Update linter configuration and sys-info output (#200)

* improve sys-info

* update linter configuration

* update stubs configuration

* update stubs

* fix parsing of metadata

* fix typo

* Update .pre-commit-config.yaml

.pre-commit-config.yaml

@@ -1,20 +1,12 @@
 repos:
-    - repo: https://github.com/pycqa/isort
-      rev: 5.13.2
-      hooks:
-          - id: isort
-            files: mne_icalabel
-
     - repo: https://github.com/astral-sh/ruff-pre-commit
-      rev: v0.5.7
+      rev: v0.6.3
       hooks:
           - id: ruff
             name: ruff linter
-            args: [--fix]
-            files: mne_icalabel
+            args: [--fix, --show-fixes]
           - id: ruff-format
             name: ruff formatter
-            files: mne_icalabel
 
     - repo: https://github.com/codespell-project/codespell
       rev: v2.3.0
@@ -23,13 +15,6 @@ repos:
             args: [--write-changes]
             additional_dependencies: [tomli]
 
-    - repo: https://github.com/pycqa/pydocstyle
-      rev: 6.3.0
-      hooks:
-          - id: pydocstyle
-            files: mne_icalabel
-            additional_dependencies: [tomli]
-
     - repo: https://github.com/mscheltienne/bibclean
       rev: 0.8.0
       hooks:

doc/conf.py

@@ -21,7 +21,7 @@
 
 project = "MNE-ICALabel"
 author = "Adam Li, Mathieu Scheltienne"
-copyright = (
+copyright = (  # noqa: A001
     f"2021-{date.today().year}, MNE Developers. "
     f"Last updated on {date.today().isoformat()}"
 )
@@ -180,7 +180,7 @@
     "EX01",  # section 'Examples' not found
     "ES01",  # no extended summary found
     "SA01",  # section 'See Also' not found
-    "RT02",  # The first line of the Returns section should contain only the type, unless multiple values are being returned  # noqa
+    "RT02",  # The first line of the Returns section should contain only the type, unless multiple values are being returned  # noqa: E501
 }
 
 numpydoc_validate = True

examples/00_iclabel.py

@@ -1,4 +1,4 @@
-"""
+r"""
 .. _tuto-iclabel:
 
 Repairing artifacts with ICA automatically using ICLabel Model

mne_icalabel/__init__.py

@@ -1,12 +1,4 @@
-"""Automatic ICA labeling for MEG, EEG and iEEG data."""
-
-from . import annotation  # noqa: F401
-from . import config  # noqa: F401
-from . import datasets  # noqa: F401
-from . import features  # noqa: F401
-from . import gui  # noqa: F401
-from . import iclabel  # noqa: F401
-from . import utils  # noqa: F401
-from ._version import __version__  # noqa: F401
-from .label_components import label_components  # noqa: F401
-from .utils.config import sys_info  # noqa: F401
+from . import annotation, config, datasets, features, gui, iclabel, utils
+from ._version import __version__
+from .label_components import label_components
+from .utils.config import sys_info

mne_icalabel/annotation/tests/test_bids.py

@@ -18,8 +18,9 @@
 raw_fname = op.join(data_path, "test_reduced.edf")
 
 
-@pytest.fixture(scope="function")
-def _tmp_bids_path(tmp_path):
+@pytest.fixture
+def tmp_bids_path(tmp_path):
+    """Create a bids path."""
     bids_path = BIDSPath(
         subject=subject_id,
         session=session_id,
@@ -35,7 +36,8 @@ def _tmp_bids_path(tmp_path):
 
 
 @pytest.fixture(scope="session")
-def _ica():
+def ica():
+    """Create an ICA object."""
     raw = read_raw_edf(raw_fname, preload=True)
     raw.filter(l_freq=1, h_freq=100)
     n_components = 5
@@ -44,8 +46,9 @@ def _ica():
     return ica
 
