def test_output_size():
Y = coldfilt(lena, (-1,1), (1,-1))
assert Y.shape == (lena.shape[0]/2, lena.shape[1])
Z = coldfilt_gold(lena, (-1,1), (1,-1))
assert_almost_equal(Y, Z)
def test_good_input_size():
A = coldfilt(lena[:,:511], (-1,1), (1,-1))
B = coldfilt_gold(lena[:,:511], (-1,1), (1,-1))
assert_almost_equal(A, B)
def test_good_input_size_non_orthogonal():
A = coldfilt(lena[:,:511], (1,1), (1,1))
B = coldfilt_gold(lena[:,:511], (1,1), (1,1))
assert_almost_equal(A, B)
def test_bad_input_size():
coldfilt(lena[:511,:], (-1,1), (1,-1))
def test_real_wavelet():
h0a, h0b, g0a, g0b, h1a, h1b, g1a, g1b = qshift('qshift_d')
A = coldfilt(lena[:,:511], h1b, h1a)
B = coldfilt_gold(lena[:,:511], h1b, h1a)
assert_almost_equal(A, B)
def test_different_size():
with raises(ValueError):
coldfilt(mandrill, (-0.5,-1,2,1,0.5), (-1,2,-1))
def test_different_size():
coldfilt(lena, (-0.5,-1,2,1,0.5), (-1,2,-1))
def test_qshift():
h0a, h0b, g0a, g0b, h1a, h1b, g1a, g1b = qshift('qshift_d')
y = coldfilt(mandrill, h1b, h1b)
z = coldfilt_gold(mandrill, h1b, h1a)
assert_almost_equal(y, z)
def _level2_xfm(X, h0a, h0b, h1a, h1b, ext_mode):
"""Perform level 2 or greater of the 3d transform.
"""
if ext_mode == 4:
if X.shape[0] % 4 != 0:
X = np.concatenate((X[[0], :, :], X, X[[-1], :, :]), 0)
if X.shape[1] % 4 != 0:
X = np.concatenate((X[:, [0], :], X, X[:, [-1], :]), 1)
if X.shape[2] % 4 != 0:
X = np.concatenate((X[:, :, [0]], X, X[:, :, [-1]]), 2)
elif self.ext_mode == 8:
if X.shape[0] % 8 != 0:
X = np.concatenate((X[(0, 0), :, :], X, X[(-1, -1), :, :]), 0)
if X.shape[1] % 8 != 0:
X = np.concatenate((X[:, (0, 0), :], X, X[:, (-1, -1), :]), 1)
if X.shape[2] % 8 != 0:
X = np.concatenate((X[:, :, (0, 0)], X, X[:, :, (-1, -1)]), 2)
# Create work area
work_shape = np.asanyarray(X.shape)
work = np.zeros(work_shape, dtype=X.dtype)
# Form some useful slices
s0a = slice(None, work.shape[0] >> 1)
s1a = slice(None, work.shape[1] >> 1)
s2a = slice(None, work.shape[2] >> 1)
s0b = slice(work.shape[0] >> 1, None)
s1b = slice(work.shape[1] >> 1, None)
s2b = slice(work.shape[2] >> 1, None)
# Assign input
work = X
# Loop over 2nd dimension extracting 2D slice from first and 3rd dimensions
for f in xrange(work.shape[1]):
# extract slice (copy required because we overwrite the work array)
y = work[:, f, :].T.copy()
# Do even Qshift filters on 3rd dim.
work[:, f, s2b] = coldfilt(y, h1b, h1a).T
work[:, f, s2a] = coldfilt(y, h0b, h0a).T
# Loop over 3rd dimension extracting 2D slice from first and 2nd dimensions
for f in xrange(work.shape[2]):
