def test_sf_to_sh():
# Subdividing a hemi_icosahedron twice produces 81 unique points, which
# is more than enough to fit a order 8 (45 coefficients) spherical harmonic
sphere = hemi_icosahedron.subdivide(2)
mevals = np.array(([0.0015, 0.0003, 0.0003], [0.0015, 0.0003, 0.0003]))
mevecs = [np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]),
np.array([[0, 1, 0], [1, 0, 0], [0, 0, 1]])]
odf = multi_tensor_odf(sphere.vertices, [0.5, 0.5], mevals, mevecs)
# 1D case with the 3 bases functions
odf_sh = sf_to_sh(odf, sphere, 8)
odf2 = sh_to_sf(odf_sh, sphere, 8)
assert_array_almost_equal(odf, odf2, 2)
odf_sh = sf_to_sh(odf, sphere, 8, "mrtrix")
odf2 = sh_to_sf(odf_sh, sphere, 8, "mrtrix")
assert_array_almost_equal(odf, odf2, 2)
odf_sh = sf_to_sh(odf, sphere, 8, "fibernav")
odf2 = sh_to_sf(odf_sh, sphere, 8, "fibernav")
assert_array_almost_equal(odf, odf2, 2)
# 2D case
odf2d = np.vstack((odf2, odf))
odf2d_sh = sf_to_sh(odf2d, sphere, 8)
odf2d_sf = sh_to_sf(odf2d_sh, sphere, 8)
assert_array_almost_equal(odf2d, odf2d_sf, 2)
def test_single_voxel_fit(self):
signal, gtab, expected = make_fake_signal()
sphere = hemi_icosahedron.subdivide(4)
model = self.model(gtab, sh_order=4, min_signal=1e-5,
assume_normed=True)
fit = model.fit(signal)
odf = fit.odf(sphere)
assert_equal(odf.shape, sphere.phi.shape)
directions, _, _ = peak_directions(odf, sphere)
# Check the same number of directions
n = len(expected)
assert_equal(len(directions), n)
# Check directions are unit vectors
cos_similarity = (directions * directions).sum(-1)
assert_array_almost_equal(cos_similarity, np.ones(n))
# Check the directions == expected or -expected
cos_similarity = (directions * expected).sum(-1)
assert_array_almost_equal(abs(cos_similarity), np.ones(n))
# Test normalize data
model = self.model(gtab, sh_order=4, min_signal=1e-5,
assume_normed=False)
fit = model.fit(signal * 5)
odf_with_norm = fit.odf(sphere)
assert_array_almost_equal(odf, odf_with_norm)
def test_hemisphere_find_closest():
hemisphere1 = hemi_icosahedron.subdivide(4)
for ii in range(hemisphere1.vertices.shape[0]):
nt.assert_equal(hemisphere1.find_closest(hemisphere1.vertices[ii]), ii)
nt.assert_equal(hemisphere1.find_closest(-hemisphere1.vertices[ii]), ii)
nt.assert_equal(hemisphere1.find_closest(hemisphere1.vertices[ii] * 2),
ii)
def test_gfa(self):
signal, gtab, expected = make_fake_signal()
signal = np.ones((2, 3, 4, 1)) * signal
sphere = hemi_icosahedron.subdivide(3)
model = self.model(gtab, 6, min_signal=1e-5)
fit = model.fit(signal)
gfa_shm = fit.gfa
gfa_odf = odf.gfa(fit.odf(sphere))
assert_array_almost_equal(gfa_shm, gfa_odf, 3)
def test_real_sph_harm_fibernav():
# This test should do for now
# The mrtrix basis should be the same as re-ordering and re-scaling the
# fibernav basis
new_order = [0, 5, 4, 3, 2, 1, 14, 13, 12, 11, 10, 9, 8, 7, 6]
sphere = hemi_icosahedron.subdivide(2)
basis, m, n = real_sph_harm_mrtrix(4, sphere.theta, sphere.phi)
expected = basis[:, new_order]
expected *= np.where(m == 0, 1., np.sqrt(2))
fibernav_basis, m, n = real_sph_harm_fibernav(4, sphere.theta, sphere.phi)
assert_array_almost_equal(fibernav_basis, expected)
