def test_minmax_normalize():
bvalue = 3000
S0 = 1
SNR = 100
sphere = get_sphere("symmetric362")
bvecs = np.concatenate(([[0, 0, 0]], sphere.vertices))
bvals = np.zeros(len(bvecs)) + bvalue
bvals[0] = 0
gtab = gradient_table(bvals, bvecs)
evals = np.array(([0.0017, 0.0003, 0.0003], [0.0017, 0.0003, 0.0003]))
S, sticks = multi_tensor(gtab, evals, S0, angles=[(0, 0), (90, 0)], fractions=[50, 50], snr=SNR)
odf = multi_tensor_odf(sphere.vertices, evals, angles=[(0, 0), (90, 0)], fractions=[50, 50])
odf2 = minmax_normalize(odf)
assert_equal(odf2.max(), 1)
assert_equal(odf2.min(), 0)
odf3 = np.empty(odf.shape)
odf3 = minmax_normalize(odf, odf3)
assert_equal(odf3.max(), 1)
assert_equal(odf3.min(), 0)
def test_minmax_normalize():
bvalue = 3000
S0 = 1
SNR = 100
sphere = get_sphere('symmetric362')
bvecs = np.concatenate(([[0, 0, 0]], sphere.vertices))
bvals = np.zeros(len(bvecs)) + bvalue
bvals[0] = 0
gtab = gradient_table(bvals, bvecs)
evals = np.array(([0.0017, 0.0003, 0.0003], [0.0017, 0.0003, 0.0003]))
multi_tensor(gtab, evals, S0, angles=[(0, 0), (90, 0)],
fractions=[50, 50], snr=SNR)
odf = multi_tensor_odf(sphere.vertices, evals, angles=[(0, 0), (90, 0)],
fractions=[50, 50])
odf2 = minmax_normalize(odf)
assert_equal(odf2.max(), 1)
assert_equal(odf2.min(), 0)
odf3 = np.empty(odf.shape)
odf3 = minmax_normalize(odf, odf3)
assert_equal(odf3.max(), 1)
assert_equal(odf3.min(), 0)
mask = data[..., 0] > 50
mask_small = mask[20:50,55:85, 38:40]
data_small = data[20:50,55:85, 38:40]
csamodel = CsaOdfModel(gtab, 4, smooth=0.006)
csa_fit = csamodel.fit(data_small)
sphere = get_sphere('symmetric724')
csa_odf = csa_fit.odf(sphere)
gfa_csa = gfa(csa_odf)
odfs = csa_odf.clip(0)
gfa_csa_wo_zeros = gfa(odfs)
csa_mm = minmax_normalize(odfs)
gfa_csa_mm = gfa(csa_mm)
qballmodel = QballModel(gtab, 6, smooth=0.006)
qball_fit = qballmodel.fit(data_small)
qball_odf = qball_fit.odf(sphere)
gfa_qball = gfa(qball_odf)
gfa_qball_mm = gfa(minmax_normalize(qball_odf))
print 'Saving GFAs...'
nib.save(nib.Nifti1Image(gfa_qball.astype('float32'), affine), 'gfa.nii.gz')
nib.save(nib.Nifti1Image(gfa_qball_mm.astype('float32'), affine), 'gfa_mm.nii.gz')
nib.save(nib.Nifti1Image(gfa_csa.astype('float32'), affine), 'gfa_csa.nii.gz')
nib.save(nib.Nifti1Image(gfa_csa_wo_zeros.astype('float32'), affine), 'gfa_csa_wo_neg.nii.gz')
nib.save(nib.Nifti1Image(gfa_csa_mm.astype('float32'), affine), 'gfa_csa_mm.nii.gz')
print('GFA.shape (%d, %d, %d)' % GFA.shape)
nib.save(nib.Nifti1Image(GFA.astype('float32'), affine), 'gfa.nii.gz')
from dipy.data import get_sphere
sphere = get_sphere('symmetric724')
csa_fit = csamodel.fit(data_small)
odfs = csa_fit.odf(sphere)
from dipy.viz import fvtk
r = fvtk.ren()
fvtk.add(r, fvtk.sphere_funcs(odfs, sphere, colormap='jet'))
fvtk.show(r)
fvtk.clear(r)
# min-max normalization
csa_mm = minmax_normalize(odfs)
r = fvtk.ren()
fvtk.add(r, fvtk.sphere_funcs(csa_mm, sphere, colormap='jet', norm=False))
fvtk.show(r)
fvtk.clear(r)
# Three ways to get the GFA
GFA = csapeaks.gfa
GFA_sh = csa_fit.gfa
GFA_odf = gfa(odfs)
coeff = csa_fit._shm_coef
nib.save(nib.Nifti1Image(GFA.astype('float32'), affine), 'gfa_small.nii.gz')
nib.save(nib.Nifti1Image(GFA_sh.astype('float32'), affine), 'gfa_sh_small.nii.gz')
nib.save(nib.Nifti1Image(GFA_sh.astype('float32'), affine), 'gfa_odf_small.nii.gz')
