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(pad(test, pad_amt, mode='edge'),
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(pad(test, pad_amt, mode=mode),
pad(test, pad_amt, mode=mode, stat_length=30))
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(pad(test, pad_amt, mode=mode),
pad(test, pad_amt, mode=mode, stat_length=30))
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(pad(test, pad_amt, mode='edge'),
pad(test, pad_amt, mode=mode, stat_length=1))
def test_check_median_stat_length(self):
a = np.arange(100).astype('f')
a[1] = 2.
a[97] = 96.
a = 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_median_stat_length(self):
a = np.arange(100).astype('f')
a[1] = 2.
a[97] = 96.
a = 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_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_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_pad_reflect():
I = np.arange(30).reshape((5, 6))
psf_5x5 = np.zeros((5, 5))
psf_5x7 = np.zeros((5, 7))
psf_9x11 = np.zeros((9, 11))
test_5x5 = pad(I, psf_5x5) # Symmetric padding
exp_5x5 = np.r_[[[14, 13, 12, 13, 14, 15, 16, 17, 16, 15],
[ 8, 7, 6, 7, 8, 9, 10, 11, 10, 9],
[ 2, 1, 0, 1, 2, 3, 4, 5, 4, 3],
[ 8, 7, 6, 7, 8, 9, 10, 11, 10, 9],
[14, 13, 12, 13, 14, 15, 16, 17, 16, 15],
[20, 19, 18, 19, 20, 21, 22, 23, 22, 21],
[26, 25, 24, 25, 26, 27, 28, 29, 28, 27],
[20, 19, 18, 19, 20, 21, 22, 23, 22, 21],
[14, 13, 12, 13, 14, 15, 16, 17, 16, 15]]]
test_5x7 = pad(I, psf_5x7) # Asymmetric padding
exp_5x7 = np.r_[[[15, 14, 13, 12, 13, 14, 15, 16, 17, 16, 15, 14],
[ 9, 8, 7, 6, 7, 8, 9, 10, 11, 10, 9, 8],
[ 3, 2, 1, 0, 1, 2, 3, 4, 5, 4, 3, 2],
[ 9, 8, 7, 6, 7, 8, 9, 10, 11, 10, 9, 8],
[15, 14, 13, 12, 13, 14, 15, 16, 17, 16, 15, 14],
[21, 20, 19, 18, 19, 20, 21, 22, 23, 22, 21, 20],
[27, 26, 25, 24, 25, 26, 27, 28, 29, 28, 27, 26],
[21, 20, 19, 18, 19, 20, 21, 22, 23, 22, 21, 20],
[15, 14, 13, 12, 13, 14, 15, 16, 17, 16, 15, 14]]]
test_9x11 = pad(I, psf_9x11) # Pad with too much for reflect
exp_9x11 = np.r_[[[22, 21, 20, 19, 18, 19, 20, 21, 22, 23, 22, 21, 20, 19],
[16, 15, 14, 13, 12, 13, 14, 15, 16, 17, 16, 15, 14, 13],
[10, 9, 8, 7, 6, 7, 8, 9, 10, 11, 10, 9, 8, 7],
[ 4, 3, 2, 1, 0, 1, 2, 3, 4, 5, 4, 3, 2, 1],
[10, 9, 8, 7, 6, 7, 8, 9, 10, 11, 10, 9, 8, 7],
[16, 15, 14, 13, 12, 13, 14, 15, 16, 17, 16, 15, 14, 13],
[22, 21, 20, 19, 18, 19, 20, 21, 22, 23, 22, 21, 20, 19],
[28, 27, 26, 25, 24, 25, 26, 27, 28, 29, 28, 27, 26, 25],
[22, 21, 20, 19, 18, 19, 20, 21, 22, 23, 22, 21, 20, 19],
[16, 15, 14, 13, 12, 13, 14, 15, 16, 17, 16, 15, 14, 13],
[10, 9, 8, 7, 6, 7, 8, 9, 10, 11, 10, 9, 8, 7]]]
assert_array_equal(test_5x5, exp_5x5)
assert_array_equal(test_5x7, exp_5x7)
assert_array_equal(test_9x11, exp_9x11)
def test_pad_reflect():
I = np.arange(30).reshape((5, 6))
psf_5x5 = np.zeros((5, 5))
psf_5x7 = np.zeros((5, 7))
psf_9x11 = np.zeros((9, 11))
test_5x5 = pad(I, psf_5x5) # Symmetric padding
exp_5x5 = np.r_[[[14, 13, 12, 13, 14, 15, 16, 17, 16, 15],
