.github/workflows/docker-ci-publish.yml

@@ -45,7 +45,7 @@ jobs:
       # https://github.com/sigstore/cosign-installer
       - name: Install cosign
         if: github.event_name != 'pull_request'
-        uses: sigstore/cosign-installer@d58896d6a1865668819e1d91763c7751a165e159 #v3.9.2
+        uses: sigstore/cosign-installer@d7543c93d881b35a8faa02e8e3605f69b7a1ce62 #v3.10.0
         with:
           cosign-release: 'v2.2.4'
 

.github/workflows/docker-docs-publish.yml

@@ -42,7 +42,7 @@ jobs:
       # https://github.com/sigstore/cosign-installer
       - name: Install cosign
         if: github.event_name != 'pull_request'
-        uses: sigstore/cosign-installer@d58896d6a1865668819e1d91763c7751a165e159 #v3.9.2
+        uses: sigstore/cosign-installer@d7543c93d881b35a8faa02e8e3605f69b7a1ce62 #v3.10.0
         with:
           cosign-release: 'v2.2.4'
 

junifer/api/queue_context/tests/test_gnu_parallel_local_adapter.py

@@ -14,7 +14,7 @@ from junifer.api.queue_context import GnuParallelLocalAdapter
 
 def test_GnuParallelLocalAdapter_env_kind_error() -> None:
     """Test error for invalid env kind."""
-    with pytest.raises(ValueError, match="Invalid value for `env.kind`"):
+    with pytest.raises(ValueError, match=r"Invalid value for `env.kind`"):
         GnuParallelLocalAdapter(
             job_name="check_env_kind",
             job_dir=Path("."),
@@ -26,7 +26,7 @@ def test_GnuParallelLocalAdapter_env_kind_error() -> None:
 
 def test_GnuParallelLocalAdapter_env_shell_error() -> None:
     """Test error for invalid env shell."""
-    with pytest.raises(ValueError, match="Invalid value for `env.shell`"):
+    with pytest.raises(ValueError, match=r"Invalid value for `env.shell`"):
         GnuParallelLocalAdapter(
             job_name="check_env_shell",
             job_dir=Path("."),

junifer/api/queue_context/tests/test_htcondor_adapter.py

@@ -14,7 +14,7 @@ from junifer.api.queue_context import HTCondorAdapter
 
 def test_HTCondorAdapter_env_kind_error() -> None:
     """Test error for invalid env kind."""
-    with pytest.raises(ValueError, match="Invalid value for `env.kind`"):
+    with pytest.raises(ValueError, match=r"Invalid value for `env.kind`"):
         HTCondorAdapter(
             job_name="check_env_kind",
             job_dir=Path("."),
@@ -26,7 +26,7 @@ def test_HTCondorAdapter_env_kind_error() -> None:
 
 def test_HTCondorAdapter_env_shell_error() -> None:
     """Test error for invalid env shell."""
-    with pytest.raises(ValueError, match="Invalid value for `env.shell`"):
+    with pytest.raises(ValueError, match=r"Invalid value for `env.shell`"):
         HTCondorAdapter(
             job_name="check_env_shell",
             job_dir=Path("."),
@@ -38,7 +38,7 @@ def test_HTCondorAdapter_env_shell_error() -> None:
 
 def test_HTCondorAdapter_collect_error() -> None:
     """Test error for invalid collect option."""
-    with pytest.raises(ValueError, match="Invalid value for `collect`"):
+    with pytest.raises(ValueError, match=r"Invalid value for `collect`"):
         HTCondorAdapter(
             job_name="check_collect",
             job_dir=Path("."),

junifer/data/parcellations/tests/test_parcellations.py

@@ -634,7 +634,7 @@ def test_aicha(version: int) -> None:
 
 def test_retrieve_aicha_incorrect_version() -> None:
     """Test retrieve AICHA with incorrect version."""
-    with pytest.raises(ValueError, match="The parameter `version`"):
+    with pytest.raises(ValueError, match=r"The parameter `version`"):
         _retrieve_aicha(
             version=100,
         )
@@ -697,7 +697,7 @@ def test_shen(
 
