from distutils.version import LooseVersion import numpy as np import pytest # note: skimage.util.pad is just numpy.pad from skimage.util import pad from skimage._shared import testing from skimage._shared.testing import (assert_array_equal, assert_allclose, TestCase) def test_deprecation(): with pytest.warns(FutureWarning): pad(np.ones((5, 5)), 2, mode='constant') class TestConditionalShortcuts(TestCase): def test_zero_padding_shortcuts(self): 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): 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): 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)) class TestStatistic(TestCase): def test_check_mean_stat_length(self): a = np.arange(100).astype('f') a = np.pad(a, ((25, 20), ), 'mean', stat_length=((2, 3), )) b = np.array( [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28., 29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41., 42., 43., 44., 45., 46., 47., 48., 49., 50., 51., 52., 53., 54., 55., 56., 57., 58., 59., 60., 61., 62., 63., 64., 65., 66., 67., 68., 69., 70., 71., 72., 73., 74., 75., 76., 77., 78., 79., 80., 81., 82., 83., 84., 85., 86., 87., 88., 89., 90., 91., 92., 93., 94., 95., 96., 97., 98., 99., 98., 98., 98., 98., 98., 98., 98., 98., 98., 98., 98., 98., 98., 98., 98., 98., 98., 98., 98., 98. ]) assert_array_equal(a, b) def test_check_maximum_1(self): a = np.arange(100) a = np.pad(a, (25, 20), 'maximum') b = np.array( [99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99] ) assert_array_equal(a, b) def test_check_maximum_2(self): a = np.arange(100) + 1 a = np.pad(a, (25, 20), 'maximum') b = np.array( [100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100] ) assert_array_equal(a, b) def test_check_maximum_stat_length(self): a = np.arange(100) + 1 a = np.pad(a, (25, 20), 'maximum', stat_length=10) b = np.array( [10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100] ) assert_array_equal(a, b) def test_check_minimum_1(self): a = np.arange(100) a = np.pad(a, (25, 20), 'minimum') b = np.array( [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] ) assert_array_equal(a, b) def test_check_minimum_2(self): a = np.arange(100) + 2 a = np.pad(a, (25, 20), 'minimum') b = np.array( [2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2] ) assert_array_equal(a, b) def test_check_minimum_stat_length(self): a = np.arange(100) + 1 a = np.pad(a, (25, 20), 'minimum', stat_length=10) b = np.array( [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91] ) assert_array_equal(a, b) def test_check_median(self): a = np.arange(100).astype('f') a = np.pad(a, (25, 20), 'median') b = np.array( [49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28., 29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41., 42., 43., 44., 45., 46., 47., 48., 49., 50., 51., 52., 53., 54., 55., 56., 57., 58., 59., 60., 61., 62., 63., 64., 65., 66., 67., 68., 69., 70., 71., 72., 73., 74., 75., 76., 77., 78., 79., 80., 81., 82., 83., 84., 85., 86., 87., 88., 89., 90., 91., 92., 93., 94., 95., 96., 97., 98., 99., 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5] ) assert_array_equal(a, b) def test_check_median_01(self): a = np.array([[3, 1, 4], [4, 5, 9], [9, 8, 2]]) a = np.pad(a, 1, 'median') b = np.array( [[4, 4, 5, 4, 4], [3, 3, 1, 4, 3], [5, 4, 5, 9, 5], [8, 9, 8, 2, 8], [4, 4, 5, 4, 4]] ) assert_array_equal(a, b) def test_check_median_02(self): a = np.array([[3, 1, 4], [4, 5, 9], [9, 8, 2]]) a = np.pad(a.T, 1, 'median').T b = np.array( [[5, 4, 5, 4, 5], [3, 3, 1, 4, 3], [5, 4, 5, 9, 5], [8, 9, 8, 2, 8], [5, 4, 5, 4, 5]] ) assert_array_equal(a, b) def test_check_median_stat_length(self): a = np.arange(100).astype('f') a[1] = 