def test_real_sym_sh_basis():
# This test should do for now
# The tournier07 basis should be the same as re-ordering and re-scaling the
# descoteaux07 basis
new_order = [0, 5, 4, 3, 2, 1, 14, 13, 12, 11, 10, 9, 8, 7, 6]
sphere = hemi_icosahedron.subdivide(2)
basis, m, n = real_sym_sh_mrtrix(4, sphere.theta, sphere.phi)
expected = basis[:, new_order]
expected *= np.where(m == 0, 1., np.sqrt(2))
descoteaux07_basis, m, n = real_sym_sh_basis(4, sphere.theta, sphere.phi)
assert_array_almost_equal(descoteaux07_basis, expected)
def test_real_sym_sh_basis():
# This test should do for now
# The tournier07 basis should be the same as re-ordering and re-scaling the
# descoteaux07 basis
new_order = [0, 5, 4, 3, 2, 1, 14, 13, 12, 11, 10, 9, 8, 7, 6]
sphere = hemi_icosahedron.subdivide(2)
basis, m, n = real_sym_sh_mrtrix(4, sphere.theta, sphere.phi)
expected = basis[:, new_order]
expected *= np.where(m == 0, 1., np.sqrt(2))
descoteaux07_basis, m, n = real_sym_sh_basis(4, sphere.theta, sphere.phi)
assert_array_almost_equal(descoteaux07_basis, expected)
def test_gfa(self):
signal, gtab, expected = make_fake_signal()
signal = np.ones((2, 3, 4, 1)) * signal
sphere = hemi_icosahedron.subdivide(3)
model = self.model(gtab, 6, min_signal=1e-5)
fit = model.fit(signal)
gfa_shm = fit.gfa
gfa_odf = odf.gfa(fit.odf(sphere))
assert_array_almost_equal(gfa_shm, gfa_odf, 3)
# gfa should be 0 if all coefficients are 0 (masked areas)
mask = np.zeros(signal.shape[:-1])
fit = model.fit(signal, mask)
assert_array_equal(fit.gfa, 0)
def test_gfa(self):
signal, gtab, expected = make_fake_signal()
signal = np.ones((2, 3, 4, 1)) * signal
sphere = hemi_icosahedron.subdivide(3)
model = self.model(gtab, 6, min_signal=1e-5)
fit = model.fit(signal)
gfa_shm = fit.gfa
gfa_odf = odf.gfa(fit.odf(sphere))
assert_array_almost_equal(gfa_shm, gfa_odf, 3)
# gfa should be 0 if all coefficients are 0 (masked areas)
mask = np.zeros(signal.shape[:-1])
fit = model.fit(signal, mask)
assert_array_equal(fit.gfa, 0)
def make_fake_signal():
hemisphere = hemi_icosahedron.subdivide(2)
bvecs = np.concatenate(([[0, 0, 0]], hemisphere.vertices))
bvals = np.zeros(len(bvecs)) + 2000
bvals[0] = 0
gtab = gradient_table(bvals, bvecs)
evals = np.array([[2.1, .2, .2], [.2, 2.1, .2]]) * 10 ** -3
evecs0 = np.eye(3)
evecs1 = evecs0
a = evecs0[0]
b = evecs1[1]
S1 = single_tensor(gtab, .55, evals[0], evecs0)
S2 = single_tensor(gtab, .45, evals[1], evecs1)
return S1 + S2, gtab, np.vstack([a, b])
def make_fake_signal():
hemisphere = hemi_icosahedron.subdivide(2)
bvecs = np.concatenate(([[0, 0, 0]], hemisphere.vertices))
bvals = np.zeros(len(bvecs)) + 2000
bvals[0] = 0
gtab = gradient_table(bvals, bvecs)
evals = np.array([[2.1, .2, .2], [.2, 2.1, .2]]) * 10**-3
evecs0 = np.eye(3)
evecs1 = evecs0
a = evecs0[0]
b = evecs1[1]
S1 = single_tensor(gtab, .55, evals[0], evecs0)
S2 = single_tensor(gtab, .45, evals[1], evecs1)
return S1 + S2, gtab, np.vstack([a, b])
def test_sf_to_sh():
# Subdividing a hemi_icosahedron twice produces 81 unique points, which
# is more than enough to fit a order 8 (45 coefficients) spherical harmonic
sphere = hemi_icosahedron.subdivide(2)
