[DOC] New CLI

.gitignore

@@ -5,7 +5,6 @@ AFQ/version.py
 docs/_build
 docs/build
 docs/source/auto_examples/
-docs/source/reference/config.rst
 examples/**/*.nii.gz
 examples/**/*.trk
 examples/**/*.npy

AFQ/api/utils.py

@@ -135,6 +135,9 @@ def check_attribute(attr_name):
     if attr_name[:-5] in task_modules:
         return None
 
+    if attr_name in ["tracking_params", "segmentation_params"]:
+        return "segmentation_imap"
+
     if attr_name in methods_sections:
         return f"{methods_sections[attr_name]}_imap"
 

AFQ/definitions/utils.py

@@ -27,9 +27,9 @@ def __init__(self):
     def find_path(self, bids_layout, from_path, subject, session, required=True):
         pass
 
-    def str_for_toml(self):
+    def str_formal(self):
         """
-        Uses __init__ in str_for_toml to make string that will instantiate
+        Uses __init__ in str_formal to make string that will instantiate
         itself. Assumes object will have attributes of same name as
         __init__ args. This is important for reading/writing definitions
         as arguments to config files.
@@ -56,7 +56,7 @@ def _arglist_to_string(args, get_attr=None):
         if get_attr is not None:
             arg = getattr(get_attr, arg)
         if isinstance(arg, Definition):
-            arg = arg.str_for_toml()
+            arg = arg.str_formal()
         elif isinstance(arg, str):
             arg = f'"{arg}"'
         elif isinstance(arg, list):

AFQ/recognition/recognize.py

@@ -114,7 +114,8 @@ def recognize(
         Default: 4
     save_intermediates : str, optional
         The full path to a folder into which intermediate products
-        are saved. Default: None, means no saving of intermediates.
+        are saved. If None, means no saving of intermediates.
+        Default: None.
     cleaning_params : dict, optional
         Cleaning params to pass to seg.clean_bundle. This will
         override the default parameters of that method. However, this

AFQ/tests/test_api.py

@@ -14,7 +14,6 @@
 import numpy.testing as npt
 import pandas as pd
 import pytest
-import toml
 from dipy.io.streamline import load_tractogram
 from dipy.segment.metric import mdf
 from pandas.testing import assert_series_equal
@@ -991,41 +990,29 @@ def test_AFQ_data_waypoint():
         "inclusive_labels=[1, 2]))"
     )
     bm_def_as_str = (
-        "LabelledImageFile(suffix='seg', "
-        "filters={'scope': 'freesurfer'}, "
+        'LabelledImageFile(suffix="seg", '
+        'filters={"scope": "freesurfer"}, '
         "exclusive_labels=[0])"
     )
-    config = dict(
-        BIDS_PARAMS=dict(
-            bids_path=bids_path,
-            dwi_preproc_pipeline="vistasoft",
-            t1_preproc_pipeline="freesurfer",
-        ),
-        STRUCTURAL=dict(
-            brain_mask_definition=bm_def_as_str,
-        ),
-        DATA=dict(bundle_info=bundle_dict_as_str),
-        TISSUE=dict(pve=pve_as_str),
-        SEGMENTATION=dict(
-            n_points_profile=50,
-            scalars=[
-                "dti_fa",
-                "dti_md",
-                "dti_ga",
-                "t1w_over_b0",
-                f"ImageFile('{t1_path_other}')",
-                f"TemplateImage('{t1_path}')",
-            ],
-        ),
-        TRACTOGRAPHY_PARAMS=tracking_params,
-        SEGMENTATION_PARAMS=segmentation_params,
-    )
 
-    config_file = op.join(tmpdir, "afq_config.toml")
-    with open(config_file, "w") as ff:
-        toml.dump(config, ff)
+    cmd = (
+        f"pyAFQ -v {op.join(vista_folder, 'sub-01_ses-01_dwi.nii.gz')}"
+        f" {op.join(freesurfer_folder, 'sub-01_ses-01_T1w.nii.gz')}"
+        f" {afq_folder}"
+        f" --brain_mask_definition='{bm_def_as_str}'"
+        f" --bundle_info='{bundle_dict_as_str}'"
+        f" --pve='{pve_as_str}'"
+        f" --n_points_profile=50"
+        f' --scalars=\'["dti_fa", "dti_md", "dti_ga", "t1w_over_b0", '
+        f'ImageFile("{t1_path_other}"), TemplateImage("{t1_path}")]\''
+        f" --odf_model=csd"
+        f" --n_seeds=2000"
+        f" --directions=prob"
+        f" --random_seeds=True"
+        f" --rng_seed=42"
+        f" --return_idx=True"
+    )
 
-    cmd = f"pyAFQ -v {config_file}"
     completed_process = subprocess.run(cmd, shell=True, capture_output=True)
     if completed_process.returncode != 0:
         print(completed_process.stdout)

AFQ/tests/test_definitions.py

@@ -15,7 +15,7 @@
 
 def test_str_instantiates_mixin():
     thresh_image = ThresholdedScalarImage("dti_fa", lower_bound=0.2)
-    thresh_image_str = thresh_image.str_for_toml()
+    thresh_image_str = thresh_image.str_formal()
     thresh_image_from_str = eval(thresh_image_str)
 
     npt.assert_(thresh_image.combine == thresh_image_from_str.combine)

AFQ/tractography/tractography.py

@@ -69,18 +69,19 @@ def track(
         pft refers to Particle Filtering Tracking ([Girard2014]_).
         Default: "prob"
     max_angle : float, optional.
-        The maximum turning angle in each step. Default: 30
+        The maximum turning angle in each step.
+        Default: 30
     sphere : str or DIPY Sphere
         The discretization of the ODF. Can be a DIPY Sphere or
         a string name of a DIPY Sphere.
         Default: "repulsion724"
     seed_mask : array, optional.
         Float or binary mask describing the ROI within which we seed for
-        tracking.
-        Default to the entire volume (all ones).
+        tracking. If None, use the entire volume (all ones).
+        Default: None
     seed_threshold : float, optional.
         A value of the seed_mask above which tracking is seeded.
-        Default to 0.
+        Default: 0
     gm_threshold : float, optional.
         A value of the pve_gm_data above which we consider a voxel to be GM
         for the purposes of ACT stopping criterion. Default: 0.4.
@@ -114,7 +115,7 @@ def track(
         {"DTI", "CSD", "DKI", "GQ", "RUMBA", "MSMT_AODF", "CSD_AODF", "MSMTCSD"}.
         If a Definition, we assume it is a definition of a file containing
         Spherical Harmonics coefficients.
-        Defaults to use "CSD_AODF"
+        Default: "CSD_AODF"
     basis_type : str, optional
         The spherical harmonic basis type used to represent the coefficients.
         One of {"descoteaux07", "tournier07"}. Default: "descoteaux07"