2. a[97] = 96. a = np.pad(a, (25, 20), 'median', stat_length=(3, 5)) b = np.array( [ 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 0., 2., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28., 29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41., 42., 43., 44., 45., 46., 47., 48., 49., 50., 51., 52., 53., 54., 55., 56., 57., 58., 59., 60., 61., 62., 63., 64., 65., 66., 67., 68., 69., 70., 71., 72., 73., 74., 75., 76., 77., 78., 79., 80., 81., 82., 83., 84., 85., 86., 87., 88., 89., 90., 91., 92., 93., 94., 95., 96., 96., 98., 99., 96., 96., 96., 96., 96., 96., 96., 96., 96., 96., 96., 96., 96., 96., 96., 96., 96., 96., 96., 96.] ) assert_array_equal(a, b) def test_check_mean_shape_one(self): a = [[4, 5, 6]] a = np.pad(a, (5, 7), 'mean', stat_length=2) b = np.array( [[4, 4, 4, 4, 4, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6], [4, 4, 4, 4, 4, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6], [4, 4, 4, 4, 4, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6], [4, 4, 4, 4, 4, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6], [4, 4, 4, 4, 4, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6], [4, 4, 4, 4, 4, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6], [4, 4, 4, 4, 4, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6], [4, 4, 4, 4, 4, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6], [4, 4, 4, 4, 4, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6], [4, 4, 4, 4, 4, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6], [4, 4, 4, 4, 4, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6], [4, 4, 4, 4, 4, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6], [4, 4, 4, 4, 4, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6]] ) assert_array_equal(a, b) def test_check_mean_2(self): a = np.arange(100).astype('f') a = np.pad(a, (25, 20), 'mean') b = np.array( [49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28., 29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41., 42., 43., 44., 45., 46., 47., 48., 49., 50., 51., 52., 53., 54., 55., 56., 57., 58., 59., 60., 61., 62., 63., 64., 65., 66., 67., 68., 69., 70., 71., 72., 73., 74., 75., 76., 77., 78., 79., 80., 81., 82., 83., 84., 85., 86., 87., 88., 89., 90., 91., 92., 93., 94., 95., 96., 97., 98., 99., 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5] ) assert_array_equal(a, b) class TestConstant(TestCase): def test_check_constant(self): a = np.arange(100) a = np.pad(a, (25, 20), 'constant', constant_values=(10, 20)) b = np.array( [10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20] ) assert_array_equal(a, b) def test_check_constant_zeros(self): a = np.arange(100) a = np.pad(a, (25, 20), 'constant') b = np.array( [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] ) assert_array_equal(a, b) def test_check_constant_float(self): # If input array is int, but constant_values are float, the dtype of # the array to be padded is kept arr = np.arange(30).reshape(5, 6) test = np.pad(arr, (1, 2), mode='constant', constant_values=1.1) expected = np.array( [[ 1, 1, 1, 1, 1, 1, 1, 1, 1], [ 1, 0, 1, 2, 3, 4, 5, 1, 1], [ 1, 6, 7, 8, 9, 10, 11, 1, 1], [ 1, 12, 13, 14, 15, 16, 17, 1, 1], [ 1, 18, 19, 20, 21, 22, 23, 1, 1], [ 1, 24, 25, 26, 27, 28, 29, 1, 1], [ 1, 1, 1, 1, 1, 1, 1, 1, 1], [ 1, 1, 1, 1, 1, 1, 1, 1, 1]] ) assert_allclose(test, expected) def test_check_constant_float2(self): # If input array is float, and constant_values are float, the dtype of # the array to be padded is kept - here retaining the float constants arr = np.arange(30).reshape(5, 6) arr_float = arr.astype(np.float64) test = np.pad(arr_float, ((1, 2), (1, 2)), mode='constant', constant_values=1.1) expected = np.array( [[ 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1], [ 1.1, 0. , 1. , 2. , 3. , 4. , 5. , 1.1, 1.1], [ 1.1, 6. , 7. , 8. , 9. , 10. , 11. , 1.1, 1.1], [ 1.1, 12. , 13. , 14. , 15. , 16. , 17. , 1.1, 1.1], [ 1.1, 18. , 19. , 20. , 21. , 22. , 23. , 1.1, 1.1], [ 1.1, 24. , 25. , 26. , 27. , 28. , 29. , 1.1, 1.1], [ 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1], [ 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1]] ) assert_allclose(test, expected) def test_check_constant_float3(self): a = np.arange(100, dtype=float) a = np.pad(a, (25, 20), 'constant', constant_values=(-1.1, -1.2)) b = np.array( [-1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, -1.1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2, -1.2] ) assert_allclose(a, b) def test_check_constant_odd_pad_amount(self): arr = np.arange(30).reshape(5, 6) test = np.pad(arr, ((1,), (2,)), mode='constant', constant_values=3) expected = np.array( [[ 3, 3, 3, 3, 3, 3, 3, 3, 3, 3], [ 3, 3, 0, 1, 2, 3, 4, 5, 3, 3], [ 3, 3, 6, 7, 8, 9, 10, 11, 3, 3], [ 3, 3, 12, 13, 14, 15, 16, 17, 3, 3], [ 3, 3, 18, 19, 20, 21, 22, 23, 3, 3], [ 3, 3, 24, 25, 26, 27, 28, 29, 3, 3], [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 3]] ) assert_allclose(test, expected) class TestLinearRamp(TestCase): def test_check_simple(self): a = np.arange(100).astype('f') a = np.pad(a, (25, 20), 'linear_ramp', end_values=(4, 5)) b = np.array( [4.00, 3.84, 3.68, 3.52, 3.36, 3.20, 3.04, 2.88, 2.72, 2.56, 2.40, 2.24, 2.08, 1.92, 1.76, 1.60, 1.44, 1.28, 1.12, 0.96, 0.80, 0.64, 0.48, 0.32, 0.16, 0.00, 1.00, 2.00, 3.00, 4.00, 5.00, 6.00, 7.00, 8.00, 9.00, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0, 40.0, 41.0, 42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 48.0, 49.0, 50.0, 51.0, 52.0, 53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0, 64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0, 72.0, 73.0, 74.0, 75.0, 76.0, 77.0, 78.0, 79.0, 80.0, 81.0, 82.0, 83.0, 84.0, 85.0, 86.0, 87.0, 88.0, 89.0, 90.0, 91.0, 92.0, 93.0, 94.0, 95.0, 96.0, 97.0, 98.0, 99.0, 94.3, 89.6, 84.9, 80.2, 75.5, 70.8, 66.1, 61.4, 56.7, 52.0, 47.3, 42.6, 37.9, 33.2, 28.5, 23.8, 19.1, 14.4, 9.7, 5.] ) assert_allclose(a, b, rtol=1e-5, atol=1e-5) def test_check_2d(self): arr = np.arange(20).reshape(4, 5).astype(np.float64) test = np.pad(arr, (2, 2), mode='linear_ramp', end_values=(0, 0)) expected = np.array( [[0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0.5, 1., 1.5, 2., 1., 0.], [0., 0., 0., 1., 2., 3., 4., 2., 0.], [0., 2.5, 5., 6., 7., 8., 9., 4.5, 0.], [0., 5., 10., 11., 12., 13., 14., 7., 0.], [0., 7.5, 15., 16., 17., 18., 19., 9.5, 0.], [0., 3.75, 7.5, 8., 8.5, 9., 9.5, 4.75, 0.], [0., 0., 0., 0., 0., 0., 0., 0., 0.]]) assert_allclose(test, expected) class TestReflect(TestCase): def test_check_simple(self): a = np.arange(100) a = np.pad(a, (25, 20), 'reflect') b = np.array( [25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 98, 97, 96, 95, 94, 93, 92, 91, 90, 89, 88, 87, 86, 85, 84, 83, 82, 81, 80, 79] ) assert_array_equal(a, b) def test_check_odd_method(self): a = np.arange(100) a = np.pad(a, (25, 20), 'reflect', reflect_type='odd') b = np.array( [-25, -24, -23, -22, -21, -20, -19, -18, -17, -16, -15, -14, -13, -12, -11, -10, -9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119] ) assert_array_equal(a, b) def test_check_large_pad(self): a = [[4, 5, 6], [6, 7, 8]] a = np.pad(a, (5, 7), 'reflect') b = np.array( [[7, 6, 7, 8, 7, 6, 7, 8, 7, 6, 7, 8, 7, 6, 7], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [7, 6, 7, 8, 7, 6, 7, 8, 7, 6, 7, 8, 7, 6, 7], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [7, 6, 