mevals = np.array(([0.0015, 0.0003, 0.0003], [0.0015, 0.0003, 0.0003]))
angles = [(0, 0), (90, 0)]
odf = multi_tensor_odf(sphere.vertices, mevals, angles, [50, 50])
# 1D case with the 3 bases functions
odf_sh = sf_to_sh(odf, sphere, 8)
odf2 = sh_to_sf(odf_sh, sphere, 8)
assert_array_almost_equal(odf, odf2, 2)
odf_sh = sf_to_sh(odf, sphere, 8, "tournier07")
odf2 = sh_to_sf(odf_sh, sphere, 8, "tournier07")
assert_array_almost_equal(odf, odf2, 2)
# Test the basis naming deprecation
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always", DeprecationWarning)
odf_sh_mrtrix = sf_to_sh(odf, sphere, 8, "mrtrix")
odf2_mrtrix = sh_to_sf(odf_sh_mrtrix, sphere, 8, "mrtrix")
assert_array_almost_equal(odf, odf2_mrtrix, 2)
assert len(w) != 0
assert issubclass(w[-1].category, DeprecationWarning)
warnings.simplefilter("default", DeprecationWarning)
odf_sh = sf_to_sh(odf, sphere, 8, "descoteaux07")
odf2 = sh_to_sf(odf_sh, sphere, 8, "descoteaux07")
assert_array_almost_equal(odf, odf2, 2)
# Test the basis naming deprecation
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always", DeprecationWarning)
odf_sh_fibernav = sf_to_sh(odf, sphere, 8, "fibernav")
odf2_fibernav = sh_to_sf(odf_sh_fibernav, sphere, 8, "fibernav")
assert_array_almost_equal(odf, odf2_fibernav, 2)
assert len(w) != 0
assert issubclass(w[-1].category, DeprecationWarning)
warnings.simplefilter("default", DeprecationWarning)
# 2D case
odf2d = np.vstack((odf2, odf))
odf2d_sh = sf_to_sh(odf2d, sphere, 8)
odf2d_sf = sh_to_sf(odf2d_sh, sphere, 8)
assert_array_almost_equal(odf2d, odf2d_sf, 2)
def test_sf_to_sh():
# Subdividing a hemi_icosahedron twice produces 81 unique points, which
# is more than enough to fit a order 8 (45 coefficients) spherical harmonic
sphere = hemi_icosahedron.subdivide(2)
mevals = np.array(([0.0015, 0.0003, 0.0003], [0.0015, 0.0003, 0.0003]))
angles = [(0, 0), (90, 0)]
odf = multi_tensor_odf(sphere.vertices, mevals, angles, [50, 50])
# 1D case with the 3 bases functions
odf_sh = sf_to_sh(odf, sphere, 8)
odf2 = sh_to_sf(odf_sh, sphere, 8)
assert_array_almost_equal(odf, odf2, 2)
odf_sh = sf_to_sh(odf, sphere, 8, "tournier07")
odf2 = sh_to_sf(odf_sh, sphere, 8, "tournier07")
assert_array_almost_equal(odf, odf2, 2)
# Test the basis naming deprecation
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always", DeprecationWarning)
odf_sh_mrtrix = sf_to_sh(odf, sphere, 8, "mrtrix")
odf2_mrtrix = sh_to_sf(odf_sh_mrtrix, sphere, 8, "mrtrix")
assert_array_almost_equal(odf, odf2_mrtrix, 2)
assert len(w) != 0
assert issubclass(w[-1].category, DeprecationWarning)
warnings.simplefilter("default", DeprecationWarning)
odf_sh = sf_to_sh(odf, sphere, 8, "descoteaux07")
odf2 = sh_to_sf(odf_sh, sphere, 8, "descoteaux07")
assert_array_almost_equal(odf, odf2, 2)
# Test the basis naming deprecation
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always", DeprecationWarning)
odf_sh_fibernav = sf_to_sh(odf, sphere, 8, "fibernav")
odf2_fibernav = sh_to_sf(odf_sh_fibernav, sphere, 8, "fibernav")
assert_array_almost_equal(odf, odf2_fibernav, 2)
assert len(w) != 0
assert issubclass(w[-1].category, DeprecationWarning)
