Fix cartesian product.

GAA-UAM · Nov 24, 2023 · 3d7d58f · 3d7d58f
1 parent 29bb62c
commit 3d7d58f
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Showing 5 changed files with 11 additions and 14 deletions.
diff --git a/skfda/_utils/ndfunction/utils.py b/skfda/_utils/ndfunction/utils.py
@@ -151,9 +151,6 @@ def cartesian_product(  # noqa: WPS234
     )
 
 
-_cartesian_product = cartesian_product
-
-
 def grid_points_equal(gp1: GridPoints[A], gp2: GridPoints[A], /) -> bool:
     """Check if grid points are equal."""
     shape_equal = gp1.shape == gp2.shape

diff --git a/skfda/datasets/_samples_generators.py b/skfda/datasets/_samples_generators.py
@@ -8,7 +8,7 @@
 from scipy.stats import multivariate_normal
 
 from .._utils import _to_grid_points, normalize_warping
-from .._utils.ndfunction.utils import _cartesian_product
+from .._utils.ndfunction.utils import cartesian_product
 from ..misc.covariances import Brownian, CovarianceLike, _execute_covariance
 from ..misc.validation import validate_random_state
 from ..representation import FDataGrid
@@ -66,7 +66,7 @@ def make_gaussian(
 
     grid_points = _to_grid_points(grid_points)
 
-    input_points = _cartesian_product(grid_points)
+    input_points = cartesian_product(grid_points)
 
     covariance = _execute_covariance(
         cov,

diff --git a/skfda/ml/regression/_historical_linear_model.py b/skfda/ml/regression/_historical_linear_model.py
@@ -9,7 +9,7 @@
 
 from ..._utils import _pairwise_symmetric
 from ..._utils._sklearn_adapter import BaseEstimator, RegressorMixin
-from ..._utils.ndfunction.utils import _cartesian_product
+from ..._utils.ndfunction.utils import cartesian_product
 from ...representation import FData, FDataBasis, FDataGrid
 from ...representation.basis import (
     Basis,
@@ -121,7 +121,7 @@ def _get_valid_points(
 ) -> NDArrayFloat:
     """Return the valid points as integer tuples."""
     interval_points = np.arange(n_intervals + 1)
-    full_grid_points = _cartesian_product((interval_points, interval_points))
+    full_grid_points = cartesian_product((interval_points, interval_points))
 
     past_points = full_grid_points[
         full_grid_points[:, 0] <= full_grid_points[:, 1]
@@ -154,7 +154,7 @@ def _get_triangles(
 
     interval_without_end = np.arange(n_intervals)
 
-    pts_coords = _cartesian_product(
+    pts_coords = cartesian_product(
         (interval_without_end, interval_without_end),
     )
 

diff --git a/skfda/preprocessing/smoothing/_basis.py b/skfda/preprocessing/smoothing/_basis.py
@@ -12,7 +12,7 @@
 from typing_extensions import Final
 
 from ..._utils import _to_grid_points
-from ..._utils.ndfunction.utils import _cartesian_product
+from ..._utils.ndfunction.utils import cartesian_product
 from ...misc.lstsq import LstsqMethod, solve_regularized_weighted_lstsq
 from ...misc.regularization import L2Regularization
 from ...representation import FData, FDataBasis, FDataGrid
@@ -234,7 +234,7 @@ def _coef_matrix(
         from ...misc.regularization import compute_penalty_matrix
 
         basis_values_input = self.basis(
-            _cartesian_product(_to_grid_points(input_points)),
+            cartesian_product(_to_grid_points(input_points)),
         ).reshape((self.basis.n_basis, -1)).T
 
         penalty_matrix = compute_penalty_matrix(
@@ -262,7 +262,7 @@ def _hat_matrix(
         output_points: GridPointsLike,
     ) -> NDArrayFloat:
         basis_values_output = self.basis(
-            _cartesian_product(
+            cartesian_product(
                 _to_grid_points(output_points),
             ),
         ).reshape((self.basis.n_basis, -1)).T

diff --git a/skfda/preprocessing/smoothing/_kernel_smoothers.py b/skfda/preprocessing/smoothing/_kernel_smoothers.py
@@ -10,7 +10,7 @@
 import numpy as np
 
 from ..._utils import _to_grid_points
-from ..._utils.ndfunction.utils import _cartesian_product
+from ..._utils.ndfunction.utils import cartesian_product
 from ...misc.hat_matrix import HatMatrix, NadarayaWatsonHatMatrix
 from ...misc.metrics import PairwiseMetric, l2_distance
 from ...typing._base import GridPointsLike
@@ -131,8 +131,8 @@ def _hat_matrix(
         output_points: GridPointsLike,
     ) -> NDArrayFloat:
 
-        input_points = _cartesian_product(_to_grid_points(input_points))
-        output_points = _cartesian_product(_to_grid_points(output_points))
+        input_points = cartesian_product(_to_grid_points(input_points))
+        output_points = cartesian_product(_to_grid_points(output_points))
 
         if self.kernel_estimator is None:
             self.kernel_estimator = NadarayaWatsonHatMatrix()