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-rw-r--r--numpy/lib/arraypad.py9
-rw-r--r--numpy/lib/tests/test_arraypad.py23
2 files changed, 31 insertions, 1 deletions
diff --git a/numpy/lib/arraypad.py b/numpy/lib/arraypad.py
index f08d425d6..62330e692 100644
--- a/numpy/lib/arraypad.py
+++ b/numpy/lib/arraypad.py
@@ -323,6 +323,12 @@ def _get_stats(padded, axis, width_pair, length_pair, stat_func):
if right_length is None or max_length < right_length:
right_length = max_length
+ if (left_length == 0 or right_length == 0) \
+ and stat_func in {np.amax, np.amin}:
+ # amax and amin can't operate on an emtpy array,
+ # raise a more descriptive warning here instead of the default one
+ raise ValueError("stat_length of 0 yields no value for padding")
+
# Calculate statistic for the left side
left_slice = _slice_at_axis(
slice(left_index, left_index + left_length), axis)
@@ -340,6 +346,7 @@ def _get_stats(padded, axis, width_pair, length_pair, stat_func):
right_chunk = padded[right_slice]
right_stat = stat_func(right_chunk, axis=axis, keepdims=True)
_round_if_needed(right_stat, padded.dtype)
+
return left_stat, right_stat
@@ -835,7 +842,7 @@ def pad(array, pad_width, mode='constant', **kwargs):
raise ValueError("unsupported keyword arguments for mode '{}': {}"
.format(mode, unsupported_kwargs))
- stat_functions = {"maximum": np.max, "minimum": np.min,
+ stat_functions = {"maximum": np.amax, "minimum": np.amin,
"mean": np.mean, "median": np.median}
# Create array with final shape and original values
diff --git a/numpy/lib/tests/test_arraypad.py b/numpy/lib/tests/test_arraypad.py
index b7630cdcd..b6dd3b31c 100644
--- a/numpy/lib/tests/test_arraypad.py
+++ b/numpy/lib/tests/test_arraypad.py
@@ -469,6 +469,29 @@ class TestStatistic(object):
)
assert_array_equal(a, b)
+ @pytest.mark.filterwarnings("ignore:Mean of empty slice:RuntimeWarning")
+ @pytest.mark.filterwarnings(
+ "ignore:invalid value encountered in (true_divide|double_scalars):"
+ "RuntimeWarning"
+ )
+ @pytest.mark.parametrize("mode", ["mean", "median"])
+ def test_zero_stat_length_valid(self, mode):
+ arr = np.pad([1., 2.], (1, 2), mode, stat_length=0)
+ expected = np.array([np.nan, 1., 2., np.nan, np.nan])
+ assert_equal(arr, expected)
+
+ @pytest.mark.parametrize("mode", ["minimum", "maximum"])
+ def test_zero_stat_length_invalid(self, mode):
+ match = "stat_length of 0 yields no value for padding"
+ with pytest.raises(ValueError, match=match):
+ np.pad([1., 2.], 0, mode, stat_length=0)
+ with pytest.raises(ValueError, match=match):
+ np.pad([1., 2.], 0, mode, stat_length=(1, 0))
+ with pytest.raises(ValueError, match=match):
+ np.pad([1., 2.], 1, mode, stat_length=0)
+ with pytest.raises(ValueError, match=match):
+ np.pad([1., 2.], 1, mode, stat_length=(1, 0))
+
class TestConstant(object):
def test_check_constant(self):