warnings.simplefilter("default", DeprecationWarning)
# 2D case
odf2d = np.vstack((odf2, odf))
odf2d_sh = sf_to_sh(odf2d, sphere, 8)
odf2d_sf = sh_to_sf(odf2d_sh, sphere, 8)
assert_array_almost_equal(odf2d, odf2d_sf, 2)
def test_sf_to_sh():
# Subdividing a hemi_icosahedron twice produces 81 unique points, which
# is more than enough to fit a order 8 (45 coefficients) spherical harmonic
hemisphere = hemi_icosahedron.subdivide(2)
mevals = np.array([[0.0015, 0.0003, 0.0003], [0.0015, 0.0003, 0.0003]])
angles = [(0, 0), (60, 0)]
odf = multi_tensor_odf(hemisphere.vertices, mevals, angles, [50, 50])
# 1D case with the 2 symmetric bases functions
odf_sh = sf_to_sh(odf, hemisphere, 8, "tournier07")
odf_reconst = sh_to_sf(odf_sh, hemisphere, 8, "tournier07")
assert_array_almost_equal(odf, odf_reconst, 2)
odf_sh = sf_to_sh(odf, hemisphere, 8, "descoteaux07")
odf_reconst = sh_to_sf(odf_sh, hemisphere, 8, "descoteaux07")
assert_array_almost_equal(odf, odf_reconst, 2)
# We now create an asymmetric signal
# to try out our full SH basis
mevals = np.array([[0.0015, 0.0003, 0.0003]])
angles = [(0, 0)]
odf2 = multi_tensor_odf(hemisphere.vertices, mevals, angles, [100])
# We simulate our asymmetric signal by using a different ODF
# per hemisphere. The sphere used is a concatenation of the
# vertices of our hemisphere, for a total of 162 vertices.
sphere = Sphere(xyz=np.vstack((hemisphere.vertices, -hemisphere.vertices)))
asym_odf = np.append(odf, odf2)
# Try out full bases with order 10 (121 coefficients)
odf_sh = sf_to_sh(asym_odf, sphere, 10, "tournier07_full")
odf_reconst = sh_to_sf(odf_sh, sphere, 10, "tournier07_full")
assert_array_almost_equal(odf_reconst, asym_odf, 2)
odf_sh = sf_to_sh(asym_odf, sphere, 10, "descoteaux07_full")
odf_reconst = sh_to_sf(odf_sh, sphere, 10, "descoteaux07_full")
assert_array_almost_equal(odf_reconst, asym_odf, 2)
# An invalid basis name should raise an error
assert_raises(ValueError, sh_to_sf, odf, hemisphere, basis_type="")
assert_raises(ValueError, sf_to_sh, odf_sh, hemisphere, basis_type="")
# 2D case
odf2d = np.vstack((odf, odf))
odf2d_sh = sf_to_sh(odf2d, hemisphere, 8)
odf2d_sf = sh_to_sf(odf2d_sh, hemisphere, 8)
assert_array_almost_equal(odf2d, odf2d_sf, 2)
def test_convert_sh_to_legacy():
hemisphere = hemi_icosahedron.subdivide(2)
mevals = np.array([[0.0015, 0.0003, 0.0003], [0.0015, 0.0003, 0.0003]])
angles = [(0, 0), (60, 0)]
odf = multi_tensor_odf(hemisphere.vertices, mevals, angles, [50, 50])
sh_coeffs = sf_to_sh(odf, hemisphere, 8, legacy=False)
converted_coeffs = convert_sh_to_legacy(sh_coeffs, 'descoteaux07')
expected_coeffs = sf_to_sh(odf, hemisphere, 8, legacy=True)
assert_array_almost_equal(converted_coeffs, expected_coeffs, 2)
sh_coeffs = sf_to_sh(odf,
hemisphere,
8,
basis_type='tournier07',
legacy=False)
converted_coeffs = convert_sh_to_legacy(sh_coeffs, 'tournier07')
expected_coeffs = sf_to_sh(odf,
hemisphere,
8,
basis_type='tournier07',
legacy=True)
assert_array_almost_equal(converted_coeffs, expected_coeffs, 2)
# 2D case
odfs = np.array([odf, odf])
sh_coeffs = sf_to_sh(odfs,
hemisphere,
8,
basis_type='tournier07',
full_basis=True,
legacy=False)
