diff options
Diffstat (limited to 'numpy/lib/tests/test_function_base.py')
| -rw-r--r-- | numpy/lib/tests/test_function_base.py | 11 |
1 files changed, 8 insertions, 3 deletions
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py index cd88c5634..5ccac62e4 100644 --- a/numpy/lib/tests/test_function_base.py +++ b/numpy/lib/tests/test_function_base.py @@ -3112,11 +3112,16 @@ class TestQuantile: # GH 14685 # test that the return value of quantile is monotonic if p0 is ordered p0 = np.arange(0, 1, 0.01) - quantile = np.quantile(np.array([0, 1, 1, 2, 2, 3, 3, 4, 5, 5, 1, 1, 9, 9, 9, 8, 8, 7]) * 0.1, p0) + quantile = np.quantile(np.array([0, 1, 1, 2, 2, 3, 3, 4, 5, 5, 1, 1, 9, 9, 9, + 8, 8, 7]) * 0.1, p0) assert_equal(np.sort(quantile), quantile) - @hypothesis.given(arr=arrays(dtype=np.float, shape=st.integers(min_value=3, max_value=1000), - elements=st.floats(allow_infinity=False, allow_nan=False))) + @hypothesis.given(arr=arrays(dtype=np.float, shape=st.integers(min_value=3, + max_value=1000), + elements=st.floats(allow_infinity=False, + allow_nan=False, + min_value=-1e300, + max_value=1e300))) def test_quantile_monotonic_hypo(self, arr): p0 = np.arange(0, 1, 0.01) quantile = np.quantile(arr, p0) |