARTHE v7.8 computer code for
 hydro-systems modelling (English version) (Report BRGM/RP-69660-FR; p. 246 p.)
  <http://ficheinfoterre.brgm.fr/document/RP-69660-FR>
-
-
diff --git a/changelog.md b/changelog.md
index f915536..adc960d 100644
--- a/changelog.md
+++ b/changelog.md
@@ -1,15 +1,19 @@
+<!-- gridmarthe changelog -->
+
 v0.1.3
 ------
 
-Released on 2025-XX-XX
+Released on 2025-09-02
 
 * add geometry functions (get_mask_array, compute_geometry)
 * add reprojection functions (still experimental)
 * add `martshp` script to easily convert a marthe grid file into a shp/gpkg file in command line
 * code refactoring (lecsem module and global organization)
+* add automatic tests
 * minor fixes in plot method
-* change: zone index is reset when the `drop_nan` option is used in `load_grid_marthe()`
 * change: rename function to write raster: `to_raster()` instead of `write_raster_from_da()` 
+* change: zone index is reset when the `drop_nan` option is used in `load_grid_marthe()`. A new
+  variable 'zone_all' store the old index for the `reset_geometry()` method
 
 
 v0.1.2
@@ -27,4 +31,16 @@ v0.1.1
 
 Released on 2024-11-03.
 
-* first release
+* first release as a stand alone package
+
+
+v0.0.1
+------
+
+Unreleased - 2021-2024
+
+* Use fortran sources from Marthe with f2py to read grids, single layer, homogeneous grids (1st version from JP Vergnes)
+* Extend to multilayer, nested grid (A Manlay)
+* Python wrappers for easy read operations (AM)
+* Add write method in Fortran sources, scan var and wrappers (AM)
+* Add command line scripts, and some derived treatments (surface layer, rescale, etc.)
diff --git a/docs/source/getting_started/nutshell.rst b/docs/source/getting_started/nutshell.rst
index 1df4f28..68bc997 100644
--- a/docs/source/getting_started/nutshell.rst
+++ b/docs/source/getting_started/nutshell.rst
@@ -4,14 +4,14 @@ Gridmarthe in a nutshell
 .. warning::
     This section is under construction !
 
-``gridmarthe`` is a python library which allows users to read/write efficiently Marthe Grids (v9, v8, constant_data, etc.)
-for any MARTHE variable.
+``gridmarthe`` allow users to read/write efficiently Marthe Grids (v9, v8, constant_data, etc.)
+with python, for any MARTHE variable.
 
 With the ``gridmarthe`` API, data are stored in a `xarray dataset <https://docs.xarray.dev/en/stable/generated/xarray.Dataset.html#xarray.Dataset>`_,
-and can be manage with `xarray <https://docs.xarray.dev/en/stable/>`_ (or `numpy <https://numpy.org/doc/stable/>`_)
-functions as with "utils" functions provided by ``gridmarthe``.
+and can be manage with `xarray <https://docs.xarray.dev/en/stable/>`_ functions (or `numpy <https://numpy.org/doc/stable/>`_).
+Specific treatments/functions are also provided by `gridmarthe`.
 
-The package also install a command line tool, ``ncmart`` to convert Marthe Grid to netCDF format.
-Help can be found with ``ncmart -h``.
+The package also install different command line tools: `ncmart` to convert Marthe Grid to netCDF format,
+`martshp` to convert in shapefile/geopackage, `cleanmgrid` to fix marthe grid format.
 
 Tutorials are available in the :ref:`userguide` section.
\ No newline at end of file

From df6667cf54f00bee76a92beb7697bed2f5700d9b Mon Sep 17 00:00:00 2001
From: Adrien Manlay <a.manlay@brgm.fr>
Date: Tue, 2 Sep 2025 11:21:25 +0200
Subject: [PATCH 30/31] minor typo fixes for doc

---
 docs/source/_static/switcher.json            |  4 ++--
 docs/source/user_guide/example/gis.ipynb     |  2 +-
 docs/source/user_guide/example/preproc.ipynb | 11 +++++++++++
 src/gridmarthe/operasem/geometry.py          |  7 ++++++-
 src/gridmarthe/scripts/cleanmgrid.py         |  2 +-
 5 files changed, 21 insertions(+), 5 deletions(-)

