def func(image, kernel):
ref = scipy.signal.fftconvolve(image, kernel, mode='same')
convol = ConvolutionOperator(kernel, image.shape)
con = convol(image)
assert np.allclose(ref, con, atol=1.e-15)
assert np.allclose(convol.todense().T.conjugate(),
convol.H.todense(), atol=1.e-15)
def test_convolution_rules_homothety():
h = HomothetyOperator(2)
c = ConvolutionOperator(np.ones((3, 3)), (5, 5))
ref = c.todense() * h.data
lambda_id = lambda x, y: (x, y)
lambda_sw = lambda x, y: (y, x)
def func(ops, r):
op = CompositionOperator(ops)
assert_same(op.todense(), r, atol=5)
for op, r in zip((c, c.T), (ref, ref.T)):
for l in (lambda_id, lambda_sw):
ops = l(op, h)
yield func, ops, r