本文整理汇总了Python中skfuzzy.image.pad函数的典型用法代码示例。如果您正苦于以下问题：Python pad函数的具体用法？Python pad怎么用？Python pad使用的例子？那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了pad函数的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_shallow_statistic_range
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))示例2: test_clip_statistic_range
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))示例3: test_check_median_stat_length
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)示例4: test_check_large_pad
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)示例5: test_pad_reflect
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)示例6: test_defocus_astronaut
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)示例7: test_check_2d
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)示例8: test_check_median_02
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)示例9: test_pad_nopsf
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)示例10: test_pad_zeros
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)示例11: test_pad_replicate
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)示例12: test_check_constant_odd_pad_amount
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)示例13: test_zero_padding_shortcuts
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))示例14: test_check_simple
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)示例15: test_check_constant_float
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)