diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index 1f8ce97..998faa3 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -8,12 +8,12 @@ jobs: deploy-package: runs-on: ubuntu-latest steps: - - uses: actions/checkout@v4 + - uses: actions/checkout@v6 with: fetch-depth: 0 - name: Set up Python - uses: actions/setup-python@v5 + uses: actions/setup-python@v6 with: python-version: '3.x' @@ -24,7 +24,6 @@ jobs: env: POETRY_PYPI_TOKEN_PYPI: ${{ secrets.POETRY_PYPI_TOKEN_PYPI}} run: | - poetry self add "poetry-dynamic-versioning[plugin]" poetry install poetry build poetry publish diff --git a/.github/workflows/sphinx.yml b/.github/workflows/sphinx.yml index 6e9b404..fc32e41 100644 --- a/.github/workflows/sphinx.yml +++ b/.github/workflows/sphinx.yml @@ -10,12 +10,12 @@ jobs: build-sphinx-doc: runs-on: ubuntu-latest steps: - - uses: actions/checkout@v4 + - uses: actions/checkout@v6 with: fetch-depth: 0 - name: Set up Python - uses: actions/setup-python@v5 + uses: actions/setup-python@v6 with: python-version: '3.x' @@ -24,7 +24,7 @@ jobs: - name: Build HTML documentation run: | - poetry self add "poetry-dynamic-versioning[plugin]" + pip install poetry-dynamic-versioning poetry install --with docs poetry run sphinx-build docs ./docs/_build/html/ diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index abd546f..c5f4d67 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -8,16 +8,21 @@ jobs: strategy: matrix: os: [ubuntu-latest, macos-latest, windows-latest] - python-version: ['3.10', '3.11', '3.12', '3.13'] + python-version: ['3.11', '3.12', '3.13'] runs-on: ${{ matrix.os }} + + env: + POETRY_VIRTUALENVS_IN_PROJECT: "true" + POETRY_CACHE_DIR: ${{ github.workspace }}/.cache/poetry + steps: - - uses: actions/checkout@v4 + - uses: actions/checkout@v6 with: fetch-depth: 0 - name: Set up Python - uses: actions/setup-python@v5 + uses: actions/setup-python@v6 with: python-version: ${{ matrix.python-version }} @@ -26,6 +31,5 @@ jobs: - name: Run ci run: | - poetry self add "poetry-dynamic-versioning[plugin]" poetry install --without docs make ci diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index eee6df1..7f061e5 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -4,7 +4,7 @@ default_language_version: # Built-in hooks repos: - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v5.0.0 + rev: v6.0.0 hooks: - id: check-added-large-files - id: check-ast @@ -24,44 +24,34 @@ repos: # Pyupgrade - repo: https://github.com/asottile/pyupgrade - rev: v3.19.1 + rev: v3.21.2 hooks: - id: pyupgrade # Conventional commit - repo: https://github.com/compilerla/conventional-pre-commit - rev: v4.0.0 + rev: v4.4.0 hooks: - id: conventional-pre-commit stages: [commit-msg] args: [] # Ruff -# We put this hook before Black hook, as autofix results may need to be reformatted by Black linter - repo: https://github.com/astral-sh/ruff-pre-commit - rev: v0.11.4 + rev: v0.15.7 hooks: - - id: ruff - args: [ --fix, --exit-non-zero-on-fix ] - exclude: ^(tests|docs)/ -# Black -- repo: https://github.com/psf/black - rev: 25.1.0 - hooks: - - id: black -# Isort -- repo: https://github.com/pycqa/isort - rev: 6.0.1 - hooks: - - id: isort - exclude: ^.*/?setup\.py$ + # Run the linter. + - id: ruff-check + args: [ --fix, --exit-non-zero-on-fix ] + # Run the formatter. + - id: ruff-format + # MyPy - repo: https://github.com/pre-commit/mirrors-mypy - rev: v1.15.0 # Use the sha / tag you want to point at + rev: v1.19.1 # Use the sha / tag you want to point at hooks: - id: mypy args: [--ignore-missing-imports] - files: ^statsplotly/ additional_dependencies: - "pydantic>=2.4" - "numpy" diff --git a/Makefile b/Makefile index b9a565b..6ca5885 100644 --- a/Makefile +++ b/Makefile @@ -5,7 +5,7 @@ PYTHON_SHELL_VERSION := $(shell python --version | cut -d " " -f 2) POETRY_AVAILABLE := $(shell which poetry > /dev/null && echo 1 || echo 0) # CI variables -CI_EXCLUDED_DIRS = __pycache__ dist tests docs +CI_EXCLUDED_DIRS = __pycache__ dist docs CI_DIRECTORIES=$(filter-out $(CI_EXCLUDED_DIRS), $(foreach dir, $(dir $(wildcard */)), $(dir:/=))) # Project targets @@ -33,13 +33,21 @@ endif # CI targets lint-%: @echo lint-"$*" - @poetry run black --check "$*" - @poetry run isort --check "$*" @poetry run ruff check "$*" + @poetry run ruff format --check "$*" @echo " ✅ All good" lint: $(addprefix lint-, $(CI_DIRECTORIES)) + +fix-%: + @echo fix-"$*" + @poetry run ruff check --fix "$*" + @poetry run ruff format "$*" + @echo " ✅ All fixed" + +fix: $(addprefix fix-, $(CI_DIRECTORIES)) ci + typecheck-%: @echo typecheck-"$*" @poetry run mypy "$*" @@ -67,7 +75,7 @@ run-pre-commit: # Documentation update-doc: - @poetry run sphinx-apidoc --module-first --no-toc --force -o docs/source $(PROJECT_NAME) + @poetry run sphinx-apidoc --module-first --no-toc --force -o docs/source src/$(PROJECT_NAME) build-doc: @poetry run sphinx-build docs ./docs/_build/html/ diff --git a/README.md b/README.md index e079a14..d85e40a 100644 --- a/README.md +++ b/README.md @@ -9,8 +9,7 @@ [![Documentation](https://img.shields.io/website?label=docs&url=https://parici75.github.io/statsplotly)](https://parici75.github.io/statsplotly) ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/statsplotly) -[![Black](https://img.shields.io/badge/Code%20style-Black-black)](https://black.readthedocs.io/en/stable/) -[![linting - Ruff](https://img.shields.io/badge/Linting-Ruff-yellow)](https://docs.astral.sh/ruff/) +[![linting - Ruff](https://img.shields.io/badge/Linting_&_Formatting-Ruff-151B54)](https://docs.astral.sh/ruff/) [![mypy](https://img.shields.io/badge/mypy-checked-blue)](https://mypy.readthedocs.io/en/stable/index.html#) [![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://pre-commit.com/) [![CI](https://github.com/Parici75/statsplotly/actions/workflows/test.yml/badge.svg)](https://github.com/Parici75/statsplotly/actions/workflows/test.yml) @@ -95,7 +94,7 @@ On the Jupyter server, select the created kernel in “Kernel” -> “Change ke The Makefile provides several targets to assist in development and code quality : - `init` creates a project-specific virtual environment and installs the dependencies of the `poetry.lock` file. -- `ci` launches Black, Ruff, mypy and pytest on your source code. +- `ci` launches Ruff, mypy and pytest on your source code. - `pre-commit` set up and run pre-commit hooks (see pre-commit [documentation](https://pre-commit.com/)). - `update-doc` and `build-doc` generates documentation from source code and builds it with [Sphinx](https://www.sphinx-doc.org/en/master/index.html). - `coverage` generates code [coverage](https://coverage.readthedocs.io/en/7.6.4/) report. diff --git a/docs/conf.py b/docs/conf.py index 0542813..a08e1d9 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -12,7 +12,7 @@ import os import sys -sys.path.insert(0, os.path.abspath("../")) +sys.path.insert(0, os.path.abspath("../src")) # -- Project information ----------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information diff --git a/docs/notebooks/barplot.ipynb b/docs/notebooks/barplot.ipynb index a321c1a..01f3a1f 100644 --- a/docs/notebooks/barplot.ipynb +++ b/docs/notebooks/barplot.ipynb @@ -12,9 +12,10 @@ }, "source": [ "# Bar plots\n", + "\n", "A bar plot uses bars of different heights or colors to compare categorical data across different groups or categories.\n", "\n", - "Bar plots are often used to represent a measure of central tendency, with an estimation of the associated error." + "Bar plots are often used to represent a measure of central tendency, with an estimation of the associated error.\n" ] }, { @@ -51,6 +52,7 @@ "outputs": [], "source": [ "import plotly.express as px\n", + "\n", "import statsplotly" ] }, @@ -82,9 +84,9 @@ "source": [ "## Controlling bar colors\n", "\n", - "Color can be specified independently of the slicer by providing the `color` parameter. \n", + "Color can be specified independently of the slicer by providing the `color` parameter.\n", "\n", - "To keep track of data slices, the `slicer` identifier is indicated on the corresponding bars." + "To keep track of data slices, the `slicer` identifier is indicated on the corresponding bars.\n" ] }, { @@ -114,11 +116,11 @@ "source": [ "## Aggregating data and displaying error bars\n", "\n", - "Barplot are often used to summarize the central tendency of data. This is accomplished with the `aggregation_func` argument. Error bars can also be specified. \n", + "Barplot are often used to summarize the central tendency of data. This is accomplished with the `aggregation_func` argument. Error bars can also be specified.\n", "\n", "Supplying only one dimension is equivalent to a count plot, with optional normalization.\n", "\n", - "Below we aggregate the fraction of tips distributed each day:" + "Below we aggregate the fraction of tips distributed each day:\n" ] }, { @@ -146,9 +148,9 @@ "id": "4a8ad8c9-146b-4a4f-a10b-5e865440e5af", "metadata": {}, "source": [ - "Supplying `x`and `y` dimensions with an `aggregation_func` argument aggregate the numeric dimension across values of the other dimensions. \n", + "Supplying `x`and `y` dimensions with an `aggregation_func` argument aggregate the numeric dimension across values of the other dimensions.\n", "\n", - "Here we perform bootstrap resampling to draw a 95% confidence interval error bar:" + "Here we perform bootstrap resampling to draw a 95% confidence interval error bar:\n" ] }, { @@ -178,7 +180,7 @@ "id": "5c8d3e97-d612-4bb7-b03d-6ede22843386", "metadata": {}, "source": [ - "The `aggregation_func` and `error_bar` arguments also accepts `Callable` arguments :" + "The `aggregation_func` and `error_bar` arguments also accepts `Callable` arguments :\n" ] }, { @@ -222,9 +224,9 @@ "source": [ "## Horizontal bar plots\n", "\n", - "The numeric dimension is the default aggregated dimension. Swapping the `x` and `y` dimensions thus produces an horizontal plot. \n", + "The numeric dimension is the default aggregated dimension. Swapping the `x` and `y` dimensions thus produces an horizontal plot.\n", "\n", - "Below we plot the median with the interquartile range:" + "Below we plot the median with the interquartile range:\n" ] }, { @@ -252,15 +254,15 @@ "id": "4673ec5a-bf2b-475d-88d0-a0ad04b9f016", "metadata": {}, "source": [ - "Full details of the API : {func}`~statsplotly.barplot`." + "Full details of the API : {func}`~statsplotly.barplot`.\n" ] } ], "metadata": { "kernelspec": { - "display_name": "statsplotly", + "display_name": ".venv", "language": "python", - "name": "statsplotly" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -272,7 +274,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.5" + "version": "3.12.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/docs/notebooks/catplot.ipynb b/docs/notebooks/catplot.ipynb index acf0d1c..bdbd7e8 100644 --- a/docs/notebooks/catplot.ipynb +++ b/docs/notebooks/catplot.ipynb @@ -51,6 +51,7 @@ "outputs": [], "source": [ "import plotly.express as px\n", + "\n", "import statsplotly" ] }, diff --git a/docs/notebooks/distplot.ipynb b/docs/notebooks/distplot.ipynb index f8efac1..3777e4d 100644 --- a/docs/notebooks/distplot.ipynb +++ b/docs/notebooks/distplot.ipynb @@ -51,6 +51,7 @@ "outputs": [], "source": [ "import plotly.express as px\n", + "\n", "import statsplotly" ] }, diff --git a/docs/notebooks/heatmap.ipynb b/docs/notebooks/heatmap.ipynb index 6cc9f4a..7d18b28 100644 --- a/docs/notebooks/heatmap.ipynb +++ b/docs/notebooks/heatmap.ipynb @@ -50,9 +50,9 @@ }, "outputs": [], "source": [ + "import pandas as pd\n", "import plotly.express as px\n", "from plotly.subplots import make_subplots\n", - "import pandas as pd\n", "\n", "import statsplotly" ] diff --git a/docs/notebooks/jointplot.ipynb b/docs/notebooks/jointplot.ipynb index 5594427..ec7819c 100644 --- a/docs/notebooks/jointplot.ipynb +++ b/docs/notebooks/jointplot.ipynb @@ -51,6 +51,7 @@ "outputs": [], "source": [ "import plotly.express as px\n", + "\n", "import statsplotly" ] }, @@ -206,8 +207,6 @@ "metadata": {}, "outputs": [], "source": [ - "import pandas as pd\n", - "\n", "df = px.data.stocks().set_index(\"date\")\n", "\n", "fig = statsplotly.jointplot(\n", diff --git a/docs/notebooks/lineplot.ipynb b/docs/notebooks/lineplot.ipynb index b49bee6..4b6ff3c 100644 --- a/docs/notebooks/lineplot.ipynb +++ b/docs/notebooks/lineplot.ipynb @@ -51,6 +51,7 @@ "outputs": [], "source": [ "import plotly.express as px\n", + "\n", "import statsplotly" ] }, diff --git a/docs/notebooks/managing_subplots.ipynb b/docs/notebooks/managing_subplots.ipynb index 97c3667..3d6c008 100644 --- a/docs/notebooks/managing_subplots.ipynb +++ b/docs/notebooks/managing_subplots.ipynb @@ -213,9 +213,7 @@ " shared_grid_axis=\"rows\", plot_axis=\"yaxis\", link_axes=True\n", ").set_common_axis_limit(\n", " shared_grid_axis=\"all\", plot_axis=\"xaxis\", link_axes=True\n", - ").set_common_coloraxis(\n", - " shared_grid_axis=\"rows\"\n", - ").tidy_subplots(\n", + ").set_common_coloraxis(shared_grid_axis=\"rows\").tidy_subplots(\n", " title=\"Sex difference in response to treatment\",\n", " col_titles=[\"control\", \"treatment\"],\n", " row_titles=[\"raw data\", \"distribution\"],\n", diff --git a/docs/notebooks/scatterplot.ipynb b/docs/notebooks/scatterplot.ipynb index c2d6f9b..4f3bb46 100644 --- a/docs/notebooks/scatterplot.ipynb +++ b/docs/notebooks/scatterplot.ipynb @@ -52,6 +52,7 @@ "outputs": [], "source": [ "import plotly.express as px\n", + "\n", "import statsplotly" ] }, diff --git a/docs/source/getting_started.md b/docs/source/getting_started.md index ac4dc24..5648167 100644 --- a/docs/source/getting_started.md +++ b/docs/source/getting_started.md @@ -15,7 +15,7 @@ This independence allows to leverage the powerful interactivity offered by [plot All plotting functions return a {obj}`plotly.graph_objects.Figure` object, and must be supplied with : -- a {obj}`pandas.DataFrame`-comptatible data structure. Dictionaries or tidy (i.e., [long-form](https://en.wikipedia.org/wiki/Wide_and_narrow_data)) DataFrames are the recommended entry point. Note that hierarchical indexes are supported only on DataFrame's {obj}`~pandas.DataFrame.index`. +- a {obj}`pandas.DataFrame`-compatible data structure. Dictionaries or tidy (i.e., [long-form](https://en.wikipedia.org/wiki/Wide_and_narrow_data)) DataFrames are the recommended entry point. Note that hierarchical indexes are supported only on a DataFrame's {obj}`~pandas.DataFrame.index`. - column or index identifiers to specify `x`, `y` and `z` -when applicable- plotting dimensions. > 💡 Read more on [tidy data](https://aeturrell.github.io/python4DS/data-tidy.html). diff --git a/docs/source/statsplotly.rst b/docs/source/statsplotly.rst index 0b2b12d..974f422 100644 --- a/docs/source/statsplotly.rst +++ b/docs/source/statsplotly.rst @@ -34,6 +34,14 @@ statsplotly.exceptions module :undoc-members: :show-inheritance: +statsplotly.types module +------------------------ + +.. automodule:: statsplotly.types + :members: + :undoc-members: + :show-inheritance: + statsplotly.utils module ------------------------ diff --git a/poetry.lock b/poetry.lock index a0b213b..d949d47 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand. [[package]] name = "alabaster" @@ -6,6 +6,7 @@ version = "0.7.16" description = "A light, configurable Sphinx theme" optional = false python-versions = ">=3.9" +groups = ["dev", "docs"] files = [ {file = "alabaster-0.7.16-py3-none-any.whl", hash = "sha256:b46733c07dce03ae4e150330b975c75737fa60f0a7c591b6c8bf4928a28e2c92"}, {file = "alabaster-0.7.16.tar.gz", hash = "sha256:75a8b99c28a5dad50dd7f8ccdd447a121ddb3892da9e53d1ca5cca3106d58d65"}, @@ -17,6 +18,7 @@ version = "0.7.0" description = "Reusable constraint types to use with typing.Annotated" optional = false python-versions = ">=3.8" +groups = ["main", "dev"] files = [ {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"}, {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, @@ -28,6 +30,8 @@ version = "0.1.4" description = "Disable App Nap on macOS >= 10.9" optional = false python-versions = ">=3.6" +groups = ["dev", "docs"] +markers = "platform_system == \"Darwin\"" files = [ {file = "appnope-0.1.4-py2.py3-none-any.whl", hash = "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c"}, {file = "appnope-0.1.4.tar.gz", hash = "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee"}, @@ -35,44 +39,39 @@ files = [ [[package]] name = "asttokens" -version = "3.0.0" +version = "3.0.1" description = "Annotate AST trees with source code positions" optional = false python-versions = ">=3.8" +groups = ["dev", "docs"] files = [ - {file = "asttokens-3.0.0-py3-none-any.whl", hash = "sha256:e3078351a059199dd5138cb1c706e6430c05eff2ff136af5eb4790f9d28932e2"}, - {file = "asttokens-3.0.0.tar.gz", hash = "sha256:0dcd8baa8d62b0c1d118b399b2ddba3c4aff271d0d7a9e0d4c1681c79035bbc7"}, + {file = "asttokens-3.0.1-py3-none-any.whl", hash = "sha256:15a3ebc0f43c2d0a50eeafea25e19046c68398e487b9f1f5b517f7c0f40f976a"}, + {file = "asttokens-3.0.1.tar.gz", hash = "sha256:71a4ee5de0bde6a31d64f6b13f2293ac190344478f081c3d1bccfcf5eacb0cb7"}, ] [package.extras] -astroid = ["astroid (>=2,<4)"] -test = ["astroid (>=2,<4)", "pytest", "pytest-cov", "pytest-xdist"] +astroid = ["astroid (>=2,<5)"] +test = ["astroid (>=2,<5)", "pytest (<9.0)", "pytest-cov", "pytest-xdist"] [[package]] name = "attrs" -version = "25.3.0" +version = "26.1.0" description = "Classes Without Boilerplate" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" +groups = ["docs"] files = [ - {file = "attrs-25.3.0-py3-none-any.whl", hash = "sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3"}, - {file = "attrs-25.3.0.tar.gz", hash = "sha256:75d7cefc7fb576747b2c81b4442d4d4a1ce0900973527c011d1030fd3bf4af1b"}, + {file = "attrs-26.1.0-py3-none-any.whl", hash = "sha256:c647aa4a12dfbad9333ca4e71fe62ddc36f4e63b2d260a37a8b83d2f043ac309"}, + {file = "attrs-26.1.0.tar.gz", hash = "sha256:d03ceb89cb322a8fd706d4fb91940737b6642aa36998fe130a9bc96c985eff32"}, ] -[package.extras] -benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"] -cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] -dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit-uv", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] -docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier"] -tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] -tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"] - [[package]] name = "autodoc-pydantic" version = "2.2.0" description = "Seamlessly integrate pydantic models in your Sphinx 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"sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931"}, - {file = "zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4"}, + {file = "zipp-3.23.0-py3-none-any.whl", hash = "sha256:071652d6115ed432f5ce1d34c336c0adfd6a884660d1e9712a256d3d3bd4b14e"}, + {file = "zipp-3.23.0.tar.gz", hash = "sha256:a07157588a12518c9d4034df3fbbee09c814741a33ff63c05fa29d26a2404166"}, ] [package.extras] -check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"] +check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""] cover = ["pytest-cov"] doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] enabler = ["pytest-enabler (>=2.2)"] -test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] +test = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more_itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] type = ["pytest-mypy"] [metadata] -lock-version = "2.0" -python-versions = ">=3.10, <3.14" -content-hash = "c04cc03ad42b50ce8e7c71e777d93a357f6e3c446c465ba3c9b04356dba9db29" +lock-version = "2.1" +python-versions = ">=3.11, <3.14" +content-hash = "973900844f23a931817584dd132b4d8e63b82fde4e7be42715c569904f3157f6" diff --git a/pyproject.toml b/pyproject.toml index 241aaf3..ae5f384 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -7,9 +7,13 @@ license = "BSD-3-Clause" readme = "README.md" homepage = "https://github.com/parici75/statsplotly" documentation = "https://parici75.github.io/statsplotly/" +packages = [ + { include = "statsplotly", from = "src" } +] + [tool.poetry.dependencies] -python = ">=3.10, <3.14" +python = ">=3.11, <3.14" pydantic = "^2.6.2" pandas = ">=1.5.0" seaborn = "^0.13.2" @@ -20,9 +24,7 @@ plotly = "^5.19.0" ipykernel = "^6.24.0" pytest = "^8.0.2" mypy = "^1.8.0" -ruff = "^0.5.6" -black = "^24.2.0" -isort = "^5.13.2" +ruff = "0.15.7" pyupgrade = "^3.15.1" pre-commit = "^3.6.2" pyclean = "^2.7.3" @@ -36,58 +38,60 @@ furo = "^2023.5.20" myst = "^1.0.4" myst-nb = "^1.1.0" + [tool.poetry-dynamic-versioning] enable = true vcs = "git" style = "semver" -pattern = "^(?P\\d+\\.\\d+\\.\\d+)(-?((?P[a-zA-Z]+)\\.?(?P\\d+)?))?" +pattern = "^(?P\\d+\\.\\d+\\.\\d+)(-?((?P[a-zA-Z]+)\\.?(?P\\d+)?))?" [build-system] requires = ["poetry-core>=1.0.0", "poetry-dynamic-versioning"] build-backend = "poetry_dynamic_versioning.backend" -## Tools -[tool.black] -target-version = ['py310', 'py311', 'py312', 'py313'] -line-length = 100 -preview = true - +# Tools +## Ruff [tool.ruff] line-length = 100 target-version = "py311" -exclude = ["tests"] +cache-dir = ".cache/ruff" [tool.ruff.lint] select = [ - "E", # pycodestyle errors - "W", # pycodestyle warnings - "F", # pyflakes - "I", # isort - "UP", # pyupgrade - "C", # flake8-comprehensions - "B", # flake8-bugbear - "S", # flake8-bandit - "A", # flake8-builtins - "INP", # flake8-no-pep420 - "PIE", # flake8-pie - "PL", # pylint -] -ignore = [ - "E501", # line too long - "PLR0913", # Too many arguments to function call + "E", # pycodestyle errors + "W", # pycodestyle warnings + "F", # pyflakes + "I", # isort + "UP", # pyupgrade + "C", # flake8-comprehensions + "B", # flake8-bugbear + "S", # flake8-bandit + "A", # flake8-builtins + "INP", # flake8-no-pep420 + "PIE", # flake8-pie + "PL", # pylint + "D200", # pydocstyle, One-line docstring should fit on one line + "D400", # pydocstyle, First line should end with a period + "D403", # pydocstyle, First word of the docstring should be capitalized ] +ignore = ["PLR0913"] # Too many arguments to function call + [tool.ruff.lint.per-file-ignores] -"statsplotly/_plotting/**.py" = ["C901", "PLR0912", "PLR0915"] +"src/statsplotly/_plotting/**.py" = [ + "C901", # Allow complex structures in plottling codes + "PLR0912", # Allow many branches + "PLR0915"] # Allow many statements +"tests/*" = [ + "S101", # Allow use of assert in tests + "PLR2004" # Allow magic-value-comparisons in tests, +] +"docs/*" = ["ALL"] -[tool.isort] -profile = "black" -sections = "FUTURE,STDLIB,THIRDPARTY,FIRSTPARTY,LOCALFOLDER" [tool.mypy] -exclude = ["tests"] -plugins = [ - "pydantic.mypy", "numpy.typing.mypy_plugin" -] -cache_dir = ".mypy_cache/strict" +mypy_path = ["src"] +python_version = "3.11" +plugins = ["pydantic.mypy"] +cache_dir = ".cache/mypy/strict" show_column_numbers = true follow_imports = "normal" @@ -107,9 +111,22 @@ strict_equality = true # mypy per-module options [[tool.mypy.overrides]] -module = ["dateutil.