Fix some warnings.

skfda/datasets/_real_datasets.py

@@ -5,12 +5,11 @@
 
 import numpy as np
 import pandas as pd
+import rdata
 from pandas import DataFrame, Series
 from sklearn.utils import Bunch
 from typing_extensions import Literal
 
-import rdata
-
 from ..representation import FDataGrid
 from ..typing._numpy import NDArrayFloat, NDArrayInt
 
@@ -180,7 +179,7 @@ def fetch_ucr(
     The UCR/UEA Time Series Classification repository, hosted at
     www.timeseriesclassification.com includes plenty of
     classification problems with univariate and multivariate time series
-    \ :footcite:p:`dau++_2019_ucr,bagnall++_2018_uea`.
+    :footcite:p:`dau++_2019_ucr,bagnall++_2018_uea`.
     They are widely used in the functional data classification literature.
 
     Args:

skfda/exploratory/visualization/_boxplot.py

@@ -11,7 +11,6 @@
 from typing import Sequence, Tuple
 
 import matplotlib
-import matplotlib.pyplot as plt
 import numpy as np
 from matplotlib.axes import Axes
 from matplotlib.colors import Colormap
@@ -376,7 +375,7 @@ def __init__(
 
         self._fdatagrid = fdatagrid
         self._prob = prob
-        self._colormap = plt.cm.get_cmap('RdPu')
+        self._colormap = matplotlib.colormaps['RdPu']
         self.barcol = "blue"
         self.outliercol = "red"
         self.mediancol = "black"
@@ -701,7 +700,7 @@ def __init__(
         self._non_outlying_envelope = _envelopes.compute_envelope(inliers)
 
         self._fdatagrid = fdatagrid
-        self.colormap = plt.cm.get_cmap('Greys')
+        self.colormap = matplotlib.colormaps['Greys']
         self._boxcol = 1.0
         self._outcol = 0.7
 

skfda/exploratory/visualization/_magnitude_shape_plot.py

@@ -10,7 +10,6 @@
 from typing import Any, Sequence
 
 import matplotlib
-import matplotlib.pyplot as plt
 import numpy as np
 from matplotlib.artist import Artist
 from matplotlib.axes import Axes
@@ -193,7 +192,7 @@ def __init__(
 
         self._fdata = fdata
         self._outliers = outliers
-        self._colormap = plt.cm.get_cmap('seismic')
+        self._colormap = matplotlib.colormaps['seismic']
         self._color = 0.2
         self._outliercol = 0.8
         self.xlabel = 'MO'

skfda/ml/classification/_depth_classifiers.py

@@ -71,7 +71,7 @@ class DDClassifier(
     Depth-versus-depth (DD) classifer for functional data.
 
     Transforms the data into a DD-plot and then classifies using a polynomial
-    of a chosen degree\ :footcite:p:`li++_2012_ddclassifier`.
+    of a chosen degree :footcite:p:`li++_2012_ddclassifier`.
     The polynomial passes through zero and maximizes the accuracy of the
     classification on the train dataset.
 
@@ -117,7 +117,7 @@ class DDClassifier(
     See also:
         :class:`~skfda.ml.classification.DDGClassifier`
         :class:`~skfda.ml.classification.MaximumDepthClassifier`
-        :class:`~skfda.preprocessing.dim_reduction.feature_extraction._ddg_transformer`
+        :class:`~skfda.preprocessing.dim_reduction.feature_construction._ddg_transformer`
 
     References:
         .. footbibliography::
@@ -307,7 +307,7 @@ class DDGClassifier(
     See also:
         :class:`~skfda.ml.classification.DDClassifier`
         :class:`~skfda.ml.classification.MaximumDepthClassifier`
-        :class:`~skfda.preprocessing.dim_reduction.feature_extraction._ddg_transformer`
+        :class:`~skfda.preprocessing.dim_reduction.feature_construction._ddg_transformer`
 
     References:
         .. footbibliography::

skfda/preprocessing/dim_reduction/feature_extraction/__init__.py

@@ -8,4 +8,5 @@
     'Please use "dim_reduction" for FPCA'
     'or "feature_construction" for feature construction techniques',
     category=DeprecationWarning,
+    stacklevel=2,
 )

skfda/preprocessing/dim_reduction/projection/__init__.py

@@ -5,4 +5,5 @@
 warnings.warn(
     'The module "projection" is deprecated. Please use "dim_reduction"',
     category=DeprecationWarning,
+    stacklevel=2,
 )

skfda/preprocessing/smoothing/kernel_smoothers.py

@@ -18,6 +18,7 @@
     "The \"kernel_smoothers\" module is deprecated. "
     "Use the \"KernelSmoother\" class instead",
     DeprecationWarning,
+    stacklevel=2,
 )
 
 

skfda/representation/basis/_bspline_basis.py

@@ -460,6 +460,7 @@ def __init__(  # noqa: WPS238
             knots=knots,
         )
         warnings.warn(
-            "The BSplines class is deprecated. Use BSplineBasis instead.",
+            "The BSpline class is deprecated. Use BSplineBasis instead.",
             DeprecationWarning,
+            stacklevel=2,
         )

skfda/representation/basis/_constant_basis.py

@@ -81,5 +81,6 @@ def __init__(self, domain_range: Optional[DomainRangeLike] = None) -> None:
         warnings.warn(
             "The Constant class is deprecated. Use ConstantBasis instead.",
             DeprecationWarning,
+            stacklevel=2,
         )
         super().__init__(domain_range=domain_range)

skfda/representation/basis/_finite_element_basis.py

@@ -229,4 +229,5 @@ def __init__(
             "The FiniteElement class is deprecated. Use "
             "FiniteElementBasis instead.",
             DeprecationWarning,
+            stacklevel=2,
         )

skfda/representation/basis/_fourier_basis.py

@@ -319,6 +319,7 @@ def __init__(
         warnings.warn(
             "The Fourier class is deprecated. Use FourierBasis instead.",
             DeprecationWarning,
+            stacklevel=2,
         )
         super().__init__(
             domain_range=domain_range,

skfda/representation/basis/_monomial_basis.py

@@ -211,4 +211,5 @@ def __init__(
         warnings.warn(
             "The Monomial class is deprecated. Use MonomialBasis instead.",
             DeprecationWarning,
+            stacklevel=2,
         )

skfda/representation/basis/_tensor_basis.py

@@ -180,4 +180,5 @@ def __init__(self, basis_list: Iterable[Basis]):
         warnings.warn(
             "The Tensor class is deprecated. Use TensorBasis instead.",
             DeprecationWarning,
+            stacklevel=2,
         )

skfda/representation/basis/_vector_basis.py

@@ -245,4 +245,5 @@ def __init__(self, basis_list: Iterable[Basis]) -> None:
             "The VectorValued class is deprecated. "
             "Use VectorValuedBasis instead.",
             DeprecationWarning,
+            stacklevel=2,
         )