converted_coeffs = convert_sh_to_legacy(sh_coeffs,
'tournier07',
full_basis=True)
expected_coeffs = sf_to_sh(odfs,
hemisphere,
8,
basis_type='tournier07',
legacy=True,
full_basis=True)
assert_array_almost_equal(converted_coeffs, expected_coeffs, 2)
assert_raises(ValueError, convert_sh_to_legacy, sh_coeffs, '', True)
def test_hat_and_lcr():
hemi = hemi_icosahedron.subdivide(3)
m, n = sph_harm_ind_list(8)
B = real_sph_harm(m, n, hemi.theta[:, None], hemi.phi[:, None])
H = hat(B)
B_hat = np.dot(H, B)
assert_array_almost_equal(B, B_hat)
R = lcr_matrix(H)
d = np.arange(len(hemi.theta))
r = d - np.dot(H, d)
lev = np.sqrt(1 - H.diagonal())
r /= lev
r -= r.mean()
r2 = np.dot(R, d)
assert_array_almost_equal(r, r2)
r3 = np.dot(d, R.T)
assert_array_almost_equal(r, r3)
def test_hat_and_lcr():
hemi = hemi_icosahedron.subdivide(3)
m, n = sph_harm_ind_list(8)
B = real_sph_harm(m, n, hemi.theta[:, None], hemi.phi[:, None])
H = hat(B)
B_hat = np.dot(H, B)
assert_array_almost_equal(B, B_hat)
R = lcr_matrix(H)
d = np.arange(len(hemi.theta))
r = d - np.dot(H, d)
lev = np.sqrt(1 - H.diagonal())
r /= lev
r -= r.mean()
r2 = np.dot(R, d)
assert_array_almost_equal(r, r2)
r3 = np.dot(d, R.T)
assert_array_almost_equal(r, r3)
def test_real_full_sh_basis():
vertices = hemi_icosahedron.subdivide(2).vertices
mevals = np.array([[0.0015, 0.0003, 0.0003], [0.0015, 0.0003, 0.0003]])
angles = [(0, 0), (60, 0)]
odf = multi_tensor_odf(vertices, mevals, angles, [50, 50])
mevals = np.array([[0.0015, 0.0003, 0.0003]])
angles = [(0, 0)]
odf2 = multi_tensor_odf(-vertices, mevals, angles, [100])
sphere = Sphere(xyz=np.vstack((vertices, -vertices)))
# Asymmetric spherical function with 162 coefficients
sf = np.append(odf, odf2)
# In order for our approximation to be precise enough, we
# will use a SH basis of orders up to 10 (121 coefficients)
B, m, n = real_full_sh_basis(10, sphere.theta, sphere.phi)
invB = smooth_pinv(B, L=np.zeros_like(n))
sh_coefs = np.dot(invB, sf)
sf_approx = np.dot(B, sh_coefs)
assert_array_almost_equal(sf_approx, sf, 2)
def test_convert_sh_to_full_basis():
hemisphere = hemi_icosahedron.subdivide(2)
mevals = np.array([[0.0015, 0.0003, 0.0003], [0.0015, 0.0003, 0.0003]])
angles = [(0, 0), (60, 0)]
odf = multi_tensor_odf(hemisphere.vertices, mevals, angles, [50, 50])
with warnings.catch_warnings():
warnings.filterwarnings("ignore",
message=descoteaux07_legacy_msg,
category=PendingDeprecationWarning)
sh_coeffs = sf_to_sh(odf, hemisphere, 8)
full_sh_coeffs = convert_sh_to_full_basis(sh_coeffs)
with warnings.catch_warnings():
warnings.filterwarnings("ignore",
message=descoteaux07_legacy_msg,
category=PendingDeprecationWarning)
odf_reconst = sh_to_sf(full_sh_coeffs, hemisphere, 8, full_basis=True)
assert_array_almost_equal(odf, odf_reconst, 2)
def test_smooth_pinv():
hemi = hemi_icosahedron.subdivide(2)
m, n = sph_harm_ind_list(4)
B = real_sph_harm(m, n, hemi.theta[:, None], hemi.phi[:, None])
L = np.zeros(len(m))
C = smooth_pinv(B, L)
D = np.dot(npl.inv(np.dot(B.T, B)), B.T)
assert_array_almost_equal(C, D)
L = n * (n + 1) * .05
C = smooth_pinv(B, L)
L = np.diag(L)
D = np.dot(npl.inv(np.dot(B.T, B) + L * L), B.T)
assert_array_almost_equal(C, D)
