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Diffstat (limited to 'numpy/lib/tests/test_arraypad.py')
| -rw-r--r-- | numpy/lib/tests/test_arraypad.py | 530 |
1 files changed, 530 insertions, 0 deletions
diff --git a/numpy/lib/tests/test_arraypad.py b/numpy/lib/tests/test_arraypad.py new file mode 100644 index 000000000..01cb5be4c --- /dev/null +++ b/numpy/lib/tests/test_arraypad.py @@ -0,0 +1,530 @@ +''' +Tests for the pad functions. +''' + +from numpy.testing import TestCase, run_module_suite, assert_array_equal +from numpy.testing import assert_raises, assert_array_almost_equal +import numpy as np +from numpy.lib import pad + + +class TestStatistic(TestCase): + def test_check_mean_stat_length(self): + a = np.arange(100).astype('f') + a = 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 = 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 = 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_minimum_1(self): + a = np.arange(100) + a = 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 = 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_median(self): + a = np.arange(100).astype('f') + a = 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 = 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 = 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_mean_shape_one(self): + a = [[4, 5, 6]] + a = pad(a, (5, 7), 'mean', stat_length=2) + b = np.array([ + [4, 4, 4, 4, 4, 4, 5, 6, 5, 5, 5, 5, 5, 5, 5], + [4, 4, 4, 4, 4, 4, 5, 6, 5, 5, 5, 5, 5, 5, 5], + [4, 4, 4, 4, 4, 4, 5, 6, 5, 5, 5, 5, 5, 5, 5], + [4, 4, 4, 4, 4, 4, 5, 6, 5, 5, 5, 5, 5, 5, 5], + [4, 4, 4, 4, 4, 4, 5, 6, 5, 5, 5, 5, 5, 5, 5], + + [4, 4, 4, 4, 4, 4, 5, 6, 5, 5, 5, 5, 5, 5, 5], + + [4, 4, 4, 4, 4, 4, 5, 6, 5, 5, 5, 5, 5, 5, 5], + [4, 4, 4, 4, 4, 4, 5, 6, 5, 5, 5, 5, 5, 5, 5], + [4, 4, 4, 4, 4, 4, 5, 6, 5, 5, 5, 5, 5, 5, 5], + [4, 4, 4, 4, 4, 4, 5, 6, 5, 5, 5, 5, 5, 5, 5], + [4, 4, 4, 4, 4, 4, 5, 6, 5, 5, 5, 5, 5, 5, 5], + [4, 4, 4, 4, 4, 4, 5, 6, 5, 5, 5, 5, 5, 5, 5], + [4, 4, 4, 4, 4, 4, 5, 6, 5, 5, 5, 5, 5, 5, 5]]) + assert_array_equal(a, b) + + def test_check_mean_2(self): + a = np.arange(100).astype('f') + a = 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 = 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) + + +class TestLinearRamp(TestCase): + def test_check_simple(self): + a = np.arange(100).astype('f') + a = 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_array_almost_equal(a, b, decimal=5) + + +class TestReflect(TestCase): + def test_check_simple(self): + a = np.arange(100) + a = 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_large_pad(self): + a = [[4, 5, 6], [6, 7, 8]] + a = 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 = 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 = 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 = 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 = 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 TestWrap(TestCase): + def test_check_simple(self): + a = np.arange(100) + a = 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 = 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 = 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 = 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 = 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 = 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 ValueError1(TestCase): + def test_check_simple(self): + arr = np.arange(30) + arr = np.reshape(arr, (6, 5)) + kwargs = dict(mode='mean', stat_length=(3, )) + assert_raises(ValueError, 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, )) + assert_raises(ValueError, 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, )) + assert_raises(ValueError, pad, arr, ((-2, 3), (3, 2)), + **kwargs) + + +class ValueError2(TestCase): + def test_check_simple(self): + arr = np.arange(30) + arr = np.reshape(arr, (6, 5)) + kwargs = dict(mode='mean', stat_length=(3, )) + assert_raises(ValueError, pad, arr, ((2, 3, 4), (3, 2)), + **kwargs) + + +class ValueError3(TestCase): + def test_check_simple(self): + arr = np.arange(30) + arr = np.reshape(arr, (6, 5)) + kwargs = dict(mode='mean', stat_length=(3, )) + assert_raises(ValueError, pad, arr, ((-2, 3), (3, 2)), + **kwargs) + + +if __name__ == "__main__": + run_module_suite() |