Add site-effect correction

.github/workflows/docker.yml

@@ -62,7 +62,7 @@ jobs:
           cache-to: type=gha,mode=max
           tags: wonky:conn
           load: true
-      # always use light mode for testing container since the full version was tested during build
+      # Always use light mode for testing container since the full version was tested during build
       - run: |
           datalad get data/halfpipe data/atlases
           docker run --rm \

.github/workflows/test.yml

@@ -65,7 +65,7 @@ jobs:
           environments: test
           frozen: true
       - run: pixi run unittest
-      - run: pixi run smoketestlight
+      - run: pixi run smoketestlight --cov-append
       - uses: codecov/codecov-action@v6
         if: ${{ always() }}
         with:

.pre-commit-config.yaml

@@ -20,7 +20,13 @@ repos:
     rev: v1.19.1
     hooks:
     -   id: mypy
-        additional_dependencies: [pandas-stubs, types-tqdm, types-setuptools, types-Jinja2]
+        additional_dependencies:
+        -   pandas-stubs
+        -   pytest
+        -   types-tqdm
+        -   types-setuptools
+        -   types-Jinja2
+        -   textual
         args: [--config-file=pyproject.toml]
 -   repo: https://github.com/codespell-project/codespell
     rev: v2.4.2

codecov.yml

@@ -14,13 +14,16 @@
 #         # noisy red coverage status on github PRs.
 #         target: auto
 #         threshold: 1%
-comment:                  # this is a top-level key
+comment: # this is a top-level key
   layout: reach, diff, flags, files
   behavior: default
-  require_changes: false  # if true: only post the comment if coverage changes
-  require_base: no        # [yes :: must have a base report to post]
-  require_head: yes       # [yes :: must have a head report to post]
+  require_changes: false # if true: only post the comment if coverage changes
+  require_base: false # if true: must have a base report to post
+  require_head: false # if true: must have a head report to post
 
 ignore:
-- '*/tests/'    # ignore folders related to testing
-- '*/data/'
+  - "**/tests/**"
+  - "**/test_*.py"
+  - "**/conftest.py"
+  - "**/data/**"
+  - "**/setup.py"

data/halfpipe/participants.tsv

@@ -1 +1 @@
-../../.git/annex/objects/gG/5m/MD5E-s16387--b0d7908c25384a3ecd7c317238748596.tsv/MD5E-s16387--b0d7908c25384a3ecd7c317238748596.tsv
+../../.git/annex/objects/Fj/K7/MD5E-s16372--3c23f937d8662e3bbd2f588f3d992e8b.tsv/MD5E-s16372--3c23f937d8662e3bbd2f588f3d992e8b.tsv

pyproject.toml

@@ -164,13 +164,18 @@ warn_unused_ignores = true
 ignore_missing_imports = true
 module = [
   "bids.*",
+  "brainspace.*",
   "datalad.*",
+  "joblib",
   "matplotlib.*",
+  "nilearn",
+  "nilearn.*",
   "numba.*",
   "patsy.*",
   "rich.*",
   "scipy.*",
   "seaborn.*",
+  "sklearn.*",
   "statsmodels.*",
   "templateflow.*",
   "nibabel.*",

wonkyconn/atlas.py

@@ -7,8 +7,8 @@
 import numpy as np
 import pandas as pd
 import scipy
-from nilearn.image import iter_img, load_img, math_img, resample_to_img  # type: ignore[import-not-found]
-from nilearn.maskers import NiftiLabelsMasker, NiftiMasker  # type: ignore[import-not-found]
+from nilearn.image import iter_img, load_img, math_img, resample_to_img
+from nilearn.maskers import NiftiLabelsMasker, NiftiMasker
 from numpy import typing as npt
 
 from .logger import logger
@@ -29,7 +29,7 @@ class Atlas(ABC):
     """
 
     seg: str
-    image: nib.nifti1.Nifti1Image
+    image: nib.nifti1.Nifti1Image  # pyright: ignore[reportAttributeAccessIssue]
 
     structure: npt.NDArray[np.bool_] = field(default_factory=lambda: np.ones((3, 3, 3), dtype=bool))
 
@@ -51,7 +51,7 @@ def get_centroids(self) -> npt.NDArray[np.float64]:
             npt.NDArray[np.float64]: An array of centroid coordinates.
         """
         centroid_points = self.get_centroid_points()
-        centroid_coordinates = nib.affines.apply_affine(self.image.affine, centroid_points)
+        centroid_coordinates = nib.affines.apply_affine(self.image.affine, centroid_points)  # pyright: ignore[reportAttributeAccessIssue]
         return centroid_coordinates
 
     def get_distance_matrix(self) -> npt.NDArray[np.float64]:
@@ -65,7 +65,7 @@ def get_distance_matrix(self) -> npt.NDArray[np.float64]:
         centroids = self.get_centroids()
         return scipy.spatial.distance.squareform(scipy.spatial.distance.pdist(centroids))
 
-    def load_yeo7_network(self) -> nib.nifti1.Nifti1Image:
+    def load_yeo7_network(self) -> nib.nifti1.Nifti1Image:  # pyright: ignore[reportAttributeAccessIssue]
         """
         Load and resample the yeo 7 networks to the atlas's space.
 