 def test_retrieve_shen_incorrect_year() -> None:
     """Test retrieve Shen with incorrect year."""
-    with pytest.raises(ValueError, match="The parameter `year`"):
+    with pytest.raises(ValueError, match=r"The parameter `year`"):
         _retrieve_shen(
             year=1969,
         )
@@ -705,7 +705,7 @@ def test_retrieve_shen_incorrect_year() -> None:
 
 def test_retrieve_shen_incorrect_n_rois() -> None:
     """Test retrieve Shen with incorrect ROIs."""
-    with pytest.raises(ValueError, match="The parameter `n_rois`"):
+    with pytest.raises(ValueError, match=r"The parameter `n_rois`"):
         _retrieve_shen(
             year=2015,
             n_rois=10,
@@ -747,7 +747,7 @@ def test_retrieve_shen_incorrect_param_combo(
         The parametrized ROI count values.
 
     """
-    with pytest.raises(ValueError, match="The parameter combination"):
+    with pytest.raises(ValueError, match=r"The parameter combination"):
         _retrieve_shen(
             resolution=resolution,
             year=year,
@@ -875,7 +875,7 @@ def test_yan(
 def test_retrieve_yan_incorrect_networks() -> None:
     """Test retrieve Yan with incorrect networks."""
     with pytest.raises(
-        ValueError, match="Either one of `yeo_networks` or `kong_networks`"
+        ValueError, match=r"Either one of `yeo_networks` or `kong_networks`"
     ):
         _retrieve_yan(
             n_rois=31418,
@@ -884,7 +884,7 @@ def test_retrieve_yan_incorrect_networks() -> None:
         )
 
     with pytest.raises(
-        ValueError, match="Either one of `yeo_networks` or `kong_networks`"
+        ValueError, match=r"Either one of `yeo_networks` or `kong_networks`"
     ):
         _retrieve_yan(
             n_rois=31418,
@@ -895,7 +895,7 @@ def test_retrieve_yan_incorrect_networks() -> None:
 
 def test_retrieve_yan_incorrect_n_rois() -> None:
     """Test retrieve Yan with incorrect ROIs."""
-    with pytest.raises(ValueError, match="The parameter `n_rois`"):
+    with pytest.raises(ValueError, match=r"The parameter `n_rois`"):
         _retrieve_yan(
             n_rois=31418,
             yeo_networks=7,
@@ -904,7 +904,7 @@ def test_retrieve_yan_incorrect_n_rois() -> None:
 
 def test_retrieve_yan_incorrect_yeo_networks() -> None:
     """Test retrieve Yan with incorrect Yeo networks."""
-    with pytest.raises(ValueError, match="The parameter `yeo_networks`"):
+    with pytest.raises(ValueError, match=r"The parameter `yeo_networks`"):
         _retrieve_yan(
             n_rois=100,
             yeo_networks=27,
@@ -913,7 +913,7 @@ def test_retrieve_yan_incorrect_yeo_networks() -> None:
 
 def test_retrieve_yan_incorrect_kong_networks() -> None:
     """Test retrieve Yan with incorrect Kong networks."""
-    with pytest.raises(ValueError, match="The parameter `kong_networks`"):
+    with pytest.raises(ValueError, match=r"The parameter `kong_networks`"):
         _retrieve_yan(
             n_rois=100,
             kong_networks=27,
@@ -976,7 +976,7 @@ def test_brainnetome(
 
 def test_retrieve_brainnetome_incorrect_threshold() -> None:
     """Test retrieve Brainnetome with incorrect threshold."""
-    with pytest.raises(ValueError, match="The parameter `threshold`"):
+    with pytest.raises(ValueError, match=r"The parameter `threshold`"):
         _retrieve_brainnetome(
             threshold=100,
         )
@@ -1091,7 +1091,7 @@ def test_merge_parcellations_3D_multiple_overlapping() -> None:
     names = ["high", "low"]
     labels_lists = [labels1, labels2]
 
-    with pytest.warns(RuntimeWarning, match="overlapping voxels"):
+    with pytest.warns(RuntimeWarning, match=r"overlapping voxels"):
         merge_parcellations(parcellation_list, names, labels_lists)
 
     parc_data = parcellation.get_fdata()
@@ -1128,7 +1128,7 @@ def test_merge_parcellations_3D_multiple_duplicated_labels() -> None:
     names = ["high", "low"]
     labels_lists = [labels1, labels2]
 
