projektAI/venv/Lib/site-packages/scipy/ndimage/tests/test_c_api.py

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2021-06-06 22:13:05 +02:00
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)