[8, 7, 6, 7, 8, 9, 10, 11, 10, 9],
[2, 1, 0, 1, 2, 3, 4, 5, 4, 3],
[8, 7, 6, 7, 8, 9, 10, 11, 10, 9],
[14, 13, 12, 13, 14, 15, 16, 17, 16, 15],
[20, 19, 18, 19, 20, 21, 22, 23, 22, 21],
[26, 25, 24, 25, 26, 27, 28, 29, 28, 27],
[20, 19, 18, 19, 20, 21, 22, 23, 22, 21],
[14, 13, 12, 13, 14, 15, 16, 17, 16, 15]]]
test_5x7 = pad(I, psf_5x7) # Asymmetric padding
exp_5x7 = np.r_[[[15, 14, 13, 12, 13, 14, 15, 16, 17, 16, 15, 14],
[9, 8, 7, 6, 7, 8, 9, 10, 11, 10, 9, 8],
[3, 2, 1, 0, 1, 2, 3, 4, 5, 4, 3, 2],
[9, 8, 7, 6, 7, 8, 9, 10, 11, 10, 9, 8],
[15, 14, 13, 12, 13, 14, 15, 16, 17, 16, 15, 14],
[21, 20, 19, 18, 19, 20, 21, 22, 23, 22, 21, 20],
[27, 26, 25, 24, 25, 26, 27, 28, 29, 28, 27, 26],
[21, 20, 19, 18, 19, 20, 21, 22, 23, 22, 21, 20],
[15, 14, 13, 12, 13, 14, 15, 16, 17, 16, 15, 14]]]
test_9x11 = pad(I, psf_9x11) # Pad with too much for reflect
exp_9x11 = np.r_[[[22, 21, 20, 19, 18, 19, 20, 21, 22, 23, 22, 21, 20, 19],
[16, 15, 14, 13, 12, 13, 14, 15, 16, 17, 16, 15, 14, 13],
[10, 9, 8, 7, 6, 7, 8, 9, 10, 11, 10, 9, 8, 7],
[4, 3, 2, 1, 0, 1, 2, 3, 4, 5, 4, 3, 2, 1],
[10, 9, 8, 7, 6, 7, 8, 9, 10, 11, 10, 9, 8, 7],
[16, 15, 14, 13, 12, 13, 14, 15, 16, 17, 16, 15, 14, 13],
[22, 21, 20, 19, 18, 19, 20, 21, 22, 23, 22, 21, 20, 19],
[28, 27, 26, 25, 24, 25, 26, 27, 28, 29, 28, 27, 26, 25],
[22, 21, 20, 19, 18, 19, 20, 21, 22, 23, 22, 21, 20, 19],
[16, 15, 14, 13, 12, 13, 14, 15, 16, 17, 16, 15, 14, 13],
[10, 9, 8, 7, 6, 7, 8, 9, 10, 11, 10, 9, 8, 7]]]
assert_array_equal(test_5x5, exp_5x5)
assert_array_equal(test_5x7, exp_5x7)
assert_array_equal(test_9x11, exp_9x11)
def test_defocus_astronaut(self):
im = np.load(os.path.join(skfuzzy.image.__path__[0],
'astronaut_gray.npy')).astype(np.float64)
result = defocus_local_means(im)
expected = view_as_windows(
pad(im, 1, mode='reflect'),
(3, 3))[:, :, [1, 1, 0, 2], [0, 2, 1, 1]].mean(axis=2)
assert_allclose(result, expected)
def test_check_simple(self):
a = np.arange(12)
a = np.reshape(a, (4, 3))
a = 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)
def test_check_constant_odd_pad_amount(self):
arr = np.arange(30).reshape(5, 6)
test = 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)
def test_check_2d(self):
arr = np.arange(20).reshape(4, 5).astype(np.float64)
test = 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)
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_2d(self):
arr = np.arange(20).reshape(4, 5).astype(np.float64)
test = 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)
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 = 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)
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_pad_nopsf():
I = np.arange(30).reshape((5, 6))
exp_5x5 = np.r_[[[14, 13, 12, 13, 14, 15, 16, 17, 16, 15],
[ 8, 7, 6, 7, 8, 9, 10, 11, 10, 9],
[ 2, 1, 0, 1, 2, 3, 4, 5, 4, 3],
[ 8, 7, 6, 7, 8, 9, 10, 11, 10, 9],
[14, 13, 12, 13, 14, 15, 16, 17, 16, 15],
[20, 19, 18, 19, 20, 21, 22, 23, 22, 21],
[26, 25, 24, 25, 26, 27, 28, 29, 28, 27],