diff --git a/docs/source/_static/switcher.json b/docs/source/_static/switcher.json
index 5c72e10..8908852 100644
--- a/docs/source/_static/switcher.json
+++ b/docs/source/_static/switcher.json
@@ -5,8 +5,8 @@
         "url": "https://gridmarthe.readthedocs.io/en/dev/"
     },
     {
-        "name": "0.1.2 (stable)",
-        "version": "v0.1.2",
+        "name": "0.1.3 (stable)",
+        "version": "stable",
         "url": "https://gridmarthe.readthedocs.io/en/stable/"
     }
 ]
diff --git a/docs/source/user_guide/example/gis.ipynb b/docs/source/user_guide/example/gis.ipynb
index 5bde7f7..133f706 100644
--- a/docs/source/user_guide/example/gis.ipynb
+++ b/docs/source/user_guide/example/gis.ipynb
@@ -199,7 +199,7 @@
     "For all time steps at once, use ``ds.mart.to_raster(filename_tpl='chasim_hallue')``, the filename template\n",
     "argument must not contain any extension.\n",
     "\n",
-    "CAUTION: this is only for regular grids. For irregular/nested grids,\n",
+    "**CAUTION**: this is only for regular grids. For irregular/nested grids,\n",
     "the QGIS plugin PostMARTHE is preferable to save chasim as .tiff\n",
     "It will save the results in raster file with the smallest resolution\n",
     "available in all nested grids."
diff --git a/docs/source/user_guide/example/preproc.ipynb b/docs/source/user_guide/example/preproc.ipynb
index 0545f68..ee00d12 100644
--- a/docs/source/user_guide/example/preproc.ipynb
+++ b/docs/source/user_guide/example/preproc.ipynb
@@ -124,6 +124,17 @@
     "!cleanmgrid -h"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "`cleanmgrid` is designed to work with single grid files or rma (Marthe Projects) files.\n",
+    "In the first case, you need to give to the program the value to fix (number of layer,\n",
+    "number of nested grids) before the argument (file to clean).\n",
+    "In the second case (rma mode), you only need to give the rma file as argument. All\n",
+    "values will be parsed from marthe files."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 7,
diff --git a/src/gridmarthe/operasem/geometry.py b/src/gridmarthe/operasem/geometry.py
index f895e43..353377a 100644
--- a/src/gridmarthe/operasem/geometry.py
+++ b/src/gridmarthe/operasem/geometry.py
@@ -223,7 +223,12 @@ def get_surface_layer(ds, aquif_layers=None):
 def search_zone(ds, i=None, j=None, x=None, y=None, z=None):
     """ search zone number in marthe grid,
     based on xy or ij (col, lig)
-    
+
+    This function can be used to search zone number from coordinates or indices.
+    You must provide either (i,j) or (x,y).
+
+    Note
+    ----
     if ds is multilayered, you need to provide the layer you want (int)
     ds should contains dx and dy
     ds should not have assigned coords (x and y are variables, zone is the dimension coordinates (with time))
diff --git a/src/gridmarthe/scripts/cleanmgrid.py b/src/gridmarthe/scripts/cleanmgrid.py
index 78d0ce8..2a2e1d3 100644
--- a/src/gridmarthe/scripts/cleanmgrid.py
+++ b/src/gridmarthe/scripts/cleanmgrid.py
@@ -116,7 +116,7 @@ def parse_args():
     return args
 
 
-def fread(file:str):
+def fread(file):
     with open(file, 'r', encoding='ISO-8859-1') as f:
         content = f.read()
     return content

From 69d7977ef8109c0e70a12c1faf57ca2a2e423d27 Mon Sep 17 00:00:00 2001
From: Adrien Manlay <a.manlay@brgm.fr>
Date: Tue, 2 Sep 2025 12:02:09 +0200
Subject: [PATCH 31/31] build: revert numpy include search command for CI build

---
 meson.build | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/meson.build b/meson.build
index 9e980f6..66c4432 100644
--- a/meson.build
+++ b/meson.build
@@ -71,7 +71,7 @@ endif
 
 
 fortran_args = fc.get_supported_arguments(fargs)
-link_args = fc.get_supported_arguments(largs)
+link_args = fc.get_supported_link_arguments(largs)
 add_project_arguments(fortran_args, language: 'fortran')
 add_project_link_arguments(link_args, language: 'fortran')
 
@@ -83,7 +83,8 @@ python_install_dir = py.get_install_dir()
 deps += [py_dep]
 
 incdir_numpy = run_command(py,
-  ['-c', 'import os; import numpy; print(os.path.relpath(numpy.get_include()))'],
+  # ['-c', 'import os; import numpy; print(os.path.relpath(numpy.get_include()))'],
+  ['-c', 'import os; os.chdir(".."); import numpy; print(numpy.get_include())'],
   check : true
 ).stdout().strip()