*", "numpy.*", "scipy.*", "pandas.*", "seaborn.*", "plotly.*", "pymodules.*"] +module = [ + "dateutil.*", + "numpy.*", + "scipy.*", + "pandas.*", + "seaborn.*", + "plotly.*" +] ignore_missing_imports = true +[[tool.mypy.overrides]] +module = "tests.*" +disallow_untyped_defs = false +disallow_incomplete_defs = false +disallow_untyped_calls = false +disallow_untyped_decorators = false [tool.pydantic-mypy] init_forbid_extra = true @@ -118,6 +135,7 @@ warn_required_dynamic_aliases = true [tool.pytest.ini_options] +cache_dir = ".cache/pytest" log_cli = true log_cli_level = 10 testpaths = ["tests"] diff --git a/statsplotly/__init__.py b/src/statsplotly/__init__.py similarity index 100% rename from statsplotly/__init__.py rename to src/statsplotly/__init__.py diff --git a/statsplotly/_base.py b/src/statsplotly/_base.py similarity index 100% rename from statsplotly/_base.py rename to src/statsplotly/_base.py diff --git a/statsplotly/_plotting/__init__.py b/src/statsplotly/_plotting/__init__.py similarity index 100% rename from statsplotly/_plotting/__init__.py rename to src/statsplotly/_plotting/__init__.py diff --git a/statsplotly/_plotting/_barplot.py b/src/statsplotly/_plotting/_barplot.py similarity index 80% rename from statsplotly/_plotting/_barplot.py rename to src/statsplotly/_plotting/_barplot.py index 0035fe7..1fa61a1 100644 --- a/statsplotly/_plotting/_barplot.py +++ b/src/statsplotly/_plotting/_barplot.py @@ -1,12 +1,14 @@ -"""Bar plots""" +"""Bar plots.""" import logging -from collections.abc import Sequence +from collections.abc import Callable, Sequence +from typing import Any import numpy as np -import plotly import plotly.graph_objs as go import plotly.io as pio +from numpy.typing import NDArray +from plotly.basedatatypes import BaseTraceType from statsplotly import constants from statsplotly.exceptions import StatsPlotSpecificationError @@ -18,6 +20,7 @@ from statsplotly.plot_specifiers.data import ( AggregationSpecifier, AggregationTraceData, + AggregationType, DataDimension, DataFormat, DataHandler, @@ -25,14 +28,21 @@ TraceData, ) from statsplotly.plot_specifiers.figure import create_fig + +# Trace objects from statsplotly.plot_specifiers.layout import ( AxesSpecifier, ColoraxisReference, LegendSpecifier, ) - -# Trace objects from statsplotly.plot_specifiers.trace import OrientedPlotSpecifier +from statsplotly.types import ( + AggregationTypeLiteral, + AxisFormatLiteral, + BarModeLiteral, + ErrorBarLiteral, + PlotOrientationTypeLiteral, +) pio.templates.default = constants.DEFAULT_TEMPLATE np.seterr(invalid="ignore") @@ -44,9 +54,9 @@ def barplot( data: DataFormat, x: str | None = None, y: str | None = None, - orientation: str | None = None, + orientation: PlotOrientationTypeLiteral | None = None, slicer: str | None = None, - slice_order: list[str] | None = None, + slice_order: list[Any] | None = None, color: str | None = None, color_palette: list[str] | str | None = None, shared_coloraxis: bool = False, @@ -54,17 +64,17 @@ def barplot( logscale: float | None = None, colorbar: bool = True, text: str | None = None, - axis: str | None = None, + axis: AxisFormatLiteral | None = None, opacity: float | None = None, - barmode: str | None = None, - error_bar: str | None = None, - aggregation_func: str | None = None, + barmode: BarModeLiteral | None = None, + error_bar: ErrorBarLiteral | Callable[[Any], NDArray[Any]] | None = None, + aggregation_func: AggregationTypeLiteral | Callable[[Any], float] | None = None, x_label: str | None = None, y_label: str | None = None, title: str | None = None, x_range: Sequence[float | str] | None = None, y_range: Sequence[float | str] | None = None, - fig: go.Figure = None, + fig: go.Figure | None = None, row: int | None = None, col: int | None = None, ) -> go.Figure: @@ -74,8 +84,10 @@ def barplot( data: A :obj:`pandas.DataFrame`-compatible structure of data x: The name of the `x` dimension column in `data`. y: The name of the `y` dimension column in `data`. - orientation: A :obj:`~statsplotly.plot_specifiers.trace.PlotOrientation` value to force the orientation of the plot. - slicer: The name of the column in `data` with values to slice the data : one trace is drawn for each level of the `slicer` dimension. + orientation: A :obj:`~statsplotly.plot_specifiers.trace.PlotOrientation` value to force the + orientation of the plot. + slicer: The name of the column in `data` with values to slice the data : one trace is drawn + for each level of the `slicer` dimension. slice_order: A list of identifiers to order and/or subset data slices specified by `slicer`. color: The name of the column in `data` with values to map onto the colormap. color_palette: @@ -83,25 +95,31 @@ def barplot( - A list of CSS color names or HTML color codes. The color palette is used, by order of precedence : - - To map color data specified by the `color` parameter onto the corresponding colormap. + - To map color data specified by the `color` parameter onto the corresponding + colormap. - To assign discrete colors to `slices` of data. shared_coloraxis: If True, colorscale limits are shared across slices of data. color_limits: A tuple specifying the (min, max) values of the colormap. logscale: A float specifying the log base to use for colorscaling. colorbar: If True, draws a colorbar. - text: A string or the name of the column in `data` with values to appear in the hover tooltip. Column names can be concatenated with '+' to display values from multiple columns. Ignored when `aggregation_func` is not None. + text: A string or the name of the column in `data` with values to appear in the hover + tooltip. Column names can be concatenated with '+' to display values from multiple columns. + Ignored when `aggregation_func` is not None. axis: A :obj:`~statsplotly.plot_specifiers.layout.AxisFormat` value. opacity: A numeric value in the (0, 1) interval to specify bar opacity. barmode: A :obj:`~statsplotly.plot_specifiers.layout.BarMode` value. - error_bar: A :obj:`~statsplotly.plot_specifiers.data.ErrorBarType` value or a `Callable` taking the `x` or `y` dimension as input and returning a (inferior_limit, superior_limit) tuple. - aggregation_func: A :obj:`~statsplotly.plot_specifiers.data.AggregationType` value or a `Callable` taking the `x` or `y` dimension as input and returning a single value. + error_bar: A :obj:`~statsplotly.plot_specifiers.data.ErrorBarType` value or a `Callable` + taking the `x` or `y` dimension as input and returning a (dow, up) limit tuple. + aggregation_func: A :obj:`~statsplotly.plot_specifiers.data.AggregationType` value or a + `Callable` taking the `x` or `y` dimension as input and returning a single value. x_label: A string to label the x_axis in place of the corresponding column name in `data`. y_label: A string to label the y_axis in place of the corresponding column name in `data`. title: A string for the title of the plot. x_range: A tuple defining the (min_range, max_range) of the x_axis. y_range: A tuple defining the (min_range, max_range) of the y_axis. - fig: A :obj:`plotly.graph_obj.Figure` to add the plot to. Use in conjunction with `row` and `col`. + fig: A :obj:`plotly.graph_obj.Figure` to add the plot to. Use in conjunction with `row` and + `col`. row: An integer identifying the row to add the plot to. col: An integer identifying the column to add the plot to. @@ -140,7 +158,7 @@ def barplot( opacity=opacity, ) - traces: dict[str, plotly.basedatatypes.BaseTraceType] = {} + traces: dict[str, BaseTraceType] = {} traces_data: list[TraceData] = [] for (slice_name, slice_data), trace_color in zip( data_handler.iter_slices(), @@ -149,12 +167,12 @@ def barplot( ): trace_data: AggregationTraceData | TraceData if aggregation_specifier.aggregation_func is not None: - trace_data = AggregationTraceData.build_aggregation_trace_data( + trace_data = AggregationTraceData.build_from_aggregated_data( data=slice_data, aggregation_specifier=aggregation_specifier, ) else: - trace_data = TraceData.build_trace_data( + trace_data = TraceData.build_from_data( data=slice_data, pointer=data_handler.data_pointer ) @@ -176,13 +194,13 @@ def barplot( x_transformation=( aggregation_func if aggregation_specifier.aggregation_plot_dimension is DataDimension.X - and isinstance(aggregation_func, str) + and isinstance(aggregation_func, AggregationType) else None ), y_transformation=( aggregation_func if aggregation_specifier.aggregation_plot_dimension is DataDimension.Y - and isinstance(aggregation_func, str) + and isinstance(aggregation_func, AggregationType) else None ), error_bar=error_bar if isinstance(error_bar, str) else None, diff --git a/statsplotly/_plotting/_catplot.py b/src/statsplotly/_plotting/_catplot.py similarity index 82% rename from statsplotly/_plotting/_catplot.py rename to src/statsplotly/_plotting/_catplot.py index fb27b21..c82204f 100644 --- a/statsplotly/_plotting/_catplot.py +++ b/src/statsplotly/_plotting/_catplot.py @@ -1,13 +1,13 @@ -"""Strip/Box/Violin plots""" +"""Strip/Box/Violin plots.""" import logging from collections.abc import Sequence from typing import Any import numpy as np -import plotly import plotly.graph_objs as go import plotly.io as pio +from plotly.basedatatypes import BaseTraceType from statsplotly import constants from statsplotly.plot_objects.layout import CategoricalLayout @@ -23,17 +23,23 @@ TraceData, ) from statsplotly.plot_specifiers.figure import create_fig + +# Trace objects from statsplotly.plot_specifiers.layout import ( AxesSpecifier, ColoraxisReference, LegendSpecifier, ) - -# Trace objects from statsplotly.plot_specifiers.trace import ( CategoricalPlotSpecifier, CategoricalPlotType, ) +from statsplotly.types import ( + AxisFormatLiteral, + CategoricalPlotTypeLiteral, + NormalizationTypeLiteral, + PlotOrientationTypeLiteral, +) pio.templates.default = constants.DEFAULT_TEMPLATE np.seterr(invalid="ignore") @@ -45,26 +51,26 @@ def catplot( data: DataFormat, x: str | None = None, y: str | None = None, - orientation: str | None = None, + orientation: PlotOrientationTypeLiteral | None = None, slicer: str | None = None, - slice_order: list[str] | None = None, + slice_order: list[Any] | None = None, color: str | None = None, color_palette: list[str] | str | None = None, shared_coloraxis: bool = False, text: str | None = None, marker: str | None = None, - axis: str | None = None, + axis: AxisFormatLiteral | None = None, opacity: str | float | None = None, - plot_type: str | None = None, + plot_type: CategoricalPlotTypeLiteral | None = None, jitter: float | None = None, - normalizer: str | None = None, + normalizer: NormalizationTypeLiteral | None = None, size: float = constants.DEFAULT_MARKER_SIZE, x_label: str | None = None, y_label: str | None = None, title: str | None = None, x_range: Sequence[float | str] | None = None, y_range: Sequence[float | str] | None = None, - fig: go.Figure = None, + fig: go.Figure | None = None, row: int | None = None, col: int | None = None, ) -> go.Figure: @@ -74,8 +80,10 @@ def catplot( data: A :obj:`pandas.DataFrame`-compatible structure of data x: The name of the `x` dimension column in `data`. y: The name of the `y` dimension column in `data`. - orientation: A :obj:`~Astatsplotly.plot_specifiers.trace.PlotOrientation` value to force the orientation of the plot. - slicer: The name of the column in `data` with values to slice the data : one trace is drawn for each level of the `slicer` dimension. + orientation: A :obj:`~Astatsplotly.plot_specifiers.trace.PlotOrientation` value to force the + orientation of the plot. + slicer: The name of the column in `data` with values to slice the data : one trace is drawn + for each level of the `slicer` dimension. slice_order: A list of identifiers to order and/or subset data slices specified by `slicer`. color: The name of the column in `data` with values to map onto the colormap. color_palette: @@ -83,24 +91,30 @@ def catplot( - A list of CSS color names or HTML color codes. The color palette is used, by order of precedence : - - To map color data specified by the `color` parameter onto the corresponding colormap. + - To map color data specified by the `color` parameter onto the corresponding + colormap. - To assign discrete colors to `slices` of data. shared_coloraxis: If True, colorscale limits are shared across slices of data. - text: A string or the name of the column in `data` with values to appear in the hover tooltip. Column names can be concatenated with '+' to display values from multiple columns. - marker: A valid marker symbol or the name of the column in `data` with values to assign marker symbols. + text: A string or the name of the column in `data` with values to appear in the hover + tooltip. Column names can be concatenated with '+' to display values from multiple columns. + marker: A valid marker symbol or the name of the column in `data` with values to assign + marker symbols. axis: A :obj:`~statsplotly.plot_specifiers.layout.AxisFormat` value. - opacity: A numeric value in the (0, 1) interval or the name of the column in `data` with values to specify marker opacity. + opacity: A numeric value in the (0, 1) interval or the name of the column in `data` with + values to specify marker opacity. plot_type: A :obj:`~statsplotly.plot_specifiers.trace.CategoricalPlotType` value. jitter: A numeric value to specify jitter amount on the categorical dimension. - normalizer: A :obj:`~statsplotly.plot_specifiers.data.NormalizationType` value to normalize data on the continous dimension. + normalizer: A :obj:`~statsplotly.plot_specifiers.data.NormalizationType` value to normalize + data on the continous dimension. size: A numeric value or the name of the column in `data` with values to assign mark sizes. x_label: A string to label the x_axis in place of the corresponding column name in `data`. y_label: A string to label the y_axis in place of the corresponding column name in `data`. title: A string for the title of the plot. x_range: A tuple defining the (min_range, max_range) of the x_axis. y_range: A tuple defining the (min_range, max_range) of the y_axis. - fig: A :obj:`plotly.graph_obj.Figure` to add the plot to. Use in conjunction with row and col. + fig: A :obj:`plotly.graph_obj.Figure` to add the plot to. Use in conjunction with row and + col. row: An integer identifying the row to add the plot to. col: An integer identifying the column to add the plot to. @@ -129,7 +143,7 @@ def catplot( if jitter is not None and categorical_plot_specifier.plot_type is not CategoricalPlotType.STRIP: logger.warning( - f"Jitter parameters have no effect for {categorical_plot_specifier.plot_type.value}" + f"Jitter parameters have no effect for {categorical_plot_specifier.plot_type}" ) color_specifier = ColorSpecifier.build_from_color_data( @@ -139,6 +153,9 @@ def catplot( opacity=opacity, ) + if categorical_plot_specifier.anchored_dimension is None: + msg = "Categorical plot requires an anchored dimension." + raise ValueError(msg) data_processor = DataProcessor( data_values_map=categorical_plot_specifier.get_category_strip_map(data_handler), jitter_settings=( @@ -153,14 +170,14 @@ def catplot( normalizer={categorical_plot_specifier.anchored_dimension: normalizer}, ) - traces: dict[str, plotly.basedatatypes.BaseTraceType] = {} + traces: dict[str, BaseTraceType] = {} traces_data: list[TraceData] = [] for (slice_name, slice_data), trace_color in zip( data_handler.iter_slices(), color_specifier.get_color_hues(n_colors=data_handler.n_slices), strict=True, ): - trace_data = TraceData.build_trace_data( + trace_data = TraceData.build_from_data( data=slice_data, pointer=data_handler.data_pointer, processor=data_processor, @@ -177,6 +194,10 @@ def catplot( case CategoricalPlotType.BOX: trace_constructor = BoxTrace + case _: + msg = f"Unsupported categorical plot type: {categorical_plot_specifier.plot_type}" + raise ValueError(msg) + traces[slice_name] = trace_constructor.build_trace( trace_data=trace_data, trace_name=slice_name, diff --git a/statsplotly/_plotting/_distplot.py b/src/statsplotly/_plotting/_distplot.py similarity index 89% rename from statsplotly/_plotting/_distplot.py rename to src/statsplotly/_plotting/_distplot.py index aafcfab..7b26782 100644 --- a/statsplotly/_plotting/_distplot.py +++ b/src/statsplotly/_plotting/_distplot.py @@ -1,13 +1,14 @@ -"""Distribution plots""" +"""Distribution plots.""" import logging from collections.abc import Sequence +from typing import TYPE_CHECKING, Any import numpy as np import pandas as pd -import plotly import plotly.graph_objs as go import plotly.io as pio +from plotly.basedatatypes import BaseTraceType from statsplotly import constants from statsplotly.plot_objects.layout import HistogramLayout @@ -24,10 +25,19 @@ TraceData, ) from statsplotly.plot_specifiers.figure import HistogramPlot, create_fig -from statsplotly.plot_specifiers.layout import AxesSpecifier, LegendSpecifier # Trace objects +from statsplotly.plot_specifiers.layout import ( + AxesSpecifier, + LegendSpecifier, +) from statsplotly.plot_specifiers.trace import HistogramSpecifier, TraceMode +from statsplotly.types import ( + AxisFormatLiteral, + CentralTendencyTypeLiteral, + HistogramBarModeLiteral, + HistogramNormTypeLiteral, +) # Helpers from ._plot import plot @@ -44,9 +54,9 @@ def distplot( x: str | None = None, y: str | None = None, slicer: str | None = None, - slice_order: list[str] | None = None, + slice_order: list[Any] | None = None, color_palette: list[str] | str | None = None, - axis: str | None = None, + axis: AxisFormatLiteral | None = None, opacity: float | None = None, hist: bool = True, rug: bool | None = None, @@ -56,17 +66,17 @@ def distplot( equal_bins: bool | None = None, bins: Sequence[float] | int | str | None = None, cumulative: bool | None = None, - histnorm: str | None = None, - central_tendency: str | None = None, + histnorm: HistogramNormTypeLiteral | None = None, + central_tendency: CentralTendencyTypeLiteral | None = None, vlines: dict[str, tuple[str, float]] | None = None, hlines: dict[str, tuple[str, float]] | None = None, - barmode: str | None = None, + barmode: HistogramBarModeLiteral | None = None, x_label: str | None = None, y_label: str | None = None, title: str | None = None, x_range: Sequence[float] | None = None, y_range: Sequence[float] | None = None, - fig: go.Figure = None, + fig: go.Figure | None = None, row: int | None = None, col: int | None = None, ) -> go.Figure: @@ -76,7 +86,8 @@ def distplot( data: A :obj:`pandas.DataFrame`-compatible structure of data x: The name of the `x` dimension column in `data`. If not None, draws vertical histograms. y: The name of the `y` dimension column in `data`. If not None, draws horizontal histograms. - slicer: The name of the column in `data` with values to slice the data : one trace is drawn for each level of the `slicer` dimension. + slicer: The name of the column in `data` with values to slice the data : one trace is drawn + for each level of the `slicer` dimension. slice_order: A list of identifiers to order and/or subset data slices specified by `slicer`. color_palette: - A string refering to a built-in `plotly`, `seaborn` or `matplotlib` colormap. @@ -91,19 +102,22 @@ def distplot( kde: If True, plot a line of a Kernel Density Estimation of the distribution. step: If True, plot a step histogram instead of a standard histogram bars. equal_bins: If True, uses the same bins for all `slices` in the data. - bins: A string, integer, or sequence specifying the `bins` parameter for :func:`numpy.histogram`. + bins: A string, integer, or sequence specifying the `bins` parameter for + :func:`numpy.histogram`. cumulative: If True, draws a cumulative histogram. histnorm: A :obj:`~statsplotly.plot_specifiers.data.HistogramNormType` value. central_tendency: A :obj:`~statsplotly.plot_specifiers.data.CentralTendencyType` value. vlines: A dictionary of {slice: (line_name, vertical_coordinates)} to draw vertical lines. - hlines: A dictionary of {slice: (line_name, horizontal_coordinates)} to draw horizontal lines. + hlines: A dictionary of {slice: (line_name, horizontal_coordinates)} to draw horizontal + lines. barmode: A :obj:`~statsplotly.plot_specifiers.layout.HistogramBarMode` value. x_label: A string to label the x_axis in place of the corresponding column name in `data`. y_label: A string to label the y_axis in place of the corresponding column name in `data`. title: A string for the title of the plot. x_range: A tuple defining the (min_range, max_range) of the x_axis. y_range: A tuple defining the (min_range, max_range) of the y_axis. - fig: A :obj:`plotly.graph_obj.Figure` to add the plot to. Use in conjunction with row and col. + fig: A :obj:`plotly.graph_obj.Figure` to add the plot to. Use in