-    with pytest.warns(RuntimeWarning, match="duplicated labels."):
+    with pytest.warns(RuntimeWarning, match=r"duplicated labels."):
         merged_parc, _ = merge_parcellations(
             parcellation_list, names, labels_lists
         )

junifer/external/nilearn/tests/test_junifer_connectivity_measure.py

@@ -223,7 +223,7 @@ def signals_and_covariances(
 def test_check_square() -> None:
     """Test square matrix assertion."""
     non_square = np.ones((2, 3))
-    with pytest.raises(ValueError, match="Expected a square matrix"):
+    with pytest.raises(ValueError, match=r"Expected a square matrix"):
         _check_square(non_square)
 
 
@@ -244,7 +244,7 @@ def test_check_spd(invalid_input: np.ndarray) -> None:
 
     """
     with pytest.raises(
-        ValueError, match="Expected a symmetric positive definite matrix."
+        ValueError, match=r"Expected a symmetric positive definite matrix."
     ):
         _check_spd(invalid_input)
 
@@ -555,7 +555,7 @@ def test_geometric_mean_error_non_square_matrix() -> None:
     n_features = 5
     mat1 = np.ones((n_features, n_features + 1))
 
-    with pytest.raises(ValueError, match="Expected a square matrix"):
+    with pytest.raises(ValueError, match=r"Expected a square matrix"):
         _geometric_mean([mat1])
 
 
@@ -566,7 +566,7 @@ def test_geometric_mean_error_input_matrices_have_different_shapes() -> None:
     mat2 = np.ones((n_features + 1, n_features + 1))
 
     with pytest.raises(
-        ValueError, match="Matrices are not of the same shape."
+        ValueError, match=r"Matrices are not of the same shape."
     ):
         _geometric_mean([mat1, mat2])
 
@@ -577,7 +577,7 @@ def test_geometric_mean_error_non_spd_input_matrix() -> None:
     mat2 = np.ones((n_features + 1, n_features + 1))
 
     with pytest.raises(
-        ValueError, match="Expected a symmetric positive definite matrix."
+        ValueError, match=r"Expected a symmetric positive definite matrix."
     ):
         _geometric_mean([mat2])
 
@@ -588,19 +588,20 @@ def test_connectivity_measure_errors():
     conn_measure = JuniferConnectivityMeasure()
 
     with pytest.raises(
-        ValueError, match="'subjects' input argument must be an iterable"
+        ValueError, match=r"'subjects' input argument must be an iterable"
     ):
         conn_measure.fit(1.0)
 
     # input subjects not 2D numpy.ndarrays
     with pytest.raises(
-        ValueError, match="Each subject must be 2D numpy.ndarray."
+        ValueError, match=r"Each subject must be 2D numpy.ndarray."
     ):
         conn_measure.fit([np.ones((100, 40)), np.ones((10,))])
 
     # input subjects with different number of features
     with pytest.raises(
-        ValueError, match="All subjects must have the same number of features."
+        ValueError,
+        match=r"All subjects must have the same number of features.",
     ):
         conn_measure.fit([np.ones((100, 40)), np.ones((100, 41))])
 
@@ -609,7 +610,7 @@ def test_connectivity_measure_errors():
 
     with pytest.raises(
         ValueError,
-        match="Tangent space parametrization .* only be .* group of subjects",
+        match=r"Tangent space parametrization .* only be .* group of subjects",
     ):
         conn_measure.fit_transform([np.ones((100, 40))])
 
@@ -873,7 +874,7 @@ def test_connectivity_measure_check_vectorization_option(
     )
 
     # Check not fitted error
-    with pytest.raises(ValueError, match="has not been fitted. "):
+    with pytest.raises(ValueError, match=r"has not been fitted. "):
         JuniferConnectivityMeasure().inverse_transform(
             vectorized_connectivities
         )
@@ -956,7 +957,7 @@ def test_connectivity_measure_check_inverse_transformation_discard_diag(
 
         assert_array_almost_equal(inverse_transformed, connectivities)
         with pytest.raises(
-            ValueError, match="cannot reconstruct connectivity matrices"
+            ValueError, match=r"cannot reconstruct connectivity matrices"
         ):
             conn_measure.inverse_transform(vectorized_connectivities)
 