[20, 19, 18, 19, 20, 21, 22, 23, 22, 21],
[14, 13, 12, 13, 14, 15, 16, 17, 16, 15]]]
test_nopsf = pad(I, [5, 5])
assert_array_equal(test_nopsf, exp_5x5)
def test_pad_zeros():
I = np.arange(30).reshape((5, 6))
test_5x7 = pad(I, [5, 7], mode='zero')
exp_5x7 = np.r_[[[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, 0, 0, 1, 2, 3, 4, 5, 0, 0, 0],
[0, 0, 0, 6, 7, 8, 9, 10, 11, 0, 0, 0],
[0, 0, 0, 12, 13, 14, 15, 16, 17, 0, 0, 0],
[0, 0, 0, 18, 19, 20, 21, 22, 23, 0, 0, 0],
[0, 0, 0, 24, 25, 26, 27, 28, 29, 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, 0]]]
assert_array_equal(test_5x7, exp_5x7)
def test_pad_nopsf():
I = np.arange(30).reshape((5, 6))
exp_5x5 = np.r_[[[14, 13, 12, 13, 14, 15, 16, 17, 16, 15],
[8, 7, 6, 7, 8, 9, 10, 11, 10, 9],
[2, 1, 0, 1, 2, 3, 4, 5, 4, 3],
[8, 7, 6, 7, 8, 9, 10, 11, 10, 9],
[14, 13, 12, 13, 14, 15, 16, 17, 16, 15],
[20, 19, 18, 19, 20, 21, 22, 23, 22, 21],
[26, 25, 24, 25, 26, 27, 28, 29, 28, 27],
[20, 19, 18, 19, 20, 21, 22, 23, 22, 21],
[14, 13, 12, 13, 14, 15, 16, 17, 16, 15]]]
test_nopsf = pad(I, [5, 5])
assert_array_equal(test_nopsf, exp_5x5)
def test_pad_zeros():
I = np.arange(30).reshape((5, 6))
test_5x7 = pad(I, [5, 7], mode='zero')
exp_5x7 = np.r_[[[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, 0, 0, 1, 2, 3, 4, 5, 0, 0, 0],
[0, 0, 0, 6, 7, 8, 9, 10, 11, 0, 0, 0],
[0, 0, 0, 12, 13, 14, 15, 16, 17, 0, 0, 0],
[0, 0, 0, 18, 19, 20, 21, 22, 23, 0, 0, 0],
[0, 0, 0, 24, 25, 26, 27, 28, 29, 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, 0]]]
assert_array_equal(test_5x7, exp_5x7)
def test_check_constant_zeros(self):
a = np.arange(100)
a = 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 = 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_pad_replicate():
I = np.arange(30).reshape((5, 6))
test_5x7 = pad(I, [5, 7], mode='replicate')
exp_5x7 = np.r_[[[0, 0, 0, 0, 1, 2, 3, 4, 5, 5, 5, 5],
[0, 0, 0, 0, 1, 2, 3, 4, 5, 5, 5, 5],
[0, 0, 0, 0, 1, 2, 3, 4, 5, 5, 5, 5],
[6, 6, 6, 6, 7, 8, 9, 10, 11, 11, 11, 11],
[12, 12, 12, 12, 13, 14, 15, 16, 17, 17, 17, 17],
[18, 18, 18, 18, 19, 20, 21, 22, 23, 23, 23, 23],
[24, 24, 24, 24, 25, 26, 27, 28, 29, 29, 29, 29],
[24, 24, 24, 24, 25, 26, 27, 28, 29, 29, 29, 29],
[24, 24, 24, 24, 25, 26, 27, 28, 29, 29, 29, 29],
[24, 24, 24, 24, 25, 26, 27, 28, 29, 29, 29, 29]]]
assert_array_equal(test_5x7, exp_5x7)
def test_check_odd_method(self):
a = np.arange(100)
a = 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_pad_replicate():
I = np.arange(30).reshape((5, 6))
test_5x7 = pad(I, [5, 7], mode='replicate')
exp_5x7 = np.r_[[[ 0, 0, 0, 0, 1, 2, 3, 4, 5, 5, 5, 5],
[ 0, 0, 0, 0, 1, 2, 3, 4, 5, 5, 5, 5],
[ 0, 0, 0, 0, 1, 2, 3, 4, 5, 5, 5, 5],
[ 6, 6, 6, 6, 7, 8, 9, 10, 11, 11, 11, 11],
[12, 12, 12, 12, 13, 14, 15, 16, 17, 17, 17, 17],
[18, 18, 18, 18, 19, 20, 21, 22, 23, 23, 23, 23],
[24, 24, 24, 24, 25, 26, 27, 28, 29, 29, 29, 29],
[24, 24, 24, 24, 25, 26, 27, 28, 29, 29, 29, 29],
[24, 24, 24, 24, 25, 26, 27, 28, 29, 29, 29, 29],