7, 8, 7, 6, 7, 8, 7, 6, 7, 8, 7, 6, 7], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [7, 6, 7, 8, 7, 6, 7, 8, 7, 6, 7, 8, 7, 6, 7], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [7, 6, 7, 8, 7, 6, 7, 8, 7, 6, 7, 8, 7, 6, 7], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [7, 6, 7, 8, 7, 6, 7, 8, 7, 6, 7, 8, 7, 6, 7], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [7, 6, 7, 8, 7, 6, 7, 8, 7, 6, 7, 8, 7, 6, 7], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5]] ) assert_array_equal(a, b) def test_check_shape(self): a = [[4, 5, 6]] a = np.pad(a, (5, 7), 'reflect') b = np.array( [[5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5], [5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5, 6, 5, 4, 5]] ) assert_array_equal(a, b) def test_check_01(self): a = np.pad([1, 2, 3], 2, 'reflect') b = np.array([3, 2, 1, 2, 3, 2, 1]) assert_array_equal(a, b) def test_check_02(self): a = np.pad([1, 2, 3], 3, 'reflect') b = np.array([2, 3, 2, 1, 2, 3, 2, 1, 2]) assert_array_equal(a, b) def test_check_03(self): a = np.pad([1, 2, 3], 4, 'reflect') b = np.array([1, 2, 3, 2, 1, 2, 3, 2, 1, 2, 3]) assert_array_equal(a, b) class TestSymmetric(TestCase): def test_check_simple(self): a = np.arange(100) a = np.pad(a, (25, 20), 'symmetric') b = np.array( [24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 99, 98, 97, 96, 95, 94, 93, 92, 91, 90, 89, 88, 87, 86, 85, 84, 83, 82, 81, 80] ) assert_array_equal(a, b) def test_check_odd_method(self): a = np.arange(100) a = np.pad(a, (25, 20), 'symmetric', reflect_type='odd') b = np.array( [-24, -23, -22, -21, -20, -19, -18, -17, -16, -15, -14, -13, -12, -11, -10, -9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118] ) assert_array_equal(a, b) def test_check_large_pad(self): a = [[4, 5, 6], [6, 7, 8]] a = np.pad(a, (5, 7), 'symmetric') b = np.array( [[5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [7, 8, 8, 7, 6, 6, 7, 8, 8, 7, 6, 6, 7, 8, 8], [7, 8, 8, 7, 6, 6, 7, 8, 8, 7, 6, 6, 7, 8, 8], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [7, 8, 8, 7, 6, 6, 7, 8, 8, 7, 6, 6, 7, 8, 8], [7, 8, 8, 7, 6, 6, 7, 8, 8, 7, 6, 6, 7, 8, 8], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [7, 8, 8, 7, 6, 6, 7, 8, 8, 7, 6, 6, 7, 8, 8], [7, 8, 8, 7, 6, 6, 7, 8, 8, 7, 6, 6, 7, 8, 8], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6]] ) assert_array_equal(a, b) def test_check_large_pad_odd(self): a = [[4, 5, 6], [6, 7, 8]] a = np.pad(a, (5, 7), 'symmetric', reflect_type='odd') b = np.array( [[-3, -2, -2, -1, 0, 0, 1, 2, 2, 3, 4, 4, 5, 6, 6], [-3, -2, -2, -1, 0, 0, 1, 2, 2, 3, 4, 4, 5, 6, 6], [-1, 0, 0, 1, 2, 2, 3, 4, 4, 5, 6, 6, 7, 8, 8], [-1, 0, 0, 1, 2, 2, 3, 4, 4, 5, 6, 6, 7, 8, 8], [ 1, 2, 2, 3, 4, 4, 5, 6, 6, 7, 8, 8, 9, 10, 10], [ 1, 2, 2, 3, 4, 4, 5, 6, 6, 7, 8, 8, 9, 10, 10], [ 3, 4, 4, 5, 6, 6, 7, 8, 8, 9, 10, 10, 11, 12, 12], [ 3, 4, 4, 5, 6, 6, 7, 8, 8, 9, 10, 10, 11, 12, 12], [ 5, 6, 6, 7, 8, 8, 9, 10, 10, 11, 12, 12, 13, 14, 14], [ 5, 6, 6, 7, 8, 8, 9, 10, 10, 11, 12, 12, 13, 14, 14], [ 7, 8, 8, 9, 10, 10, 11, 12, 12, 13, 14, 14, 15, 16, 16], [ 7, 8, 8, 9, 10, 10, 11, 12, 12, 13, 14, 14, 15, 16, 16], [ 9, 10, 10, 11, 12, 12, 13, 14, 14, 15, 16, 16, 17, 18, 18], [ 9, 10, 10, 11, 12, 12, 13, 14, 14, 15, 16, 16, 17, 18, 18]] ) assert_array_equal(a, b) def test_check_shape(self): a = [[4, 5, 6]] a = np.pad(a, (5, 7), 'symmetric') b = np.array( [[5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6], [5, 6, 6, 5, 4, 4, 5, 6, 6, 5, 4, 4, 5, 6, 6]] ) assert_array_equal(a, b) def test_check_01(self): a = np.pad([1, 2, 3], 2, 'symmetric') b = np.array([2, 1, 1, 2, 3, 3, 2]) assert_array_equal(a, b) def test_check_02(self): a = np.pad([1, 