linted

src/nemos/basis/_basis.py

@@ -242,7 +242,9 @@ def add_constant(x):
         return X
 
     @check_transform_input
-    def compute_features(self, *xi: ArrayLike | Tsd | TsdFrame |  TsdTensor) -> FeatureMatrix:
+    def compute_features(
+        self, *xi: ArrayLike | Tsd | TsdFrame | TsdTensor
+    ) -> FeatureMatrix:
         """
         Apply the basis transformation to the input data.
 
@@ -276,7 +278,9 @@ def compute_features(self, *xi: ArrayLike | Tsd | TsdFrame |  TsdTensor) -> Feat
         return self._compute_features(*xi)
 
     @abc.abstractmethod
-    def _compute_features(self, *xi: NDArray | Tsd | TsdFrame | TsdTensor) -> FeatureMatrix:
+    def _compute_features(
+        self, *xi: NDArray | Tsd | TsdFrame | TsdTensor
+    ) -> FeatureMatrix:
         """Convolve or evaluate the basis."""
         pass
 
@@ -901,7 +905,9 @@ def _evaluate(self, *xi: ArrayLike | Tsd | TsdFrame | TsdTensor) -> FeatureMatri
         return X
 
     @add_docstring("compute_features", Basis)
-    def compute_features(self, *xi: ArrayLike | Tsd | TsdFrame | TsdTensor) -> FeatureMatrix:
+    def compute_features(
+        self, *xi: ArrayLike | Tsd | TsdFrame | TsdTensor
+    ) -> FeatureMatrix:
         r"""
         Examples
         --------
@@ -918,7 +924,9 @@ def compute_features(self, *xi: ArrayLike | Tsd | TsdFrame | TsdTensor) -> Featu
         """
         return super().compute_features(*xi)
 
-    def _compute_features(self, *xi: NDArray | Tsd | TsdFrame | TsdTensor) -> FeatureMatrix:
+    def _compute_features(
+        self, *xi: NDArray | Tsd | TsdFrame | TsdTensor
+    ) -> FeatureMatrix:
         """
         Compute features for added bases and concatenate.
 
@@ -1304,7 +1312,9 @@ def _evaluate(self, *xi: ArrayLike | Tsd | TsdFrame | TsdTensor) -> FeatureMatri
         )
         return X
 
-    def _compute_features(self, *xi: NDArray | Tsd | TsdFrame | TsdTensor) -> FeatureMatrix:
+    def _compute_features(
+        self, *xi: NDArray | Tsd | TsdFrame | TsdTensor
+    ) -> FeatureMatrix:
         """
         Compute the features for the multiplied bases, and compute their outer product.
 
@@ -1397,7 +1407,9 @@ def evaluate_on_grid(self, *n_samples: int) -> Tuple[Tuple[NDArray], NDArray]:
         return super().evaluate_on_grid(*n_samples)
 
     @add_docstring("compute_features", Basis)
-    def compute_features(self, *xi: ArrayLike | Tsd | TsdFrame | TsdTensor) -> FeatureMatrix:
+    def compute_features(
+        self, *xi: ArrayLike | Tsd | TsdFrame | TsdTensor
+    ) -> FeatureMatrix:
         """
         Examples
         --------

src/nemos/basis/_decaying_exponential.py

@@ -9,6 +9,7 @@
 import numpy as np
 import scipy.linalg
 from numpy.typing import ArrayLike, NDArray
+from pynapple import Tsd, TsdFrame, TsdTensor
 
 from ..type_casting import support_pynapple
 from ..typing import FeatureMatrix
@@ -19,7 +20,6 @@
     min_max_rescale_samples,
 )
 
-from pynapple import Tsd, TsdFrame, TsdTensor
 
 class OrthExponentialBasis(Basis, abc.ABC):
     """Set of 1D basis decaying exponential functions numerically orthogonalized.

src/nemos/basis/_raised_cosine_basis.py

@@ -6,6 +6,7 @@
 
 import numpy as np
 from numpy.typing import ArrayLike, NDArray
+from pynapple import Tsd, TsdFrame, TsdTensor
 
 from ..type_casting import support_pynapple
 from ..typing import FeatureMatrix
@@ -16,7 +17,6 @@
     min_max_rescale_samples,
 )
 
-from pynapple import Tsd, TsdFrame, TsdTensor
 
 class RaisedCosineBasisLinear(Basis, abc.ABC):
     """Represent linearly-spaced raised cosine basis functions.

src/nemos/basis/_spline_basis.py

@@ -7,6 +7,7 @@
 
 import numpy as np
 from numpy.typing import ArrayLike, NDArray
+from pynapple import Tsd, TsdFrame, TsdTensor
 from scipy.interpolate import splev
 
 from ..type_casting import support_pynapple
@@ -18,7 +19,6 @@
     min_max_rescale_samples,
 )
 
-from pynapple import Tsd, TsdFrame, TsdTensor
 
 class SplineBasis(Basis, abc.ABC):
     """
@@ -218,7 +218,9 @@ def __init__(
     @support_pynapple(conv_type="numpy")
     @check_transform_input
     @check_one_dimensional
-    def _evaluate(self, sample_pts: ArrayLike | Tsd | TsdFrame | TsdTensor) -> FeatureMatrix:
+    def _evaluate(
+        self, sample_pts: ArrayLike | Tsd | TsdFrame | TsdTensor
+    ) -> FeatureMatrix:
         """
         Evaluate the M-spline basis functions at given sample points.
 
@@ -335,7 +337,9 @@ def __init__(
     @support_pynapple(conv_type="numpy")
     @check_transform_input
     @check_one_dimensional
-    def _evaluate(self, sample_pts: ArrayLike | Tsd | TsdFrame | TsdTensor) -> FeatureMatrix:
+    def _evaluate(
+        self, sample_pts: ArrayLike | Tsd | TsdFrame | TsdTensor
+    ) -> FeatureMatrix:
         """
         Evaluate the B-spline basis functions with given sample points.
 

src/nemos/basis/basis.py

@@ -9,7 +9,7 @@
 
 from ..typing import FeatureMatrix
 from ._basis import add_docstring
-from ._basis_mixin import BasisTransformerMixin, ConvBasisMixin, EvalBasisMixin
+from ._basis_mixin import ConvBasisMixin, EvalBasisMixin
 from ._decaying_exponential import OrthExponentialBasis
 from ._raised_cosine_basis import RaisedCosineBasisLinear, RaisedCosineBasisLog
 from ._spline_basis import BSplineBasis, CyclicBSplineBasis, MSplineBasis
@@ -794,9 +794,7 @@ def evaluate_on_grid(self, n_samples: int) -> Tuple[NDArray, NDArray]:
         return super().evaluate_on_grid(n_samples)
 
 
-class RaisedCosineLinearEval(
-    EvalBasisMixin, RaisedCosineBasisLinear
-):
+class RaisedCosineLinearEval(EvalBasisMixin, RaisedCosineBasisLinear):
     """
     Represent linearly-spaced raised cosine basis functions.
 
@@ -910,9 +908,7 @@ def split_by_feature(
         return super().split_by_feature(x, axis=axis)
 
 
-class RaisedCosineLinearConv(
-    ConvBasisMixin, RaisedCosineBasisLinear
-):
+class RaisedCosineLinearConv(ConvBasisMixin, RaisedCosineBasisLinear):
     """
     Represent linearly-spaced raised cosine basis functions.