本文整理汇总了Python中scipy.ndimage.minimum_filter方法的典型用法代码示例。如果您正苦于以下问题：Python ndimage.minimum_filter方法的具体用法？Python ndimage.minimum_filter怎么用？Python ndimage.minimum_filter使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类scipy.ndimage的用法示例。
在下文中一共展示了ndimage.minimum_filter方法的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_valid_origins
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_valid_origins():
"""Regression test for #1311."""
func = lambda x: np.mean(x)
data = np.array([1,2,3,4,5], dtype=np.float64)
assert_raises(ValueError, sndi.generic_filter, data, func, size=3,
origin=2)
func2 = lambda x, y: np.mean(x + y)
assert_raises(ValueError, sndi.generic_filter1d, data, func,
filter_size=3, origin=2)
assert_raises(ValueError, sndi.percentile_filter, data, 0.2, size=3,
origin=2)
for filter in [sndi.uniform_filter, sndi.minimum_filter,
sndi.maximum_filter, sndi.maximum_filter1d,
sndi.median_filter, sndi.minimum_filter1d]:
# This should work, since for size == 3, the valid range for origin is
# -1 to 1.
list(filter(data, 3, origin=-1))
list(filter(data, 3, origin=1))
# Just check this raises an error instead of silently accepting or
# segfaulting.
assert_raises(ValueError, filter, data, 3, origin=2) 示例2: test_minimum_filter01
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_minimum_filter01(self):
array = numpy.array([1, 2, 3, 4, 5])
filter_shape = numpy.array([2])
output = ndimage.minimum_filter(array, filter_shape)
assert_array_almost_equal([1, 1, 2, 3, 4], output) 示例3: test_minimum_filter02
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_minimum_filter02(self):
array = numpy.array([1, 2, 3, 4, 5])
filter_shape = numpy.array([3])
output = ndimage.minimum_filter(array, filter_shape)
assert_array_almost_equal([1, 1, 2, 3, 4], output) 示例4: test_minimum_filter03
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_minimum_filter03(self):
array = numpy.array([3, 2, 5, 1, 4])
filter_shape = numpy.array([2])
output = ndimage.minimum_filter(array, filter_shape)
assert_array_almost_equal([3, 2, 2, 1, 1], output) 示例5: test_minimum_filter04
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_minimum_filter04(self):
array = numpy.array([3, 2, 5, 1, 4])
filter_shape = numpy.array([3])
output = ndimage.minimum_filter(array, filter_shape)
assert_array_almost_equal([2, 2, 1, 1, 1], output) 示例6: test_minimum_filter05
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_minimum_filter05(self):
array = numpy.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
filter_shape = numpy.array([2, 3])
output = ndimage.minimum_filter(array, filter_shape)
assert_array_almost_equal([[2, 2, 1, 1, 1],
[2, 2, 1, 1, 1],
[5, 3, 3, 1, 1]], output) 示例7: test_minimum_filter07
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_minimum_filter07(self):
array = numpy.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
output = ndimage.minimum_filter(array,
footprint=footprint)
assert_array_almost_equal([[2, 2, 1, 1, 1],
[2, 3, 1, 3, 1],
[5, 5, 3, 3, 1]], output) 示例8: test_minimum_filter08
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_minimum_filter08(self):
array = numpy.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
output = ndimage.minimum_filter(array,
footprint=footprint, origin=-1)
assert_array_almost_equal([[3, 1, 3, 1, 1],
[5, 3, 3, 1, 1],
[3, 3, 1, 1, 1]], output) 示例9: test_minimum_filter09
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_minimum_filter09(self):
array = numpy.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
output = ndimage.minimum_filter(array,
footprint=footprint, origin=[-1, 0])
assert_array_almost_equal([[2, 3, 1, 3, 1],
[5, 5, 3, 3, 1],
[5, 3, 3, 1, 1]], output) 示例10: test_minimum_filter05
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_minimum_filter05(self):
array = numpy.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
filter_shape = numpy.array([2, 3])
output = ndimage.minimum_filter(array, filter_shape)
assert_array_almost_equal([[2, 2, 1, 1, 1],
[2, 2, 1, 1, 1],
[5, 3, 3, 1, 1]], output) 示例11: test_minimum_filter07
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_minimum_filter07(self):
array = numpy.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
output = ndimage.minimum_filter(array, footprint=footprint)
assert_array_almost_equal([[2, 2, 1, 1, 1],
[2, 3, 1, 3, 1],
[5, 5, 3, 3, 1]], output) 示例12: test_minimum_filter08
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_minimum_filter08(self):
array = numpy.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
output = ndimage.minimum_filter(array, footprint=footprint, origin=-1)
assert_array_almost_equal([[3, 1, 3, 1, 1],
[5, 3, 3, 1, 1],
[3, 3, 1, 1, 1]], output) 示例13: test_minimum_filter09
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_minimum_filter09(self):
array = numpy.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
output = ndimage.minimum_filter(array, footprint=footprint,
origin=[-1, 0])
assert_array_almost_equal([[2, 3, 1, 3, 1],
[5, 5, 3, 3, 1],
[5, 3, 3, 1, 1]], output) 示例14: test_multiple_modes
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_multiple_modes():
# Test that the filters with multiple mode cababilities for different
# dimensions give the same result as applying a single mode.
arr = np.array([[1., 0., 0.],
[1., 1., 0.],
[0., 0., 0.]])
mode1 = 'reflect'
mode2 = ['reflect', 'reflect']
assert_equal(sndi.gaussian_filter(arr, 1, mode=mode1),
sndi.gaussian_filter(arr, 1, mode=mode2))
assert_equal(sndi.prewitt(arr, mode=mode1),
sndi.prewitt(arr, mode=mode2))
assert_equal(sndi.sobel(arr, mode=mode1),
sndi.sobel(arr, mode=mode2))
assert_equal(sndi.laplace(arr, mode=mode1),
sndi.laplace(arr, mode=mode2))
assert_equal(sndi.gaussian_laplace(arr, 1, mode=mode1),
sndi.gaussian_laplace(arr, 1, mode=mode2))
assert_equal(sndi.maximum_filter(arr, size=5, mode=mode1),
sndi.maximum_filter(arr, size=5, mode=mode2))
assert_equal(sndi.minimum_filter(arr, size=5, mode=mode1),
sndi.minimum_filter(arr, size=5, mode=mode2))
assert_equal(sndi.gaussian_gradient_magnitude(arr, 1, mode=mode1),
sndi.gaussian_gradient_magnitude(arr, 1, mode=mode2))
assert_equal(sndi.uniform_filter(arr, 5, mode=mode1),
sndi.uniform_filter(arr, 5, mode=mode2)) 示例15: test_minmax_filter
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import minimum_filter [as 别名]
def test_minmax_filter(self):
d = np.random.randn(500, 500)
os = np.empty([4] + list(d.shape))
ot = np.empty_like(os)
self.check_func_serial(4, sndi.maximum_filter, (d, 3), os)
self.check_func_thread(4, sndi.maximum_filter, (d, 3), ot)
assert_array_equal(os, ot)
self.check_func_serial(4, sndi.minimum_filter, (d, 3), os)
self.check_func_thread(4, sndi.minimum_filter, (d, 3), ot)
assert_array_equal(os, ot)