本文整理汇总了Python中scipy.ndimage.spline_filter方法的典型用法代码示例。如果您正苦于以下问题：Python ndimage.spline_filter方法的具体用法？Python ndimage.spline_filter怎么用？Python ndimage.spline_filter使用的例子？那么恭喜您, 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.spline_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_affine_transform09
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def test_affine_transform09(self):
data = numpy.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
for order in range(0, 6):
if (order > 1):
filtered = ndimage.spline_filter(data,
order=order)
else:
filtered = data
out = ndimage.affine_transform(filtered,[[1, 0],
[0, 1]],
[-1, -1], order=order, prefilter=False)
assert_array_almost_equal(out, [[0, 0, 0, 0],
[0, 4, 1, 3],
[0, 7, 6, 8]]) 示例2: test_affine_transform26
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def test_affine_transform26(self):
# test homogeneous coordinates
data = numpy.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
for order in range(0, 6):
if (order > 1):
filtered = ndimage.spline_filter(data, order=order)
else:
filtered = data
tform_original = numpy.eye(2)
offset_original = -numpy.ones((2, 1))
tform_h1 = numpy.hstack((tform_original, offset_original))
tform_h2 = numpy.vstack((tform_h1, [[0, 0, 1]]))
out1 = ndimage.affine_transform(filtered, tform_original,
offset_original.ravel(),
order=order, prefilter=False)
out2 = ndimage.affine_transform(filtered, tform_h1, order=order,
prefilter=False)
out3 = ndimage.affine_transform(filtered, tform_h2, order=order,
prefilter=False)
for out in [out1, out2, out3]:
assert_array_almost_equal(out, [[0, 0, 0, 0],
[0, 4, 1, 3],
[0, 7, 6, 8]]) 示例3: save_spline_arrays
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def save_spline_arrays(self, pickleName, what):
if _DEBUG:
print('. Pickling splines to\n{0}'.format(pickleName))
splines = []
for ia, a in enumerate(what):
a = np.concatenate((a[:, self.extraRows:0:-1, :], a), axis=1)
a = np.concatenate((a[:, :, self.extraRows:0:-1], a), axis=2)
if self.order == 3:
spline = ndimage.spline_filter(a)
else:
spline = a
splines.append(spline)
Imax = np.max(what[0])
with open(pickleName, 'wb') as f:
pickle.dump((Imax, splines), f, protocol=2)
return splines, Imax 示例4: test_spline01
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def test_spline01(self):
for type in self.types:
data = numpy.ones([], type)
for order in range(2, 6):
out = ndimage.spline_filter(data, order=order)
assert_array_almost_equal(out, 1) 示例5: test_spline02
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def test_spline02(self):
for type in self.types:
data = numpy.array([1])
for order in range(2, 6):
out = ndimage.spline_filter(data, order=order)
assert_array_almost_equal(out, [1]) 示例6: test_spline03
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def test_spline03(self):
for type in self.types:
data = numpy.ones([], type)
for order in range(2, 6):
out = ndimage.spline_filter(data, order,
output=type)
assert_array_almost_equal(out, 1) 示例7: test_spline04
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def test_spline04(self):
for type in self.types:
data = numpy.ones([4], type)
for order in range(2, 6):
out = ndimage.spline_filter(data, order)
assert_array_almost_equal(out, [1, 1, 1, 1]) 示例8: test_spline05
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def test_spline05(self):
for type in self.types:
data = numpy.ones([4, 4], type)
for order in range(2, 6):
out = ndimage.spline_filter(data, order=order)
assert_array_almost_equal(out, [[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1]]) 示例9: test_shift09
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def test_shift09(self):
data = numpy.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
for order in range(0, 6):
if (order > 1):
filtered = ndimage.spline_filter(data,
order=order)
else:
filtered = data
out = ndimage.shift(filtered, [1, 1], order=order,
prefilter=False)
assert_array_almost_equal(out, [[0, 0, 0, 0],
[0, 4, 1, 3],
[0, 7, 6, 8]]) 示例10: test_spline01
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def test_spline01(self):
for type_ in self.types:
data = numpy.ones([], type_)
for order in range(2, 6):
out = ndimage.spline_filter(data, order=order)
assert_array_almost_equal(out, 1) 示例11: test_spline02
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def test_spline02(self):
for type_ in self.types:
data = numpy.array([1], type_)
for order in range(2, 6):
out = ndimage.spline_filter(data, order=order)
assert_array_almost_equal(out, [1]) 示例12: test_spline03
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def test_spline03(self):
for type_ in self.types:
data = numpy.ones([], type_)
for order in range(2, 6):
out = ndimage.spline_filter(data, order,
output=type_)
assert_array_almost_equal(out, 1) 示例13: test_spline04
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def test_spline04(self):
for type_ in self.types:
data = numpy.ones([4], type_)
for order in range(2, 6):
out = ndimage.spline_filter(data, order)
assert_array_almost_equal(out, [1, 1, 1, 1]) 示例14: test_spline05
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def test_spline05(self):
for type_ in self.types:
data = numpy.ones([4, 4], type_)
for order in range(2, 6):
out = ndimage.spline_filter(data, order=order)
assert_array_almost_equal(out, [[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1]]) 示例15: test_affine_transform09
# 需要导入模块: from scipy import ndimage [as 别名]
# 或者: from scipy.ndimage import spline_filter [as 别名]
def test_affine_transform09(self):
data = numpy.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
for order in range(0, 6):
if (order > 1):
filtered = ndimage.spline_filter(data, order=order)
else:
filtered = data
out = ndimage.affine_transform(filtered, [[1, 0], [0, 1]],
[-1, -1], order=order,
prefilter=False)
assert_array_almost_equal(out, [[0, 0, 0, 0],
[0, 4, 1, 3],
[0, 7, 6, 8]])