 
-def test_write_channels_tsv(_ica, _tmp_bids_path):
-    root = _tmp_bids_path.root
+def test_write_channels_tsv(ica: ICA, tmp_bids_path):
+    """Test writing components to a channels.tsv file."""
+    root = tmp_bids_path.root
     deriv_root = root / "derivatives" / "ICA"
     deriv_fname = BIDSPath(
         root=deriv_root,
@@ -57,10 +60,10 @@ def test_write_channels_tsv(_ica, _tmp_bids_path):
         suffix="channels",
         extension=".tsv",
     )
-    _ica = _ica.copy()
-    _ica.labels_["ecg"] = [0]
+    ica = ica.copy()
+    ica.labels_["ecg"] = [0]
 
-    write_components_tsv(_ica, deriv_fname)
+    write_components_tsv(ica, deriv_fname)
 
     assert deriv_fname.fpath.exists()
     expected_json = deriv_fname.copy().update(extension=".json")
@@ -72,8 +75,9 @@ def test_write_channels_tsv(_ica, _tmp_bids_path):
     assert ch_tsv["ic_type"].values[0] == "ecg"
 
 
-def test_mark_components(_ica, _tmp_bids_path):
-    root = _tmp_bids_path.root
+def test_mark_components(ica, tmp_bids_path):
+    """Test marking components."""
+    root = tmp_bids_path.root
     deriv_root = root / "derivatives" / "ICA"
     deriv_fname = BIDSPath(
         root=deriv_root,
@@ -85,7 +89,7 @@ def test_mark_components(_ica, _tmp_bids_path):
         suffix="channels",
         extension=".tsv",
     )
-    write_components_tsv(_ica, deriv_fname)
+    write_components_tsv(ica, deriv_fname)
 
     # mark components
     with pytest.raises(ValueError, match="not a valid label"):

mne_icalabel/conftest.py

@@ -1,3 +1,5 @@
+import numpy as np
+import pytest
 from mne import set_log_level
 
 
@@ -20,3 +22,9 @@ def pytest_configure(config):
         if warning_line and not warning_line.startswith("#"):
             config.addinivalue_line("filterwarnings", warning_line)
     set_log_level("WARNING")
+
+
+@pytest.fixture(scope="session")
+def rng():
+    """Return a numpy random generator."""
+    return np.random.default_rng()

mne_icalabel/datasets/__init__.py

@@ -1 +1 @@
-from . import icalabel  # noqa: F401
+from . import icalabel

mne_icalabel/datasets/icalabel/__init__.py

@@ -1 +1 @@
-from .icalabel import data_path, has_icalabel_testing_data  # noqa: F401
+from .icalabel import data_path, has_icalabel_testing_data

mne_icalabel/features/__init__.py

@@ -1,3 +1 @@
-"""Features for the ICLabel"""
-
-from .topomap import get_topomaps  # noqa: F401
+from .topomap import get_topomaps

mne_icalabel/features/tests/test_topomap.py

@@ -26,9 +26,9 @@
 
 
 @pytest.mark.filterwarnings("ignore:invalid value encountered in divide:RuntimeWarning")
-@pytest.mark.parametrize("ica", (ica, ica_eeg))
+@pytest.mark.parametrize("ica", [ica, ica_eeg])
 def test_topomap_defaults(ica):
-    """Test scalp topography array generation"""
+    """Test scalp topography array generation."""
     topomaps = get_topomaps(ica, picks=None)
     assert isinstance(topomaps, dict)
     for topomaps_ in topomaps.values():
@@ -41,7 +41,8 @@ def test_topomap_defaults(ica):
 
 @pytest.mark.filterwarnings("ignore:invalid value encountered in divide:RuntimeWarning")
 @pytest.mark.parametrize(
-    "picks, res", [(0, 32), ([0, 1, 2], 50), (slice(1, 3), 128), (np.array([1, 2]), 10)]
+    ("picks", "res"),
+    [(0, 32), ([0, 1, 2], 50), (slice(1, 3), 128), (np.array([1, 2]), 10)],
 )
 def test_topomap_arguments(picks, res):
     """Test arguments that influence the output shape."""

