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- import numpy as np
- from numpy.testing import assert_allclose
- from scipy import ndimage
- from scipy.ndimage import _ctest
- from scipy.ndimage import _cytest
- from scipy._lib._ccallback import LowLevelCallable
- FILTER1D_FUNCTIONS = [
- lambda filter_size: _ctest.filter1d(filter_size),
- lambda filter_size: _cytest.filter1d(filter_size, with_signature=False),
- lambda filter_size: LowLevelCallable(_cytest.filter1d(filter_size, with_signature=True)),
- lambda filter_size: LowLevelCallable.from_cython(_cytest, "_filter1d",
- _cytest.filter1d_capsule(filter_size)),
- ]
- FILTER2D_FUNCTIONS = [
- lambda weights: _ctest.filter2d(weights),
- lambda weights: _cytest.filter2d(weights, with_signature=False),
- lambda weights: LowLevelCallable(_cytest.filter2d(weights, with_signature=True)),
- lambda weights: LowLevelCallable.from_cython(_cytest, "_filter2d", _cytest.filter2d_capsule(weights)),
- ]
- TRANSFORM_FUNCTIONS = [
- lambda shift: _ctest.transform(shift),
- lambda shift: _cytest.transform(shift, with_signature=False),
- lambda shift: LowLevelCallable(_cytest.transform(shift, with_signature=True)),
- lambda shift: LowLevelCallable.from_cython(_cytest, "_transform", _cytest.transform_capsule(shift)),
- ]
- def test_generic_filter():
- def filter2d(footprint_elements, weights):
- return (weights*footprint_elements).sum()
- def check(j):
- func = FILTER2D_FUNCTIONS[j]
- im = np.ones((20, 20))
- im[:10,:10] = 0
- footprint = np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])
- footprint_size = np.count_nonzero(footprint)
- weights = np.ones(footprint_size)/footprint_size
- res = ndimage.generic_filter(im, func(weights),
- footprint=footprint)
- std = ndimage.generic_filter(im, filter2d, footprint=footprint,
- extra_arguments=(weights,))
- assert_allclose(res, std, err_msg="#{} failed".format(j))
- for j, func in enumerate(FILTER2D_FUNCTIONS):
- check(j)
- def test_generic_filter1d():
- def filter1d(input_line, output_line, filter_size):
- for i in range(output_line.size):
- output_line[i] = 0
- for j in range(filter_size):
- output_line[i] += input_line[i+j]
- output_line /= filter_size
- def check(j):
- func = FILTER1D_FUNCTIONS[j]
- im = np.tile(np.hstack((np.zeros(10), np.ones(10))), (10, 1))
- filter_size = 3
- res = ndimage.generic_filter1d(im, func(filter_size),
- filter_size)
- std = ndimage.generic_filter1d(im, filter1d, filter_size,
- extra_arguments=(filter_size,))
- assert_allclose(res, std, err_msg="#{} failed".format(j))
- for j, func in enumerate(FILTER1D_FUNCTIONS):
- check(j)
- def test_geometric_transform():
- def transform(output_coordinates, shift):
- return output_coordinates[0] - shift, output_coordinates[1] - shift
- def check(j):
- func = TRANSFORM_FUNCTIONS[j]
- im = np.arange(12).reshape(4, 3).astype(np.float64)
- shift = 0.5
- res = ndimage.geometric_transform(im, func(shift))
- std = ndimage.geometric_transform(im, transform, extra_arguments=(shift,))
- assert_allclose(res, std, err_msg="#{} failed".format(j))
- for j, func in enumerate(TRANSFORM_FUNCTIONS):
- check(j)
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