diff options
Diffstat (limited to 'numpy/lib/tests/test_arraypad.py')
| -rw-r--r-- | numpy/lib/tests/test_arraypad.py | 156 |
1 files changed, 108 insertions, 48 deletions
diff --git a/numpy/lib/tests/test_arraypad.py b/numpy/lib/tests/test_arraypad.py index b7393294a..d43c0d32e 100644 --- a/numpy/lib/tests/test_arraypad.py +++ b/numpy/lib/tests/test_arraypad.py @@ -2,6 +2,7 @@ """ from __future__ import division, absolute_import, print_function +from itertools import chain import pytest @@ -21,6 +22,7 @@ _all_modes = { 'reflect': {'reflect_type': 'even'}, 'symmetric': {'reflect_type': 'even'}, 'wrap': {}, + 'empty': {} } @@ -108,46 +110,25 @@ class TestAsPairs(object): class TestConditionalShortcuts(object): - def test_zero_padding_shortcuts(self): + @pytest.mark.parametrize("mode", _all_modes.keys()) + def test_zero_padding_shortcuts(self, mode): test = np.arange(120).reshape(4, 5, 6) - pad_amt = [(0, 0) for axis in test.shape] - modes = ['constant', - 'edge', - 'linear_ramp', - 'maximum', - 'mean', - 'median', - 'minimum', - 'reflect', - 'symmetric', - 'wrap', - ] - for mode in modes: - assert_array_equal(test, np.pad(test, pad_amt, mode=mode)) - - def test_shallow_statistic_range(self): + pad_amt = [(0, 0) for _ in test.shape] + assert_array_equal(test, np.pad(test, pad_amt, mode=mode)) + + @pytest.mark.parametrize("mode", ['maximum', 'mean', 'median', 'minimum',]) + def test_shallow_statistic_range(self, mode): test = np.arange(120).reshape(4, 5, 6) - pad_amt = [(1, 1) for axis in test.shape] - modes = ['maximum', - 'mean', - 'median', - 'minimum', - ] - for mode in modes: - assert_array_equal(np.pad(test, pad_amt, mode='edge'), - np.pad(test, pad_amt, mode=mode, stat_length=1)) - - def test_clip_statistic_range(self): + pad_amt = [(1, 1) for _ in test.shape] + assert_array_equal(np.pad(test, pad_amt, mode='edge'), + np.pad(test, pad_amt, mode=mode, stat_length=1)) + + @pytest.mark.parametrize("mode", ['maximum', 'mean', 'median', 'minimum',]) + def test_clip_statistic_range(self, mode): test = np.arange(30).reshape(5, 6) - pad_amt = [(3, 3) for axis in test.shape] - modes = ['maximum', - 'mean', - 'median', - 'minimum', - ] - for mode in modes: - assert_array_equal(np.pad(test, pad_amt, mode=mode), - np.pad(test, pad_amt, mode=mode, stat_length=30)) + pad_amt = [(3, 3) for _ in test.shape] + assert_array_equal(np.pad(test, pad_amt, mode=mode), + np.pad(test, pad_amt, mode=mode, stat_length=30)) class TestStatistic(object): @@ -444,7 +425,7 @@ class TestStatistic(object): assert_array_equal(a, b) @pytest.mark.parametrize("mode", [ - pytest.param("mean", marks=pytest.mark.xfail(reason="gh-11216")), + "mean", "median", "minimum", "maximum" @@ -662,6 +643,11 @@ class TestConstant(object): assert_array_equal(arr, expected) + def test_pad_empty_dimension(self): + arr = np.zeros((3, 0, 2)) + result = np.pad(arr, [(0,), (2,), (1,)], mode="constant") + assert result.shape == (3, 4, 4) + class TestLinearRamp(object): def test_check_simple(self): @@ -721,6 +707,14 @@ class TestLinearRamp(object): ]) assert_equal(actual, expected) + def test_end_values(self): + """Ensure that end values are exact.""" + a = np.pad(np.ones(10).reshape(2, 5), (223, 123), mode="linear_ramp") + assert_equal(a[:, 0], 0.) + assert_equal(a[:, -1], 0.) + assert_equal(a[0, :], 0.) + assert_equal(a[-1, :], 0.) + class TestReflect(object): def test_check_simple(self): @@ -831,19 +825,29 @@ class TestReflect(object): b = np.array([1, 2, 3, 2, 1, 2, 3, 2, 1, 2, 3]) assert_array_equal(a, b) - def test_check_padding_an_empty_array(self): - a = np.pad(np.zeros((0, 3)), ((0,), (1,)), mode='reflect') - b = np.zeros((0, 5)) - assert_array_equal(a, b) - def test_padding_empty_dimension(self): - match = "There aren't any elements to reflect in axis 0" +class TestEmptyArray(object): + """Check how padding behaves on arrays