def show_sph_grid():
r=fvtk.ren()
print verts.shape, faces.shape
sph=np.abs(np.dot(gradients[1],verts.T)**2)
print sph.shape
cols=fvtk.colors(sph,'jet')
#fvtk.add(r,fvtk.point(verts,cols,point_radius=.1,theta=10,phi=10))
for (i,v) in enumerate(gradients):
fvtk.label(r,str(i),pos=v,scale=(.02,.02,.02))
if i in [62,76,58]:
fvtk.label(r,str(i),pos=v,scale=(.05,.05,.05),color=(1,0,0))
fvtk.show(r)
def simulations_marta():
#gq_tn_calc_save()
#a_few_phantoms()
#sd=['fibres_2_SNR_100_angle_60_l1_1.4_l2_0.35_l3_0.35_iso_0_diso_00']
#sd=['fibres_2_SNR_60_angle_60_l1_1.4_l2_0.35_l3_0.35_iso_0_diso_00']
#sd=['fibres_2_SNR_100_angle_60_l1_1.4_l2_0.35_l3_0.35_iso_1_diso_0.7']
sd=['fibres_2_SNR_100_angle_90_l1_1.4_l2_0.35_l3_0.35_iso_0_diso_00']
#sd=['fibres_1_SNR_100_angle_00_l1_1.4_l2_0.35_l3_0.35_iso_0_diso_00']
#sd=['fibres_2_SNR_20_angle_90_l1_1.4_l2_0.35_l3_0.35_iso_0_diso_00']
#for simfile in simdata:
np.set_printoptions(2)
dotpow=6
width=6
sincpow=2
sampling_length=1.2
print dotpow,width,sincpow
print sampling_length
verts,faces=get_sphere('symmetric362')
for simfile in sd:
data=np.loadtxt(simdir+simfile)
sf=simfile.split('_')
b_vals_dirs=np.loadtxt(simdir+'Dir_and_bvals_DSI_marta.txt')
bvals=b_vals_dirs[:,0]*1000
gradients=b_vals_dirs[:,1:]
data2=data[::1000,:]
table={'fibres':sf[1],'snr':sf[3],'angle':sf[5],'l1':sf[7],'l2':sf[9],\
'l3':sf[11],'iso':sf[13],'diso':sf[15],\
'data':data2,'bvals':bvals,'gradients':gradients}
print table['data'].shape
pdi=ProjectiveDiffusivity(table['data'],table['bvals'],table['gradients'],dotpow,width,sincpow)
gqs=GeneralizedQSampling(table['data'],table['bvals'],table['gradients'],sampling_length)
ten=Tensor(table['data'],table['bvals'],table['gradients'])
r=fvtk.ren()
for i in range(10):#range(len(sdi.xa())):
print 'No:',i
print 'simulation fibres ',table['fibres'], ' snr ',table['snr'],' angle ', table['angle']
pdiind=pdi.ind()[i]
gqsind=gqs.ind()[i]
print 'indices',pdiind,gqsind,\
np.rad2deg(np.arccos(np.dot(verts[pdiind[0]],verts[pdiind[1]]))),\
np.rad2deg(np.arccos(np.dot(verts[gqsind[0]],verts[gqsind[1]])))
#ten.ind()[i],
print 'peaks', pdi.xa()[i]*10**3,gqs.qa()[i]
pd=pdi.spherical_diffusivity(table['data'][i])#*10**3
#print 'pd stat',pd.min(),pd.max(),pd.mean(),pd.std()
#colors=fvtk.colors(sdf,'jet')
sdfcol=np.interp(pd,[pd.mean()-4*pd.std(),pd.mean()+4*pd.std()],[0,1])
colors=fvtk.colors(sdfcol,'jet',False)
fvtk.add(r,fvtk.point(5*pdi.odf_vertices+np.array([12*i,0,0]),colors,point_radius=.6,theta=10,phi=10))
odf=gqs.odf(table['data'][i])
colors=fvtk.colors(odf,'jet')
fvtk.add(r,fvtk.point(5*gqs.odf_vertices+np.array([12*i,-12,0]),colors,point_radius=.6,theta=10,phi=10))
fvtk.show(r)
def test():
# img=nib.load('/home/eg309/Data/project01_dsi/connectome_0001/tp1/RAWDATA/OUT/mr000001.nii.gz')
btable = np.loadtxt(get_data("dsi515btable"))