@@ -1010,7 +1011,7 @@ def test_connectivity_measure_inverse_transform_tangent(
 
     assert_array_almost_equal(inverse_transformed, covariances)
     with pytest.raises(
-        ValueError, match="cannot reconstruct connectivity matrices"
+        ValueError, match=r"cannot reconstruct connectivity matrices"
     ):
         tangent_measure.inverse_transform(vectorized_displacements)
 
@@ -1050,7 +1051,7 @@ def test_confounds_connectivity_measure_errors() -> None:
 
     # Raising error for input confounds are not iterable
     conn_measure = JuniferConnectivityMeasure(vectorize=True)
-    msg = "'confounds' input argument must be an iterable"
+    msg = r"'confounds' input argument must be an iterable"
 
     with pytest.raises(ValueError, match=msg):
         conn_measure._check_input(X=signals, confounds=1.0)
@@ -1066,7 +1067,7 @@ def test_confounds_connectivity_measure_errors() -> None:
     # Raising error for input confounds are given but not vectorize=True
     conn_measure = JuniferConnectivityMeasure(vectorize=False)
     with pytest.raises(
-        ValueError, match="'confounds' are provided but vectorize=False"
+        ValueError, match=r"'confounds' are provided but vectorize=False"
     ):
         conn_measure.fit_transform(signals, None, confounds[:10])
 
@@ -1082,7 +1083,7 @@ def test_connectivity_measure_standardize(
         The input signals.
 
     """
-    match = "default strategy for standardize"
+    match = r"default strategy for standardize"
 
     with pytest.warns(DeprecationWarning, match=match):
         JuniferConnectivityMeasure(kind="correlation").fit_transform(signals)
@@ -1101,7 +1102,7 @@ def test_connectivity_measure_standardize(
 )
 def test_xi_correlation_error() -> None:
     """Check xi correlation according to paper."""
-    with pytest.raises(RuntimeError, match="scipy.stats.chatterjeexi"):
+    with pytest.raises(RuntimeError, match=r"scipy.stats.chatterjeexi"):
         JuniferConnectivityMeasure(kind="xi correlation").fit_transform(
             np.zeros((2, 2))
         )

junifer/external/nilearn/tests/test_junifer_nifti_spheres_masker.py

@@ -144,7 +144,7 @@ def test_anisotropic_sphere_extraction() -> None:
 def test_errors() -> None:
     """Test errors."""
     masker = JuniferNiftiSpheresMasker(seeds=([1, 2]), radius=0.2)
-    with pytest.raises(ValueError, match="Seeds must be a list .+"):
+    with pytest.raises(ValueError, match=r"Seeds must be a list .+"):
         masker.fit()
 
 
@@ -183,7 +183,7 @@ def test_nifti_spheres_masker_overlap() -> None:
         radius=2,
         allow_overlap=False,
     )
-    with pytest.raises(ValueError, match="Overlap detected"):
+    with pytest.raises(ValueError, match=r"Overlap detected"):
         noverlapping_masker.fit_transform(fmri_img)
 
 
@@ -288,7 +288,7 @@ def test_nifti_spheres_masker_inverse_transform() -> None:
     masker = JuniferNiftiSpheresMasker(seeds=[(1, 1, 1)], radius=1)
     with pytest.raises(
         NotImplementedError,
-        match="some of which are non-reversible",
+        match=r"some of which are non-reversible",
     ):
         masker.inverse_transform(data[0, 0, 0, :])
 
@@ -319,7 +319,7 @@ def test_nifti_spheres_masker_io_shapes() -> None:
     masker.fit()
 
     # DeprecationWarning *should* be raised for 3D inputs
-    with pytest.warns(DeprecationWarning, match="Starting in version 0.12"):
+    with pytest.warns(DeprecationWarning, match=r"Starting in version 0.12"):
         test_data = masker.transform(img_3d)
         assert test_data.shape == (1, n_regions)
 

junifer/preprocess/confounds/tests/test_fmriprep_confound_remover.py

@@ -26,16 +26,16 @@ from junifer.testing.datagrabbers import (
 def test_fMRIPrepConfoundRemover_init() -> None:
     """Test fMRIPrepConfoundRemover init."""
 