conjunction with row and + col. row: An integer identifying the row to add the plot to. col: An integer identifying the column to add the plot to. @@ -144,14 +158,14 @@ def distplot( color_palette=color_palette, opacity=opacity, barmode=barmode ) - traces: dict[str, plotly.basedatatypes.BaseTraceType] = {} + traces: dict[str, BaseTraceType] = {} traces_data: list[TraceData] = [] for (slice_name, slice_data), trace_color in zip( data_handler.iter_slices(), color_specifier.get_color_hues(n_colors=data_handler.n_slices), strict=True, ): - trace_data = TraceData.build_trace_data(data=slice_data, pointer=data_handler.data_pointer) + trace_data = TraceData.build_from_data(data=slice_data, pointer=data_handler.data_pointer) traces.update( plot_distplot_traces( @@ -210,7 +224,7 @@ def distplot( layout = HistogramLayout.build_layout(axes_specifier=axes_specifier, barmode=barmode) figure_plot = HistogramPlot.initialize( - plot_specifier=histogram_specifier, fig=fig, row=row, col=col + plot_specifier=histogram_specifier, fig=fig, row=row or 1, col=col or 1 ) if histogram_specifier.central_tendency is not None: @@ -240,7 +254,7 @@ def distplot( else (slicer or "index") ), slicer=slicer, - mode=TraceMode.MARKERS, + mode=TraceMode.MARKERS.value, color_palette=color_palette, error_x=( AGG_TO_ERROR_MAPPING[histogram_specifier.central_tendency] @@ -254,6 +268,8 @@ def distplot( ), ) # Update name + if TYPE_CHECKING: + assert histogram_specifier.central_tendency is not None fig.for_each_trace( lambda trace: trace.update( name=( diff --git a/statsplotly/_plotting/_heatmap.py b/src/statsplotly/_plotting/_heatmap.py similarity index 85% rename from statsplotly/_plotting/_heatmap.py rename to src/statsplotly/_plotting/_heatmap.py index 6ed40ad..5a97ba7 100644 --- a/statsplotly/_plotting/_heatmap.py +++ b/src/statsplotly/_plotting/_heatmap.py @@ -1,13 +1,14 @@ -"""Heatmap plots""" +"""Heatmap plots.""" import logging from collections.abc import Sequence from functools import reduce +from typing import Any import numpy as np -import plotly import plotly.graph_objs as go import plotly.io as pio +from plotly.basedatatypes import BaseTraceType from statsplotly import constants from statsplotly.plot_objects.layout import HeatmapLayout @@ -32,6 +33,7 @@ LegendSpecifier, add_update_menu, ) +from statsplotly.types import AxisFormatLiteral, NormalizationTypeLiteral pio.templates.default = constants.DEFAULT_TEMPLATE np.seterr(invalid="ignore") @@ -45,23 +47,23 @@ def heatmap( y: str | None = None, z: str | None = None, slicer: str | None = None, - slice_order: list[str] | None = None, + slice_order: list[Any] | None = None, color_palette: list[str] | str | None = None, shared_coloraxis: bool = False, color_limits: Sequence[float] | None = None, logscale: float | None = None, colorbar: bool = True, text: str | None = None, - axis: str | None = None, + axis: AxisFormatLiteral | None = None, opacity: float | None = None, - normalizer: str | None = None, + normalizer: NormalizationTypeLiteral | None = None, x_label: str | None = None, y_label: str | None = None, z_label: str | None = None, title: str | None = None, x_range: Sequence[float | str] | None = None, y_range: Sequence[float | str] | None = None, - fig: go.Figure = None, + fig: go.Figure | None = None, row: int | None = None, col: int | None = None, ) -> go.Figure: @@ -72,31 +74,37 @@ def heatmap( x: The name of the `x` dimension column in `data`. y: The name of the `y` dimension column in `data`. z: The name of the `z` dimension (i.e., color) column in `data`. - slicer: The name of the column in `data` with values to slice the data : one trace is drawn for each level of the `slicer` dimension. + slicer: The name of the column in `data` with values to slice the data : one trace is drawn + for each level of the `slicer` dimension. slice_order: A list of identifiers to order and/or subset data slices specified by `slicer`. color_palette: - A string refering to a built-in `plotly`, `seaborn` or `matplotlib` colormap. - A list of CSS color names or HTML color codes. The color palette is used, by order of precedence : - - To map color data specified by the `color` parameter onto the corresponding colormap. + - To map color data specified by the `color` parameter onto the corresponding + colormap. - To assign discrete colors to `slices` of data. shared_coloraxis: If True, colorscale limits are shared across slices of data. color_limits: A tuple specifying the (min, max) values of the colormap. logscale: A float specifying the log base to use for colorscaling. colorbar: If True, draws a colorbar. - text: A string or the name of the column in `data` with values to appear in the hover tooltip. Column names can be concatenated with '+' to display values from multiple columns. + text: A string or the name of the column in `data` with values to appear in the hover + tooltip. Column names can be concatenated with '+' to display values from multiple columns. axis: A :obj:`~statsplotly.plot_specifiers.layout.AxisFormat` value. opacity: A numeric value in the (0, 1) interval to specify heatmap opacity. - normalizer: The normalizer for the `z` dimension. A :obj:`~statsplotly.plot_specifiers.data.NormalizationType` value. + normalizer: The normalizer for the `z` dimension. A + :obj:`~statsplotly.plot_specifiers.data.NormalizationType` value. x_label: A string to label the x_axis in place of the corresponding column name in `data`. y_label: A string to label the y_axis in place of the corresponding column name in `data`. - z_label: A string to label the coloraxis in place of the corresponding column name in `data`. + z_label: A string to label the coloraxis in place of the corresponding column name in `data` + . title: A string to label the resulting plot. x_range: A tuple defining the (min_range, max_range) of the x_axis. y_range: A tuple defining the (min_range, max_range) of the y_axis. - fig: A :obj:`plotly.graph_obj.Figure` to add the plot to. Use in conjunction with row and col. + fig: A :obj:`plotly.graph_obj.Figure` to add the plot to. Use in conjunction with row and + col. row: An integer identifying the row to add the plot to. col: An integer identifying the colum to add the plot to. @@ -122,7 +130,7 @@ def heatmap( data_processor = DataProcessor(normalizer={DataDimension.Z: normalizer}) - traces: dict[str, plotly.basedatatypes.BaseTraceType] = {} + traces: dict[str, BaseTraceType] = {} traces_data: list[TraceData] = [] if data_handler.n_slices > 1 and not all( @@ -138,7 +146,7 @@ def heatmap( for dimension in DataDimension ): global_trace = HeatmapTrace.build_trace( - trace_data=TraceData.build_trace_data( + trace_data=TraceData.build_from_data( data=data_handler.data, pointer=data_handler.data_pointer, ), @@ -148,7 +156,7 @@ def heatmap( traces[global_trace.name] = global_trace.to_plotly_trace() for slice_name, slice_data in data_handler.iter_slices(): - trace_data = TraceData.build_trace_data( + trace_data = TraceData.build_from_data( data=slice_data, pointer=data_handler.data_pointer, processor=data_processor, @@ -187,10 +195,9 @@ def heatmap( coloraxis=coloraxis, ) + preplotted_traces: dict[str, BaseTraceType] = {} if fig is not None: - preplotted_traces = {trace.name: trace for trace in fig.data} - else: - preplotted_traces = {} + preplotted_traces.update({trace.name: trace for trace in fig.data}) # Create fig fig = create_fig(fig=fig, traces=traces, layout=layout, row=row, col=col) diff --git a/statsplotly/_plotting/_jointplot.py b/src/statsplotly/_plotting/_jointplot.py similarity index 84% rename from statsplotly/_plotting/_jointplot.py rename to src/statsplotly/_plotting/_jointplot.py index d792cff..0e544e1 100644 --- a/statsplotly/_plotting/_jointplot.py +++ b/src/statsplotly/_plotting/_jointplot.py @@ -1,13 +1,14 @@ -"""Jointplots""" +"""Jointplots.""" import logging from collections.abc import Sequence +from typing import TYPE_CHECKING, Any import numpy as np -import plotly import plotly.graph_objs as go import plotly.io as pio from pandas.api.types import is_numeric_dtype +from plotly.basedatatypes import BaseTraceType from pydantic import ValidationError from statsplotly import constants @@ -27,6 +28,8 @@ TraceData, ) from statsplotly.plot_specifiers.figure import JointplotPlot, create_fig + +# Trace objects from statsplotly.plot_specifiers.layout import ( AxesSpecifier, AxisFormat, @@ -35,15 +38,23 @@ add_update_menu, adjust_jointplot_legends, ) - -# Trace objects from statsplotly.plot_specifiers.trace import ( HistogramSpecifier, JointplotSpecifier, JointplotType, MarginalPlotDimension, ScatterSpecifier, - TraceMode, +) +from statsplotly.types import ( + AxisFormatLiteral, + CentralTendencyTypeLiteral, + HistogramBarModeLiteral, + HistogramNormTypeLiteral, + JointplotTypeLiteral, + MarginalPlotDimensionLiteral, + NormalizationTypeLiteral, + RegressionTypeLiteral, + TraceModeLiteral, ) # Helpers @@ -64,7 +75,7 @@ def jointplot( x: str | None = None, y: str | None = None, slicer: str | None = None, - slice_order: list[str] | None = None, + slice_order: list[Any] | None = None, color: str | None = None, color_palette: list[str] | str | None = None, shared_coloraxis: bool = False, @@ -73,9 +84,9 @@ def jointplot( colorbar: bool = True, text: str | None = None, marker: str | None = None, - mode: str | None = TraceMode.MARKERS, - axis: str | None = None, - marginal_plot: str | None = MarginalPlotDimension.ALL, + mode: TraceModeLiteral | None = "markers", + axis: AxisFormatLiteral | None = None, + marginal_plot: MarginalPlotDimensionLiteral | None = "all", kde_color_palette: list[str] | str = constants.DEFAULT_KDE_COLOR_PALETTE, hist: bool = True, rug: bool | None = None, @@ -86,26 +97,26 @@ def jointplot( equal_bins_y: bool | None = None, bins_x: Sequence[float] | int | str = constants.DEFAULT_HISTOGRAM_BIN_COMPUTATION_METHOD, bins_y: Sequence[float] | int | str = constants.DEFAULT_HISTOGRAM_BIN_COMPUTATION_METHOD, - histnorm: str | None = None, - central_tendency: str | None = None, - barmode: str | None = None, - plot_type: str = JointplotType.SCATTER, + histnorm: HistogramNormTypeLiteral | None = None, + central_tendency: CentralTendencyTypeLiteral | None = None, + barmode: HistogramBarModeLiteral | None = None, + plot_type: JointplotTypeLiteral = JointplotType.SCATTER.value, opacity: float = constants.DEFAULT_HISTOGRAM_OPACITY, jitter_x: float = 0, jitter_y: float = 0, - normalizer_x: str | None = None, - normalizer_y: str | None = None, + normalizer_x: NormalizationTypeLiteral | None = None, + normalizer_y: NormalizationTypeLiteral | None = None, shaded_error: str | None = None, error_x: str | None = None, error_y: str | None = None, - fit: str | None = None, + fit: RegressionTypeLiteral | None = None, size: float | str | None = None, x_label: str | None = None, y_label: str | None = None, title: str | None = None, x_range: Sequence[float | str] | None = None, y_range: Sequence[float | str] | None = None, - fig: go.Figure = None, + fig: go.Figure | None = None, row: int | None = None, col: int | None = None, ) -> go.Figure: @@ -115,23 +126,28 @@ def jointplot( data: A :obj:`pandas.DataFrame`-compatible structure of data x: The name of the `x` dimension column in `data`. y: The name of the `y` dimension column in `data`. - slicer: The name of the column in `data` with values to slice the data : one trace is drawn for each level of the `slicer` dimension. + slicer: The name of the column in `data` with values to slice the data : one trace is drawn + for each level of the `slicer` dimension. slice_order: A list of identifiers to order and/or subset data slices specified by `slicer`. - color: The name of the column in `data` with values to map onto the colormap. Specifying a `color` along with `marginal != None` raises a `StatsPlotSpecificationError`. + color: The name of the column in `data` with values to map onto the colormap. Specifying a + `color` along with `marginal != None` raises a `StatsPlotSpecificationError`. color_palette: - A string refering to a built-in `plotly`, `seaborn` or `matplotlib` colormap. - A list of CSS color names or HTML color codes. The color palette is used, by order of precedence : - - To map color data specified by the `color` parameter onto the corresponding colormap. + - To map color data specified by the `color` parameter onto the corresponding + colormap. - To assign discrete colors to `slices` of data. shared_coloraxis: If True, colorscale limits are shared across slices of data. color_limits: A tuple specifying the (min, max) values of the colormap. logscale: A float specifying the log base to use for colorscaling. colorbar: If True, draws a colorbar. - text: A string or the name of the column in `data` with values to appear in the hover tooltip. Column names can be concatenated with '+' to display values from multiple columns. - marker: A valid marker symbol or the name of the column in `data` with values to assign marker symbols. + text: A string or the name of the column in `data` with values to appear in the hover + tooltip. Column names can be concatenated with '+' to display values from multiple columns. + marker: A valid marker symbol or the name of the column in `data` with values to assign + marker symbols. mode: A :obj:`~statsplotly.plot_specifiers.trace.TraceMode` value. axis: A :obj:`~statsplotly.plot_specifiers.layout.AxisFormat` value. opacity: A numeric value in the (0, 1) interval to specify bar and line opacity. @@ -144,8 +160,10 @@ def jointplot( step: If True, plot a step histogram instead of a standard histogram bars. equal_bins_x: If True, uses the same bins for the `x` dimension of all `slices` in the data. equal_bins_y: If True, uses the same bins for the `y` dimension of all `slices` in the data. - bins_x: A string, integer, or sequence specifying the `bins` parameter for the `x` dimension for :func:`numpy.histogram`. - bins_y: A string, integer, or sequence specifying the `bins` parameter for the `y` dimension for :func:`numpy.histogram`. + bins_x: A string, integer, or sequence specifying the `bins` parameter for the `x` dimension + for :func:`numpy.histogram`. + bins_y: A string, integer, or sequence specifying the `bins` parameter for the `y` dimension + for :func:`numpy.histogram`. histnorm: A :obj:`~statsplotly.plot_specifiers.data.HistogramNormType` value. central_tendency: A :obj:`~statsplotly.plot_specifiers.data.CentralTendencyType` value. barmode: A :obj:`~statsplotly.plot_specifiers.layout.BarMode` value. @@ -153,19 +171,25 @@ def jointplot( opacity: A numeric value in the (0, 1) interval to specify marker opacity. jitter_x: A numeric value to specify jitter amount on the `x` dimension. jitter_y: A numeric value to specify jitter amount on the `y` dimension. - normalizer_x: The normalizer for the `x` dimension. A :obj:`~statsplotly.plot_specifiers.data.NormalizationType` value. - normalizer_y: The normalizer for the `y` dimension. A :obj:`~statsplotly.plot_specifiers.data.NormalizationType` value. + normalizer_x: A :obj:`~statsplotly.plot_specifiers.data.NormalizationType` value to + normalize the `x` dimension. + normalizer_y: A :obj:`~statsplotly.plot_specifiers.data.NormalizationType` value to + normalize the `y` dimension. shaded_error: The name of the column in `data` with values to plot continuous error shade. - error_x: The name of the column in `data` with values to plot error bar in the `x` dimension. - error_y: The name of the column in `data` with values to plot error bar in the `y` dimension. - fit: A :obj:`~statsplotly.plot_specifiers.data.RegressionType` value. Computes and plot the corresponding regression. + error_x: The name of the column in `data` with values to plot error bar in the `x` dimension + . + error_y: The name of the column in `data` with values to plot error bar in the `y` dimension + . + fit: A :obj:`~statsplotly.plot_specifiers.data.RegressionType` value. Computes and plot the + corresponding regression. size: A numeric value or the name of the column in `data` with values to assign mark sizes. x_label: A string to label the x_axis in place of the corresponding column name in `data`. y_label: A string to label the y_axis in place of the corresponding column name in `data`. title: A string for the title of the plot. x_range: A tuple defining the (min_range, max_range) of the x_axis. y_range: A tuple defining the (min_range, max_range) of the y_axis. - fig: A :obj:`plotly.graph_obj.Figure` to add the plot to. Use in conjunction with row and col. + fig: A :obj:`plotly.graph_obj.Figure` to add the plot to. Use in conjunction with row and + col. row: An integer identifying the row to add the plot to. col: An integer identifying the column to add the plot to. @@ -205,7 +229,8 @@ def jointplot( if data_handler.data_pointer.color is not None: if jointplot_specifier.plot_type in (JointplotType.HISTOGRAM, JointplotType.KDE): logger.warning( - f"Color mapping have no effect with `plot_type={jointplot_specifier.plot_type.value}`" + "Color mapping have no effect with `plot_type=%s`", + jointplot_specifier.plot_type.value, ) def specify_marginal_histogram( @@ -227,9 +252,11 @@ def specify_marginal_histogram( dimension=dimension, ) except ValidationError as exc: - raise StatsPlotSpecificationError( - f"Error when initializing marginal histogram for {dimension.value} dimension, try to change `marginal_plot` argument" - ) from exc + msg = ( + f"Error when initializing marginal histogram for {dimension.value} dimension, try " + f"to change `marginal_plot` argument" + ) + raise StatsPlotSpecificationError(msg) from exc if equal_bins: histogram_specifier.bin_edges = histogram_specifier.get_histogram_bin_edges( @@ -295,10 +322,10 @@ def specify_marginal_histogram( }, ) - global_main_traces: dict[str, plotly.basedatatypes.BaseTraceType] = {} - slices_main_traces: dict[str, plotly.basedatatypes.BaseTraceType] = {} - slices_marginal_traces: dict[str, plotly.basedatatypes.BaseTraceType] = {} - preplotted_traces: dict[str, plotly.basedatatypes.BaseTraceType] = {} + global_main_traces: dict[str, BaseTraceType] = {} + slices_main_traces: dict[str, BaseTraceType] = {} + slices_marginal_traces: dict[str, BaseTraceType] = {} + preplotted_traces: dict[str, BaseTraceType] = {} traces_data: list[TraceData] = [] @@ -306,7 +333,7 @@ def specify_marginal_histogram( if data_handler.n_slices > 1: global_main_traces.update( plot_jointplot_main_traces( - trace_data=TraceData.build_trace_data( + trace_data=TraceData.build_from_data( data=data_handler.data, pointer=data_handler.data_pointer, processor=data_processor, @@ -324,7 +351,7 @@ def specify_marginal_histogram( sliced_data_color_specifier.get_color_hues(n_colors=data_handler.n_slices), strict=True, ): - trace_data = TraceData.build_trace_data( + trace_data = TraceData.build_from_data( data=slice_data, pointer=data_handler.data_pointer, processor=data_processor, @@ -398,7 +425,7 @@ def specify_marginal_histogram( ) figure_plot = JointplotPlot.initialize( - plot_specifier=jointplot_specifier, fig=fig, row=row, col=col + plot_specifier=jointplot_specifier, fig=fig, row=row or 1, col=col or 1 ) preplotted_traces.update({trace.name: trace for trace in figure_plot.fig.data}) @@ -419,15 +446,15 @@ def add_marginal_distribution_to_layout( marginal_row = figure_plot.main_row if dimension is DataDimension.Y else figure_plot.row marginal_col = figure_plot.col + 1 if dimension is DataDimension.Y else figure_plot.col - _data_pointer = data_handler.data_pointer.copy() + _data_pointer = data_handler.data_pointer.model_copy() + if TYPE_CHECKING: + assert jointplot_specifier.histogram_specifier is not None if dimension is DataDimension.Y: _data_pointer.x = None _data_pointer.y = y _legend_specifier = LegendSpecifier( data_pointer=_data_pointer, - x_transformation=jointplot_specifier.histogram_specifier[ - DataDimension.Y - ].histnorm, # type: ignore + x_transformation=jointplot_specifier.histogram_specifier[DataDimension.Y].histnorm, ) elif dimension is DataDimension.X: @@ -435,11 +462,13 @@ def add_marginal_distribution_to_layout( _data_pointer.y = None _legend_specifier = LegendSpecifier( data_pointer=_data_pointer, - y_transformation=jointplot_specifier.histogram_specifier[ - DataDimension.X - ].histnorm, # type: ignore + y_transformation=jointplot_specifier.histogram_specifier[DataDimension.X].histnorm, ) + else: + msg = f"Unsupported marginal dimension: {dimension}" + raise StatsPlotSpecificationError(msg) + axes_specifier = AxesSpecifier( traces=traces_data, legend=_legend_specifier, diff --git a/statsplotly/_plotting/_plot.py b/src/statsplotly/_plotting/_plot.py similarity index 83% rename from statsplotly/_plotting/_plot.py rename to src/statsplotly/_plotting/_plot.py index a2e0520..f46859f 100644 --- a/statsplotly/_plotting/_plot.py +++ b/src/statsplotly/_plotting/_plot.py @@ -1,13 +1,13 @@ -"""Line or scatter plots""" +"""Line or scatter plots.""" import logging from collections.abc import Sequence from typing import Any import numpy as np -import plotly import plotly.graph_objs as go import plotly.io as pio +from plotly.basedatatypes import BaseTraceType from statsplotly import constants from statsplotly.exceptions import StatsPlotSpecificationError @@ -33,7 +33,13 @@ ) # Trace objects -from statsplotly.plot_specifiers.trace import ScatterSpecifier, TraceMode +from statsplotly.plot_specifiers.trace import ScatterSpecifier +from statsplotly.types import ( + AxisFormatLiteral, + NormalizationTypeLiteral, + RegressionTypeLiteral, + TraceModeLiteral, +) # Helpers from .helpers import plot_scatter_traces @@ -50,7 +56,7 @@ def plot( y: str | None = None, z: str | None = None, slicer: str | None = None, - slice_order: list[str] | None = None, + slice_order: list[Any] | None = None, color: str | None = None, color_palette: list[str] | str | None = None, shared_coloraxis: bool = False, @@ -59,20 +65,20 @@ def plot( colorbar: bool = True, text: str | None = None, marker: str | None = None, - mode: str | None = None, - axis: str | None = None, + mode: TraceModeLiteral | None = None, + axis: AxisFormatLiteral | None = None, opacity: str | float | None = None, jitter_x: float = 0, jitter_y: float = 0, jitter_z: float = 0, - normalizer_x: str | None = None, - normalizer_y: str | None = None, - normalizer_z: str | None = None, + normalizer_x: NormalizationTypeLiteral | None = None, + normalizer_y: NormalizationTypeLiteral | None = None, + normalizer_z: NormalizationTypeLiteral | None = None, shaded_error: str | None = None, error_x: str | None = None, error_y: str | None = None, error_z: str | None = None, - fit: str | None = None, + fit: RegressionTypeLiteral | None = None, size: float | str | None = None, x_label: str | None = None, y_label: str | None = None, @@ -81,7 +87,7 @@ def plot( x_range: Sequence[float | str] | None = None, y_range: Sequence[float | str] | None = None, z_range: Sequence[float | str] | None = None, - fig: go.Figure = None, + fig: go.Figure | None = None, row: int | None = None, col: int | None = None, secondary_y: bool = False, @@ -93,7 +99,8 @@ def plot( x: The name of the `x` dimension column in `data`. y: The name of the `y` dimension column in `data`. z: The name of the `z` dimension column in `data`. - slicer: The name of the column in `data` with values to slice the data : one trace is drawn for each level of the `slicer` dimension. + slicer: The name of the column in `data` with values to slice the data : one trace is drawn + for each level of the `slicer` dimension. slice_order: A list of identifiers to order and/or subset data slices specified by `slicer`. color: The name of the column in `data` with values to map onto the colormap. color_palette: @@ -101,29 +108,40 @@ def plot( - A list of CSS color names or HTML color codes. The color palette is used, by order of precedence : - - To map color data specified by the `color` parameter onto the corresponding colormap. + - To map color data specified by the `color` parameter onto the corresponding + colormap. - To assign discrete colors to `slices` of data. shared_coloraxis: If True, colorscale limits are shared across slices of data. color_limits: A tuple specifying the (min, max) values of the colormap. logscale: A float specifying the log base to use for colorscaling. colorbar: If True, draws a colorbar. - text: A string or the name of the column in `data` with values to appear in the hover tooltip. Column names can be concatenated with '+' to display values from multiple columns. - marker: A valid marker symbol or the name of the column in `data` with values to assign marker symbols. + text: A string or the name of the column in `data` with values to appear in the hover + tooltip. Column names can be concatenated with '+' to display values from multiple columns. + marker: A valid marker symbol or the name of the column in `data` with values to assign + marker symbols. mode: A :obj:`~statsplotly.plot_specifiers.trace.TraceMode` value. axis: A :obj:`~statsplotly.plot_specifiers.layout.AxisFormat` value. - opacity: A numeric value in the (0, 1) interval or the name of the column in `data` with values to specify marker opacity. + opacity: A numeric value in the (0, 1) interval or the name of the column in `data` with + values to specify marker opacity. jitter_x: A numeric value to specify jitter amount on the `x` dimension. jitter_y: A numeric value to specify jitter amount on the `y` dimension. jitter_z: A numeric value to specify jitter amount on the `z` dimension. - normalizer_x: The normalizer for the `x` dimension. A :obj:`~statsplotly.plot_specifiers.data.NormalizationType` value. - normalizer_y: The normalizer for the `y` dimension. A :obj:`~statsplotly.plot_specifiers.data.NormalizationType` value. - normalizer_z: The normalizer for the `z` dimension. A :obj:`~statsplotly.plot_specifiers.data.NormalizationType` value. + normalizer_x: A :obj:`~statsplotly.plot_specifiers.data.NormalizationType` value for the `x` + dimension. + normalizer_y: A :obj:`~statsplotly.plot_specifiers.data.NormalizationType` value for the `y` + dimension. + normalizer_z: A :obj:`~statsplotly.plot_specifiers.data.NormalizationType` value for the `z` + dimension. shaded_error: The name of the column in `data` with values to plot continuous error shade. - error_x: The name of the column in `data` with values to plot error bar in the `x` dimension. - error_y: The name of the column in `data` with values to plot error bar in the `y` dimension. - error_z: The name of the column in `data` with values to plot error bar in the `z` dimension. - fit: A :obj:`~statsplotly.plot_specifiers.data.RegressionType` value. Computes and plot the corresponding regression. + error_x: The name of the column in `data` with values to plot error bar in the `x` dimension + . + error_y: The name of the column in `data` with values to plot error bar in the `y` dimension + . + error_z: The name of the column in `data` with values to plot error bar in the `z` dimension + . + fit: A :obj:`~statsplotly.plot_specifiers.data.RegressionType` value. Computes and plot the + corresponding regression. size: A numeric value or the name of the column in `data` with values to assign mark sizes. x_label: A string to label the x_axis in place of the corresponding column name in `data`. y_label: A string to label the y_axis in place of the corresponding column name in `data`. @@ -132,7 +150,8 @@ def plot( x_range: A tuple defining the (min_range, max_range) of the x_axis. y_range: A tuple defining the (min_range, max_range) of the y_axis. z_range: A tuple defining the (min_range, max_range) of the z_axis. - fig: A :obj:`plotly.graph_obj.Figure` to add the plot to. Use in conjunction with row and col. + fig: A :obj:`plotly.graph_obj.Figure` to add the plot to. Use in conjunction with row and + col. row: An integer identifying the row to add the plot to. col: An integer identifying the column to add the plot to. secondary_y: If True, plot on a secondary y_axis of the `fig` object. @@ -142,14 +161,12 @@ def plot( """ if (color is not None or size is not None or marker is not None) and mode is None: - mode = TraceMode.MARKERS - if color is not None and mode is TraceMode.LINES: - raise ValueError("Only markers can be mapped to colormap") - if size is not None and mode is TraceMode.LINES: + mode = "markers" + if size is not None and mode == "lines": raise ValueError("Size specification only applies to markers") if z is not None: if mode is None: - mode = TraceMode.MARKERS + mode = "markers" if fit is not None: raise ValueError("Regression can not be computed on a three-dimensional plot") if size is None: @@ -217,14 +234,14 @@ def plot( }, ) - traces: dict[str, plotly.basedatatypes.BaseTraceType] = {} + traces: dict[str, BaseTraceType] = {} traces_data: list[TraceData] = [] for (slice_name, slice_data), trace_color in zip( data_handler.iter_slices(), color_specifier.get_color_hues(n_colors=data_handler.n_slices), strict=True, ): - trace_data = TraceData.build_trace_data( + trace_data = TraceData.build_from_data( data=slice_data, pointer=data_handler.data_pointer, processor=data_processor, diff --git a/statsplotly/_plotting/helpers.py b/src/statsplotly/_plotting/helpers.py similarity index 94% rename from statsplotly/_plotting/helpers.py rename to src/statsplotly/_plotting/helpers.py index 7f592e7..fd8ceda 100644 --- a/statsplotly/_plotting/helpers.py +++ b/src/statsplotly/_plotting/helpers.py @@ -1,6 +1,8 @@ """Helper modules for plotting routines.""" -import plotly +from typing import Any + +from plotly.basedatatypes import BaseTraceType from statsplotly.plot_objects.trace import ( ContourTrace, @@ -31,10 +33,10 @@ def plot_jointplot_main_traces( trace_color: str, color_specifier: ColorSpecifier, jointplot_specifier: JointplotSpecifier, -) -> dict[str, plotly.basedatatypes.BaseTraceType]: +) -> dict[str, Any]: """Constructs the main traces of a jointplot layout.""" - traces: dict[str, plotly.basedatatypes.BaseTraceType] = {} + traces: dict[str, BaseTraceType] = {} if jointplot_specifier.plot_kde: contour_trace = ContourTrace.build_trace( trace_data=trace_data, @@ -69,7 +71,8 @@ def plot_jointplot_main_traces( jointplot_specifier=jointplot_specifier, ) # Make colorbars horizontal - # TODO: Get read of this one when we use _SubplotGridCommonColoraxisFormatter class for managing coloraxis + # TODO: Get read of this one when we use _SubplotGridCommonColoraxisFormatter class + # for managing coloraxis if heatmap_trace.colorbar is not None: heatmap_trace.colorbar = set_horizontal_colorbar(heatmap_trace.colorbar) @@ -84,10 +87,10 @@ def plot_scatter_traces( trace_color: str, color_specifier: ColorSpecifier, scatter_specifier: ScatterSpecifier, -) -> dict[str, plotly.basedatatypes.BaseTraceType]: +) -> dict[str, Any]: """Constructs scatter traces.""" - traces: dict[str, plotly.basedatatypes.BaseTraceType] = {} + traces: dict[str, BaseTraceType] = {} traces[trace_name] = ScatterTrace.build_trace( trace_data=trace_data, trace_name=trace_name, @@ -129,10 +132,10 @@ def plot_distplot_traces( trace_color: str, color_specifier: ColorSpecifier, histogram_specifier: HistogramSpecifier, -) -> dict[str, plotly.basedatatypes.BaseTraceType]: +) -> dict[str, BaseTraceType]: """Constructs distplot traces.""" - traces: dict[str, plotly.basedatatypes.BaseTraceType] = {} + traces: dict[str, BaseTraceType] = {} if histogram_specifier.dimension is None: raise ValueError("`histogram_specifier.dimension` can not be `None`") diff --git a/statsplotly/constants.py b/src/statsplotly/constants.py similarity index 100% rename from statsplotly/constants.py rename to src/statsplotly/constants.py diff --git a/statsplotly/exceptions.py b/src/statsplotly/exceptions.py similarity index 100% rename from statsplotly/exceptions.py rename to src/statsplotly/exceptions.py diff --git a/statsplotly/plot_objects/__init__.py b/src/statsplotly/plot_objects/__init__.py similarity index 100% rename from statsplotly/plot_objects/__init__.py rename to src/statsplotly/plot_objects/__init__.py diff --git a/statsplotly/plot_objects/layout/__init__.py b/src/statsplotly/plot_objects/layout/__init__.py similarity index 67% rename from statsplotly/plot_objects/layout/__init__.py rename to src/statsplotly/plot_objects/layout/__init__.py index e3f662e..5e816dc 100644 --- a/statsplotly/plot_objects/layout/__init__.py +++ b/src/statsplotly/plot_objects/layout/__init__.py @@ -1,5 +1,3 @@ -from typing import TypeAlias - from ._axis import ColorAxis from ._layout import ( BarLayout, @@ -19,7 +17,3 @@ "ScatterLayout", "SceneLayout", ] - -layout_type: TypeAlias = ( - HeatmapLayout | CategoricalLayout | ScatterLayout | SceneLayout | BarLayout | HistogramLayout -) diff --git a/statsplotly/plot_objects/layout/_axis.py b/src/statsplotly/plot_objects/layout/_axis.py similarity index 66% rename from statsplotly/plot_objects/layout/_axis.py rename to src/statsplotly/plot_objects/layout/_axis.py index 8b3331d..efde893 100644 --- a/statsplotly/plot_objects/layout/_axis.py +++ b/src/statsplotly/plot_objects/layout/_axis.py @@ -2,13 +2,13 @@ import datetime import logging -from typing import Any, TypeAlias +from typing import Any, Self from pydantic import ValidationInfo, field_validator, model_validator from statsplotly._base import BaseModel -axis_coordinates_type: TypeAlias = float | datetime.datetime | str +AxisCoordinatesType = float | datetime.datetime | str logger = logging.getLogger(__name__) @@ -25,12 +25,12 @@ class BaseAxis(BaseModel): """Compatible properties with 2D and 3D (Scene) Layout.""" title: str | None = None - range: list[axis_coordinates_type] | None = None # noqa: A003 + range: list[AxisCoordinatesType] | None = None # noqa: A003 type: str | None = None # noqa: A003 autorange: bool | str | None = None showgrid: bool | None = None tickmode: str | None = None - tickvals: list[axis_coordinates_type] | None = None + tickvals: list[AxisCoordinatesType] | None = None ticktext: list[str] | None = None zeroline: bool | None = None @@ -42,19 +42,17 @@ def validate_autorange( return False return value - @model_validator(mode="after") # type: ignore - def validate_axis_consistency(cls, model: BaseAxis) -> BaseAxis: - if model.range is not None and model.tickvals is not None: - model.tickvals = model.range - if model.ticktext is not None: + @model_validator(mode="after") + def validate_axis_consistency(self) -> Self: + if self.range is not None and self.tickvals is not None: + self.tickvals = self.range + if self.ticktext is not None: try: - model.ticktext = [ - model.ticktext[int(idx)] for idx in model.tickvals # type: ignore - ] + self.ticktext = [self.ticktext[idx] for idx in self.tickvals] # type: ignore except TypeError: logger.error("Can not adjust tick text labels to tick values") - return model + return self class XYAxis(BaseAxis): diff --git a/statsplotly/plot_objects/layout/_layout.py b/src/statsplotly/plot_objects/layout/_layout.py similarity index 99% rename from statsplotly/plot_objects/layout/_layout.py rename to src/statsplotly/plot_objects/layout/_layout.py index 53904d8..e00d70a 100644 --- a/statsplotly/plot_objects/layout/_layout.py +++ b/src/statsplotly/plot_objects/layout/_layout.py @@ -218,14 +218,12 @@ def build_layout( class ScatterLayout(_XYColorAxisLayout): - @classmethod def build_layout( cls, axes_specifier: AxesSpecifier, coloraxis: ColorAxis, ) -> ScatterLayout: - return cls.model_validate( super().build_coloraxis_layout(axes_specifier=axes_specifier, coloraxis=coloraxis) ) @@ -241,7 +239,6 @@ def build_layout( coloraxis: ColorAxis, barmode: str | None, ) -> BarLayout: - return cls( **_XYColorAxisLayout.build_coloraxis_layout( axes_specifier=axes_specifier, coloraxis=coloraxis @@ -262,7 +259,6 @@ def validate_histogram_barmode(cls, value: str | None) -> HistogramBarMode: @classmethod def build_layout(cls, axes_specifier: AxesSpecifier, barmode: str | None) -> HistogramLayout: - return cls( **_XYLayout.build_xy_layout(axes_specifier=axes_specifier).model_dump(), barmode=barmode ) diff --git a/statsplotly/plot_objects/trace.py b/src/statsplotly/plot_objects/trace.py similarity index 92% rename from statsplotly/plot_objects/trace.py rename to src/statsplotly/plot_objects/trace.py index d70aa98..bd3c2f0 100644 --- a/statsplotly/plot_objects/trace.py +++ b/src/statsplotly/plot_objects/trace.py @@ -2,12 +2,10 @@ import logging from abc import ABCMeta, abstractmethod -from collections.abc import Callable -from typing import Any +from typing import Any, ClassVar import numpy as np import pandas as pd -import plotly import plotly.graph_objects as go from numpy.typing import NDArray from pydantic.v1.utils import deep_update @@ -31,6 +29,7 @@ kde_2d, regress, ) +from statsplotly.plot_specifiers.layout import ColoraxisReference from statsplotly.plot_specifiers.trace import ( CategoricalPlotSpecifier, HistogramSpecifier, @@ -44,10 +43,10 @@ logger = logging.getLogger(__name__) -class _BasePlotlyTrace(BaseModel): - _PLOTLY_GRAPH_FCT: Callable[[Any], Any] +class _PlotlyTraceMixin(BaseModel): + _PLOTLY_GRAPH_FCT: ClassVar[type] - def to_plotly_trace(self) -> plotly.basedatatypes.BaseTraceType: + def to_plotly_trace(self) -> Any: return self._PLOTLY_GRAPH_FCT(self.model_dump()) @@ -99,6 +98,7 @@ def build_trace(cls, *args: Any, **kwargs: Any) -> BaseTrace: class _ScatterBaseTrace(BaseTrace): marker: dict[str, Any] | None = None + line: dict[str, Any] | None = None mode: TraceMode | None = None error_x: dict[str, Any] | None = None error_y: dict[str, Any] | None = None @@ -129,8 +129,8 @@ def build_trace( marker={ "size": trace_data.size_data, "color": ( - color_specifier.format_color_data(trace_data.color_data) - if trace_data.color_data is not None + color_specifier.get_marker_color(trace_data.color_data) + if trace_data.color_data is not None and mode is not TraceMode.LINES else trace_color ), "opacity": trace_data.opacity_data, @@ -141,6 +141,11 @@ def build_trace( else None ), }, + line={ + "color": color_specifier.get_line_color(trace_data.color_data) + if trace_data.color_data is not None and mode is TraceMode.LINES + else trace_color + }, legendgroup=trace_name, ) @@ -153,7 +158,7 @@ class _DensityTrace(BaseTrace): text: str | pd.Series | None = None -class HeatmapTrace(_DensityTrace, _BasePlotlyTrace): +class HeatmapTrace(_DensityTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Heatmap hoverinfo: str = "x+y+z+text" @@ -199,10 +204,13 @@ def build_trace( trace_name: str, color_specifier: ColorSpecifier, ) -> HeatmapTrace: + if trace_data.z_values is None: + msg = "`z_values` can not be `None`" + raise ValueError(msg) return cls( x=trace_data.x_values, y=trace_data.y_values, - z=color_specifier.format_color_data(trace_data.z_values), + z=color_specifier.get_marker_color(trace_data.z_values), zmin=color_specifier.zmin, zmax=color_specifier.zmax, coloraxis=color_specifier.coloraxis_reference, @@ -213,13 +221,13 @@ def build_trace( ) -class ShadedTrace(_ScatterBaseTrace, _BasePlotlyTrace): +class ShadedTrace(_ScatterBaseTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Scatter hoverinfo: str = "x+y+name+text" line: dict[str, Any] fill: str - fillcolor: str + fillcolor: str | None @classmethod def build_lower_error_trace( @@ -269,7 +277,7 @@ def build_upper_error_trace( ) -class ScatterTrace(_ScatterBaseTrace, _BasePlotlyTrace): +class ScatterTrace(_ScatterBaseTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Scattergl hoverinfo: str = "x+y+name+text" @@ -307,13 +315,19 @@ def build_regression_trace( raise ValueError("`trace_data.x_values` and `trace_data.x_values` can not be `None`") if regression_type is RegressionType.LINEAR: - p, r2, (x_grid, y_fit) = regress(trace_data.x_values, trace_data.y_values, affine_func) + p, r2, (x_grid, y_fit) = regress( + trace_data.x_values.to_numpy(), trace_data.y_values.to_numpy(), affine_func + ) regression_legend = f"alpha={p[0]:.2f}, r={np.sqrt(r2):.2f}" elif regression_type is RegressionType.EXPONENTIAL: - p, r2, (x_grid, y_fit) = exponential_regress(trace_data.x_values, trace_data.y_values) + p, r2, (x_grid, y_fit) = exponential_regress( + trace_data.x_values.to_numpy(), trace_data.y_values.to_numpy() + ) regression_legend = f"R2={r2:.2f}" elif regression_type is RegressionType.INVERSE: - p, r2, (x_grid, y_fit) = regress(trace_data.x_values, trace_data.y_values, inverse_func) + p, r2, (x_grid, y_fit) = regress( + trace_data.x_values.to_numpy(), trace_data.y_values.to_numpy(), inverse_func + ) regression_legend = f"R2={r2:.2f}" return cls( @@ -350,7 +364,7 @@ def build_trace( ) -class Scatter3DTrace(_ScatterBaseTrace, _BasePlotlyTrace): +class Scatter3DTrace(_ScatterBaseTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Scatter3d hoverinfo: str = "x+y+z+name+text" @@ -425,7 +439,7 @@ def build_trace( marker={ "size": trace_data.size_data, "color": ( - color_specifier.format_color_data(trace_data.color_data) + color_specifier.get_marker_color(trace_data.color_data) if trace_data.color_data is not None else trace_color ), @@ -435,7 +449,7 @@ def build_trace( ) -class StripTrace(_CategoricalTrace, _BasePlotlyTrace): +class StripTrace(_CategoricalTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Scattergl mode: str = TraceMode.MARKERS @@ -449,7 +463,6 @@ def build_trace( color_specifier: ColorSpecifier, categorical_plot_specifier: CategoricalPlotSpecifier, ) -> StripTrace: - categorical_trace = _CategoricalTrace.build_trace( trace_data, trace_name, trace_color, color_specifier, categorical_plot_specifier ) @@ -478,7 +491,6 @@ def build_trace( color_specifier: ColorSpecifier, categorical_plot_specifier: CategoricalPlotSpecifier, ) -> _OrientedTrace: - categorical_trace = _CategoricalTrace.build_trace( trace_data, trace_name, trace_color, color_specifier, categorical_plot_specifier ) @@ -491,7 +503,7 @@ def build_trace( ) -class BoxTrace(_OrientedTrace, _BasePlotlyTrace): +class BoxTrace(_OrientedTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Box boxmean: bool = True @@ -512,7 +524,7 @@ def build_trace( ) -class ViolinTrace(_OrientedTrace, _BasePlotlyTrace): +class ViolinTrace(_OrientedTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Violin meanline_visible: bool = True @@ -534,7 +546,7 @@ def build_trace( ) -class BarTrace(BaseTrace, _BasePlotlyTrace): +class BarTrace(BaseTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Bar hoverinfo: str = "x+y+name+text" @@ -570,7 +582,7 @@ def build_trace( error_y=error_y_data, marker={ "color": ( - color_specifier.format_color_data(trace_data.color_data) + color_specifier.get_marker_color(trace_data.color_data) if trace_data.color_data is not None else trace_color ), @@ -581,7 +593,7 @@ def build_trace( ) -class StepHistogramTrace(BaseTrace, _BasePlotlyTrace): +class StepHistogramTrace(BaseTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Scatter line: dict[str, Any] @@ -617,7 +629,7 @@ def build_trace( ) -class RugTrace(BaseTrace, _BasePlotlyTrace): +class RugTrace(BaseTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Scatter hoverinfo: str @@ -676,7 +688,7 @@ def build_trace( ) -class HistogramTrace(BaseTrace, _BasePlotlyTrace): +class HistogramTrace(BaseTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Histogram marker: dict[str, Any] | None = None @@ -714,7 +726,7 @@ def build_trace( ) -class EcdfTrace(BaseTrace, _BasePlotlyTrace): +class EcdfTrace(BaseTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Scatter line: dict[str, Any] @@ -747,12 +759,13 @@ def build_trace( ) -class Histogram2dTrace(BaseTrace, _BasePlotlyTrace): +class Histogram2dTrace(BaseTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Histogram2d marker: dict[str, Any] | None = None