mne_icalabel/gui/_label_components.py

@@ -269,8 +269,8 @@ def _update_selected_labels(self) -> None:
         self._save_labels()  # updates the ICA instance every time
 
     @Slot()
-    def _reset(self) -> None:  # noqa: D401
-        """Action of the reset button."""
+    def _reset(self) -> None:
+        """Remove the label from the current component."""
         self._reset_buttons()
         if self.selected_component in self.selected_labels:
             del self.selected_labels[self.selected_component]

mne_icalabel/gui/_label_components.pyi

@@ -87,7 +87,7 @@ class ICAComponentLabeler(QMainWindow):
         """Update the labels saved."""
 
     def _reset(self) -> None:
-        """Action of the reset button."""
+        """Remove the label from the current component."""
 
     def _reset_buttons(self) -> None:
         """Reset all buttons."""

mne_icalabel/gui/tests/test_label_components.py

@@ -18,6 +18,7 @@
 
 
 def test_label_components_gui_display():
+    """Test that the GUI is displayed correctly."""
     ica_ = ica.copy()
     gui = label_ica_components(raw, ica_, show=False)
     # test setting the label

mne_icalabel/iclabel/__init__.py

@@ -1,9 +1,3 @@
-"""ICLabel - An automated electroencephalographic independent component
-classifier, dataset, and website.
-
-This is a python implementation of the EEGLAB plugin 'ICLabel'.
-"""
-
-from .features import get_iclabel_features  # noqa: F401
-from .label_components import iclabel_label_components  # noqa: F401
-from .network import run_iclabel  # noqa: F401
+from .features import get_iclabel_features
+from .label_components import iclabel_label_components
+from .network import run_iclabel

mne_icalabel/iclabel/_utils.py

@@ -243,18 +243,8 @@ def _mergepoints2D(
 
 def _mergesimpts(
     data: ArrayLike, tols: list[ArrayLike], mode: str = "average"
-) -> ArrayLike:  # noqa
-    """
-    Parameters
-    ----------
-    data : array
-    tols : list of 3 arrays
-    mode : str
-
-    Returns
-    -------
-    array
-    """
+) -> ArrayLike:
+    """Merge similar points."""
     data_ = data.copy()[np.argsort(data[:, 0])]
     newdata = []
     tols_ = np.array(tols)

mne_icalabel/iclabel/_utils.pyi

@@ -99,14 +99,4 @@ def _mergepoints2D(
 def _mergesimpts(
     data: ArrayLike, tols: list[ArrayLike], mode: str = "average"
 ) -> ArrayLike:
-    """
-    Parameters
-    ----------
-    data : array
-    tols : list of 3 arrays
-    mode : str
-
-    Returns
-    -------
-    array
-    """
+    """Merge similar points."""

mne_icalabel/iclabel/features.py

@@ -307,7 +307,8 @@ def _eeg_rpsd_constants(
     # possible to reproduce the output in python.
     # 'subset' is used to select from arrays and is 0-index in Python while its
     # 1-index in MATLAB.
-    subset = np.random.permutation(range(n_seg))  # 0-index
+    rng = np.random.default_rng()
+    subset = rng.permutation(range(n_seg))  # 0-index
 
     return ncomp, nfreqs, n_points, nyquist, index, window, subset
 

mne_icalabel/iclabel/network/tests/test_network.py

@@ -84,9 +84,9 @@ def test_weights_pytorch():
 
 @requires_module("torch")
 def test_network_outputs_pytorch():
-    """
-    Compare that the ICLabel network in pytorch and matlab outputs the same
-    values for a common set of features (input to the forward pass).
+    """Compare that the ICLabel network in pytorch and matlab outputs the same values.
+
+    Compare the outputs for a common set of features (input to the forward pass).
 