-    with pytest.raises(ValueError, match="keys must be strings"):
+    with pytest.raises(ValueError, match=r"keys must be strings"):
         fMRIPrepConfoundRemover(strategy={1: "full"})  # type: ignore
 
-    with pytest.raises(ValueError, match="values must be strings"):
+    with pytest.raises(ValueError, match=r"values must be strings"):
         fMRIPrepConfoundRemover(strategy={"motion": 1})  # type: ignore
 
-    with pytest.raises(ValueError, match="component names"):
+    with pytest.raises(ValueError, match=r"component names"):
         fMRIPrepConfoundRemover(strategy={"wrong": "full"})
 
-    with pytest.raises(ValueError, match="confound types"):
+    with pytest.raises(ValueError, match=r"confound types"):
         fMRIPrepConfoundRemover(strategy={"motion": "wrong"})
 
 
@@ -342,7 +342,7 @@ def test_fMRIPrepConfoundRemover__get_scrub_regressors_errors(
         The parametrized preprocessor.
 
     """
-    with pytest.raises(RuntimeError, match="Invalid confounds file."):
+    with pytest.raises(RuntimeError, match=r"Invalid confounds file."):
         preprocessor._get_scrub_regressors(pd.DataFrame({"a": [1, 2]}))
 
 
@@ -354,7 +354,7 @@ def test_fMRIPrepConfoundRemover__validate_data() -> None:
         element_data = DefaultDataReader().fit_transform(dg["sub-01"])
         vbm = element_data["VBM_GM"]
         with pytest.raises(
-            DimensionError, match="incompatible dimensionality"
+            DimensionError, match=r"incompatible dimensionality"
         ):
             confound_remover._validate_data(vbm)
     # Check missing nested type in correct data type
@@ -363,22 +363,22 @@ def test_fMRIPrepConfoundRemover__validate_data() -> None:
         bold = element_data["BOLD"]
         # Test confound type
         with pytest.raises(
-            ValueError, match="`BOLD.confounds` data type not provided"
+            ValueError, match=r"`BOLD.confounds` data type not provided"
         ):
             confound_remover._validate_data(bold)
         # Test confound data
         bold["confounds"] = {}
         with pytest.raises(
-            ValueError, match="`BOLD.confounds.data` not provided"
+            ValueError, match=r"`BOLD.confounds.data` not provided"
         ):
             confound_remover._validate_data(bold)
         # Test confound data is valid type
         bold["confounds"] = {"data": None}
-        with pytest.raises(ValueError, match="must be a `pandas.DataFrame`"):
+        with pytest.raises(ValueError, match=r"must be a `pandas.DataFrame`"):
             confound_remover._validate_data(bold)
         # Test confound data dimension mismatch with BOLD
         bold["confounds"] = {"data": pd.DataFrame()}
-        with pytest.raises(ValueError, match="Image time series and"):
+        with pytest.raises(ValueError, match=r"Image time series and"):
             confound_remover._validate_data(bold)
     # Check nested type variations
     with PartlyCloudyTestingDataGrabber(reduce_confounds=False) as dg:
@@ -393,19 +393,19 @@ def test_fMRIPrepConfoundRemover__validate_data() -> None:
         }
         # Test incorrect format
         modified_bold["confounds"].update({"format": "wrong"})
-        with pytest.raises(ValueError, match="Invalid confounds format"):
+        with pytest.raises(ValueError, match=r"Invalid confounds format"):
             confound_remover._validate_data(modified_bold)
         # Test missing mappings for adhoc
         modified_bold["confounds"].update({"format": "adhoc"})
         with pytest.raises(
-            ValueError, match="`BOLD.confounds.mappings` need to be set"
+            ValueError, match=r"`BOLD.confounds.mappings` need to be set"
         ):
             confound_remover._validate_data(modified_bold)
         # Test missing fmriprep mappings for adhoc
         modified_bold["confounds"].update({"mappings": {}})
         with pytest.raises(
             ValueError,
-            match="`BOLD.confounds.mappings.fmriprep` need to be set",
+            match=r"`BOLD.confounds.mappings.fmriprep` need to be set",
         ):
             confound_remover._validate_data(modified_bold)
         # Test incorrect fmriprep mappings for adhoc