xbins: dict[str, Any] | None = None ybins: dict[str, Any] | None = None + coloraxis: ColoraxisReference | None = None colorbar: dict[str, Any] | None = None colorscale: str | list[list[str | float]] | None = None histnorm: HistogramNormType | None = None @@ -800,13 +813,12 @@ def build_trace( ) -class KdeTrace(BaseTrace, _BasePlotlyTrace): +class KdeTrace(BaseTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Scatter hoverinfo: str = "x+y" line: dict[str, Any] mode: TraceMode = TraceMode.LINES - showlegend: bool = False @classmethod def build_trace( @@ -837,10 +849,11 @@ def build_trace( name=f"{trace_name} pdf", line={"color": line_color}, legendgroup=trace_name, + showlegend=False, ) -class HistogramLineTrace(BaseTrace, _BasePlotlyTrace): +class HistogramLineTrace(BaseTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Scatter hoverinfo: str @@ -904,7 +917,7 @@ def build_trace( ) -class ContourTrace(_DensityTrace, _BasePlotlyTrace): +class ContourTrace(_DensityTrace, _PlotlyTraceMixin): _PLOTLY_GRAPH_FCT = go.Contour colorscale: str | list[list[str | float]] | None = None diff --git a/statsplotly/plot_specifiers/__init__.py b/src/statsplotly/plot_specifiers/__init__.py similarity index 100% rename from statsplotly/plot_specifiers/__init__.py rename to src/statsplotly/plot_specifiers/__init__.py diff --git a/statsplotly/plot_specifiers/color/__init__.py b/src/statsplotly/plot_specifiers/color/__init__.py similarity index 100% rename from statsplotly/plot_specifiers/color/__init__.py rename to src/statsplotly/plot_specifiers/color/__init__.py diff --git a/statsplotly/plot_specifiers/color/_core.py b/src/statsplotly/plot_specifiers/color/_core.py similarity index 74% rename from statsplotly/plot_specifiers/color/_core.py rename to src/statsplotly/plot_specifiers/color/_core.py index 43fe6b1..27dca69 100644 --- a/statsplotly/plot_specifiers/color/_core.py +++ b/src/statsplotly/plot_specifiers/color/_core.py @@ -1,7 +1,7 @@ from __future__ import annotations import logging -from typing import Any +from typing import Any, overload import numpy as np import pandas as pd @@ -18,7 +18,11 @@ from statsplotly.exceptions import StatsPlotSpecificationError from statsplotly.plot_objects.layout import ColorAxis from statsplotly.plot_specifiers.common import smart_legend -from statsplotly.plot_specifiers.layout import BarMode, ColoraxisReference +from statsplotly.plot_specifiers.layout import ( + BarMode, + ColoraxisReference, + HistogramBarMode, +) from ._utils import ColorSystem, compute_colorscale, rgb_string_array_from_colormap @@ -26,7 +30,6 @@ class ColorSpecifier(BaseModel): - barmode: BarMode | None = None coloraxis_reference: ColoraxisReference | None = None colormap: dict[str | np.datetime64 | bool, Any] | None = None logscale: float | None = None @@ -90,17 +93,19 @@ def convert_datetime_to_timestamp(x: np.datetime64) -> float: @classmethod def _register_colormap( - cls, color_data: pd.Series + cls, color_data: pd.Series | None ) -> dict[str | np.datetime64 | bool, Any] | None: if color_data is None: return None if cls._check_is_direct_color_specification(color_data): logger.debug( - f"{color_data.name} values are all color-like, statsplotly will assume direct color specification" + "%s values are all color-like, statsplotly will assume direct color specification", + color_data, ) if cls._check_is_discrete_color_data_type(color_data): + # For consistent discrete colormapping, colormap needs to be fixed across all traces return dict( zip( color_data.dropna().unique(), @@ -111,34 +116,59 @@ def _register_colormap( return None - def format_color_data(self, color_data: str | pd.Series) -> pd.Series: + @overload + def get_marker_color(self, color_data: str) -> str: ... + + @overload + def get_marker_color(self, color_data: pd.Series) -> pd.Series: ... + + def get_marker_color(self, color_data: str | pd.Series) -> str | pd.Series: + if isinstance(color_data, str): + return color_data + if self._check_is_direct_color_specification(color_data): logger.debug( - f"{color_data.name} values are all color-like, statsplotly will assume direct color specification" # type: ignore + "%s values are all color-like, statsplotly will assume direct color specification", + color_data.name, ) return color_data if self._check_is_datetime_color_data_type(color_data): - return color_data.map(self.convert_datetime_to_timestamp) # type: ignore - + return color_data.map(self.convert_datetime_to_timestamp) if self._check_is_discrete_color_data_type(color_data): logger.debug( - f"{color_data.name} values of type='{color_data.dtype}' are not continuous type, statsplotly will map it to colormap" # type: ignore + "%s values of type='%s' are not continuous type, statsplotly will map it to " + "colormap", + color_data.name, + color_data.dtype, ) if self.colormap is None: - raise StatsPlotSpecificationError( - f"No colormap attribute to map discrete data onto, check {ColorSpecifier.__name__} instantiation" + msg = ( + f"No colormap defined to map discrete data onto, check " + f"{self.__class__.__name__} instantiation" ) - return color_data.map(self.colormap) # type: ignore + raise StatsPlotSpecificationError(msg) + return color_data.map(self.colormap) return color_data + def get_line_color(self, color_data: str | pd.Series) -> str: + if isinstance(color_data, str): + return color_data + + if len((line_colors := color_data.dropna()).unique()) > 1: + logger.warning( + "Multiple color values found for line: %s, the first one will be used", + line_colors.unique().tolist(), + ) + return line_colors.iloc[0] + def build_colorbar(self, color_values: pd.Series | None) -> dict[str, Any] | None: if color_values is None: return None colorbar_dict = { - "title": smart_legend(color_values.name), + "title": smart_legend(str(color_values.name)), "len": 1, "xanchor": "left", "yanchor": "middle", @@ -163,7 +193,7 @@ def build_colorbar(self, color_values: pd.Series | None) -> dict[str, Any] | Non ticktext = list(colormap.keys()) elif self._check_is_datetime_color_data_type(color_values): - tickvals = self.format_color_data(color_values).iloc[[0, -1]] + tickvals = self.get_marker_color(color_values).iloc[[0, -1]] ticktext = [ datum.strftime("%B %Y") for datum in color_values.dropna().sort_values().iloc[[0, -1]] @@ -185,12 +215,12 @@ def build_colorscale( return None if self._check_is_direct_color_specification(color_data): - logger.debug(f"{color_data.name} data is all color-like, returning no colorscale") + logger.debug("%s data is all color-like, returning no colorscale", color_data.name) return None # Select the appropriate color system if self._check_is_discrete_color_data_type(color_data): - _color_data = self.format_color_data(color_data) + _color_data = self.get_marker_color(color_data) n_colors = _color_data.dropna().nunique() color_system = ColorSystem.DISCRETE else: @@ -199,10 +229,11 @@ def build_colorscale( if self.logscale is not None: if color_system is ColorSystem.DISCRETE: - raise ValueError( - f"{ColorSystem.LOGARITHMIC.value} color system is not compatible with" - f" {ColorSystem.DISCRETE.value} colormapping" + msg = ( + f"{ColorSystem.LOGARITHMIC.value} color system is not compatible with " + f"{ColorSystem.DISCRETE.value} colormapping" ) + raise ValueError(msg) color_system = ColorSystem.LOGARITHMIC colorscale = compute_colorscale( @@ -228,7 +259,11 @@ def build_coloraxis(self, color_data: pd.Series | None, shared: bool = False) -> colorbar = self.build_colorbar(color_data) if colorscale is not None else None return ColorAxis( - cmin=cmin, cmax=cmax, colorscale=colorscale, colorbar=colorbar, showscale=self.colorbar + cmin=cmin, + cmax=cmax, + colorscale=colorscale, + colorbar=colorbar, + showscale=self.colorbar, ) def get_color_hues(self, n_colors: int) -> list[str]: @@ -237,7 +272,7 @@ def get_color_hues(self, n_colors: int) -> list[str]: @classmethod def build_from_color_data( cls, - color_data: pd.Series, + color_data: pd.Series | None, **kwargs: Any, ) -> ColorSpecifier: colormap = cls._register_colormap(color_data=color_data) @@ -249,7 +284,14 @@ def build_from_color_data( class HistogramColorSpecifier(ColorSpecifier): - opacity: float + barmode: BarMode + + @field_validator("barmode", mode="before") + def validate_histogram_barmode(cls, value: str | None) -> HistogramBarMode: + if value is None: + return HistogramBarMode.OVERLAY + + return HistogramBarMode(value) @field_validator("opacity", mode="before") def check_opacity(cls, value: str | float | None, info: ValidationInfo) -> float: @@ -259,7 +301,9 @@ def check_opacity(cls, value: str | float | None, info: ValidationInfo) -> float if value is None: if info.data.get("barmode") is BarMode.OVERLAY: logger.info( - f"Setting up histogram opacity to {constants.DEFAULT_OVERLAID_HISTOGRAM_OPACITY} for `barmode={BarMode.OVERLAY.value}`" + f"Setting up histogram opacity to " + f"{constants.DEFAULT_OVERLAID_HISTOGRAM_OPACITY} " + f"for `barmode={BarMode.OVERLAY.value}`" ) return constants.DEFAULT_OVERLAID_HISTOGRAM_OPACITY diff --git a/statsplotly/plot_specifiers/color/_utils.py b/src/statsplotly/plot_specifiers/color/_utils.py similarity index 91% rename from statsplotly/plot_specifiers/color/_utils.py rename to src/statsplotly/plot_specifiers/color/_utils.py index b3ecef6..1b503c4 100644 --- a/statsplotly/plot_specifiers/color/_utils.py +++ b/src/statsplotly/plot_specifiers/color/_utils.py @@ -1,7 +1,7 @@ import logging import re -from enum import Enum -from typing import Any, TypeAlias, cast +from enum import StrEnum +from typing import Any, cast import matplotlib import matplotlib.pyplot as plt @@ -16,16 +16,16 @@ logger = logging.getLogger(__name__) -Cmap_specs: TypeAlias = str | list[str] | list[tuple[float, float, float]] +CmapSpecs = str | list[str] | list[tuple[float, float, float]] -class ColorSystem(str, Enum): +class ColorSystem(StrEnum): LINEAR = "linear" LOGARITHMIC = "logarithmic" DISCRETE = "discrete" -def get_colorarray_from_seaborn(cmap: Cmap_specs | None, n_colors: int) -> NDArray[Any]: +def get_colorarray_from_seaborn(cmap: CmapSpecs | None, n_colors: int) -> NDArray[Any]: try: return sns.color_palette(cmap, n_colors=n_colors) except ValueError as exc: @@ -35,7 +35,7 @@ def get_colorarray_from_seaborn(cmap: Cmap_specs | None, n_colors: int) -> NDArr def get_colorarray_from_matplotlib( - cmap: Cmap_specs | None, + cmap: CmapSpecs | None, n_colors: int, ) -> NDArray[Any]: if isinstance(cmap, list): @@ -49,7 +49,7 @@ def get_colorarray_from_matplotlib( return mpl_cmap(np.linspace(0, 1, n_colors)) -def get_colorarray_from_plotly(cmap: Cmap_specs, n_colors: int) -> NDArray[Any]: +def get_colorarray_from_plotly(cmap: CmapSpecs, n_colors: int) -> NDArray[Any]: if n_colors == 1: return plotly.colors.sample_colorscale(cmap, samplepoints=0.5, colortype="tuple") @@ -58,7 +58,7 @@ def get_colorarray_from_plotly(cmap: Cmap_specs, n_colors: int) -> NDArray[Any]: def cmap_to_array( n_colors: int, - cmap: Cmap_specs | matplotlib.colors.Colormap | None, + cmap: CmapSpecs | matplotlib.colors.Colormap | None, ) -> NDArray[Any]: """Returns n_colors linearly spaced values on the colormap specified from cmap.""" @@ -85,7 +85,7 @@ def cmap_to_array( def to_rgb_string(color_reference: tuple[float, float, float] | str) -> str: - """Transforms a color reference into a plotly-compatible rgb string""" + """Transforms a color reference into a plotly-compatible rgb string.""" if isinstance(color_reference, str): color_reference = to_rgb(color_reference) @@ -93,11 +93,12 @@ def to_rgb_string(color_reference: tuple[float, float, float] | str) -> str: def rgb_string_array_from_colormap( - n_colors: int, color_palette: Cmap_specs | matplotlib.colors.Colormap | None + n_colors: int, color_palette: CmapSpecs | matplotlib.colors.Colormap | None ) -> list[str]: """Returns a list of RGB string given `n_colors` and a `color_palette` reference. - This function attempts to extract RGB color values from built-in Plotly, Seaborn and finally Matplotlib colormaps. + This function attempts to extract RGB color values from built-in Plotly, Seaborn and finally + Matplotlib colormaps. """ rgb_array = cmap_to_array(n_colors, color_palette) @@ -110,7 +111,7 @@ def compute_colorscale( # noqa PLR0912 C901 n_colors: int, color_system: ColorSystem, logscale: float | None = 10, - color_palette: Cmap_specs | matplotlib.colors.Colormap | None = None, + color_palette: CmapSpecs | matplotlib.colors.Colormap | None = None, ) -> str | list[list[float | str]]: """Returns a plotly-compatible colorscale depending on the color system chosen by user. diff --git a/statsplotly/plot_specifiers/common.py b/src/statsplotly/plot_specifiers/common.py similarity index 100% rename from statsplotly/plot_specifiers/common.py rename to src/statsplotly/plot_specifiers/common.py diff --git a/statsplotly/plot_specifiers/data/__init__.py b/src/statsplotly/plot_specifiers/data/__init__.py similarity index 100% rename from statsplotly/plot_specifiers/data/__init__.py rename to src/statsplotly/plot_specifiers/data/__init__.py diff --git a/statsplotly/plot_specifiers/data/_core.py b/src/statsplotly/plot_specifiers/data/_core.py similarity index 88% rename from statsplotly/plot_specifiers/data/_core.py rename to src/statsplotly/plot_specifiers/data/_core.py index 9e0f2a9..46e86e9 100644 --- a/statsplotly/plot_specifiers/data/_core.py +++ b/src/statsplotly/plot_specifiers/data/_core.py @@ -2,14 +2,16 @@ import logging from collections.abc import Callable, Generator, Sequence -from enum import Enum -from functools import wraps -from typing import Any, TypeAlias, TypeVar +from enum import StrEnum +from functools import cached_property, wraps +from typing import Any, ParamSpec, TypeAlias, TypeVar import numpy as np import pandas as pd import scipy as sc -from numpy.typing import ArrayLike, NDArray +from numpy.typing import NDArray +from pandas.api.extensions import ExtensionDtype +from pandas.core.groupby import DataFrameGroupBy from pydantic import ValidationInfo, field_validator, model_validator from statsplotly import constants @@ -25,30 +27,30 @@ logger = logging.getLogger(__name__) -class DataDimension(str, Enum): +class DataDimension(StrEnum): X = "x" Y = "y" Z = "z" -class SliceTraceType(str, Enum): +class SliceTraceType(StrEnum): ALL_DATA = "all data" SLICE = "slice" -class NormalizationType(str, Enum): +class NormalizationType(StrEnum): CENTER = "center" MIN_MAX = "minmax" ZSCORE = "zscore" -class RegressionType(str, Enum): +class RegressionType(StrEnum): LINEAR = "linear" EXPONENTIAL = "exponential" INVERSE = "inverse" -class AggregationType(str, Enum): +class AggregationType(StrEnum): MEAN = "mean" GEO_MEAN = "geo_mean" COUNT = "count" @@ -58,12 +60,12 @@ class AggregationType(str, Enum): SUM = "sum" -class CentralTendencyType(str, Enum): +class CentralTendencyType(StrEnum): MEAN = "mean" MEDIAN = "median" -class ErrorBarType(str, Enum): +class ErrorBarType(StrEnum): SEM = "sem" IQR = "iqr" STD = "std" @@ -71,7 +73,7 @@ class ErrorBarType(str, Enum): BOOTSTRAP = "bootstrap" -class HistogramNormType(str, Enum): +class HistogramNormType(StrEnum): COUNT = "" PERCENT = "percent" PROBABILITY = "probability" @@ -92,7 +94,7 @@ class HistogramNormType(str, Enum): ) ) -AGG_DIMENSION_TO_ERROR_DIMENSION = dict( +AGG_DIMENSION_TO_ERROR_DIMENSION_MAP = dict( zip( DataDimension, ["_".join(("error", dimension.value)) for dimension in DataDimension], @@ -100,21 +102,22 @@ class HistogramNormType(str, Enum): ) ) - F = TypeVar("F", bound=Callable[..., Any]) +P = ParamSpec("P") + -_Dtype: TypeAlias = np.dtype[Any] | pd.ArrowDtype -DataFormat: TypeAlias = pd.DataFrame | dict[str, Sequence[ArrayLike]] | ArrayLike +DataFormat: TypeAlias = pd.DataFrame | dict[str, Sequence[NDArray[Any]]] | NDArray[Any] +_DType: TypeAlias = ExtensionDtype | np.dtype[Any] class DataTypes(BaseModel): - x: _Dtype | None = None - y: _Dtype | None = None - z: _Dtype | None = None - color: _Dtype | None = None - marker: _Dtype | None = None - size: _Dtype | None = None - text: _Dtype | None = None + x: _DType | None = None + y: _DType | None = None + z: _DType | None = None + color: _DType | None = None + marker: _DType | None = None + size: _DType | None = None + text: _DType | None = None class DataPointer(BaseModel): @@ -148,7 +151,7 @@ def text_identifiers(self) -> list[str] | None: class DataHandler(BaseModel): data: pd.DataFrame data_pointer: DataPointer - slice_order: list[str] | None = None + slice_order: list[Any] | None = None slice_logical_indices: dict[str, NDArray[Any]] | None = None @model_validator(mode="after") @@ -172,7 +175,7 @@ def check_header_format(cls, value: pd.DataFrame) -> pd.DataFrame: return value @field_validator("data") - def convert_categorical_dtype_columns(cls, value: pd.DataFrame) -> pd.DataFrame: + def convert_categorical_columns(cls, value: pd.DataFrame) -> pd.DataFrame: for column in value.columns: if isinstance(value[column].dtype, pd.CategoricalDtype): logger.debug(f"Casting categorical '{column}' data to string") @@ -191,7 +194,7 @@ def n_slices(self) -> int: return len(self.slice_logical_indices) return 1 - @property + @cached_property def data_types(self) -> DataTypes: dtypes = self.data.dtypes data_types: dict[str, Any] = {} @@ -202,20 +205,20 @@ def data_types(self) -> DataTypes: return DataTypes.model_validate(data_types) @property - def _slicer_groupby_data(self) -> pd.DataFrame | pd.Grouper: + def _slicer_groupby_data(self) -> pd.DataFrame | DataFrameGroupBy: if self.data_pointer.slicer is not None: return self.data.groupby(self.data_pointer.slicer, sort=False) return self.data @staticmethod def _get_data_slice_indices( - slice_ids: pd.Series, slice_order: list[str] | None + slice_ids: pd.Series, slice_order: list[Any] | None ) -> dict[str, NDArray[Any]]: if slice_order is not None: if len(excluded_slices := set(slice_ids.unique()).difference(set(slice_order))) > 0: logger.info( - f"{np.array([*excluded_slices])} slices are not present in slices {slice_order} and" - " will not be plotted" + f"{np.array([*excluded_slices])} slices are not present in slices " + f"{slice_order} and will not be plotted" ) slices: list[str] = [] for slice_id in slice_order: @@ -226,7 +229,7 @@ def _get_data_slice_indices( ) slices.append(str(slice_id)) else: - slices = slice_ids.dropna().unique().astype(str) + slices = slice_ids.dropna().unique().astype(str).tolist() logical_indices: dict[str, NDArray[Any]] = {} for slice_id in slices: @@ -235,11 +238,11 @@ def _get_data_slice_indices( return logical_indices @staticmethod - def to_dataframe(function: F) -> pd.DataFrame: - @wraps(function) + def to_dataframe(func: Callable[P, pd.DataFrame]) -> Callable[P, pd.DataFrame]: + @wraps(func) def wrapper(*args: Any, **kwargs: Any) -> pd.DataFrame: - pandas_output = function(*args, **kwargs) - if len(pandas_output.shape) == 1: + pandas_output = func(*args, **kwargs) + if isinstance(pandas_output, pd.Series): return pandas_output.to_frame().transpose() return pandas_output @@ -250,7 +253,7 @@ def build_handler( cls, data: DataFormat, data_pointer: DataPointer, - slice_order: list[str] | None = None, + slice_order: list[Any] | None = None, ) -> DataHandler: slice_logical_indices = None @@ -313,25 +316,14 @@ def iter_slices( class DataProcessor(BaseModel): data_values_map: dict[DataDimension, dict[str, Any]] | None = None jitter_settings: dict[DataDimension, float] | None = None - normalizer: dict[DataDimension, NormalizationType] | None = None - - @field_validator("normalizer", mode="before") - def check_normalizer( - cls, value: dict[DataDimension, Any] - ) -> dict[DataDimension, NormalizationType]: - validated_norm: dict[DataDimension, NormalizationType] = {} - for dimension, normalization in value.items(): - if normalization is not None: - validated_norm.update({dimension: normalization}) - - return validated_norm + normalizer: dict[DataDimension, NormalizationType | None] | None = None @staticmethod def jitter_data(data_series: pd.Series, jitter_amount: float) -> pd.Series: if jitter_amount == 0: return data_series - return pd.Series(rand_jitter(data_series, jitter_amount), name=data_series.name) + return pd.Series(rand_jitter(data_series.to_numpy(), jitter_amount), name=data_series.name) @staticmethod def normalize_data(data_series: pd.Series, normalizer: NormalizationType) -> pd.Series: @@ -349,7 +341,7 @@ def normalize_data(data_series: pd.Series, normalizer: NormalizationType) -> pd. name=data_series.name, ) - def process_trace_data(self, trace_data: dict[str, pd.Series]) -> pd.Series: + def process_trace_data(self, trace_data: dict[str, pd.Series]) -> dict[str, pd.Series]: if self.data_values_map is not None: for dimension, values_map in self.data_values_map.items(): trace_data[TRACE_DIMENSION_MAP[dimension]] = ( @@ -417,7 +409,8 @@ def check_aggregation_specifier(self) -> AggregationSpecifier: if (aggregation_func := self.aggregation_func) is not None: if getattr(self.data_pointer, self.aggregated_dimension) is None: raise StatsPlotSpecificationError( - f"aggregation dimension `{self.aggregated_dimension}` not found in the data" + f"aggregation dimension `{self.aggregated_dimension.value}` not found in the " + f"data" ) # text can not be displayed along aggregation trace @@ -500,8 +493,9 @@ def check_error_data(cls, value: pd.Series | None) -> pd.Series | None: if not all( value.apply( - lambda x: np.issubdtype(np.asarray(x).dtype, np.number) - or any(xx is None for xx in x) + lambda x: ( + np.issubdtype(np.asarray(x).dtype, np.number) or any(xx is None for xx in x) + ) ) ): raise ValueError(f"{value.name} error data must be numeric") @@ -518,7 +512,7 @@ def check_error_data(cls, value: pd.Series | None) -> pd.Series | None: def assemble_hover_text( cls, data: pd.DataFrame, text_pointers: list[str] | None ) -> pd.Series | None: - """Converts text