add some skips [skip ci]

Author: lucascolley

scipy/ndimage/_support_alternative_backends.py

@@ -46,7 +46,7 @@ def wrapper(*args, **kwds):
                 # XXX: output arrays
                 result = func(*args, **kwds)
 
-                if isinstance(result, (np.ndarray, np.generic)):
+                if isinstance(result, np.ndarray | np.generic):
                     # XXX: np.int32->np.array_0D
                     return xp.asarray(result)
                 elif isinstance(result, int):

scipy/ndimage/tests/test_measurements.py

@@ -23,6 +23,7 @@
 
 from scipy.conftest import array_api_compatible
 skip_xp_backends = pytest.mark.skip_xp_backends
+xfail_xp_backends = pytest.mark.xfail_xp_backends
 pytestmark = [array_api_compatible, pytest.mark.usefixtures("skip_xp_backends"),
               skip_xp_backends(cpu_only=True, exceptions=['cupy', 'jax.numpy'],)]
 
@@ -365,10 +366,9 @@ def test_label_output_dtype(xp):
         assert output.dtype == t
 
 
+@xfail_xp_backends('dask.array', reason='Dask does not raise')
+@xfail_xp_backends('jax.numpy', reason='JAX does not raise')
 def test_label_output_wrong_size(xp):
-    if is_jax(xp):
-        pytest.xfail("JAX does not raise")
-
     data = xp.ones([5])
     for t in types:
         dtype = getattr(xp, t)
@@ -569,7 +569,7 @@ def test_value_indices03(xp):
         assert list(vi.keys()) == list(trueKeys)
         for k in [int(x) for x in trueKeys]:
             trueNdx = xp.nonzero(a == k, **nnz_kwd)
-            assert len(vi[k]) == len(trueNdx)
+            assert vi[k].shape[0] == trueNdx.shape[0]
             for vik, true_vik in zip(vi[k], trueNdx):
                 xp_assert_equal(vik, true_vik)
 
@@ -772,6 +772,7 @@ def test_minimum03(xp):
         assert_almost_equal(output, xp.asarray(2.0), check_0d=False)
 
 
+@skip_xp_backends('dask.array', reason="no argsort in Dask")
 def test_minimum04(xp):
     labels = xp.asarray([[1, 2], [2, 3]])
     for type in types:
@@ -811,6 +812,7 @@ def test_maximum03(xp):
         assert_almost_equal(output, xp.asarray(4.0), check_0d=False)
 
 
+@skip_xp_backends('dask.array', reason="no argsort in Dask")
 def test_maximum04(xp):
     labels = xp.asarray([[1, 2], [2, 3]])
     for type in types:
@@ -1059,6 +1061,7 @@ def test_minimum_position06(xp):
         assert output == (0, 1)
 
 
+@skip_xp_backends('dask.array', reason="no argsort in Dask")
 def test_minimum_position07(xp):
     labels = xp.asarray([1, 2, 3, 4])
     for type in types:
@@ -1124,6 +1127,7 @@ def test_maximum_position05(xp):
         assert output == (0, 0)
 
 
+@skip_xp_backends('dask.array', reason="no argsort in Dask")
 def test_maximum_position06(xp):
     labels = xp.asarray([1, 2, 0, 4])
     for type in types:
@@ -1188,6 +1192,7 @@ def test_extrema02(xp):
         assert output1 == (output2, output3, output4, output5)
 
 
+@skip_xp_backends('dask.array', reason="no argsort in Dask")
 def test_extrema03(xp):
     labels = xp.asarray([[1, 2], [2, 3]])
     for type in types:
@@ -1216,6 +1221,7 @@ def test_extrema03(xp):
         assert output1[3] == output5
 
 
+@skip_xp_backends('dask.array', reason="no argsort in Dask")
 def test_extrema04(xp):
     labels = xp.asarray([1, 2, 0, 4])
     for type in types:
@@ -1589,7 +1595,8 @@ def test_watershed_ift08(self, xp):
     @skip_xp_backends("cupy", reason="no watershed_ift on CuPy"	)
     def test_watershed_ift09(self, xp):
         # Test large cost. See gh-19575
-        data = xp.asarray([[xp.iinfo(xp.uint16).max, 0],
+        xp_test = array_namespace(xp.empty(0))  # dask.array needs iinfo
+        data = xp.asarray([[xp_test.iinfo(xp.uint16).max, 0],
                            [0, 0]], dtype=xp.uint16)
         markers = xp.asarray([[1, 0],
                               [0, 0]], dtype=xp.int8)

scipy/optimize/tests/test_chandrupatla.py

@@ -187,6 +187,7 @@ def _bracket_minimum(func, x1, x2):
 
 @array_api_compatible
 @pytest.mark.usefixtures("skip_xp_backends")
+@pytest.mark.skip_xp_backends('dask.array', reason='no argsort in Dask')
 @pytest.mark.skip_xp_backends('jax.numpy',
                               reason='JAX arrays do not support item assignment.')
 @pytest.mark.skip_xp_backends('array_api_strict',
@@ -553,6 +554,7 @@ def f(x):
 
 @array_api_compatible
 @pytest.mark.usefixtures("skip_xp_backends")
+@pytest.mark.skip_xp_backends('dask.array', reason='boolean indexing assignment')
 @pytest.mark.skip_xp_backends('array_api_strict',
                               reason='Currently uses fancy indexing assignment.')
 @pytest.mark.skip_xp_backends('jax.numpy',