for s_id in np.arange(len(source_ids)):
print '-----------------------------------------------------------------------------------------'
print 'Source: ', source_ids[s_id]
source = str(source_ids[s_id])
flirt_filename = '/home/bao/Personal/PhD_at_Trento/Research/ALS_Nivedita_Bao/Code/data/' + source+'/DIFF2DEPI_EKJ_64dirs_14/DTI/flirt.mat'
fa_filename= '/home/bao/Personal/PhD_at_Trento/Research/ALS_Nivedita_Bao/Segmentation_CST_francesca/' + source + '/DTI/dti_fa_brain.nii.gz'
tracks_filename = '/home/bao/Personal/PhD_at_Trento/Research/ALS_Nivedita_Bao/Segmentation_CST_francesca/' + source + '/DTI/dti.trk'
linear_filename = '/home/bao/Personal/PhD_at_Trento/Research/ALS_Nivedita_Bao/Segmentation_CST_francesca/' + source + '/DTI/dti_linear.dpy'
warp_tracks_linearly(flirt_filename,fa_filename, tracks_filename,linear_filename)
print 'Saved ', linear_filename
tract_linear = load_whole_tract(linear_filename)
if save:
from common_functions import save_tract_trk
fa_warped = '/home/bao/Personal/PhD_at_Trento/Research/ALS_Nivedita_Bao/Code/data/' + source+'/DIFF2DEPI_EKJ_64dirs_14/DTI/fa_warped.nii.gz'
fname_out = '/home/bao/Personal/PhD_at_Trento/Research/ALS_Nivedita_Bao/Segmentation_CST_francesca/' + source + '/DTI/dti_linear.trk'
save_tract_trk(tract_linear, fa_warped, fname_out )
print 'Saved ', fname_out
if vis:
tract = load_whole_tract(tracks_filename)
from dipy.viz import fvtk
from common_functions import visualize_tract
ren = fvtk.ren()
visualize_tract(ren, tract,color=fvtk.red)
visualize_tract(ren, tract_linear,color=fvtk.blue)
fvtk.show(ren)
clearall()
cst_ext_vtk_fname = '/home/bao/tiensy/Tractography_Mapping/data/trackvis_tractography/ROI_seg_tvis/ROI_seg_tvis_native/' + subj + '_cst_L_tvis_ext.vtk'
'''
#CST_Right
#saving CST as trk file
s_file = '/home/bao/tiensy/Tractography_Mapping/data/trackvis_tractography/tvis_tractography/' + subj + '_tracks_dti_tvis.trk'
#cst_ind = '/home/bao/tiensy/Tractography_Mapping/data/trackvis_tractography/ROI_seg_tvis/ROI_seg_tvis_native/' + subj + '_corticospinal_R_tvis.pkl'
#cst_tract = load_tract(s_file,cst_ind)
cst_ext_ind = '/home/bao/tiensy/Tractography_Mapping/data/trackvis_tractography/50_SFF_in_ext/ROI_seg_native/' + subj + '_cst_R_tvis_ext.pkl'
cst_tract_ext = load_tract(s_file,cst_ext_ind)
s_fa = '/home/bao/Personal/PhD_at_Trento/Research/ALS_Nivedita_Bao/Segmentation_CST_francesca/' + subj + '/DTI/dti_fa_brain.nii.gz'
#cst_trk_fname = '/home/bao/tiensy/Tractography_Mapping/data/trackvis_tractography/ROI_seg_tvis/ROI_seg_tvis_native/' + subj + '_corticospinal_R_tvis.trk'
#save_tract_trk(cst_tract, s_fa, cst_trk_fname)
cst_ext_trk_fname = '/home/bao/tiensy/Tractography_Mapping/data/trackvis_tractography/ROI_seg_tvis/ROI_seg_tvis_native/' + subj + '_cst_R_tvis_ext.trk'
save_tract_trk(cst_tract_ext, s_fa, cst_ext_trk_fname)
#converting trk file to vtk file
input_anatomy_ref = '/home/bao/tiensy/Lauren_registration/data_compare_mapping/anatomy/' + subj + '_data_brain.nii.gz'
#it is a link to '/home/bao/Personal/PhD_at_Trento/Research/ALS_Nivedita_Bao/Segmentation_CST_francesca/' + subj + '/DTI/data_brain.nii.gz'
#cst_vtk_fname = '/home/bao/tiensy/Tractography_Mapping/data/trackvis_tractography/ROI_seg_tvis/ROI_seg_tvis_native/' + subj + '_corticospinal_R_tvis.vtk'
cst_ext_vtk_fname = '/home/bao/tiensy/Tractography_Mapping/data/trackvis_tractography/ROI_seg_tvis/ROI_seg_tvis_native/' + subj + '_cst_R_tvis_ext.vtk'
in_format = str(".trk")
out_format = ".vtk"
#input_file = cst_trk_fname
#output_file = cst_vtk_fname
input_file = cst_ext_trk_fname
output_file = cst_ext_vtk_fname