# volume size
sz = 16
# shifting
origin = 8
# hanning width
filter_width = 32.0
# number of signal sampling points
n = 515
# odf radius
radius = np.arange(2.1, 6, 0.2)
# create q-table
bv = btable[:, 0]
bmin = np.sort(bv)[1]
bv = np.sqrt(bv / bmin)
qtable = np.vstack((bv, bv, bv)).T * btable[:, 1:]
qtable = np.floor(qtable + 0.5)
# copy bvals and bvecs
bvals = btable[:, 0]
bvecs = btable[:, 1:]
# S=img.get_data()[38,50,20]#[96/2,96/2,20]
S, stics = SticksAndBall(
bvals, bvecs, d=0.0015, S0=100, angles=[(0, 0), (60, 0), (90, 90)], fractions=[0, 0, 0], snr=None
)
S2 = S.copy()
S2 = S2.reshape(1, len(S))
dn = DiffusionNabla(S2, bvals, bvecs, auto=False)
pR = dn.equators
odf = dn.odf(S)
# Xs=dn.precompute_interp_coords()
peaks, inds = peak_finding(odf.astype("f8"), dn.odf_faces.astype("uint16"))
print peaks
print peaks / peaks.min()
# print dn.PK
dn.fit()
print dn.PK
# """
ren = fvtk.ren()
colors = fvtk.colors(odf, "jet")
fvtk.add(ren, fvtk.point(dn.odf_vertices, colors, point_radius=0.05, theta=8, phi=8))
fvtk.show(ren)
# """
stop
# ds=DiffusionSpectrum(S2,bvals,bvecs)
# tpr=ds.pdf(S)
# todf=ds.odf(tpr)
"""
#show projected signal
Bvecs=np.concatenate([bvecs[1:],-bvecs[1:]])
X0=np.dot(np.diag(np.concatenate([S[1:],S[1:]])),Bvecs)
ren=fvtk.ren()
fvtk.add(ren,fvtk.point(X0,fvtk.yellow,1,2,16,16))
fvtk.show(ren)
"""
# qtable=5*matrix[:,1:]
# calculate radius for the hanning filter
r = np.sqrt(qtable[:, 0] ** 2 + qtable[:, 1] ** 2 + qtable[:, 2] ** 2)
# setting hanning filter width and hanning
hanning = 0.5 * np.cos(2 * np.pi * r / filter_width)
# center and index in q space volume
q = qtable + origin
q = q.astype("i8")
# apply the hanning filter
values = S * hanning
"""
#plot q-table
ren=fvtk.ren()
colors=fvtk.colors(values,'jet')
fvtk.add(ren,fvtk.point(q,colors,1,0.1,6,6))
fvtk.show(ren)
"""
# create the signal volume
Sq = np.zeros((sz, sz, sz))
for i in range(n):
Sq[q[i][0], q[i][1], q[i][2]] += values[i]
# apply fourier transform
Pr = fftshift(np.abs(np.real(fftn(fftshift(Sq), (sz, sz, sz)))))
# """
ren = fvtk.ren()
vol = fvtk.volume(Pr)
fvtk.add(ren, vol)
fvtk.show(ren)
# """
"""
from enthought.mayavi import mlab
mlab.pipeline.volume(mlab.pipeline.scalar_field(Sq))
mlab.show()
"""
# vertices, edges, faces = create_unit_sphere(5)
vertices, faces = sphere_vf_from("symmetric362")
odf = np.zeros(len(vertices))
for m in range(len(vertices)):
xi = origin + radius * vertices[m, 0]
yi = origin + radius * vertices[m, 1]
zi = origin + radius * vertices[m, 2]
PrI = map_coordinates(Pr, np.vstack((xi, yi, zi)), order=1)
for i in range(len(radius)):
odf[m] = odf[m] + PrI[i] * radius[i] ** 2
"""
ren=fvtk.ren()
colors=fvtk.colors(odf,'jet')
fvtk.add(ren,fvtk.point(vertices,colors,point_radius=.05,theta=8,phi=8))
fvtk.show(ren)
