def main():
#set some values to be used later
sh_order = 6
verts, edges, efaces = create_unit_sphere(4)
#read_data from disk
data, fa, bvec, bval, voxel_size = sample_hardi_data()
data_slice = data[32:76, 32:76, 26:27]
fa_slice = fa[32:76, 32:76, 26]
#normalize data by dividing by b0, this is needed so we can take log later
norm_data = normalize_data(data_slice, bval, min_signal=1)
#create an instance of the model
model_instance = MonoExpOpdfModel(sh_order, bval, bvec, .006)
model_instance.set_sampling_points(verts, edges)
#use the model it fit the data
opdfs_sampled_at_verts = model_instance.evaluate(norm_data)
opdfs_sph_harm_coef = model_instance.fit_data(norm_data)
#display the opdf blobs using mayavi
faces = edges[efaces, 0]
show_blobs(opdfs_sampled_at_verts, verts, faces)
mlab.imshow(fa_slice, colormap='gray', interpolate=False)
mlab.show()
## verts = np.column_stack(sph2car(theta, phi))
## from dipy.core.meshes import faces_from_vertices
## faces = faces_from_vertices(verts)
def separation_from_odf(odf):
# Find angles
from dipy.reconst.recspeed import local_maxima
p, i = local_maxima(odf, edges)
p = p[:2]
i = i[:2]
print "Peaks:", p
print "Angular separation:", np.rad2deg(np.arccos(np.abs(np.dot(verts[i[0]], verts[i[1]]))))
ODFs = []
#m = SlowAdcOpdfModel(coords['b'], sampling_xyz, sh_order=8, odf_vertices=verts)
m = MonoExpOpdfModel(coords['b'], sampling_xyz, sh_order=8, odf_vertices=verts)
for k, fn in enumerate(sorted(glob.glob(os.path.join(sph_io.data_path,
'odf_coeffs_*.npz')))):
data = sph_io.load(os.path.basename(fn))
print "Dipy model..."
odf = m.evaluate_odf(data['signal'])
ODFs.append(odf)
separation_from_odf(odf)
print "Quadrature model..."
odf = kernel_reconstruct(coords['odf_theta'], coords['odf_phi'], data['beta'],
theta, phi,
kernel=even_kernel, N=data['kernel_N'])
odf[odf < 0] = 0