     Notes
     -----
@@ -132,9 +132,9 @@ def test_network_outputs_pytorch():
 
 @requires_module("onnxruntime")
 def test_network_outputs_onnx():
-    """
-    Compare that the ICLabel network in onnx and matlab outputs the same
-    values for a common set of features (input to the forward pass).
+    """Compare that the ICLabel network in onnx and matlab outputs the same values.
+
+    Compare the outputs for a common set of features (input to the forward pass).
 
     Notes
     -----
@@ -176,7 +176,7 @@ def test_network_outputs_onnx():
 
 
 @pytest.mark.parametrize(
-    "eeglab_feature_file, eeglab_feature_formatted_file",
+    ("eeglab_feature_file", "eeglab_feature_formatted_file"),
     [
         (features_raw_path, features_formatted_raw_path),
         (features_epo_path, features_formatted_epo_path),
@@ -200,18 +200,21 @@ def test_format_input(eeglab_feature_file, eeglab_feature_formatted_file):
 
 
 @pytest.mark.parametrize(
-    "eeglab_feature_file, eeglab_output_file",
+    ("eeglab_feature_file", "eeglab_output_file"),
     [
         (features_raw_path, iclabel_output_raw_path),
         (features_epo_path, iclabel_output_epo_path),
     ],
 )
 @requires_module("onnxruntime")
 def test_run_iclabel_onnx(eeglab_feature_file, eeglab_output_file):
-    """Test that the network outputs the same values for the features in
-    'features_raw_path' and 'features_epo_path' that contains the features
-    extracted in EEGLAB. This set of feature is compared with the set of
-    features retrieved in python in 'test_features.py:test_get_features'."""
+    """Test that the network outputs the same values as MATLAB.
+
+    Test the the network outputs the same values for the features in
+    'features_raw_path' and 'features_epo_path' that contains the features extracted in
+    EEGLAB. This set of feature is compared with the set of features retrieved in python
+    in 'test_features.py:test_get_features'.
+    """
     from mne_icalabel.iclabel.network.onnx import _run_iclabel
 
     features_eeglab = loadmat(eeglab_feature_file)["features"]
@@ -230,18 +233,21 @@ def test_run_iclabel_onnx(eeglab_feature_file, eeglab_output_file):
 
 
 @pytest.mark.parametrize(
-    "eeglab_feature_file, eeglab_output_file",
+    ("eeglab_feature_file", "eeglab_output_file"),
     [
         (features_raw_path, iclabel_output_raw_path),
         (features_epo_path, iclabel_output_epo_path),
     ],
 )
 @requires_module("torch")
 def test_run_iclabel_pytorch(eeglab_feature_file, eeglab_output_file):
-    """Test that the network outputs the same values for the features in
-    'features_raw_path' and 'features_epo_path' that contains the features
-    extracted in EEGLAB. This set of feature is compared with the set of
-    features retrieved in python in 'test_features.py:test_get_features'."""
+    """Test that the network outputs matches MATLAB.
+
+    Test that the net work outputs the same values for the features in
+    'features_raw_path' and 'features_epo_path' that contains the features extracted in
+    EEGLAB. This set of feature is compared with the set of features retrieved in python
+    in 'test_features.py:test_get_features'.
+    """
     from mne_icalabel.iclabel.network.torch import _run_iclabel
 
     features_eeglab = loadmat(eeglab_feature_file)["features"]

mne_icalabel/iclabel/network/torch.py

@@ -154,9 +154,9 @@ def reshape_concat(self, tensor: torch.Tensor) -> torch.Tensor:  # noqa: D102
         tensor = tensor.permute((0, 3, 1, 2))
         return tensor
 
-    def forward(
+    def forward(  # noqa: D102
         self, images: torch.Tensor, psds: torch.Tensor, autocorr: torch.Tensor
-    ) -> torch.Tensor:  # noqa: D102
+    ) -> torch.Tensor:
         out_img = self.img_conv(images)
         out_psds = self.psds_conv(psds)
         out_autocorr = self.autocorr_conv(autocorr)