Merge branch 'main' into matrix_rank-doc-fix

1 files changed, 69 insertions, 0 deletions

diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py
index 4c7c0480c..a4f49a78b 100644
--- a/numpy/lib/tests/test_function_base.py
+++ b/numpy/lib/tests/test_function_base.py
@@ -1798,6 +1798,24 @@ class TestUnwrap:
         assert_array_equal(unwrap([1, 1 + 2 * np.pi]), [1, 1])
         # check that unwrap maintains continuity
         assert_(np.all(diff(unwrap(rand(10) * 100)) < np.pi))
+    
+    def test_period(self):
+        # check that unwrap removes jumps greater that 255
+        assert_array_equal(unwrap([1, 1 + 256], period=255), [1, 2])
+        # check that unwrap maintains continuity
+        assert_(np.all(diff(unwrap(rand(10) * 1000, period=255)) < 255))
+        # check simple case
+        simple_seq = np.array([0, 75, 150, 225, 300])
+        wrap_seq = np.mod(simple_seq, 255)
+        assert_array_equal(unwrap(wrap_seq, period=255), simple_seq)
+        # check custom discont value
+        uneven_seq = np.array([0, 75, 150, 225, 300, 430])
+        wrap_uneven = np.mod(uneven_seq, 250)
+        no_discont = unwrap(wrap_uneven, period=250)
+        assert_array_equal(no_discont, [0, 75, 150, 225, 300, 180])
+        sm_discont = unwrap(wrap_uneven, period=250, discont=140)
+        assert_array_equal(sm_discont, [0, 75, 150, 225, 300, 430])
+        assert sm_discont.dtype == wrap_uneven.dtype
 
 
 class TestFilterwindows:
@@ -2307,6 +2325,27 @@ class TestMeshgrid:
         assert_equal(x[0, :], 0)
         assert_equal(x[1, :], X)
 
+    def test_nd_shape(self):
+        a, b, c, d, e = np.meshgrid(*([0] * i for i in range(1, 6)))
+        expected_shape = (2, 1, 3, 4, 5)
+        assert_equal(a.shape, expected_shape)
+        assert_equal(b.shape, expected_shape)
+        assert_equal(c.shape, expected_shape)
+        assert_equal(d.shape, expected_shape)
+        assert_equal(e.shape, expected_shape)
+
+    def test_nd_values(self):
+        a, b, c = np.meshgrid([0], [1, 2], [3, 4, 5])
+        assert_equal(a, [[[0, 0, 0]], [[0, 0, 0]]])
+        assert_equal(b, [[[1, 1, 1]], [[2, 2, 2]]])
+        assert_equal(c, [[[3, 4, 5]], [[3, 4, 5]]])
+
+    def test_nd_indexing(self):
+        a, b, c = np.meshgrid([0], [1, 2], [3, 4, 5], indexing='ij')
+        assert_equal(a, [[[0, 0, 0], [0, 0, 0]]])
+        assert_equal(b, [[[1, 1, 1], [2, 2, 2]]])
+        assert_equal(c, [[[3, 4, 5], [3, 4, 5]]])
+
 
 class TestPiecewise:
 
@@ -2399,6 +2438,14 @@ class TestPiecewise:
         assert_array_equal(y, np.array([[-1., -1., -1.],
                                         [3., 3., 1.]]))
 
+    def test_subclasses(self):
+        class subclass(np.ndarray):
+            pass
+        x = np.arange(5.).view(subclass)
+        r = piecewise(x, [x<2., x>=4], [-1., 1., 0.])
+        assert_equal(type(r), subclass)
+        assert_equal(r, [-1., -1., 0., 0., 1.])
+
 
 class TestBincount:
 
@@ -2721,6 +2768,10 @@ class TestPercentile:
         assert_equal(p, Fraction(7, 4))
         assert_equal(type(p), Fraction)
 
+        p = np.percentile(x, [Fraction(50)])
+        assert_equal(p, np.array([Fraction(7, 4)]))
+        assert_equal(type(p), np.ndarray)
+
     def test_api(self):
         d = np.ones(5)
         np.percentile(d, 5, None, None, False)
@@ -3115,6 +3166,16 @@ class TestPercentile:
         assert_equal(np.percentile(
             a, [0.3, 0.6], (0, 2), interpolation='nearest'), b)
 
+    def test_nan_q(self):
+        # GH18830
+        with pytest.raises(ValueError, match="Percentiles must be in"):
+            np.percentile([1, 2, 3, 4.0], np.nan)
+        with pytest.raises(ValueError, match="Percentiles must be in"):
+            np.percentile([1, 2, 3, 4.0], [np.nan])
+        q = np.linspace(1.0, 99.0, 16)
+        q[0] = np.nan
+        with pytest.raises(ValueError, match="Percentiles must be in"):
+            np.percentile([1, 2, 3, 4.0], q)
 
 class TestQuantile:
     # most of this is already tested by TestPercentile
@@ -3151,6 +3212,14 @@ class TestQuantile:
         assert_equal(q, Fraction(7, 4))
         assert_equal(type(q), Fraction)
 
+        q = np.quantile(x, [Fraction(1, 2)])
+        assert_equal(q, np.array([Fraction(7, 4)]))
+        assert_equal(type(q), np.ndarray)
+
+        q = np.quantile(x, [[Fraction(1, 2)]])
+        assert_equal(q, np.array([[Fraction(7, 4)]]))
+        assert_equal(type(q), np.ndarray)
+
         # repeat with integral input but fractional quantile
         x = np.arange(8)
         assert_equal(np.quantile(x, Fraction(1, 2)), Fraction(7, 2))