2, 3], 3, 'symmetric') b = np.array([3, 2, 1, 1, 2, 3, 3, 2, 1]) assert_array_equal(a, b) def test_check_03(self): a = np.pad([1, 2, 3], 6, 'symmetric') b = np.array([1, 2, 3, 3, 2, 1, 1, 2, 3, 3, 2, 1, 1, 2, 3]) assert_array_equal(a, b) class TestWrap(TestCase): def test_check_simple(self): a = np.arange(100) a = np.pad(a, (25, 20), 'wrap') b = np.array( [75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19] ) assert_array_equal(a, b) def test_check_large_pad(self): a = np.arange(12) a = np.reshape(a, (3, 4)) a = np.pad(a, (10, 12), 'wrap') b = np.array( [[10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11], [2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3], [6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7], [10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11], [2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3], [6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7], [10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11], [2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3], [6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7], [10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11], [2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3], [6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7], [10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11], [2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3], [6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7], [10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11], [2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3], [6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7], [10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11], [2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3], [6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7], [10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11], [2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3], [6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7, 4, 5, 6, 7], [10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11, 8, 9, 10, 11]] ) assert_array_equal(a, b) def test_check_01(self): a = np.pad([1, 2, 3], 3, 'wrap') b = np.array([1, 2, 3, 1, 2, 3, 1, 2, 3]) assert_array_equal(a, b) def test_check_02(self): a = np.pad([1, 2, 3], 4, 'wrap') b = np.array([3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1]) assert_array_equal(a, b) class TestStatLen(TestCase): def test_check_simple(self): a = np.arange(30) a = np.reshape(a, (6, 5)) a = np.pad(a, ((2, 3), (3, 2)), mode='mean', stat_length=(3,)) b = np.array( [[6, 6, 6, 5, 6, 7, 8, 9, 8, 8], [6, 6, 6, 5, 6, 7, 8, 9, 8, 8], [1, 1, 1, 0, 1, 2, 3, 4, 3, 3], [6, 6, 6, 5, 6, 7, 8, 9, 8, 8], [11, 11, 11, 10, 11, 12, 13, 14, 13, 13], [16, 16, 16, 15, 16, 17, 18, 19, 18, 18], [21, 21, 21, 20, 21, 22, 23, 24, 23, 23], [26, 26, 26, 25, 26, 27, 28, 29, 28, 28], [21, 21, 21, 20, 21, 22, 23, 24, 23, 23], [21, 21, 21, 20, 21, 22, 23, 24, 23, 23], [21, 21, 21, 20, 21, 22, 23, 24, 23, 23]] ) assert_array_equal(a, b) class TestEdge(TestCase): def test_check_simple(self): a = np.arange(12) a = np.reshape(a, (4, 3)) a = np.pad(a, ((2, 3), (3, 2)), 'edge') b = np.array( [[0, 0, 0, 0, 1, 2, 2, 2], [0, 0, 0, 0, 1, 2, 2, 2], [0, 0, 0, 0, 1, 2, 2, 2], [3, 3, 3, 3, 4, 5, 5, 5], [6, 6, 6, 6, 7, 8, 8, 8], [9, 9, 9, 9, 10, 11, 11, 11], [9, 9, 9, 9, 10, 11, 11, 11], [9, 9, 9, 9, 10, 11, 11, 11], [9, 9, 9, 9, 10, 11, 11, 11]] ) assert_array_equal(a, b) class TestZeroPadWidth(TestCase): def test_zero_pad_width(self): arr = np.arange(30) arr = np.reshape(arr, (6, 5)) for pad_width in (0, (0, 0), ((0, 0), (0, 0))): assert_array_equal(arr, np.pad(arr, pad_width, mode='constant')) class