remove psc as an option for standardising output (#113)

* remove psc as an option for standardising output, leaving zscore the only behaviour so removing the parameter all together

* some missing files

* remove analysis level

giga_connectome/denoise.py

@@ -108,7 +108,7 @@ def is_ica_aroma(strategy: STRATEGY_TYPE) -> bool:
 def denoise_nifti_voxel(
     strategy: STRATEGY_TYPE,
     group_mask: str | Path,
-    standardize: str | bool,
+    standardize: bool,
     smoothing_fwhm: float,
     img: str,
 ) -> Nifti1Image:
@@ -120,9 +120,9 @@ def denoise_nifti_voxel(
         Denoising strategy parameter to pass to load_confounds_strategy.
     group_mask : str | Path
         Path to the group mask.
-    standardize : str | bool
-        Standardize the data. If 'zscore', zscore the data. If 'psc', convert
-        the data to percent signal change. If False, do not standardize.
+    standardize : bool
+        Standardize the data. If True, zscore the data. If False, do \
+            not standardize.
     smoothing_fwhm : float
         Smoothing kernel size in mm.
     img : str

giga_connectome/postprocess.py

@@ -26,7 +26,7 @@ def run_postprocessing_dataset(
     resampled_atlases: Sequence[str | Path],
     images: Sequence[BIDSImageFile],
     group_mask: str | Path,
-    standardize: str | bool,
+    standardize: bool,
     smoothing_fwhm: float,
     output_path: Path,
     calculate_average_correlation: bool = False,
@@ -77,9 +77,9 @@ def run_postprocessing_dataset(
     group_mask : str or pathlib.Path
         Group level grey matter mask.
 
-    standardize : str or bool
-        Standardization options used in nilearn, passed to nilearn masker.
-        Options: True, False, "psc"
+    standardize : bool
+        Standardization to zscore or not used in nilearn, passed to nilearn \
+            masker.
 
     smoothing_fwhm : float
         Smoothing kernel size, passed to nilearn masker.

giga_connectome/run.py

@@ -73,13 +73,6 @@ def global_parser() -> argparse.ArgumentParser:
         "is 'simple'.",
         default="simple",
     )
-    parser.add_argument(
-        "--standardize",
-        help="The choice of signal standardization. The choices are z score "
-        "or percent signal change (psc). The default is 'zscore'.",
-        choices=["zscore", "psc"],
-        default="zscore",
-    )
     parser.add_argument(
         "--smoothing_fwhm",
         help="Size of the full-width at half maximum in millimeters of "

giga_connectome/tests/test_cli.py

@@ -54,8 +54,6 @@ def test_smoke(tmp_path, capsys):
             "Schaefer20187Networks",
             "--denoise-strategy",
             "simple",
-            "--standardize",
-            "zscore",
             "--reindex-bids",
             "--calculate-intranetwork-average-correlation",
             str(bids_dir),

giga_connectome/tests/test_utils.py

@@ -53,9 +53,3 @@ def test_get_subject_lists():
     )
     assert len(subjects) == 1
     assert subjects[0] == "01"
-
-
-def test_parse_standardize_options():
-    with pytest.raises(ValueError) as msg:
-        utils.parse_standardize_options(True)
-    assert "True is not a" in str(msg.value)

giga_connectome/utils.py

@@ -130,12 +130,6 @@ def parse_bids_filter(value: Path) -> None | dict[str, dict[str, str]]:
     return tmp
 
 
-def parse_standardize_options(standardize: str) -> str | bool:
-    if standardize not in ["zscore", "psc"]:
-        raise ValueError(f"{standardize} is not a valid standardize strategy.")
-    return standardize if standardize == "psc" else True
-
-
 def parse_bids_name(img: str) -> tuple[str, str | None, str]:
     """Get subject, session, and specifier for a fMRIPrep output."""
     reference = parse_bids_filename(img)

giga_connectome/workflow.py

@@ -40,7 +40,7 @@ def workflow(args: argparse.Namespace) -> None:
     bids_dir = args.bids_dir
     output_dir = args.output_dir
     working_dir = args.work_dir
-    standardize = utils.parse_standardize_options(args.standardize)
+    standardize = True  # always standardising the time series
     smoothing_fwhm = args.smoothing_fwhm
     calculate_average_correlation = (
         args.calculate_intranetwork_average_correlation
@@ -71,7 +71,7 @@ def workflow(args: argparse.Namespace) -> None:
         output_dir=output_dir,
         atlas=atlas["name"],
         smoothing_fwhm=smoothing_fwhm,
-        standardize=args.standardize,
+        standardize="zscore",
         strategy=args.denoise_strategy,
         mni_space=template,
         average_correlation=calculate_average_correlation,