"""
"""
#Pr[Pr<500]=0
ren=fvtk.ren()
#ren.SetBackground(1,1,1)
fvtk.add(ren,fvtk.volume(Pr))
fvtk.show(ren)
"""
peaks, inds = peak_finding(odf.astype("f8"), faces.astype("uint16"))
Eq = np.zeros((sz, sz, sz))
for i in range(n):
Eq[q[i][0], q[i][1], q[i][2]] += S[i] / S[0]
LEq = laplace(Eq)
# Pr[Pr<500]=0
ren = fvtk.ren()
# ren.SetBackground(1,1,1)
fvtk.add(ren, fvtk.volume(Eq))
fvtk.show(ren)
phis = np.linspace(0, 2 * np.pi, 100)
planars = []
for phi in phis:
planars.append(sphere2cart(1, np.pi / 2, phi))
planars = np.array(planars)
planarsR = []
for v in vertices:
R = vec2vec_rotmat(np.array([0, 0, 1]), v)
planarsR.append(np.dot(R, planars.T).T)
"""
ren=fvtk.ren()
fvtk.add(ren,fvtk.point(planarsR[0],fvtk.green,1,0.1,8,8))
fvtk.add(ren,fvtk.point(2*planarsR[1],fvtk.red,1,0.1,8,8))
fvtk.show(ren)
"""
azimsums = []
for disk in planarsR:
diskshift = 4 * disk + origin
# Sq0=map_coordinates(Sq,diskshift.T,order=1)
# azimsums.append(np.sum(Sq0))
# Eq0=map_coordinates(Eq,diskshift.T,order=1)
# azimsums.append(np.sum(Eq0))
LEq0 = map_coordinates(LEq, diskshift.T, order=1)
azimsums.append(np.sum(LEq0))
azimsums = np.array(azimsums)
# """
ren = fvtk.ren()
colors = fvtk.colors(azimsums, "jet")
fvtk.add(ren, fvtk.point(vertices, colors, point_radius=0.05, theta=8, phi=8))
fvtk.show(ren)
# """
# for p in planarsR[0]:
"""
#print grad3.shape
#vertices = grad3*gradients
vertices = gradients
if omit > 0:
vertices = vertices[omit:,:]
if entry['hemi']:
vertices = np.vstack([vertices, -vertices])
return vertices[omit:,:]
print sphere_dic.keys()
#vertices = get_vertex_set('create5')
#vertices = get_vertex_set('siem64')
#vertices = get_vertex_set('dsi102')
vertices = get_vertex_set('fy362')
gradients = get_vertex_set('siem64')
gradients = gradients[:gradients.shape[0]/2]
print gradients.shape
from dipy.viz import fvtk
sph=-np.sinc(np.dot(gradients[1],vertices.T))
r=fvtk.ren()
#sph = np.arange(vertices.shape[0])
print sph.shape
cols=fvtk.colors(sph,'jet')
fvtk.add(r,fvtk.point(vertices,cols,point_radius=.1,theta=10,phi=10))
fvtk.show(r)
#print grad3.shape
#vertices = grad3*gradients
vertices = gradients
if omit > 0:
vertices = vertices[omit:, :]
if entry['hemi']:
vertices = np.vstack([vertices, -vertices])
return vertices[omit:, :]
print sphere_dic.keys()
#vertices = get_vertex_set('create5')
#vertices = get_vertex_set('siem64')
#vertices = get_vertex_set('dsi102')
vertices = get_vertex_set('fy362')
gradients = get_vertex_set('siem64')
gradients = gradients[:gradients.shape[0] / 2]
print gradients.shape
from dipy.viz import fvtk
sph = -np.sinc(np.dot(gradients[1], vertices.T))
r = fvtk.ren()
#sph = np.arange(vertices.shape[0])
print sph.shape
cols = fvtk.colors(sph, 'jet')
fvtk.add(r, fvtk.point(vertices, cols, point_radius=.1, theta=10, phi=10))
fvtk.show(r)