TestLegacyVectorFunction(TestCase): def test_legacy_vector_functionality(self): def _padwithtens(vector, pad_width, iaxis, kwargs): vector[:pad_width[0]] = 10 vector[-pad_width[1]:] = 10 return vector a = np.arange(6).reshape(2, 3) a = np.pad(a, 2, _padwithtens) b = np.array( [[10, 10, 10, 10, 10, 10, 10], [10, 10, 10, 10, 10, 10, 10], [10, 10, 0, 1, 2, 10, 10], [10, 10, 3, 4, 5, 10, 10], [10, 10, 10, 10, 10, 10, 10], [10, 10, 10, 10, 10, 10, 10]] ) assert_array_equal(a, b) class TestNdarrayPadWidth(TestCase): def test_check_simple(self): a = np.arange(12) a = np.reshape(a, (4, 3)) a = np.pad(a, np.array(((2, 3), (3, 2))), 'edge') b = np.array( [[0, 0, 0, 0, 1, 2, 2, 2], [0, 0, 0, 0, 1, 2, 2, 2], [0, 0, 0, 0, 1, 2, 2, 2], [3, 3, 3, 3, 4, 5, 5, 5], [6, 6, 6, 6, 7, 8, 8, 8], [9, 9, 9, 9, 10, 11, 11, 11], [9, 9, 9, 9, 10, 11, 11, 11], [9, 9, 9, 9, 10, 11, 11, 11], [9, 9, 9, 9, 10, 11, 11, 11]] ) assert_array_equal(a, b) class ValueError1(TestCase): def test_check_simple(self): arr = np.arange(30) arr = np.reshape(arr, (6, 5)) kwargs = dict(mode='mean', stat_length=(3, )) with testing.raises(ValueError): np.pad(arr, ((2, 3), (3, 2), (4, 5)), **kwargs) def test_check_negative_stat_length(self): arr = np.arange(30) arr = np.reshape(arr, (6, 5)) kwargs = dict(mode='mean', stat_length=(-3, )) with testing.raises(ValueError): np.pad(arr, ((2, 3), (3, 2)), **kwargs) def test_check_negative_pad_width(self): arr = np.arange(30) arr = np.reshape(arr, (6, 5)) kwargs = dict(mode='mean', stat_length=(3, )) with testing.raises(ValueError): np.pad(arr, ((-2, 3), (3, 2)), **kwargs) class ValueError2(TestCase): def test_check_negative_pad_amount(self): arr = np.arange(30) arr = np.reshape(arr, (6, 5)) kwargs = dict(mode='mean', stat_length=(3, )) with testing.raises(ValueError): np.pad(arr, ((-2, 3), (3, 2)), **kwargs) class ValueError3(TestCase): def test_check_kwarg_not_allowed(self): arr = np.arange(30).reshape(5, 6) with testing.raises(ValueError): np.pad(arr, 4, mode='mean', reflect_type='odd') @testing.skipif(LooseVersion(np.__version__) >= LooseVersion('1.17'), reason='Error removed in NumPy 1.17') def test_mode_not_set(self): arr = np.arange(30).reshape(5, 6) with testing.raises(TypeError): np.pad(arr, 4) def test_malformed_pad_amount(self): arr = np.arange(30).reshape(5, 6) with testing.raises(ValueError): np.pad(arr, (4, 5, 6, 7), mode='constant') def test_malformed_pad_amount2(self): arr = np.arange(30).reshape(5, 6) with testing.raises(ValueError): np.pad(arr, ((3, 4, 5), (0, 1, 2)), mode='constant') def test_pad_too_many_axes(self): arr = np.arange(30).reshape(5, 6) # Attempt to pad using a 3D array equivalent bad_shape = (((3,), (4,), (5,)), ((0,), (1,), (2,))) with testing.raises(ValueError): np.pad(arr, bad_shape, mode='constant') class TypeError1(TestCase): def test_float(self): arr = np.arange(30) with testing.raises(TypeError): np.pad(arr, ((-2.1, 3), (3, 2))) with testing.raises(TypeError): np.pad(arr, np.array(((-2.1, 3), (3, 2)))) def test_str(self): arr = np.arange(30) with testing.raises(TypeError): np.pad(arr, 'foo') with testing.raises(TypeError): np.pad(arr, np.array('foo')) def test_object(self): class FooBar(object): pass arr = np.arange(30) with testing.raises(TypeError): np.pad(arr, FooBar()) def test_complex(self): arr = np.arange(30) with testing.raises(TypeError): np.pad(arr, complex(1, -1)) with testing.raises(TypeError): np.pad(arr, np.array(complex(1, -1))) def test_check_wrong_pad_amount(self): arr = np.arange(30) arr = np.reshape(arr, (6, 5)) kwargs = dict(mode='mean', stat_length=(3, )) with testing.raises(TypeError): np.pad(arr, ((2, 3, 4), (3, 2)), **kwargs)