import numpy as np for datat in range(2): if datat == 0: print 'fitting with dti' data, affine, gtab = get_train_dti(30) elif datat == 1: print 'fitting with hardi' data, affine, gtab = get_train_hardi(30) elif datat == 2: print 'fitting with dsi' data, affine, gtab = get_train_dsi(30) mask, affine = get_train_mask() data.shape mask.shape model = TensorModel(gtab) fit = model.fit(data, mask) print 'done!' fa = fit.fa slice_z = 25 Th = [0.05, 0.075, 0.1,0.15]