junifer/storage/tests/test_hdf5.py

@@ -1174,7 +1174,7 @@ def test_collect_error_single_output() -> None:
     """Test error for collect in single output storage."""
     with pytest.raises(
         NotImplementedError,
-        match="is not implemented for single output.",
+        match=r"is not implemented for single output.",
     ):
         storage = HDF5FeatureStorage(uri="/tmp", single_output=True)
         storage.collect()

junifer/storage/tests/test_utils.py

@@ -211,7 +211,7 @@ def test_process_meta_element(meta: dict, elements: list[str]) -> None:
         The parametrized elements to assert against.
 
     """
-    hash1, processed_meta, _ = process_meta(meta)
+    _, processed_meta, _ = process_meta(meta)
     assert "_element_keys" in processed_meta
     assert processed_meta["_element_keys"] == elements
     assert "A" in processed_meta

junifer/tests/test_stats.py

@@ -41,41 +41,41 @@ def test_get_aggfunc_by_name(name: str, params: Optional[dict]) -> None:
 
 def test_get_aggfunc_by_name_errors() -> None:
     """Test aggregation function retrieval using wrong name."""
-    with pytest.raises(ValueError, match="unknown. Please provide any of"):
+    with pytest.raises(ValueError, match=r"unknown. Please provide any of"):
         get_aggfunc_by_name(name="invalid", func_params=None)
 
-    with pytest.raises(ValueError, match="list of limits"):
+    with pytest.raises(ValueError, match=r"list of limits"):
         get_aggfunc_by_name(name="winsorized_mean", func_params=None)
 
-    with pytest.raises(ValueError, match="list of limits"):
+    with pytest.raises(ValueError, match=r"list of limits"):
         get_aggfunc_by_name(
             name="winsorized_mean", func_params={"limits": 0.1}
         )
 
-    with pytest.raises(ValueError, match="list of two limits"):
+    with pytest.raises(ValueError, match=r"list of two limits"):
         get_aggfunc_by_name(
             name="winsorized_mean", func_params={"limits": [0.2]}
         )
 
-    with pytest.raises(ValueError, match="list of two"):
+    with pytest.raises(ValueError, match=r"list of two"):
         get_aggfunc_by_name(
             name="winsorized_mean", func_params={"limits": [0.2, 0.7, 0.1]}
         )
 
-    with pytest.raises(ValueError, match="must be between 0 and 1"):
+    with pytest.raises(ValueError, match=r"must be between 0 and 1"):
         get_aggfunc_by_name(
             name="winsorized_mean", func_params={"limits": [-1, 0.7]}
         )
 
-    with pytest.raises(ValueError, match="must be between 0 and 1"):
+    with pytest.raises(ValueError, match=r"must be between 0 and 1"):
         get_aggfunc_by_name(
             name="winsorized_mean", func_params={"limits": [0.1, 2]}
         )
 
-    with pytest.raises(ValueError, match="must be specified."):
+    with pytest.raises(ValueError, match=r"must be specified."):
         get_aggfunc_by_name(name="select", func_params=None)
 
-    with pytest.raises(ValueError, match="must be specified, not both."):
+    with pytest.raises(ValueError, match=r"must be specified, not both."):
         get_aggfunc_by_name(
             name="select", func_params={"pick": [0], "drop": [1]}
         )
@@ -110,10 +110,10 @@ def test_select() -> None:
     """Test select."""
     input = np.arange(28).reshape(7, 4)
 
-    with pytest.raises(ValueError, match="must be specified."):
+    with pytest.raises(ValueError, match=r"must be specified."):
         select(input, axis=2)
 
-    with pytest.raises(ValueError, match="must be specified, not both."):
+    with pytest.raises(ValueError, match=r"must be specified, not both."):
         select(input, pick=[1], drop=[2], axis=2)
 
     out1 = select(input, pick=[1], axis=0)