[24, 24, 24, 24, 25, 26, 27, 28, 29, 29, 29, 29]]]
assert_array_equal(test_5x7, exp_5x7)
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, pad(test, pad_amt, mode=mode))
def test_check_constant_odd_pad_amount(self):
arr = np.arange(30).reshape(5, 6)
test = 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)
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, pad(test, pad_amt, mode=mode))
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)
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_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, 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_shape(self):
a = [[4, 5, 6]]
a = 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_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 = 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_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_simple(self):
a = np.arange(12)
a = np.reshape(a, (4, 3))
a = 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)
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 = 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_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 = 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)
def test_check_large_pad(self):
a = [[4, 5, 6], [6, 7, 8]]
a = 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_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_allclose(a, b, rtol=1e-5, atol=1e-5)
def test_check_large_pad_odd(self):
a = [[4, 5, 6], [6, 7, 8]]
a = 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_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)
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 = 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_shape(self):
a = [[4, 5, 6]]
a = 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_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, 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_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_large_pad_odd(self):
a = [[4, 5, 6], [6, 7, 8]]
a = 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_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_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_allclose(a, b, rtol=1e-5, atol=1e-5)
def test_check_constant_float3(self):
a = np.arange(100, dtype=float)
a = 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_odd_method(self):
a = np.arange(100)
a = 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_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_large_pad(self):
a = [[4, 5, 6], [6, 7, 8]]
a = 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_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, pad(arr, pad_width, mode='constant'))
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, pad(arr, pad_width, mode='constant'))
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)
def test_check_03(self):
a = 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)
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)
