def test_bwt2d():
# 2D test
n = 16
x = np.zeros((n, n))
x[5:10, 5:10] = 1
wbasis = 'josbiorth5'
nscales = 3
# Define a discretized domain
domain = odl.FunctionSpace(odl.Rectangle([-1, -1], [1, 1]))
nPoints = np.array([n, n])
disc_domain = odl.uniform_discr_fromspace(domain, nPoints)
disc_phantom = disc_domain.element(x)
# Create the discrete wavelet transform operator.
# Only the domain of the operator needs to be defined
Bop = BiorthWaveletTransform(disc_domain, nscales, wbasis)
Bop2 = InverseAdjBiorthWaveletTransform(disc_domain, nscales, wbasis)
# Compute the discrete wavelet transform of discrete imput image
coeffs = Bop(disc_phantom)
coeffs2 = Bop2(disc_phantom)
reconstruction = Bop.inverse(coeffs)
reconstruction2 = Bop2.inverse(coeffs2)
assert all_almost_equal(reconstruction.asarray(), x)
assert all_almost_equal(reconstruction2.asarray(), x)
def test_bwt2d():
# 2D test
n = 16
x = np.zeros((n, n))
x[5:10, 5:10] = 1
wbasis = 'josbiorth5'
nscales = 3
# Define a discretized domain
domain = odl.FunctionSpace(odl.Rectangle([-1, -1], [1, 1]))
nPoints = np.array([n, n])
disc_domain = odl.uniform_discr_fromspace(domain, nPoints)
disc_phantom = disc_domain.element(x)
# Create the discrete wavelet transform operator.
# Only the domain of the operator needs to be defined
Bop = BiorthWaveletTransform(disc_domain, nscales, wbasis)
Bop2 = InverseAdjBiorthWaveletTransform(disc_domain, nscales, wbasis)
# Compute the discrete wavelet transform of discrete imput image
coeffs = Bop(disc_phantom)
coeffs2 = Bop2(disc_phantom)
reconstruction = Bop.inverse(coeffs)
reconstruction2 = Bop2.inverse(coeffs2)
assert all_almost_equal(reconstruction.asarray(), x)
assert all_almost_equal(reconstruction2.asarray(), x)
def test_bwt1d(wbasis):
# Verify that the operator works as axpected
# 1D test
n = 16
x = np.zeros(n)
x[5:10] = 1
nscales = 2
# Define a discretized domain
domain = odl.FunctionSpace(odl.Interval([-1], [1]))
nPoints = np.array([n])
disc_domain = odl.uniform_discr_fromspace(domain, nPoints)
disc_phantom = disc_domain.element(x)
# Create the discrete wavelet transform operator.
# Only the domain of the operator needs to be defined
Wop = BiorthWaveletTransform(disc_domain, nscales, wbasis)
# Compute the discrete wavelet transform of discrete imput image
coeffs = Wop(disc_phantom)
# Compute the inverse wavelet transform
reconstruction = Wop.inverse(coeffs)
# Verify that reconstructions lie in correct discretized domain
assert reconstruction in disc_domain
assert all_almost_equal(reconstruction.asarray(), x)
def test_bwt1d(wbasis):
# Verify that the operator works as axpected
# 1D test
n = 16
x = np.zeros(n)
x[5:10] = 1
nscales = 2
# Define a discretized domain
domain = odl.FunctionSpace(odl.Interval([-1], [1]))
nPoints = np.array([n])
disc_domain = odl.uniform_discr_fromspace(domain, nPoints)
disc_phantom = disc_domain.element(x)
# Create the discrete wavelet transform operator.
# Only the domain of the operator needs to be defined
Wop = BiorthWaveletTransform(disc_domain, nscales, wbasis)
# Compute the discrete wavelet transform of discrete imput image
coeffs = Wop(disc_phantom)
# Compute the inverse wavelet transform
reconstruction = Wop.inverse(coeffs)
# Verify that reconstructions lie in correct discretized domain
assert reconstruction in disc_domain
assert all_almost_equal(reconstruction.asarray(), x)