with an empty dimension.""" + + @pytest.mark.parametrize( + # Keep parametrization ordered, otherwise pytest-xdist might believe + # that different tests were collected during parallelization + "mode", sorted(_all_modes.keys() - {"constant", "empty"}) + ) + def test_pad_empty_dimension(self, mode): + match = ("can't extend empty axis 0 using modes other than 'constant' " + "or 'empty'") with pytest.raises(ValueError, match=match): - np.pad([], 4, mode='reflect') + np.pad([], 4, mode=mode) with pytest.raises(ValueError, match=match): - np.pad(np.ndarray(0), 4, mode='reflect') + np.pad(np.ndarray(0), 4, mode=mode) with pytest.raises(ValueError, match=match): - np.pad(np.zeros((0, 3)), ((1,), (0,)), mode='reflect') + np.pad(np.zeros((0, 3)), ((1,), (0,)), mode=mode) + + @pytest.mark.parametrize("mode", _all_modes.keys()) + def test_pad_non_empty_dimension(self, mode): + result = np.pad(np.ones((2, 0, 2)), ((3,), (0,), (1,)), mode=mode) + assert result.shape == (8, 0, 4) class TestSymmetric(object): @@ -1080,6 +1084,19 @@ class TestWrap(object): b = np.pad(a, (0, 5), mode="wrap") assert_array_equal(a, b[:-5, :-5]) + def test_repeated_wrapping(self): + """ + Check wrapping on each side individually if the wrapped area is longer + than the original array. + """ + a = np.arange(5) + b = np.pad(a, (12, 0), mode="wrap") + assert_array_equal(np.r_[a, a, a, a][3:], b) + + a = np.arange(5) + b = np.pad(a, (0, 12), mode="wrap") + assert_array_equal(np.r_[a, a, a, a][:-3], b) + class TestEdge(object): def test_check_simple(self): @@ -1120,6 +1137,19 @@ class TestEdge(object): assert_array_equal(padded, expected) +class TestEmpty(object): + def test_simple(self): + arr = np.arange(24).reshape(4, 6) + result = np.pad(arr, [(2, 3), (3, 1)], mode="empty") + assert result.shape == (9, 10) + assert_equal(arr, result[2:-3, 3:-1]) + + def test_pad_empty_dimension(self): + arr = np.zeros((3, 0, 2)) + result = np.pad(arr, [(0,), (2,), (1,)], mode="empty") + assert result.shape == (3, 4, 4) + + def test_legacy_vector_functionality(): def _padwithtens(vector, pad_width, iaxis, kwargs): vector[:pad_width[0]] = 10 @@ -1244,7 +1274,7 @@ def test_kwargs(mode): np.pad([1, 2, 3], 1, mode, **allowed) # Test if prohibited keyword arguments of other modes raise an error for key, value in not_allowed.items(): - match = 'keyword not in allowed keywords' + match = "unsupported keyword arguments for mode '{}'".format(mode) with pytest.raises(ValueError, match=match): np.pad([1, 2, 3], 1, mode, **{key: value}) @@ -1254,9 +1284,39 @@ def test_constant_zero_default(): assert_array_equal(np.pad(arr, 2), [0, 0, 1, 1, 0, 0]) +@pytest.mark.parametrize("mode", [1, "const", object(), None, True, False]) +def test_unsupported_mode(mode): + match= "mode '{}' is not supported".format(mode) + with pytest.raises(ValueError, match=match): + np.pad([1, 2, 3], 4, mode=mode) + + @pytest.mark.parametrize("mode", _all_modes.keys()) def test_non_contiguous_array(mode): arr = np.arange(24).reshape(4, 6)[::2, ::2] result = np.pad(arr, (2, 3), mode) assert result.shape == (7, 8) assert_equal(result[2:-3, 2:-3], arr) + + +@pytest.mark.parametrize("mode", _all_modes.keys()) +def test_memory_layout_persistence(mode): + """Test if C and F order is preserved for all pad modes.""" + x = np.ones((5, 10), order='C') + assert np.pad(x, 5, mode).flags["C_CONTIGUOUS"] + x = np.ones((5, 10), order='F') + assert np.pad(x, 5, mode).flags["F_CONTIGUOUS"] + + +@pytest.mark.parametrize("dtype", chain( + # Skip "other" dtypes as they are not supported by all modes + np.sctypes["int"], + np.sctypes["uint"], + np.sctypes["float"], + np.sctypes["complex"] +)) +@pytest.mark.parametrize("mode", _all_modes.keys()) +def test_dtype_persistence(dtype, mode): + arr = np.zeros((3, 2, 1), dtype=dtype) + result = np.pad(arr, 1, mode=mode) + assert result.dtype == dtype |