chore: lint

juaml · Nov 13, 2023 · 6d15eb2 · 6d15eb2
1 parent 76ecfbd
commit 6d15eb2
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diff --git a/junifer/markers/complexity/complexity_base.py b/junifer/markers/complexity/complexity_base.py
@@ -4,7 +4,16 @@
 # License: AGPL
 
 from abc import abstractmethod
-from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    ClassVar,
+    Dict,
+    List,
+    Optional,
+    Set,
+    Union,
+)
 
 from ...utils import raise_error
 from ..base import BaseMarker
@@ -39,7 +48,7 @@ class ComplexityBase(BaseMarker):
 
     """
 
-    _DEPENDENCIES = {"nilearn", "neurokit2"}
+    _DEPENDENCIES: ClassVar[Set[str]] = {"nilearn", "neurokit2"}
 
     def __init__(
         self,
@@ -101,21 +110,22 @@ def compute(
         """Compute.
 
         Parameters
-         ----------
-         input : dict
-             A single input from the pipeline data object in which to compute
-             the marker.
-         extra_input : dict, optional
-             The other fields in the pipeline data object. Useful for accessing
-             other data kind that needs to be used in the computation.
-         Returns
-         -------
-         dict
-             The computed result as dictionary. The following keys will be
-             included in the dictionary:
-
-            * ``data`` : ROI-wise complexity measures as ``numpy.ndarray``
-            * ``col_names`` : ROI labels for the complexity measures as list
+        ----------
+        input : dict
+            A single input from the pipeline data object in which to compute
+            the marker.
+        extra_input : dict, optional
+            The other fields in the pipeline data object. Useful for accessing
+            other data kind that needs to be used in the computation.
+
+        Returns
+        -------
+        dict
+            The computed result as dictionary. The following keys will be
+            included in the dictionary:
+
+           * ``data`` : ROI-wise complexity measures as ``numpy.ndarray``
+           * ``col_names`` : ROI labels for the complexity measures as list
 
         """
         # Initialize a ParcelAggregation

diff --git a/junifer/markers/complexity/hurst_exponent.py b/junifer/markers/complexity/hurst_exponent.py
@@ -89,9 +89,9 @@ def compute_complexity(
         .. [1] Peng, C.; Havlin, S.; Stanley, H.E.; Goldberger, A.L.
                Quantification of scaling exponents and crossover phenomena in
                nonstationary heartbeat time series.
-               Chaos Interdiscip. J. Nonlinear Sci., 5, 82–87, 1995.
+               Chaos Interdiscip. J. Nonlinear Sci., 5, 82-87, 1995.
 
-        See also
+        See Also
         --------
         neurokit2.fractal_dfa
 

diff --git a/junifer/markers/complexity/multiscale_entropy_auc.py b/junifer/markers/complexity/multiscale_entropy_auc.py
@@ -91,7 +91,7 @@ def compute_complexity(
                Multiscale entropy analysis of complex physiologic time series.
                Physical review letters, 89(6), 068102, 2002.
 
-        See also
+        See Also
         --------
         neurokit2.entropy_multiscale
 
@@ -125,11 +125,9 @@ def compute_complexity(
 
         if np.isnan(np.sum(MSEn_auc_roi)):
             warn_with_log(
-                (
-                    "There is NaN in the entropy values, likely due "
-                    "to too short data length. A possible solution "
-                    "may be to choose a smaller value for 'scale'."
-                )
+                "There is NaN in the entropy values, likely due "
+                "to too short data length. A possible solution "
+                "may be to choose a smaller value for 'scale'."
             )
 
         return MSEn_auc_roi.T  # 1 X n_roi
diff --git a/junifer/markers/complexity/perm_entropy.py b/junifer/markers/complexity/perm_entropy.py
@@ -91,7 +91,7 @@ def compute_complexity(
                series.
                Physical review letters, 88(17), 174102.
 
-        See also
+        See Also
         --------
         neurokit2.entropy_permutation
 

diff --git a/junifer/markers/complexity/range_entropy.py b/junifer/markers/complexity/range_entropy.py
@@ -91,7 +91,7 @@ def compute_complexity(
                Self-Similarity.
                Entropy, vol. 20, no. 12, p. 962, 2018.
 
-        See also
+        See Also
         --------
         neurokit2.entropy_range
 
@@ -112,7 +112,6 @@ def compute_complexity(
         range_en_roi = np.zeros((n_roi, 1))
 
         for idx_roi in range(n_roi):
-
             sig = extracted_bold_values[:, idx_roi]
             tmp = nk.entropy_range(
                 sig,

diff --git a/junifer/markers/complexity/range_entropy_auc.py b/junifer/markers/complexity/range_entropy_auc.py
@@ -92,7 +92,7 @@ def compute_complexity(
                Self-Similarity.
                Entropy, vol. 20, no. 12, p. 962, 2018.
 
-        See also
+        See Also
         --------
         neurokit2.entropy_range
 
@@ -112,13 +112,11 @@ def compute_complexity(
         range_en_auc_roi = np.zeros((n_roi, 1))
 
         for idx_roi in range(n_roi):
-
             sig = extracted_bold_values[:, idx_roi]
 
-            range_ent_vec = np.zeros((n_r))
+            range_ent_vec = np.zeros(n_r)
             idx_r = 0
             for tolerance in r_span:
-
                 range_en_auc_roi_tmp = nk.entropy_range(
                     sig,
                     dimension=emb_dim,

diff --git a/junifer/markers/complexity/sample_entropy.py b/junifer/markers/complexity/sample_entropy.py
@@ -92,7 +92,7 @@ def compute_complexity(
                Am. J. Physiol. Heart Circ. Physiol., 278 (6) (2000),
                pp. H2039-2049
 
-        See also
+        See Also
         --------
         neurokit2.entropy_sample
 

diff --git a/junifer/markers/complexity/weighted_perm_entropy.py b/junifer/markers/complexity/weighted_perm_entropy.py
@@ -92,7 +92,7 @@ def compute_complexity(
                time series incorporating amplitude information.
                Physical Review E, 87(2), 022911.
 
-        See also
+        See Also
         --------
         neurokit2.entropy_permutation