ENH: stats.kde.resample can use np.random.Generator

scipy/stats/kde.py

@@ -445,13 +445,15 @@ def resample(self, size=None, seed=None):
             The number of samples to draw.  If not provided, then the size is
             the same as the effective number of samples in the underlying
             dataset.
-        seed : None or int or `np.random.RandomState`, optional
-            If `seed` is None, random variates are drawn by the RandomState
-            singleton used by np.random.
-            If `seed` is an int, a new `np.random.RandomState` instance is used,
-            seeded with seed.
-            If `seed` is already a `np.random.RandomState instance`, then that
-            `np.random.RandomState` instance is used.
+        seed : {None, int, `~np.random.RandomState`, `~np.random.Generator`}, optional
+            This parameter defines the object to use for drawing random
+            variates.
+            If `seed` is `None` the `~np.random.RandomState` singleton is used.
+            If `seed` is an int, a new ``RandomState`` instance is used, seeded
+            with seed.
+            If `seed` is already a ``RandomState`` or ``Generator`` instance,
+            then that object is used.
+            Default is None.
             Specify `seed` for reproducible drawing of random variates.
 
         Returns

scipy/stats/tests/test_kdeoth.py

@@ -413,6 +413,15 @@ def test_seed_sub(gkde_trail):
         samp2 = gkde_trail.resample(n_sample, seed=rstate2)
         assert_allclose(samp1, samp2, atol=1e-13)
 
+        # check that np.random.Generator can be used (numpy >= 1.17)
+        try:
+            # obtain a np.random.Generator object
+            rng = np.random.default_rng(1234)
+            gkde_trail.resample(n_sample, seed=rng)
+        except AttributeError:
+            # only available in numpy >= 1.17
+            pass
+
     np.random.seed(8765678)
     n_basesample = 500
     wn = np.random.rand(n_basesample)