# Do even Qshift filters on rows.
y1 = work[:, :, f].T
y2 = np.vstack((coldfilt(y1, h0b, h0a), coldfilt(y1, h1b, h1a))).T
# Do even Qshift filters on columns.
work[s0a, :, f] = coldfilt(y2, h0b, h0a)
work[s0b, :, f] = coldfilt(y2, h1b, h1a)
# Return appropriate slices of output
return (
work[s0a, s1a, s2a], # LLL
np.concatenate(
(
cube2c(work[s0a, s1b, s2a]), # HLL
cube2c(work[s0b, s1a, s2a]), # LHL
cube2c(work[s0b, s1b, s2a]), # HHL
cube2c(work[s0a, s1a, s2b]), # LLH
cube2c(work[s0a, s1b, s2b]), # HLH
cube2c(work[s0b, s1a, s2b]), # LHH
cube2c(work[s0b, s1b, s2b]), # HLH
),
axis=3))
def test_good_input_size_non_orthogonal():
A = coldfilt(mandrill[:,:511], (1,1), (1,1))
B = coldfilt_gold(mandrill[:,:511], (1,1), (1,1))
assert_almost_equal(A, B)
def test_output_size():
Y = coldfilt(mandrill, (-1,1), (1,-1))
assert Y.shape == (mandrill.shape[0]/2, mandrill.shape[1])
Z = coldfilt_gold(mandrill, (-1,1), (1,-1))
assert_almost_equal(Y, Z)
def test_good_input_size():
A = coldfilt(mandrill[:,:511], (-1,1), (1,-1))
B = coldfilt_gold(mandrill[:,:511], (-1,1), (1,-1))
assert_almost_equal(A, B)
def test_real_wavelet():
h0a, h0b, g0a, g0b, h1a, h1b, g1a, g1b = qshift('qshift_d')
A = coldfilt(mandrill[:,:511], h1b, h1a)
B = coldfilt_gold(mandrill[:,:511], h1b, h1a)
assert_almost_equal(A, B)
def test_bad_input_size():
with raises(ValueError):
coldfilt(mandrill[:511,:], (-1,1), (1,-1))
def test_qshift():
h0a, h0b, g0a, g0b, h1a, h1b, g1a, g1b = qshift('qshift_d')
y = coldfilt(lena, h1b, h1b)
z = coldfilt_gold(lena, h1b, h1a)
assert_almost_equal(y, z)
def test_odd_filter():
coldfilt(lena, (-1,2,-1), (-1,2,1))
def _level2_xfm(X, h0a, h0b, h1a, h1b, ext_mode):
"""Perform level 2 or greater of the 3d transform.
"""
if ext_mode == 4:
if X.shape[0] % 4 != 0:
X = np.concatenate((X[[0],:,:], X, X[[-1],:,:]), 0)
if X.shape[1] % 4 != 0:
X = np.concatenate((X[:,[0],:], X, X[:,[-1],:]), 1)
if X.shape[2] % 4 != 0:
X = np.concatenate((X[:,:,[0]], X, X[:,:,[-1]]), 2)
elif self.ext_mode == 8:
if X.shape[0] % 8 != 0:
X = np.concatenate((X[(0,0),:,:], X, X[(-1,-1),:,:]), 0)
if X.shape[1] % 8 != 0:
X = np.concatenate((X[:,(0,0),:], X, X[:,(-1,-1),:]), 1)
if X.shape[2] % 8 != 0:
X = np.concatenate((X[:,:,(0,0)], X, X[:,:,(-1,-1)]), 2)
# Create work area
work_shape = np.asanyarray(X.shape)
work = np.zeros(work_shape, dtype=X.dtype)
# Form some useful slices
s0a = slice(None, work.shape[0] >> 1)
s1a = slice(None, work.shape[1] >> 1)
s2a = slice(None, work.shape[2] >> 1)
s0b = slice(work.shape[0] >> 1, None)
s1b = slice(work.shape[1] >> 1, None)
s2b = slice(work.shape[2] >> 1, None)
# Assign input
work = X
# Loop over 2nd dimension extracting 2D slice from first and 3rd dimensions
for f in xrange(work.shape[1]):
# extract slice (copy required because we overwrite the work array)
y = work[:, f, :].T.copy()
# Do even Qshift filters on 3rd dim.
work[:, f, s2b] = coldfilt(y, h1b, h1a).T
work[:, f, s2a] = coldfilt(y, h0b, h0a).T
# Loop over 3rd dimension extracting 2D slice from first and 2nd dimensions
for f in xrange(work.shape[2]):
# Do even Qshift filters on rows.
y1 = work[:, :, f].T
y2 = np.vstack((coldfilt(y1, h0b, h0a), coldfilt(y1, h1b, h1a))).T
# Do even Qshift filters on columns.
work[s0a, :, f] = coldfilt(y2, h0b, h0a)
work[s0b, :, f] = coldfilt(y2, h1b, h1a)
# Return appropriate slices of output
return (
work[s0a, s1a, s2a], # LLL
np.concatenate((
cube2c(work[s0a, s1b, s2a]), # HLL
cube2c(work[s0b, s1a, s2a]), # LHL
cube2c(work[s0b, s1b, s2a]), # HHL
cube2c(work[s0a, s1a, s2b]), # LLH
cube2c(work[s0a, s1b, s2b]), # HLH
cube2c(work[s0b, s1a, s2b]), # LHH
cube2c(work[s0b, s1b, s2b]), # HLH
), axis=3)
)
def test_odd_filter():
with raises(ValueError):
coldfilt(mandrill, (-1,2,-1), (-1,2,1))