@@ -102,10 +102,10 @@ def create(seg: str, path: Path) -> "Atlas":
             None
 
         """
-        image = nib.nifti1.load(path)
+        image = nib.nifti1.load(path)  # pyright: ignore[reportAttributeAccessIssue]
 
         if image.ndim <= 3 or image.shape[3] == 1:
-            return DsegAtlas(seg, nib.funcs.squeeze_image(image))
+            return DsegAtlas(seg, nib.funcs.squeeze_image(image))  # pyright: ignore[reportAttributeAccessIssue]
         else:
             return ProbsegAtlas(seg, image)
 
@@ -142,7 +142,8 @@ def get_yeo7_membership(self) -> pd.DataFrame:
         for n in network_labels:
             cur_region = math_img(f"img=={n}", img=yeo7_nii)
             masker = NiftiMasker(cur_region)
-            atlas_parcel_in_network = masker.fit_transform(self.image)
+            masker.fit()
+            atlas_parcel_in_network = masker.transform(self.image)
             atlas_parcel_in_network = np.unique(atlas_parcel_in_network)[1:]
             region_membership.loc[atlas_parcel_in_network, f"yeo7-{int(n)}"] = 1
         return region_membership
@@ -161,7 +162,7 @@ def _get_centroid_point(self, i: int, array: npt.NDArray[np.float64]) -> tuple[f
 
     def get_centroid_points(self) -> npt.NDArray[np.float64]:
         return np.asarray(
-            [self._get_centroid_point(i, image.get_fdata()) for i, image in enumerate(nib.funcs.four_to_three(self.image))]
+            [self._get_centroid_point(i, image.get_fdata()) for i, image in enumerate(nib.funcs.four_to_three(self.image))]  # pyright: ignore[reportAttributeAccessIssue]
         )
 
     def get_yeo7_membership(self) -> pd.DataFrame:

wonkyconn/config.py

@@ -3,7 +3,7 @@
 import argparse
 from dataclasses import dataclass, field
 from pathlib import Path
-from typing import Iterable, Sequence
+from typing import Literal, TypeAlias
 
 
 def _coerce_path(value: str | Path | None) -> Path | None:
@@ -13,66 +13,53 @@ def _coerce_path(value: str | Path | None) -> Path | None:
     return Path(value).expanduser().resolve()
 
 
+Metric: TypeAlias = Literal["motion", "analytic-insights", "gradients", "prediction"]
+
+light_mode_metrics: set[Metric] = {"motion", "analytic-insights"}
+all_metrics: set[Metric] = {"motion", "analytic-insights", "gradients", "prediction"}
+
+
 @dataclass
-class WonkyConnConfig:
+class WonkyconnConfig:
     """Shared configuration for CLI and GUI."""
 
     bids_dir: Path | None = None
     output_dir: Path | None = None
     analysis_level: str = "group"
     phenotypes: Path | None = None
     atlas: list[tuple[str, Path]] = field(default_factory=list)
-    verbosity: int = 2
+    log_level: str | None = None
     debug: bool = False
-    light_mode: bool = False
+    metrics: set[Metric] | None = None
     theme: str | None = None  # GUI-only
     suppress_warnings: bool = False
+    site_correction: bool = False
+
+    @property
+    def light_mode(self) -> bool:
+        return self.metrics == light_mode_metrics
 
     @classmethod
-    def from_cli_args(cls, args: argparse.Namespace | None) -> "WonkyConnConfig":
+    def from_cli_args(cls, args: argparse.Namespace | None) -> "WonkyconnConfig":
         """Create a config from argparse args (may be partial when GUI is requested)."""
         if args is None:
             return cls()
 
-        verbosity = args.verbosity
-        if isinstance(verbosity, Sequence) and not isinstance(verbosity, (str, bytes)):
-            verbosity = verbosity[0]
-
         atlas_entries: list[tuple[str, Path]] = list()
-        for label, atlas_path in getattr(args, "atlas", []) or []:
+        for label, atlas_path in args.atlas or []:
             atlas_entries.append((label, Path(atlas_path).expanduser().resolve()))
 
+        metrics: set[Metric] = light_mode_metrics if args.light_mode else set(args.metrics)
+
         return cls(
-            bids_dir=_coerce_path(getattr(args, "bids_dir", None)),
-            output_dir=_coerce_path(getattr(args, "output_dir", None)),
-            analysis_level=getattr(args, "analysis_level", "group"),
-            phenotypes=_coerce_path(getattr(args, "phenotypes", None)),
+            bids_dir=_coerce_path(args.bids_dir),
+            output_dir=_coerce_path(args.output_dir),
+            analysis_level=args.analysis_level,
+            phenotypes=_coerce_path(args.phenotypes),
             atlas=atlas_entries,
-            verbosity=int(verbosity) if verbosity is not None else 2,
-            debug=bool(getattr(args, "debug", False)),
-            light_mode=bool(getattr(args, "light_mode", False)),
-            suppress_warnings=bool(getattr(args, "suppress_warnings", False)),
-        )
-
-    def to_namespace(self) -> argparse.Namespace:
-        """Convert to argparse.Namespace expected by workflow."""
-        if self.bids_dir is None:
-            raise ValueError("bids_dir is required")
-        if self.output_dir is None:
-            raise ValueError("output_dir is required")
-        if self.phenotypes is None:
-            raise ValueError("phenotypes is required")
-        if not self.atlas:
-            raise ValueError("At least one atlas entry is required")
-
-        atlas_as_str: Iterable[tuple[str, str]] = ((label, str(path)) for label, path in self.atlas)
-        return argparse.Namespace(
-            bids_dir=self.bids_dir,
-            output_dir=self.output_dir,
-            analysis_level=self.analysis_level,
-            phenotypes=str(self.phenotypes),
-            atlas=list(atlas_as_str),
-            verbosity=self.verbosity,
-            debug=self.debug,
-            light_mode=self.light_mode,
+            log_level=args.log_level,
+            debug=bool(args.debug),
+            metrics=metrics,
+            suppress_warnings=bool(args.suppress_warnings),
+            site_correction=bool(args.site_correction),
         )