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