Merge branch 'release/0.5.7'

dcor/VERSION

@@ -1 +1 @@
-0.5.6
+0.5.7

dcor/__init__.py

@@ -10,36 +10,39 @@
 import os as _os
 import pathlib as _pathlib
 
-from . import distances  # noqa
-from . import homogeneity  # noqa
-from . import independence  # noqa
-from ._dcor import (  # noqa
-    CompileMode,
-    DistanceCovarianceMethod,
-    distance_correlation,
-    distance_correlation_af_inv,
-    distance_correlation_af_inv_sqr,
-    distance_correlation_sqr,
-    distance_covariance,
-    distance_covariance_sqr,
-    distance_stats,
-    distance_stats_sqr,
-    u_distance_correlation_sqr,
-    u_distance_covariance_sqr,
-    u_distance_stats_sqr,
+from . import distances, homogeneity, independence
+from ._dcor import (
+    DistanceCovarianceMethod as DistanceCovarianceMethod,
+    distance_correlation as distance_correlation,
+    distance_correlation_af_inv as distance_correlation_af_inv,
+    distance_correlation_af_inv_sqr as distance_correlation_af_inv_sqr,
+    distance_correlation_sqr as distance_correlation_sqr,
+    distance_covariance as distance_covariance,
+    distance_covariance_sqr as distance_covariance_sqr,
+    distance_stats as distance_stats,
+    distance_stats_sqr as distance_stats_sqr,
+    u_distance_correlation_sqr as u_distance_correlation_sqr,
+    u_distance_covariance_sqr as u_distance_covariance_sqr,
+    u_distance_stats_sqr as u_distance_stats_sqr,
 )
-from ._dcor_internals import (  # noqa
-    double_centered,
-    mean_product,
-    u_centered,
-    u_complementary_projection,
-    u_product,
-    u_projection,
+from ._dcor_internals import (
+    double_centered as double_centered,
+    mean_product as mean_product,
+    u_centered as u_centered,
+    u_complementary_projection as u_complementary_projection,
+    u_product as u_product,
+    u_projection as u_projection,
 )
-from ._energy import EstimationStatistic, energy_distance  # noqa
-from ._partial_dcor import partial_distance_covariance  # noqa
-from ._partial_dcor import partial_distance_correlation
-from ._rowwise import RowwiseMode, rowwise
+from ._energy import (
+    EstimationStatistic as EstimationStatistic,
+    energy_distance as energy_distance,
+)
+from ._partial_dcor import (
+    partial_distance_correlation,
+    partial_distance_covariance as partial_distance_covariance,
+)
+from ._rowwise import RowwiseMode as RowwiseMode, rowwise as rowwise
+from ._utils import CompileMode as CompileMode
 
 try:
     __version__ = (

dcor/_dcor.py

@@ -288,7 +288,7 @@ def _distance_sqr_stats_naive_generic(
     # Comparisons using a tolerance can change results if the
     # covariance has a similar order of magnitude
     if denominator == 0.0:
-        correlation_xy_sqr = xp.asarray(0, dtype=covariance_xy_sqr.dtype)
+        correlation_xy_sqr = xp.zeros_like(covariance_xy_sqr)
     else:
         correlation_xy_sqr = covariance_xy_sqr / denominator
 
@@ -388,7 +388,7 @@ def _distance_stats_sqr_generic(
     # Comparisons using a tolerance can change results if the
     # covariance has a similar order of magnitude
     if denominator == 0.0:
-        correlation_xy_sqr = xp.asarray(0, dtype=covariance_xy_sqr.dtype)
+        correlation_xy_sqr = xp.zeros_like(covariance_xy_sqr)
     else:
         correlation_xy_sqr = covariance_xy_sqr / denominator
 
@@ -1120,7 +1120,7 @@ def distance_correlation_af_inv_sqr(
     xp = get_namespace(x, y)
 
     return (
-        xp.asarray(0, dtype=correlation.dtype)
+        xp.zeros_like(correlation)
         if xp.isnan(correlation)
         else correlation
     )

dcor/_rowwise.py

@@ -6,7 +6,7 @@
 
 from . import _dcor
 from ._fast_dcov_avl import _rowwise_distance_covariance_sqr_avl_generic
-from ._utils import _sqrt, RowwiseMode
+from ._utils import RowwiseMode as RowwiseMode, _sqrt
 
 
 def _generate_rowwise_distance_covariance_sqr(unbiased):

dcor/tests/test_dcor.py

@@ -498,6 +498,19 @@ def test_u_statistic(self) -> None:
         """Test that the fast and naive algorithms for unbiased dcor match."""
         self._test_fast_naive_generic(dcor.u_distance_correlation_sqr)
 
+    def test_dcor_constant(self) -> None:
+        """Test that it works with constant random variables."""
+        a = np.ones(100)
+
+        cov = dcor.distance_covariance(a, a)
+        self.assertAlmostEqual(cov, 0)
+
+        corr = dcor.distance_correlation(a, a)
+        self.assertAlmostEqual(corr, 0)
+
+        corr_af_inv = dcor.distance_correlation_af_inv(a, a)
+        self.assertAlmostEqual(corr_af_inv, 0)
+
 
 class TestDcorArrayAPI(unittest.TestCase):
     """Check that the energy distance works with the Array API standard."""
@@ -583,6 +596,22 @@ def test_distance_correlation(self) -> None:
             (1.0, 0.526640387, 1.0),
         )
 
+    def test_dcor_constant(self) -> None:
+        """Test that it works with constant random variables."""
+        a = np.array_api.ones(100)
+
+        cov = dcor.distance_covariance(a, a)
+        self.assertIsInstance(cov, type(self.a))
+        self.assertAlmostEqual(cov, 0)
+
+        corr = dcor.distance_correlation(a, a)
+        self.assertIsInstance(corr, type(self.a))
+        self.assertAlmostEqual(corr, 0)
+
+        corr_af_inv = dcor.distance_correlation_af_inv(a, a)
+        self.assertIsInstance(corr_af_inv, type(self.a))
+        self.assertAlmostEqual(corr_af_inv, 0)
+
 
 if __name__ == "__main__":
     unittest.main()  # pragma: no cover

setup.py

@@ -52,6 +52,7 @@
 ).read_text().strip()
 
 setup(
+    name="dcor",
     version=version,
     include_package_data=True,
     packages=find_packages(),