columns of a DataFrame into plotly text box""" + """Converts text columns of a DataFrame into plotly text box.""" if text_pointers is None: return None lines = [] @@ -562,14 +556,19 @@ def _build_trace_data_from_pointer( data[pointer.color] if pointer.color in data.columns else pointer.color ) trace_data["size_data"] = ( - range_normalize( - data[pointer.size], constants.MIN_MARKER_SIZE, constants.MAX_MARKER_SIZE + pd.Series( + range_normalize( + data[pointer.size].to_numpy(), + constants.MIN_MARKER_SIZE, + constants.MAX_MARKER_SIZE, + ), + name=pointer.size, ) if pointer.size in data.columns else pointer.size ) trace_data["opacity_data"] = ( - range_normalize(data[pointer.opacity], 0, 1) + pd.Series(range_normalize(data[pointer.opacity].to_numpy(), 0, 1), name=pointer.opacity) if pointer.opacity in data.columns else pointer.opacity ) @@ -579,7 +578,7 @@ def _build_trace_data_from_pointer( class TraceData(_BaseTraceData): @classmethod - def build_trace_data( + def build_from_data( cls, data: pd.DataFrame, pointer: DataPointer, @@ -593,12 +592,11 @@ def build_trace_data( class AggregationTraceData(TraceData): - @classmethod def _compute_error_bar( cls, - data_group: pd.Grouper, - agg_function: F, + data_group: DataFrameGroupBy, + agg_function: Callable[[Any], float], error_bar: ErrorBarType | Callable[[Any], NDArray[Any]], ) -> pd.Series: if error_bar in (ErrorBarType.STD, ErrorBarType.SEM): @@ -609,8 +607,11 @@ def _compute_error_bar( case ErrorBarType.SEM: error_data = data_group.apply( - lambda series: sem(series, 1 - constants.CI_ALPHA) + lambda series: sem(series.to_numpy(), 1 - constants.CI_ALPHA) ) + case _: + msg = f"Unsupported error bar type: {error_bar}" + raise StatsPlotMissingImplementationError(msg) return pd.Series( zip(data_agg - error_data, data_agg + error_data, strict=True), @@ -640,7 +641,7 @@ def _compute_error_bar( ) ) - if isinstance(error_bar, Callable): # type: ignore + if callable(error_bar): return data_group.apply(error_bar) raise StatsPlotMissingImplementationError(f"Unsupported error bar type: {error_bar}") @@ -713,7 +714,7 @@ def _build_aggregation_data_from_pointer( if aggregation_specifier.error_bar is not None: trace_data[ - AGG_DIMENSION_TO_ERROR_DIMENSION[aggregation_specifier.aggregated_dimension] + AGG_DIMENSION_TO_ERROR_DIMENSION_MAP[aggregation_specifier.aggregated_dimension] ] = cls._compute_error_bar( data.groupby(aggregation_specifier.reference_data, sort=False)[ aggregation_specifier.aggregated_data @@ -725,7 +726,7 @@ def _build_aggregation_data_from_pointer( return trace_data @classmethod - def build_aggregation_trace_data( + def build_from_aggregated_data( cls, data: pd.DataFrame, aggregation_specifier: AggregationSpecifier ) -> AggregationTraceData: trace_data = cls._build_aggregation_data_from_pointer(data, aggregation_specifier) diff --git a/statsplotly/plot_specifiers/data/_utils.py b/src/statsplotly/plot_specifiers/data/_utils.py similarity index 71% rename from statsplotly/plot_specifiers/data/_utils.py rename to src/statsplotly/plot_specifiers/data/_utils.py index b89aeca..c6f29da 100644 --- a/statsplotly/plot_specifiers/data/_utils.py +++ b/src/statsplotly/plot_specifiers/data/_utils.py @@ -7,8 +7,8 @@ def rand_jitter(data: NDArray[Any], jitter_amount: float = 1) -> NDArray[Any]: - """from https://stackoverflow.com/questions/8671808/matplotlib-avoiding - -overlapping-datapoints-in-a-scatter-dot-beeswarm-plot""" + """From https://stackoverflow.com/questions/8671808/matplotlib-avoiding + -overlapping-datapoints-in-a-scatter-dot-beeswarm-plot.""" spread = 0.01 * ((max(data) - min(data)) or 1) * jitter_amount return data + np.random.randn(len(data)) * spread diff --git a/statsplotly/plot_specifiers/data/statistics.py b/src/statsplotly/plot_specifiers/data/statistics.py similarity index 96% rename from statsplotly/plot_specifiers/data/statistics.py rename to src/statsplotly/plot_specifiers/data/statistics.py index 4c92225..48a800a 100644 --- a/statsplotly/plot_specifiers/data/statistics.py +++ b/src/statsplotly/plot_specifiers/data/statistics.py @@ -25,17 +25,17 @@ def compute_ssquares(y: NDArray[Any], yhat: NDArray[Any]) -> tuple[float, float, def inverse_func(x: NDArray[Any], a: float, b: float) -> NDArray[Any]: - """The reciprocal function""" + """The reciprocal function.""" return b + a / x def affine_func(x: NDArray[Any], a: float, b: float) -> NDArray[Any]: - """The affine function""" + """The affine function.""" return a * x + b -def logarithmic_func(x: NDArray[Any], a: float, b: float) -> float: - """The logarithmic function""" +def logarithmic_func(x: NDArray[Any], a: float, b: float) -> NDArray[Any]: + """The logarithmic function.""" return b + a * np.log(x) @@ -63,7 +63,7 @@ def regress( def exponential_regress( x: NDArray[Any], y: NDArray[Any] ) -> tuple[NDArray[Any], float, tuple[NDArray[Any], NDArray[Any]]]: - """Exponential regression via linear regression of the logarithm""" + """Exponential regression via linear regression of the logarithm.""" # For fitting y = AeBx, take the logarithm of both side gives # log y = log A + Bx. So fit (log y) against x # We weigh the points by the square root of their magnitude diff --git a/statsplotly/plot_specifiers/figure/__init__.py b/src/statsplotly/plot_specifiers/figure/__init__.py similarity index 100% rename from statsplotly/plot_specifiers/figure/__init__.py rename to src/statsplotly/plot_specifiers/figure/__init__.py diff --git a/statsplotly/plot_specifiers/figure/_core.py b/src/statsplotly/plot_specifiers/figure/_core.py similarity index 83% rename from statsplotly/plot_specifiers/figure/_core.py rename to src/statsplotly/plot_specifiers/figure/_core.py index 0333ac6..9609d08 100644 --- a/statsplotly/plot_specifiers/figure/_core.py +++ b/src/statsplotly/plot_specifiers/figure/_core.py @@ -3,13 +3,20 @@ import logging import re from abc import ABCMeta, abstractmethod -from typing import Generic, TypeVar +from typing import TYPE_CHECKING, Generic, Self, TypeVar import plotly.graph_objs as go +from plotly.basedatatypes import BaseTraceType from plotly.subplots import make_subplots -from statsplotly.plot_objects.layout import SceneLayout, layout_type -from statsplotly.plot_objects.trace import BaseTrace +from statsplotly.plot_objects.layout import ( + BarLayout, + CategoricalLayout, + HeatmapLayout, + HistogramLayout, + ScatterLayout, + SceneLayout, +) from statsplotly.plot_specifiers.data import DataDimension from statsplotly.plot_specifiers.layout import ColoraxisReference from statsplotly.plot_specifiers.trace import HistogramSpecifier, JointplotSpecifier @@ -21,19 +28,25 @@ T = TypeVar("T") +LayoutType = ( + HeatmapLayout | CategoricalLayout | ScatterLayout | SceneLayout | BarLayout | HistogramLayout +) + + class BasePlot(FigureSubplotFormatter, Generic[T], metaclass=ABCMeta): plot_specifier: T + @classmethod @abstractmethod - def initialize( - cls, fig: go.Figure | None, row: int | None, col: int | None, plot_specifier: T - ) -> BasePlot[T]: - """This method implements the logic to initialize a subplot layout.""" + def initialize(cls, fig: go.Figure | None, row: int, col: int, plot_specifier: T) -> Self: + """Initializes a subplot layout.""" + ... @property @abstractmethod def main_row(self) -> int: - """This method returns the index of the main row in the subplot (i.e., the row with the core Figure object).""" + """Returns the index of the main row in the subplot.""" + ... class HistogramPlot(BasePlot[HistogramSpecifier]): @@ -58,10 +71,10 @@ def main_row(self) -> int: def initialize( cls, fig: go.Figure | None, - row: int | None, - col: int | None, + row: int, + col: int, plot_specifier: HistogramSpecifier, - ) -> HistogramPlot: + ) -> Self: if fig is None: if plot_specifier.central_tendency is not None: match plot_specifier.dimension: @@ -84,6 +97,8 @@ def initialize( else: fig = make_subplots(rows=1, cols=1) + if TYPE_CHECKING: + assert fig is not None return cls( fig=fig, row=row, @@ -100,17 +115,21 @@ def main_row(self) -> int: return self.row + 1 if self.plot_specifier.plot_x_distribution else self.row def tidy_plot(self) -> JointplotPlot: - # We are limited to formatting only axes in the figure, as in the current implementation of jointplot, - # coloraxes are managed at the trace level instead of the layout level. - # TODO: Define coloraxes at the layout level and use _SubplotGridCommonColoraxisFormatter class for formatting. + """Tidies up the jointplot figure layout. + + We are limited to formatting only axes in the figure, as in the current implementation of + jointplot, coloraxes are managed at the trace level instead of the layout level. + """ + # TODO: Define coloraxes at the layout level and use _SubplotGridCommonColoraxisFormatter + # class for formatting. subplot_grid_formatter = SubplotGridFormatter(fig=self.fig) if self.plot_specifier.plot_x_distribution: subplot_grid_formatter.set_common_axis_limit( - shared_grid_axis=SharedGridAxis.COLS, common_range=True, link_axes=True + shared_grid_axis=SharedGridAxis.COLS.value, common_range=True, link_axes=True ) if self.plot_specifier.plot_y_distribution: subplot_grid_formatter.set_common_axis_limit( - shared_grid_axis=SharedGridAxis.ROWS, common_range=True, link_axes=True + shared_grid_axis=SharedGridAxis.ROWS.value, common_range=True, link_axes=True ) subplot_grid_formatter.tidy_subplots() @@ -120,8 +139,8 @@ def tidy_plot(self) -> JointplotPlot: def initialize( cls, fig: go.Figure | None, - row: int | None, - col: int | None, + row: int, + col: int, plot_specifier: JointplotSpecifier, ) -> JointplotPlot: if fig is None: @@ -145,9 +164,9 @@ def initialize( def create_fig( # noqa: PLR0912 C901 - fig: go.Figure, - traces: dict[str, BaseTrace], - layout: layout_type, + fig: go.Figure | None, + traces: dict[str, BaseTraceType], + layout: LayoutType, row: int | None, col: int | None, secondary_y: bool = False, diff --git a/statsplotly/plot_specifiers/figure/_utils.py b/src/statsplotly/plot_specifiers/figure/_utils.py similarity index 83% rename from statsplotly/plot_specifiers/figure/_utils.py rename to src/statsplotly/plot_specifiers/figure/_utils.py index a778d41..8953df8 100644 --- a/statsplotly/plot_specifiers/figure/_utils.py +++ b/src/statsplotly/plot_specifiers/figure/_utils.py @@ -5,16 +5,18 @@ import functools import logging from abc import ABCMeta, abstractmethod -from collections.abc import Callable, Generator -from enum import Enum -from typing import Any +from collections.abc import Callable, Generator, Sequence +from enum import StrEnum +from typing import Any, Self import numpy as np +import pandas as pd import plotly import plotly.graph_objs as go from numpy.typing import NDArray from plotly.exceptions import PlotlyKeyError -from pydantic import ValidationInfo, field_validator +from pydantic import Field, field_validator, model_validator +from typing_extensions import override from statsplotly import constants from statsplotly._base import BaseModel @@ -27,16 +29,17 @@ ColoraxisReference, PlotAxis, ) +from statsplotly.types import PlotAxisLiteral, SharedGridAxisLiteral logger = logging.getLogger(__name__) -class GridAxis(str, Enum): +class GridAxis(StrEnum): COLS = "cols" ROWS = "rows" -class SharedGridAxis(str, Enum): +class SharedGridAxis(StrEnum): COLS = "cols" ROWS = "rows" ALL = "all" @@ -45,8 +48,8 @@ class SharedGridAxis(str, Enum): AXIS_TO_DATA_MAP = {PlotAxis.XAXIS: DataDimension.X, PlotAxis.YAXIS: DataDimension.Y} -class FigureLayoutFormatter(BaseModel): - fig: go.Figure +class _FigureLayoutFormatter(BaseModel): + fig: go.Figure = Field(..., kw_only=False) @property def coloraxis_references(self) -> NDArray[Any]: @@ -96,8 +99,7 @@ def update_coloraxis_reference( trace.marker = trace.marker.update({"coloraxis": new_coloraxis_ref}) -class _SubplotGridValidator(FigureLayoutFormatter): - +class _SubplotGridValidator(_FigureLayoutFormatter): @field_validator("fig") def validate_subplot_grid(cls, fig: go.Figure) -> go.Figure: if fig._grid_ref is None: @@ -161,19 +163,8 @@ def format_colorbar_in_subplots_layout( class _SubplotGridCommonAxisFormatter(BaseModel, metaclass=ABCMeta): fig: go.Figure - plot_axis: PlotAxis | None shared_grid_axis: SharedGridAxis - @property - def dimension(self) -> PlotAxis | None: - if self.plot_axis is None: - if self.shared_grid_axis is SharedGridAxis.COLS: - return PlotAxis.XAXIS - if self.shared_grid_axis is SharedGridAxis.ROWS: - return PlotAxis.YAXIS - - return self.plot_axis - @property def _plot_groups(self) -> list[list[plotly.subplots.SubplotRef]]: if self.shared_grid_axis == GridAxis.COLS: # type: ignore[comparison-overlap] @@ -207,37 +198,15 @@ def get_plot_group_axes_reference( ) -> list[dict[str, Any]]: return [axes[0].trace_kwargs for axes in plot_group] - def get_target_axes_from_target_traces( - self, target_traces: list[plotly.basedatatypes.BaseTraceType] - ) -> list[str]: - if self.dimension is PlotAxis.XAXIS: - idx = 0 - elif self.dimension is PlotAxis.YAXIS: - idx = 1 - else: - raise StatsPlotSpecificationError( - f"Can not get target axes for plot_axis={self.plot_axis}" - ) - - return [ - axes[0].layout_keys[idx] - for plot_group in self.iter_plot_groups() - for axes in plot_group - if axes[0].trace_kwargs[self.dimension.value] - in [trace[self.dimension.value] for trace in target_traces] - ] - @abstractmethod - def get_target_traces( - self, plot_group: list[plotly.subplots.SubplotRef] - ) -> list[plotly.basedatatypes.BaseTraceType]: - """This method returns a list of plotly traces belonging to the `plot_group` and relevant to the formatter.""" + def get_target_traces(self, plot_group: list[plotly.subplots.SubplotRef]) -> list[Any]: + """Returns a list of plotly traces belonging to the `plot_group` to be formatted.""" + ... @abstractmethod - def update_traces_and_layout( - self, target_traces: list[plotly.basedatatypes.BaseTraceType] - ) -> None: - """This method updates traces and layout attributes given the formatting arguments.""" + def update_traces_and_layout(self, target_traces: list[Any]) -> None: + """Updates traces and layout attributes given the formatting arguments.""" + ... def update_along_grid_axis(self) -> None: for plot_group in self.iter_plot_groups(): @@ -253,7 +222,7 @@ class _SubplotGridCommonColoraxisFormatter(_SubplotGridCommonAxisFormatter): @staticmethod def _get_heatmap_trace_colorlimit( - trace: plotly.basedatatypes.BaseTraceType, + trace: Any, ) -> tuple[float, float]: if trace.zmin is not None: z_min = trace.zmin @@ -269,14 +238,11 @@ def _get_heatmap_trace_colorlimit( @staticmethod def _get_scatter_trace_colorlimit( - trace: plotly.basedatatypes.BaseTraceType, + trace: Any, ) -> tuple[float, float]: - return np.min(trace.marker.color), np.max(trace.marker.color) - def get_target_traces( - self, plot_group: list[plotly.subplots.SubplotRef] - ) -> list[plotly.basedatatypes.BaseTraceType]: + def get_target_traces(self, plot_group: list[plotly.subplots.SubplotRef]) -> list[Any]: axes_reference = self.get_plot_group_axes_reference(plot_group=plot_group) return [ @@ -292,26 +258,23 @@ def get_target_traces( and (PlotAxis.COLORAXIS in trace or trace.marker[PlotAxis.COLORAXIS] is not None) ] - def update_traces_and_layout( - self, target_traces: list[plotly.basedatatypes.BaseTraceType] - ) -> None: + @override + def update_traces_and_layout(self, target_traces: list[Any]) -> None: # Update traces try: reference_coloraxis = target_traces[-1][PlotAxis.COLORAXIS] color_limit_function = self._get_heatmap_trace_colorlimit self.fig.for_each_trace( - lambda trace, reference_coloraxis=reference_coloraxis, target_traces=target_traces: ( - trace.update(coloraxis=reference_coloraxis) if trace in target_traces else () + lambda trace, ref_coloraxis=reference_coloraxis, target_traces=target_traces: ( + trace.update(coloraxis=ref_coloraxis) if trace in target_traces else () ) ) except PlotlyKeyError: reference_coloraxis = target_traces[-1].marker[PlotAxis.COLORAXIS] color_limit_function = self._get_scatter_trace_colorlimit self.fig.for_each_trace( - lambda trace, reference_coloraxis=reference_coloraxis, target_traces=target_traces: ( - trace.update(marker_coloraxis=reference_coloraxis) - if trace in target_traces - else () + lambda trace, ref_coloraxis=reference_coloraxis, target_traces=target_traces: ( + trace.update(marker_coloraxis=ref_coloraxis) if trace in target_traces else () ) ) @@ -362,29 +325,39 @@ def update_traces_and_layout( class _SubplotGridCommonXYAxisFormatter(_SubplotGridCommonAxisFormatter): + plot_axis: PlotAxis | None = None common_range: bool link_axes: bool - @field_validator("shared_grid_axis", mode="after") - def check_shared_grid_axis(cls, value: SharedGridAxis, info: ValidationInfo) -> SharedGridAxis: - if value is SharedGridAxis.ALL and info.data.get("plot_axis") is None: - raise StatsPlotSpecificationError( - f"`plot_axis` must be specified when using `shared_grid_axis = {SharedGridAxis.ALL.value}`" + @model_validator(mode="after") + def check_plot_axis_specification(self) -> Self: + if self.shared_grid_axis is SharedGridAxis.ALL and self.plot_axis is None: + msg = ( + f"`plot_axis` must be specified when using `shared_grid_axis = " + f"{SharedGridAxis.ALL.value}`" ) - return value + raise StatsPlotSpecificationError(msg) + return self + + @property + def dimension(self) -> PlotAxis | None: + if self.plot_axis is None: + if self.shared_grid_axis is SharedGridAxis.COLS: + return PlotAxis.XAXIS + if self.shared_grid_axis is SharedGridAxis.ROWS: + return PlotAxis.YAXIS + + return self.plot_axis @staticmethod def _check_numeric_cast(data: NDArray[Any]) -> bool: try: data.astype("float") return True - except (ValueError, AttributeError): + except (TypeError, AttributeError): return False - def _get_trace_axis_limit( - self, trace: plotly.basedatatypes.BaseTraceType - ) -> tuple[float, float] | None: - + def _get_trace_axis_limit(self, trace: Any) -> tuple[float, float] | None: if (trace_data := trace[AXIS_TO_DATA_MAP[self.dimension]]) is None: # type: ignore logger.info(f"Axis limits of {trace.name} of type {type(trace)} can not be extracted") return None @@ -395,15 +368,31 @@ def _get_trace_axis_limit( ) return None - sanitized_trace_data = [datum for datum in trace_data if datum is not None] + sanitized_trace_data = [d for d in trace_data if not pd.isna(d)] if len(sanitized_trace_data) == 0: return None - return np.min(sanitized_trace_data), np.max(sanitized_trace_data) + return min(sanitized_trace_data), max(sanitized_trace_data) - def get_target_traces( - self, plot_group: list[plotly.subplots.SubplotRef] - ) -> list[plotly.basedatatypes.BaseTraceType]: + def get_target_axes_from_target_traces(self, target_traces: list[Any]) -> list[str]: + if self.dimension is PlotAxis.XAXIS: + idx = 0 + elif self.dimension is PlotAxis.YAXIS: + idx = 1 + else: + raise StatsPlotSpecificationError( + f"Can not get target axes for plot_axis={self.plot_axis}" + ) + + return [ + axes[0].layout_keys[idx] + for plot_group in self.iter_plot_groups() + for axes in plot_group + if axes[0].trace_kwargs[self.dimension.value] + in [trace[self.dimension.value] for trace in target_traces] + ] + + def get_target_traces(self, plot_group: list[plotly.subplots.SubplotRef]) -> list[Any]: axes_reference = self.get_plot_group_axes_reference(plot_group=plot_group) if self.dimension not in [PlotAxis.XAXIS, PlotAxis.YAXIS]: raise StatsPlotSpecificationError( @@ -432,17 +421,18 @@ def _compute_axis_range( np.max([limit[1] if limit is not None else None for limit in axis_limits]), ] + logger.debug("Computed axis range: %s", [min_value, max_value]) return AxesSpecifier.pad_axis_range( axis_range=[min_value, max_value], padding_factor=constants.RANGE_PADDING_FACTOR ) except (ValueError, TypeError): # No computable limits + logger.debug("Could not compute axis range") return None - def update_traces_and_layout( - self, target_traces: list[plotly.basedatatypes.BaseTraceType] - ) -> None: + @override + def update_traces_and_layout(self, target_traces: list[Any]) -> None: # Update axis limits range_dict: dict[str, list[float] | None] = {"range": None} if self.common_range: @@ -482,7 +472,6 @@ def _get_col_xaxes_references(self, col_idx: int) -> list[str]: def _reduce_axis_ticks_union( self, axes_reference_function: Callable[[int], list[str]] ) -> Callable[[int], list[str]]: - def _get_common_ticks(subplot_idx: int) -> list[str]: return list( functools.reduce( @@ -513,8 +502,8 @@ def check_common_yaxes_ticks(self, row_idx: int) -> bool: except TypeError: return True - def set_common_coloraxis(self, shared_grid_axis: str) -> SubplotGridFormatter: - """Set a common coloraxis along a shared grid axis + def set_common_coloraxis(self, shared_grid_axis: SharedGridAxis) -> SubplotGridFormatter: + """Set a common coloraxis along a shared grid axis. Args: shared_grid_axis: A :obj:`~statsplotly.plot_specifiers.figure.SharedGridAxis` value. @@ -531,23 +520,36 @@ def set_common_coloraxis(self, shared_grid_axis: str) -> SubplotGridFormatter: def set_common_axis_limit( self, - shared_grid_axis: str = SharedGridAxis.ALL, - plot_axis: str | None = None, + shared_grid_axis: SharedGridAxisLiteral = SharedGridAxis.ALL.value, + plot_axis: PlotAxisLiteral | None = None, common_range: bool = True, link_axes: bool = False, ) -> SubplotGridFormatter: - """Set common axis limits of a plot axis along a shared grid axis, optionally linking the axes. + """Set common axis limits along a shared grid axis, optionally linking the axes. Args: - shared_grid_axis: A :obj:`~statsplotly.plot_specifiers.figure.SharedGridAxis` value. - plot_axis: A :obj:`~statsplotly.plot_specifiers.layout.PlotAxis` value. + shared_grid_axis: + A :obj:`~statsplotly.plot_specifiers.figure.SharedGridAxis` value. + + plot_axis: + A :obj:`~statsplotly.plot_specifiers.layout.PlotAxis` value. + + - Defaults to :obj:`~statsplotly.plot_specifiers.layout.PlotAxis.YAXIS` + when ``shared_grid_axis`` = ``rows``. - - Default to :obj:`~statsplotly.plot_specifiers.layout.PlotAxis.YAXIS` when `shared_grid_axis` = :obj:`~statsplotly.plot_specifiers.figure.SharedGridAxis.ROWS`. - - Default to :obj:`~statsplotly.plot_specifiers.layout.PlotAxis.XAXIS` when `shared_grid_axis` = :obj:`~statsplotly.plot_specifiers.figure.SharedGridAxis.COLS`. - - Raises a :obj:`~statsplotly.exceptions.StatsPlotSpecificationError` when None and `shared_grid_axis` = :obj:`~statsplotly.plot_specifiers.figure.SharedGridAxis.ALL`. + - Defaults to :obj:`~statsplotly.plot_specifiers.layout.PlotAxis.XAXIS` + when ``shared_grid_axis`` = ``cols``. - common_range: If True (default), set a common range for the axes targeted by `plot_axis`. - link_axes: If True (default to False), links the axes targeted by `plot_axis`. + - Raises a :obj:`~statsplotly.exceptions.StatsPlotSpecificationError` + when ``None`` and ``shared_grid_axis`` = ``all``. + + common_range: + If ``True`` (default), set a common range for the axes targeted + by ``plot_axis``. + + link_axes: + If ``True`` (default ``False``), link the axes targeted by + ``plot_axis``. Returns: A :obj:`SubplotGridFormatter` instance. @@ -602,7 +604,8 @@ def set_suplotgrid_titles(self, grid_axis: GridAxis) -> Callable[..., Any]: def _apply_grid_titles(titles: str) -> None: if grid_axis_length != len(titles): raise StatsPlotSpecificationError( - f"Received {len(titles)} subplot titles for a {grid_axis.value} of length = {grid_axis_length}" + f"Received {len(titles)} subplot titles for a {grid_axis.value} of length = " + f"{grid_axis_length}" ) for i, title in enumerate(titles, 1): @@ -626,7 +629,6 @@ def tidy_axes(self) -> None: row < len(self.fig._grid_ref) - 1 and self.fig.layout[xaxis_ref].matches is not None ): - self.fig.update_layout( { xaxis_ref: { @@ -639,7 +641,6 @@ def tidy_axes(self) -> None: ) if col > 0 and self.fig.layout[yaxis_ref].matches is not None: - self.fig.update_layout( { yaxis_ref: { @@ -655,16 +656,18 @@ def tidy_subplots( self, title: str | None = None, no_legend: bool = False, - row_titles: list[str] | None = None, - col_titles: list[str] | None = None, + row_titles: Sequence[str] | None = None, + col_titles: Sequence[str] | None = None, ) -> SubplotGridFormatter: """Tidy a subplot grid by removing redundant axis titles and optionally adding annotations. Args: title: A string for the figure title. no_legend: If True, hides the legend. - row_titles: A list of string the size of the row dimension specifying a title for each row. - col_titles: A list of string the size of the column dimension specifying a title for each column. + row_titles: A list of string the size of the row dimension specifying a title for each + row. + col_titles: A list of string the size of the column dimension specifying a title for + each column. Returns: A :obj:`SubplotGridFormatter` instance. diff --git a/statsplotly/plot_specifiers/layout/__init__.py b/src/statsplotly/plot_specifiers/layout/__init__.py similarity index 100% rename from statsplotly/plot_specifiers/layout/__init__.py rename to src/statsplotly/plot_specifiers/layout/__init__.py diff --git a/statsplotly/plot_specifiers/layout/_core.py b/src/statsplotly/plot_specifiers/layout/_core.py similarity index 97% rename from statsplotly/plot_specifiers/layout/_core.py rename to src/statsplotly/plot_specifiers/layout/_core.py index bc1cb89..349772c 100644 --- a/statsplotly/plot_specifiers/layout/_core.py +++ b/src/statsplotly/plot_specifiers/layout/_core.py @@ -1,7 +1,7 @@ from __future__ import annotations import logging -from enum import Enum +from enum import StrEnum from typing import Any import numpy as np @@ -22,36 +22,36 @@ logger = logging.getLogger(__name__) -class PlotAxis(str, Enum): +class PlotAxis(StrEnum): XAXIS = "xaxis" YAXIS = "yaxis" COLORAXIS = "coloraxis" -class ColoraxisReference(str, Enum): +class ColoraxisReference(StrEnum): MAIN_COLORAXIS = "coloraxis" -class HistogramBarMode(str, Enum): +class HistogramBarMode(StrEnum): STACK = "stack" OVERLAY = "overlay" -class BarMode(str, Enum): +class BarMode(StrEnum): STACK = "stack" GROUP = "group" OVERLAY = "overlay" RELATIVE = "relative" -class AxisFormat(str, Enum): +class AxisFormat(StrEnum): SQUARE = "square" FIXED_RATIO = "fixed_ratio" EQUAL = "equal" ID_LINE = "id_line" -class AxisType(str, Enum): +class AxisType(StrEnum): TWO_DIMENSIONAL = "two_dimensional" THREE_DIMENSIONAL = "three_dimensional" diff --git a/statsplotly/plot_specifiers/layout/_utils.py b/src/statsplotly/plot_specifiers/layout/_utils.py similarity index 95% rename from statsplotly/plot_specifiers/layout/_utils.py rename to src/statsplotly/plot_specifiers/layout/_utils.py index a881967..af2bd9d 100644 --- a/statsplotly/plot_specifiers/layout/_utils.py +++ b/src/statsplotly/plot_specifiers/layout/_utils.py @@ -5,6 +5,7 @@ from typing import Any from plotly import graph_objs as go +from plotly.basedatatypes import BaseTraceType from statsplotly import constants from statsplotly.plot_specifiers.data import DataHandler, SliceTraceType @@ -29,7 +30,7 @@ def _slice_name_in_trace_name(slice_name: str) -> Callable[[str], re.Match[Any] def adjust_jointplot_legends( jointplot_specifier: JointplotSpecifier, - slices_marginal_traces: dict[str, Any], + slices_marginal_traces: dict[str, BaseTraceType], ) -> None: if len(slices_marginal_traces) == 0: return @@ -61,8 +62,8 @@ def adjust_jointplot_legends( def add_update_menu( fig: go.Figure, data_handler: DataHandler, - slices_traces: dict[str, Any] | None = None, - preplotted_traces: dict[str, Any] | None = None, + slices_traces: dict[str, BaseTraceType] | None = None, + preplotted_traces: dict[str, BaseTraceType] | None = None, ) -> go.Figure: trace_update_rule: dict[str, Any] = {} if slices_traces is None: diff --git a/statsplotly/plot_specifiers/trace.py b/src/statsplotly/plot_specifiers/trace.py similarity index 90% rename from statsplotly/plot_specifiers/trace.py rename to src/statsplotly/plot_specifiers/trace.py index 8929c71..5898dac 100644 --- a/statsplotly/plot_specifiers/trace.py +++ b/src/statsplotly/plot_specifiers/trace.py @@ -1,10 +1,10 @@ from __future__ import annotations import logging -from collections.abc import Callable -from enum import Enum +from collections.abc import Callable, Sequence +from enum import StrEnum from functools import wraps -from typing import Any, TypeVar, cast +from typing import TYPE_CHECKING, Any, TypeVar, cast import numpy as np import pandas as pd @@ -28,26 +28,26 @@ logger = logging.getLogger(__name__) -class TraceMode(str, Enum): +class TraceMode(StrEnum): MARKERS = "markers" LINES = "lines" MARKERS_LINES = "markers+lines" LINES_TEXT = "lines+text" -class CategoricalPlotType(str, Enum): +class CategoricalPlotType(StrEnum): STRIP = "stripplot" VIOLIN = "violinplot" BOX = "boxplot" -class MarginalPlotDimension(str, Enum): +class MarginalPlotDimension(StrEnum): X = "x" Y = "y" ALL = "all" -class JointplotType(str, Enum): +class JointplotType(StrEnum): SCATTER = "scatter" KDE = "kde" SCATTER_KDE = "scatter+kde" @@ -81,7 +81,7 @@ def validate_model(self) -> _XYTraceValidator: return self -class PlotOrientation(str, Enum): +class PlotOrientation(StrEnum): HORIZONTAL = "horizontal" VERTICAL = "vertical" @@ -133,9 +133,9 @@ def validate_mode(cls, value: str | None, info: ValidationInfo) -> TraceMode | N class CategoricalPlotSpecifier(OrientedPlotSpecifier, _TraceSpecifier, _XYTraceValidator): - plot_type: CategoricalPlotType + plot_type: CategoricalPlotType | None - @field_validator("plot_type", mode="before") + @field_validator("plot_type", mode="after") def validate_plot_type(cls, value: str | None) -> CategoricalPlotType: if value is None: return CategoricalPlotType.STRIP @@ -144,9 +144,13 @@ def validate_plot_type(cls, value: str | None) -> CategoricalPlotType: @model_validator(mode="after") def validate_model(self) -> CategoricalPlotSpecifier: if self.data_types.color is not None and self.plot_type is not CategoricalPlotType.STRIP: - raise StatsPlotSpecificationError( - f"Only slice-level color data can be specified with `{self.plot_type.value}`, got marker-level argument `color` of type {self.data_types.color}" + if TYPE_CHECKING: + assert self.plot_type is not None + msg = ( + f"Only slice-level color data can be specified with `{self.plot_type.value}`, " + f"got marker-level argument `color` of type {self.data_types.color}" ) + raise StatsPlotSpecificationError(msg) return self def get_category_strip_map( @@ -174,9 +178,9 @@ class HistogramSpecifier(_TraceSpecifier): ecdf: bool | None = None kde: bool | None = None rug: bool | None = None - histnorm: HistogramNormType + histnorm: HistogramNormType | None bin_edges: NDArray[Any] | None = None - bins: str | list[float] | int + bins: str | Sequence[float] | int central_tendency: CentralTendencyType | None = None data_type: np.dtype[Any] dimension: DataDimension @@ -194,7 +198,7 @@ def check_bins(cls, value: str | list[float] | int | None) -> str | list[float] return value if value is not None else constants.DEFAULT_HISTOGRAM_BIN_COMPUTATION_METHOD @field_validator("histnorm", mode="before") - def check_histnorm(cls, value: str | None, info: ValidationInfo) -> str | None: + def check_histnorm(cls, value: str | None, info: ValidationInfo) -> HistogramNormType: if info.data.get("kde"): if value is None: logger.info( @@ -203,7 +207,7 @@ def check_histnorm(cls, value: str | None, info: ValidationInfo) -> str | None: ) return HistogramNormType.PROBABILITY_DENSITY - return value or HistogramNormType.COUNT + return HistogramNormType(value) if value is not None else HistogramNormType.COUNT @field_validator("dimension") def check_dimension(cls, value: DataDimension, info: ValidationInfo) -> DataDimension: @@ -223,6 +227,8 @@ def check_parameter_consistency(self: HistogramSpecifier) -> HistogramSpecifier: if self.kde: if self.histnorm is not HistogramNormType.PROBABILITY_DENSITY: + if TYPE_CHECKING: + assert self.histnorm is not None raise StatsPlotSpecificationError( "Histogram norm must be set to" f" {HistogramNormType.PROBABILITY_DENSITY.value} with KDE plotting," @@ -281,7 +287,7 @@ def compute_histogram(self, data: pd.Series) -> tuple[pd.Series, NDArray[Any], f hist = np.cumsum(hist) return ( - pd.Series(hist, name=self.histnorm if len(self.histnorm) > 0 else "count"), + pd.Series(hist, name=self.histnorm if self.histnorm and len(hist) > 0 else "count"), bin_edges, bin_size, ) @@ -301,7 +307,7 @@ def compute_ecdf(self, data: pd.Series) -> tuple[pd.Series, NDArray[Any]]: cdf = cdf * 100 return ( - pd.Series(cdf, name=self.histnorm if len(self.histnorm) > 0 else "count"), + pd.Series(cdf, name=self.histnorm if len(cdf) > 0 else "count"), unique_values, ) @@ -402,6 +408,12 @@ def compute_histmap(self, trace_data: TraceData) -> tuple[pd.Series, pd.Series, trace_data.x_values, ) histogram_specifier = self.histogram_specifier[DataDimension.X].model_copy() + else: + msg = ( + f"Invalid plot type for histmap computation: {self.plot_type.value}, expected" + f" {JointplotType.X_HISTMAP.value} or {JointplotType.Y_HISTMAP.value}" + ) + raise ValueError(msg) # Get and set uniform bin edges along anchor values bin_edges, bin_size = histogram_specifier.get_histogram_bin_edges(histogram_data) @@ -417,6 +429,8 @@ def compute_histmap(self, trace_data: TraceData) -> tuple[pd.Series, pd.Series, # Bin centers bin_centers = (bin_edges[1:] + bin_edges[:-1]) / 2 + if TYPE_CHECKING: + assert histogram_specifier.histnorm is not None return ( pd.Series( np.repeat(anchor_values.unique(), hist.shape[1]), diff --git a/src/statsplotly/types.py b/src/statsplotly/types.py new file mode 100644 index 0000000..b0b2a01 --- /dev/null +++ b/src/statsplotly/types.py @@ -0,0 +1,25 @@ +from typing import Literal + +TraceModeLiteral = Literal["markers", "lines", "markers+lines", "lines+text"] +AxisFormatLiteral = Literal["square", "fixed_ratio", "equal", "id_line"] +NormalizationTypeLiteral = Literal["center", "minmax", "zscore"] +RegressionTypeLiteral = Literal["linear", "exponential", "inverse"] +ErrorBarLiteral = Literal["sem", "iqr", "std", "geo_std", "bootstrap"] +AggregationTypeLiteral = Literal[ + "mean", "geo_mean", "count", "median", "percent", "fraction", "sum" +] +CategoricalPlotTypeLiteral = Literal["boxplot", "violinplot", "stripplot"] +PlotOrientationTypeLiteral = Literal["horizontal", "vertical"] +BarModeLiteral = Literal["stack", "group", "overlay", "relative"] +HistogramBarModeLiteral = Literal["stack", "overlay"] + + +CentralTendencyTypeLiteral = Literal["mean", "median", "mode"] +HistogramNormTypeLiteral = Literal["", "percent", "probability", "probability density"] +JointplotTypeLiteral = Literal[ + "scatter", "kde", "scatter+kde", "x_histmap", "y_histmap", "histogram" +] + +MarginalPlotDimensionLiteral = Literal["x", "y", "all"] +SharedGridAxisLiteral = Literal["cols", "rows", "all"] +PlotAxisLiteral = Literal["xaxis", "yaxis", "coloraxis"] diff --git a/statsplotly/utils.py b/src/statsplotly/utils.py similarity index 100% rename from statsplotly/utils.py rename to src/statsplotly/utils.py diff --git a/tests/conftest.py b/tests/conftest.py index 35a7dd4..79bdd79 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,3 +1,6 @@ +from collections.abc import Callable +from typing import Any, Literal + import numpy as np import pandas as pd import pytest @@ -5,7 +8,7 @@ from statsplotly.plot_specifiers.data import DataHandler, DataPointer, TraceData from statsplotly.plot_specifiers.layout import LegendSpecifier -_EXAMPLE_INPUT_DATA_DICT = {"x": ["a", "b", "c"], "y": range(3), "z": range(3)} +_EXAMPLE_INPUT_DATA_DICT = {"x": ["a", "b", "c"], "y": range(3), "z": range(3), "size": [8, 8, 8]} _EXAMPLE_DATETIME_DATAFRAME = pd.DataFrame( zip( @@ -19,52 +22,62 @@ @pytest.fixture(scope="module") -def example_input_data_dict(): +def example_input_data_dict() -> dict[str, Any]: return _EXAMPLE_INPUT_DATA_DICT @pytest.fixture(scope="module") -def example_input_dataframe(): - return pd.DataFrame(_EXAMPLE_INPUT_DATA_DICT) +def dataframe_factory() -> Callable[[Literal["numpy", "pyarrow"]], pd.DataFrame]: + def inner(backend: Literal["numpy", "pyarrow"] = "pyarrow") -> pd.DataFrame: + return pd.DataFrame(_EXAMPLE_INPUT_DATA_DICT).convert_dtypes( + dtype_backend=backend if backend == "pyarrow" else "numpy_nullable" + ) + + return inner + + +@pytest.fixture(scope="module") +def example_input_dataframe(dataframe_factory) -> pd.DataFrame: + return dataframe_factory(backend="numpy_nullable") @pytest.fixture(scope="module") -def example_input_datetime_dataframe(): +def example_input_datetime_dataframe() -> pd.DataFrame: return _EXAMPLE_DATETIME_DATAFRAME @pytest.fixture(scope="module") -def example_data_handler(): +def example_data_handler() -> DataHandler: return DataHandler.build_handler( - data=_EXAMPLE_INPUT_DATA_DICT, data_pointer=DataPointer(x="x", y="y", text="z") + data=_EXAMPLE_INPUT_DATA_DICT, data_pointer=DataPointer(x="x", y="y", text="z", size="size") ) @pytest.fixture(scope="module") -def example_trace_data(example_data_handler): - return TraceData.build_trace_data( +def example_trace_data(example_data_handler: DataHandler) -> TraceData: + return TraceData.build_from_data( data=example_data_handler.data, pointer=example_data_handler.data_pointer ) @pytest.fixture(scope="module") -def example_3dtrace_data(): +def example_3dtrace_data() -> TraceData: handler = DataHandler.build_handler( data=_EXAMPLE_INPUT_DATA_DICT, data_pointer=DataPointer(x="x", y="y", z="z") ) - return TraceData.build_trace_data( + return TraceData.build_from_data( data=handler.data, pointer=handler.data_pointer, ) @pytest.fixture(scope="module") -def example_datetime_trace_data(): - return TraceData.build_trace_data( +def example_datetime_trace_data() -> TraceData: + return TraceData.build_from_data( data=_EXAMPLE_DATETIME_DATAFRAME, pointer=DataPointer(x="x", y="y", text="z") ) @pytest.fixture(scope="module") -def example_legend(): +def example_legend() -> LegendSpecifier: return LegendSpecifier(data_pointer=DataPointer(x="x", y="y", text="z")) diff --git a/tests/test_color_specifiers.py b/tests/test_color_specifiers.py index 27800a1..853679c 100644 --- a/tests/test_color_specifiers.py +++ b/tests/test_color_specifiers.py @@ -1,4 +1,5 @@ import logging +import re import numpy as np import pandas as pd @@ -28,7 +29,6 @@ class TestColorSpecifier: - def test_color_specifier(self): color_specifier = ColorSpecifier.build_from_color_data(EXAMPLE_VALID_FLOAT_COLOR_DATA) assert color_specifier.colormap is None @@ -87,44 +87,42 @@ def test_seaborn_continuous_colorscale(self): ] assert coloraxis.colorscale is not None - def test_format_color_data(self, caplog): + def test_get_marker_color(self, caplog): # String - single_string_color_data = ColorSpecifier().format_color_data(color_data="blue") + single_string_color_data = ColorSpecifier().get_marker_color(color_data="blue") assert single_string_color_data == "blue" # Direct - direct_color_data = ColorSpecifier().format_color_data( - color_data=EXAMPLE_DIRECT_COLOR_ARRAY - ) + direct_color_data = ColorSpecifier().get_marker_color(color_data=EXAMPLE_DIRECT_COLOR_ARRAY) assert all(direct_color_data == EXAMPLE_DIRECT_COLOR_ARRAY) assert ( - f"{EXAMPLE_DIRECT_COLOR_ARRAY.name} values are all color-like, statsplotly will assume direct color specification" - in caplog.text + f"{EXAMPLE_DIRECT_COLOR_ARRAY.name} values are all color-like, statsplotly will assume " + f"direct color specification" in caplog.text ) # Integer - integer_color_data = ColorSpecifier().format_color_data(EXAMPLE_VALID_INT_COLOR_DATA) + integer_color_data = ColorSpecifier().get_marker_color(EXAMPLE_VALID_INT_COLOR_DATA) assert all(integer_color_data == EXAMPLE_VALID_INT_COLOR_DATA) # Float - float_color_data = ColorSpecifier().format_color_data( + float_color_data = ColorSpecifier().get_marker_color( color_data=EXAMPLE_VALID_FLOAT_COLOR_DATA ) assert all(float_color_data == EXAMPLE_VALID_FLOAT_COLOR_DATA) # Datetime - timestamp_color_data = ColorSpecifier().format_color_data( + timestamp_color_data = ColorSpecifier().get_marker_color( color_data=EXAMPLE_VALID_DATETIME_COLOR_DATA ) expected_output = [1.577837e09, 1.577923e09, 1.580688e09] - assert np.allclose( - timestamp_color_data, [1.577837e09, 1.577923e09, 1.580688e09] - ), f"Expected {expected_output} but got {result}" + assert np.allclose(timestamp_color_data, expected_output), ( + f"Expected {expected_output} but got {timestamp_color_data}" + ) # Mapping mapped_color_data = ColorSpecifier.build_from_color_data( EXAMPLE_INT_MAPPED_COLOR_ARRAY - ).format_color_data(color_data=EXAMPLE_INT_MAPPED_COLOR_ARRAY) + ).get_marker_color(color_data=EXAMPLE_INT_MAPPED_COLOR_ARRAY) assert all( mapped_color_data == EXAMPLE_INT_MAPPED_COLOR_ARRAY.map( @@ -137,18 +135,33 @@ def test_format_color_data(self, caplog): ) ) ) - assert ( - f"{EXAMPLE_INT_MAPPED_COLOR_ARRAY.name} values of type='object' are not continuous type, statsplotly will map it to colormap" - in caplog.text + + assert re.search( + r"values of type=('object'|'str') are not continuous type, statsplotly will map it to " + r"colormap", + caplog.text, ) with pytest.raises(StatsPlotSpecificationError) as excinfo: - ColorSpecifier().format_color_data(color_data=EXAMPLE_INT_MAPPED_COLOR_ARRAY) + ColorSpecifier().get_marker_color(color_data=EXAMPLE_INT_MAPPED_COLOR_ARRAY) assert ( - f"No colormap attribute to map discrete data onto, check {ColorSpecifier.