L = np.arange(len(n)) * .05
C = smooth_pinv(B, L)
L = np.diag(L)
D = np.dot(npl.inv(np.dot(B.T, B) + L * L), B.T)
assert_array_almost_equal(C, D)
def test_smooth_pinv():
hemi = hemi_icosahedron.subdivide(2)
m, n = sph_harm_ind_list(4)
B = real_sph_harm(m, n, hemi.theta[:, None], hemi.phi[:, None])
L = np.zeros(len(m))
C = smooth_pinv(B, L)
D = np.dot(npl.inv(np.dot(B.T, B)), B.T)
assert_array_almost_equal(C, D)
L = n * (n + 1) * .05
C = smooth_pinv(B, L)
L = np.diag(L)
D = np.dot(npl.inv(np.dot(B.T, B) + L * L), B.T)
assert_array_almost_equal(C, D)
L = np.arange(len(n)) * .05
C = smooth_pinv(B, L)
L = np.diag(L)
D = np.dot(npl.inv(np.dot(B.T, B) + L * L), B.T)
assert_array_almost_equal(C, D)
def test_real_sh_descoteaux1():
# This test should do for now
# The tournier07 basis should be the same as re-ordering and re-scaling the
# descoteaux07 basis
new_order = [0, 5, 4, 3, 2, 1, 14, 13, 12, 11, 10, 9, 8, 7, 6]
sphere = hemi_icosahedron.subdivide(2)
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
basis, m, n = real_sym_sh_mrtrix(4, sphere.theta, sphere.phi)
expected = basis[:, new_order]
expected *= np.where(m == 0, 1., np.sqrt(2))
with warnings.catch_warnings(record=True) as w:
descoteaux07_basis, m, n = real_sh_descoteaux(4, sphere.theta,
sphere.phi)
npt.assert_equal(len(w), 1)
npt.assert_(issubclass(w[0].category, PendingDeprecationWarning))
npt.assert_(descoteaux07_legacy_msg in str(w[0].message))
assert_array_almost_equal(descoteaux07_basis, expected)
def test_convert_sh_to_legacy():
hemisphere = hemi_icosahedron.subdivide(2)
mevals = np.array([[0.0015, 0.0003, 0.0003], [0.0015, 0.0003, 0.0003]])
angles = [(0, 0), (60, 0)]
odf = multi_tensor_odf(hemisphere.vertices, mevals, angles, [50, 50])
sh_coeffs = sf_to_sh(odf, hemisphere, 8, legacy=False)
converted_coeffs = convert_sh_to_legacy(sh_coeffs, 'descoteaux07')
with warnings.catch_warnings():
warnings.filterwarnings("ignore",
message=descoteaux07_legacy_msg,
category=PendingDeprecationWarning)
expected_coeffs = sf_to_sh(odf, hemisphere, 8, legacy=True)
assert_array_almost_equal(converted_coeffs, expected_coeffs, 2)
sh_coeffs = sf_to_sh(odf,
hemisphere,
8,
basis_type='tournier07',
legacy=False)
converted_coeffs = convert_sh_to_legacy(sh_coeffs, 'tournier07')
with warnings.catch_warnings():
warnings.filterwarnings("ignore",
message=tournier07_legacy_msg,
category=PendingDeprecationWarning)
expected_coeffs = sf_to_sh(odf,
hemisphere,
8,
basis_type='tournier07',
legacy=True)
assert_array_almost_equal(converted_coeffs, expected_coeffs, 2)
# 2D case
odfs = np.array([odf, odf])
sh_coeffs = sf_to_sh(odfs,
hemisphere,
8,
basis_type='tournier07',
full_basis=True,
legacy=False)
converted_coeffs = convert_sh_to_legacy(sh_coeffs,
'tournier07',
full_basis=True)
with warnings.catch_warnings():
warnings.filterwarnings("ignore",
message=tournier07_legacy_msg,
category=PendingDeprecationWarning)
expected_coeffs = sf_to_sh(odfs,
hemisphere,
8,
basis_type='tournier07',
legacy=True,
full_basis=True)
assert_array_almost_equal(converted_coeffs, expected_coeffs, 2)
assert_raises(ValueError, convert_sh_to_legacy, sh_coeffs, '', True)