__name__} instantiation" + "No colormap defined to map discrete data onto, check ColorSpecifier instantiation" in str(excinfo.value) ) + def test_get_line_color(self, caplog): + # String + single_string_color_data = ColorSpecifier().get_line_color(color_data="blue") + assert single_string_color_data == "blue" + + # Multiple colors select the first one but issues a warning + direct_color_data = ColorSpecifier().get_line_color(color_data=EXAMPLE_DIRECT_COLOR_ARRAY) + assert direct_color_data == EXAMPLE_DIRECT_COLOR_ARRAY[0] + assert ( + f"Multiple color values found for line: {EXAMPLE_DIRECT_COLOR_ARRAY.unique().tolist()}," + f" the first one will be used" in caplog.text + ) + def test_shared_coloraxis(self): coloraxis = ColorSpecifier.build_from_color_data( color_data=EXAMPLE_VALID_INT_COLOR_DATA @@ -175,6 +188,7 @@ def test_discrete_integer_coloraxis(self): color_data=EXAMPLE_VALID_INT_COLOR_DATA.astype(str), color_palette="Set3" ).build_coloraxis(color_data=EXAMPLE_VALID_INT_COLOR_DATA.astype(str)) # Verify colormap indices are repeated every two values + assert coloraxis.colorscale is not None assert np.diff(np.array([value[0] for value in coloraxis.colorscale]))[1::2].sum() == 0 def test_discrete_shared_coloraxis(self): diff --git a/tests/test_data_specifiers.py b/tests/test_data_specifiers.py index 3a0a7d5..02c506a 100644 --- a/tests/test_data_specifiers.py +++ b/tests/test_data_specifiers.py @@ -8,6 +8,7 @@ from statsplotly.plot_specifiers.data import ( AggregationSpecifier, AggregationTraceData, + AggregationType, DataDimension, DataHandler, DataPointer, @@ -16,6 +17,7 @@ NormalizationType, TraceData, ) +from statsplotly.plot_specifiers.data._core import ErrorBarType from statsplotly.plot_specifiers.data.statistics import sem logging.getLogger().setLevel(logging.DEBUG) @@ -38,6 +40,13 @@ def test_array_input(self): ) assert all(data_handler.get_data("x") == pd.Series(np.array((2, 2)))) + def test_numpy_backend(self, dataframe_factory): + example_input_dataframe = dataframe_factory(backend="numpy") + DataHandler.build_handler( + data=example_input_dataframe, + data_pointer=DataPointer(x="x", y="y", slicer="z"), + ) + def test_no_slicer(self, example_input_data_dict): data_handler = DataHandler.build_handler( data=example_input_data_dict, data_pointer=DataPointer(x="x", y="y") @@ -52,6 +61,7 @@ def test_slice_reorder(self, example_input_data_dict): slice_order=[0, 2, 1], ) assert data_handler.n_slices == 3 + assert data_handler.get_data("y") is not None assert (data_handler.get_data("y").to_numpy() == np.arange(3)).all() assert data_handler.slice_levels == [str(x) for x in [0, 2, 1]] assert [level for level, trace in list(data_handler.iter_slices())] == ["0", "2", "1"] @@ -63,6 +73,7 @@ def test_slice_partition(self, example_input_data_dict, caplog): slice_order=[0, 1], ) assert data_handler.n_slices == 2 + assert data_handler.get_data("y") is not None assert (data_handler.get_data("y").to_numpy() == np.arange(3)).all() assert data_handler.slice_levels == [str(x) for x in [0, 1]] assert [level for level, trace in list(data_handler.iter_slices())] == ["0", "1"] @@ -79,23 +90,16 @@ def test_invalid_slice_order(self, example_input_data_dict): slice_order=[0, 1, "non_existing_slice_id"], ) - def test_data_types(self, example_input_data_dict, example_input_dataframe): - data_handler = DataHandler.build_handler( - data=example_input_data_dict, - data_pointer=DataPointer(x="x", y="y", slicer="z"), - ) - assert all( - example_input_dataframe.dtypes.to_dict()[getattr(data_handler.data_pointer, key)] == val - for (key, val) in data_handler.data_types.model_dump().items() - if val is not None - ) - - def test_categorical_dtype_cast(self, example_input_dataframe, caplog): + @pytest.mark.parametrize(("backend"), ["pyarrow", "numpy"]) + def test_categorical_dtype_cast(self, dataframe_factory, backend, caplog): + if backend == "pyarrow": + pytest.importorskip("pyarrow") + example_input_dataframe = dataframe_factory(backend=backend) data_handler = DataHandler.build_handler( data=example_input_dataframe.assign(x=example_input_dataframe["x"].astype("category")), data_pointer=DataPointer(x="x", y="y", slicer="z"), ) - assert data_handler.data_types.x is np.dtype("object") + assert isinstance(data_handler.data_types.x, pd.StringDtype) assert "Casting categorical 'x' data to string" in caplog.text def test_datetime_dtype(self, example_input_datetime_dataframe): @@ -103,7 +107,7 @@ def test_datetime_dtype(self, example_input_datetime_dataframe): data=example_input_datetime_dataframe, data_pointer=DataPointer(x="x", y="y", slicer="z"), ) - assert data_handler.data_types.x == np.dtype("datetime64[ns]") + assert np.issubdtype(data_handler.data_types.x, np.datetime64) def test_slicer_groupby_mean_aggregation(self, example_input_data_dict): agg_df = DataHandler.build_handler( @@ -122,7 +126,7 @@ def test_no_groupby_median_aggregation(self, example_input_data_dict): assert len(agg_df.index.tolist()) == 1 def test_invalid_pointer(self, example_input_data_dict): - with pytest.raises(ValueError, match=rf"u is not present in Index\("): + with pytest.raises(ValueError, match=r"u is not present in Index\("): DataHandler.build_handler( data=example_input_data_dict, data_pointer=DataPointer(x="u"), @@ -132,7 +136,10 @@ def test_invalid_pointer(self, example_input_data_dict): def test_invalid_dataframe(self): with pytest.raises( ValueError, - match="Multi-indexed columns are not supported, flatten the header before calling statsplotly", + match=( + "Multi-indexed columns are not supported, flatten the header before calling" + " statsplotly" + ), ): DataHandler.build_handler( data=pd.DataFrame(columns=pd.MultiIndex.from_arrays((np.arange(3), np.arange(3)))), @@ -157,10 +164,7 @@ def test_valid_processor(self): assert data_processor.normalizer[DataDimension.X] is NormalizationType.ZSCORE def test_invalid_normalizer(self): - with pytest.raises( - ValueError, - match="1 validation error for DataProcessor\nnormalizer.x\n Input should be 'center', 'minmax' or 'zscore'", - ): + with pytest.raises(ValueError, match="Input should be 'center', 'minmax' or 'zscore'"): DataProcessor( jitter_settings={DataDimension.X: 0.2}, normalizer={DataDimension.X: "awesome_scaling"}, @@ -173,8 +177,8 @@ def test_unnormalizable_data(self, example_input_dataframe, caplog): processed_data = data_processor.process_trace_data({"x_values": example_input_dataframe.x}) assert (processed_data["x_values"] == example_input_dataframe.x).all() assert ( - f"Dimension {DataDimension.X.value} of type {example_input_dataframe.x.dtype} can not be" - f" normalized with {NormalizationType.ZSCORE.value}" in caplog.text + f"Dimension {DataDimension.X.value} of type {example_input_dataframe.x.dtype} can not " + f"be normalized with {NormalizationType.ZSCORE.value}" in caplog.text ) def test_unjitterable_data(self, example_input_dataframe, caplog): @@ -184,8 +188,8 @@ def test_unjitterable_data(self, example_input_dataframe, caplog): processed_data = data_processor.process_trace_data({"x_values": example_input_dataframe.x}) assert (processed_data["x_values"] == example_input_dataframe.x).all() assert ( - f"Dimension {DataDimension.X.value} of type {example_input_dataframe.x.dtype} can not be" - " jittered" in caplog.text + f"Dimension {DataDimension.X.value} of type {example_input_dataframe.x.dtype} can not " + "be jittered" in caplog.text ) def test_normalize_data(self, example_input_dataframe): @@ -197,8 +201,8 @@ def test_normalize_data(self, example_input_dataframe): class TestTraceData: - def test_build_trace_data(self, example_data_handler): - trace_data = TraceData.build_trace_data( + def test_build_trace_data(self, example_data_handler: DataHandler): + trace_data = TraceData.build_from_data( data=example_data_handler.data, pointer=example_data_handler.data_pointer ) assert (trace_data.x_values == example_data_handler.data.x).all() @@ -211,18 +215,21 @@ def test_build_trace_data(self, example_data_handler): ) ).all() - def test_invalid_error_data(self, example_data_handler): + def test_invalid_error_data(self, example_data_handler: DataHandler): with pytest.raises(ValueError, match="x error data must be numeric"): - TraceData.build_trace_data( + TraceData.build_from_data( data=example_data_handler.data, pointer=DataPointer(x="x", y="y", error_x="x"), ) with pytest.raises( ValueError, - match="error_z error data must be bidirectional to be plotted relative to the underlying data", + match=( + "error_z error data must be bidirectional to be plotted relative to the " + "underlying data" + ), ): - TraceData.build_trace_data( + TraceData.build_from_data( data=example_data_handler.data.copy().assign( error_z=example_data_handler.data.z.apply(lambda x: [x]) ), @@ -233,8 +240,8 @@ def test_invalid_error_data(self, example_data_handler): class TestAggregationSpecifier: def test_mean_agg_specifier(self): agg_specifier = AggregationSpecifier( - aggregation_func="mean", - aggregated_dimension="y", + aggregation_func=AggregationType.MEAN, + aggregated_dimension=DataDimension.Y, data_pointer=DataPointer(x="x", y="y"), data_types=DataTypes(x=np.dtype(float), y=np.dtype(float)), ) @@ -245,19 +252,18 @@ def test_mean_agg_specifier(self): assert agg_specifier.aggregation_plot_dimension is DataDimension.Y def test_no_agg_dimension(self): - with pytest.raises(ValueError) as excinfo: + with pytest.raises(ValueError, match="aggregation dimension `y` not found in the data"): AggregationSpecifier( - aggregation_func="mean", - aggregated_dimension="y", + aggregation_func=AggregationType.MEAN, + aggregated_dimension=DataDimension.Y, data_pointer=DataPointer(x="x"), data_types=DataTypes(x=np.dtype(float), y=np.dtype(float)), ) - assert "aggregation dimension `y` not found in the data" def test_count_agg_specifier(self): agg_specifier = AggregationSpecifier( - aggregation_func="count", - aggregated_dimension="x", + aggregation_func=AggregationType.COUNT, + aggregated_dimension=DataDimension.X, data_pointer=DataPointer(x="x"), data_types=DataTypes(x=np.dtype(float)), ) @@ -267,7 +273,7 @@ def test_count_agg_specifier(self): def test_invalid_count_agg_specifier(self): with pytest.raises(ValueError) as excinfo: AggregationSpecifier( - aggregation_func="count", + aggregation_func=AggregationType.COUNT, data_pointer=DataPointer(x="x", y="y"), data_types=DataTypes(x=np.dtype(float), y=np.dtype(float)), ) @@ -276,17 +282,18 @@ def test_invalid_count_agg_specifier(self): class TestAggregationTraceData: def test_build_trace_data_with_sem(self, example_data_handler): - trace_data = AggregationTraceData.build_aggregation_trace_data( + trace_data = AggregationTraceData.build_from_aggregated_data( data=example_data_handler.data, aggregation_specifier=AggregationSpecifier( - aggregation_func="mean", - aggregated_dimension="y", - error_bar="sem", + aggregation_func=AggregationType.MEAN, + aggregated_dimension=DataDimension.Y, + error_bar=ErrorBarType.SEM, data_pointer=DataPointer(x="x", y="y"), data_types=example_data_handler.data_types, ), ) assert (trace_data.y_values == example_data_handler.data.groupby("x")["y"].mean()).all() + assert trace_data.error_y is not None assert ( trace_data.error_y.tolist() == example_data_handler.data.groupby("x")["y"] @@ -300,34 +307,38 @@ def test_build_trace_data_with_sem(self, example_data_handler): ) def test_build_count_trace_data(self, example_data_handler): - trace_data = AggregationTraceData.build_aggregation_trace_data( + trace_data = AggregationTraceData.build_from_aggregated_data( data=example_data_handler.data, aggregation_specifier=AggregationSpecifier( - aggregation_func="count", - aggregated_dimension="y", + aggregation_func=AggregationType.COUNT, + aggregated_dimension=DataDimension.Y, data_pointer=DataPointer(y="y"), data_types=example_data_handler.data_types, ), ) + assert trace_data.x_values is not None assert ( trace_data.x_values.tolist() == example_data_handler.data.groupby("y")["y"].count() ).all() + assert trace_data.y_values is not None assert (trace_data.y_values.tolist() == example_data_handler.data["y"].unique()).all() def test_build_percent_trace_data(self, example_data_handler): - trace_data = AggregationTraceData.build_aggregation_trace_data( + trace_data = AggregationTraceData.build_from_aggregated_data( data=example_data_handler.data, aggregation_specifier=AggregationSpecifier( - aggregation_func="percent", - aggregated_dimension="y", + aggregation_func=AggregationType.PERCENT, + aggregated_dimension=DataDimension.Y, data_pointer=DataPointer(y="y"), data_types=example_data_handler.data_types, ), ) + assert trace_data.x_values is not None assert ( trace_data.x_values.tolist() == example_data_handler.data.groupby("y")["y"].count() / example_data_handler.data["y"].notnull().sum() * 100 ).all() + assert trace_data.y_values is not None assert (trace_data.y_values.tolist() == example_data_handler.data["y"].unique()).all() diff --git a/tests/test_figure_specifiers.py b/tests/test_figure_specifiers.py index bf30a15..369d9cb 100644 --- a/tests/test_figure_specifiers.py +++ b/tests/test_figure_specifiers.py @@ -8,7 +8,6 @@ from pydantic import ValidationError from statsplotly import constants, heatmap -from statsplotly.exceptions import StatsPlotSpecificationError from statsplotly.plot_objects.layout import ScatterLayout from statsplotly.plot_objects.layout._axis import ColorAxis from statsplotly.plot_objects.trace import ScatterTrace @@ -20,23 +19,24 @@ SubplotGridFormatter, ) from statsplotly.plot_specifiers.layout import AxesSpecifier +from statsplotly.plot_specifiers.trace import TraceMode @pytest.fixture def example_figure_layout_traces(): fig = make_subplots(rows=2, cols=2) fig.add_trace( - go.Scatter(x=[1, 2, 3], y=[4, 5, 6], marker=dict(color=[7, 8, 9], coloraxis="coloraxis")) + go.Scatter(x=[1, 2, 3], y=[4, 5, 6], marker={"color": [7, 8, 9], "coloraxis": "coloraxis"}) ) fig.update_layout({"coloraxis": {}, "coloraxis2": {}}) layout_dict = {"coloraxis": {}} traces = { "new_trace_with_coloraxis": go.Scatter( - x=[4, 5, 6], y=[7, 8, 9], marker=dict(color=[10, 11, 12], coloraxis="coloraxis") + x=[4, 5, 6], y=[7, 8, 9], marker={"color": [10, 11, 12], "coloraxis": "coloraxis"} ), "new_trace_without_coloraxis": go.Scatter( - x=[7, 8, 9], y=[10, 11, 12], marker=dict(color=[13, 14, 15]) + x=[7, 8, 9], y=[10, 11, 12], marker={"color": [13, 14, 15]} ), } return fig, layout_dict, traces @@ -76,7 +76,7 @@ def example_figure_data(example_trace_data, example_legend): trace_name="A", trace_color="red", color_specifier=ColorSpecifier(), - mode="markers", + mode=TraceMode.MARKERS, ).model_dump() ) @@ -90,7 +90,6 @@ def example_figure_data(example_trace_data, example_legend): class TestCreateFig: - def test_create_fig(self, example_figure_data): traces, layout = example_figure_data # Create a figure with traces and layout @@ -111,7 +110,7 @@ def test_create_fig_on_second_row(self, example_figure_data): def test_error_on_create_subplot(self, example_figure_data): traces, layout = example_figure_data # Trying to add a plot to a figure object without a subplot grid raises a ValidationError - with pytest.raises(ValidationError) as excinfo: + with pytest.raises(ValidationError): create_fig(fig=go.Figure(), traces=traces, layout=layout, row=1, col=1) def test_add_fig_to_existing_layout(self, example_figure_data): @@ -127,7 +126,7 @@ def test_add_fig_to_existing_layout(self, example_figure_data): # Assert that the figure contains the expected traces and updated layout assert len(fig.data) == 2 assert "xaxis2" in fig.layout and "yaxis2" in fig.layout - assert fig.layout.xaxis.title.text == None + assert fig.layout.xaxis.title.text is None assert fig.layout.xaxis2.title.text == "X" @@ -179,7 +178,7 @@ def test_format_colorbar_in_subplots_layout(example_figure_layout_traces): class TestSetCommonColoraxis: def test_all_common_coloraxis(self, example_heatmap_subplots): SubplotGridFormatter(fig=example_heatmap_subplots).set_common_coloraxis(SharedGridAxis.ALL) - assert all([trace.coloraxis == "coloraxis5" for trace in example_heatmap_subplots.data]) + assert all(trace.coloraxis == "coloraxis5" for trace in example_heatmap_subplots.data) assert example_heatmap_subplots.layout["coloraxis5"]["cmin"] == 0 assert example_heatmap_subplots.layout["coloraxis5"]["cmax"] == 12 @@ -187,10 +186,8 @@ def test_columns_common_coloraxis(self, example_heatmap_subplots): # Set common color axis for columns SubplotGridFormatter(fig=example_heatmap_subplots).set_common_coloraxis(SharedGridAxis.COLS) assert all( - [ - trace.coloraxis in ["coloraxis4", "coloraxis5"] - for trace in example_heatmap_subplots.data - ] + trace.coloraxis in ["coloraxis4", "coloraxis5"] + for trace in example_heatmap_subplots.data ) assert example_heatmap_subplots.layout["coloraxis4"]["cmin"] == 0 assert example_heatmap_subplots.layout["coloraxis4"]["cmax"] == 8 @@ -206,10 +203,8 @@ def test_rows_common_coloraxis(self, example_heatmap_subplots): # Set common color axis for rows SubplotGridFormatter(fig=example_heatmap_subplots).set_common_coloraxis(SharedGridAxis.ROWS) assert all( - [ - trace.coloraxis in ["coloraxis3", "coloraxis5"] - for trace in example_heatmap_subplots.data - ] + trace.coloraxis in ["coloraxis3", "coloraxis5"] + for trace in example_heatmap_subplots.data ) assert example_heatmap_subplots.layout["coloraxis3"]["cmin"] == 0 assert example_heatmap_subplots.layout["coloraxis3"]["cmax"] == 8 @@ -236,9 +231,8 @@ def test_all_common_axis_limits(self, example_heatmap_subplots): SubplotGridFormatter(fig=example_heatmap_subplots).set_common_axis_limit( shared_grid_axis=SharedGridAxis.ALL ) - assert ( - f"`plot_axis` must be specified when using `shared_grid_axis = {SharedGridAxis.ALL.value}`" - in str(excinfo.value) + assert "`plot_axis` must be specified when using `shared_grid_axis = all`" in str( + excinfo.value ) def test_columns_common_axis_limits(self, example_heatmap_subplots): diff --git a/tests/test_layout_specifiers.py b/tests/test_layout_specifiers.py index c9c14e1..c3f27b4 100644 --- a/tests/test_layout_specifiers.py +++ b/tests/test_layout_specifiers.py @@ -1,4 +1,5 @@ import logging +import re import numpy as np import pandas as pd @@ -7,6 +8,7 @@ from statsplotly.plot_specifiers.data import DataPointer, TraceData from statsplotly.plot_specifiers.layout import ( AxesSpecifier, + AxisFormat, LegendSpecifier, set_horizontal_colorbar, ) @@ -34,13 +36,13 @@ class TestAxesSpecifier: legend_specifier = LegendSpecifier(data_pointer=DataPointer(x="x", y="y", text="z")) def test_invalid_range(self): - trace_data = TraceData.build_trace_data( + trace_data = TraceData.build_from_data( data=EXAMPLE_DATAFRAME, pointer=DataPointer(x="x", y="y", text="z") ) with pytest.raises(ValueError) as excinfo: AxesSpecifier( - axis_format="square", + axis_format=AxisFormat("square"), traces=[trace_data], legend=self.legend_specifier, x_range=["a", "b"], @@ -48,37 +50,40 @@ def test_invalid_range(self): assert "Value error, Axis range must be numeric or `datetime`" in str(excinfo.value) def test_equal_range(self): - trace_data = TraceData.build_trace_data( + trace_data = TraceData.build_from_data( data=EXAMPLE_DATAFRAME.assign(x=np.arange(6, 9)), pointer=DataPointer(x="x", y="y", text="z"), ) axes_specifier = AxesSpecifier( - axis_format="equal", traces=[trace_data], legend=self.legend_specifier + axis_format=AxisFormat("equal"), traces=[trace_data], legend=self.legend_specifier ) assert axes_specifier.yaxis_range == [0.0, 8.8] def test_datetime_range(self, caplog): - trace_data = TraceData.build_trace_data( + trace_data = TraceData.build_from_data( data=EXAMPLE_DATETIME_DATAFRAME, pointer=DataPointer(x="x", y="y", text="z"), ) axes_specifier = AxesSpecifier( - axis_format="equal", traces=[trace_data], legend=self.legend_specifier + axis_format=AxisFormat("equal"), traces=[trace_data], legend=self.legend_specifier ) assert axes_specifier.yaxis_range == [ np.datetime64("2020-01-01T00:00:00.000000000"), np.datetime64("2020-01-04T00:00:00.000000000"), ] - assert "Can not pad a common range for values of type = 'datetime64[ns]'" in caplog.text + assert re.search( + r"Can not pad a common range for values of type = 'datetime64\[\w+\]'", + caplog.text, + ) def test_incompatible_axes(self, caplog): - trace_data = TraceData.build_trace_data( + trace_data = TraceData.build_from_data( data=EXAMPLE_DATAFRAME.assign(y=pd.date_range("2020-01-01", "2020-01-03", freq="D")), pointer=DataPointer(x="x", y="y", text="z"), ) axes_specifier = AxesSpecifier( - axis_format="equal", traces=[trace_data], legend=self.legend_specifier + axis_format=AxisFormat("equal"), traces=[trace_data], legend=self.legend_specifier ) assert axes_specifier.xaxis_range is None assert "Can not calculate a common range for values of type = 'object'" in caplog.text diff --git a/tests/test_plot_objects.py b/tests/test_plot_objects.py index 11c959d..efc4657 100644 --- a/tests/test_plot_objects.py +++ b/tests/test_plot_objects.py @@ -1,3 +1,5 @@ +from collections.abc import Iterable + import numpy as np import pytest @@ -11,6 +13,7 @@ ) from statsplotly.plot_specifiers.color import ColorSpecifier from statsplotly.plot_specifiers.data import DataDimension, HistogramNormType +from statsplotly.plot_specifiers.data._core import TraceData from statsplotly.plot_specifiers.trace import HistogramSpecifier, TraceMode TRACE_NAME = "dummy_name" @@ -38,7 +41,7 @@ def test_heatmap_trace(example_3dtrace_data): assert heatmap_trace.colorscale is None -def test_scatter_trace(example_trace_data): +def test_scatter_trace(example_trace_data: TraceData): scatter_trace = ScatterTrace.build_trace( trace_data=example_trace_data, trace_name=TRACE_NAME, @@ -46,15 +49,21 @@ def test_scatter_trace(example_trace_data): color_specifier=ColorSpecifier(), mode=None, ) + assert scatter_trace.x is not None assert all(scatter_trace.x == example_trace_data.x_values) + assert scatter_trace.y is not None assert all(scatter_trace.y == example_trace_data.y_values) - assert all(scatter_trace.text == example_trace_data.text_data) + assert isinstance(scatter_trace.text, Iterable) + assert isinstance(example_trace_data.text_data, Iterable) + assert all( + a == b for a, b in zip(scatter_trace.text, example_trace_data.text_data, strict=True) + ) assert scatter_trace.mode is None assert scatter_trace.name == TRACE_NAME assert scatter_trace.legendgroup == TRACE_NAME assert scatter_trace.showlegend is None assert scatter_trace.marker == { - "size": None, + "size": example_trace_data.size_data, "color": None, "opacity": None, "symbol": None, diff --git a/tests/test_statistics.py b/tests/test_statistics.py index d28c7f3..6d9b60d 100644 --- a/tests/test_statistics.py +++ b/tests/test_statistics.py @@ -38,11 +38,10 @@ def test_inverse_func(): result = inverse_func(x, a, b) expected = np.array([9.0, 7.0, 6.333333]) - assert np.allclose(result, expected), f"Expected {expected_output} but got {result}" + assert np.allclose(result, expected), f"Expected {expected} but got {result}" def test_affine_func(): - """Test for affine function""" x = np.array([1, 2, 3]) a = 0.5 b = 2 diff --git a/tests/test_trace_specifiers.py b/tests/test_trace_specifiers.py index 8b115f4..caf02e7 100644 --- a/tests/test_trace_specifiers.py +++ b/tests/test_trace_specifiers.py @@ -1,11 +1,8 @@ -import datetime - import numpy as np import pandas as pd import pytest from pydantic import ValidationError -from statsplotly.exceptions import StatsPlotSpecificationError from statsplotly.plot_specifiers.data import ( DataDimension, DataHandler, @@ -129,7 +126,10 @@ def test_color_data_not_allowed(self, example_input_data_dict): ) with pytest.raises( ValueError, - match="Only slice-level color data can be specified with `boxplot`, got marker-level argument `color` of type int64", + match=( + "Only slice-level color data can be specified with `boxplot`, got marker-level " + "argument `color` of type int64" + ), ): CategoricalPlotSpecifier( plot_type="boxplot", @@ -232,7 +232,6 @@ def test_compute_ecdf(self): class TestJointplotSpecifier: - def test_jointplot_specifier(self, caplog): jointplot_specifier = JointplotSpecifier( plot_type="kde",