Example #1
0
def transform(floating, T, reference=None, interp_order=3):

    # Convert assumed nibabel-like input images to local image class
    floating = Image(floating)
    if not reference == None: 
        reference = Image(reference)

    return asNifti1Image(floating.transform(np.asarray(T), grid_coords=False,
                                            reference=reference, interp_order=interp_order))
Example #2
0
 def resample(self, align_runs=True): 
     """
     Return a list of 4d nibabel-like images corresponding to the resampled runs. 
     """
     if align_runs: 
         transforms = self._transforms
     else: 
         transforms = self._within_run_transforms
     indices = range(len(self._runs))
     data = [resample4d(self._runs[i], transforms=transforms[i]) for i in indices]
     return [asNifti1Image(Image(data[i], self._runs[i].to_world)) for i in indices]
Example #3
0
    T = GridTransform(I, defmodes.data.reshape(list(I.shape)+[7,3]))
    # freeze mean deformation component
    T._param[0] = 1
    T._free_param_idx = [1,2,3,4,5,6]

    if 'defrand' in TYPE: 
        best_param = np.load('t3_def_crl1.npy')
        best_simi = 0.0 
        for i in range(NTRIALS): 
            T.param = best_param + std*np.random.normal(std.size)
            T = R.optimize(T)
            optimum = R.eval(T)
            if optimum > best_simi: 
                print(' *** New best ***') 
                best_simi = optimum 
                best_param = T.param
            else: 
                print(' *** Unbeaten optimum ***') 
                T.param = best_param 
    else: 
        T.param = identity 
        T = R.optimize(T)


# Create matcher instance
fname = 't'+str(ID)+'_'+TYPE+'_'+SIMI+'_'+INTERP
outfile = join(DATADIR, fname+'.nii') 
print('Saving resampled source in: %s' % outfile)
Jt = J.transform(T, reference=I)
save(asNifti1Image(Jt), outfile)
Example #4
0
import numpy as np 
from nibabel import load, save
from nipy.neurospin.image import Image, asNifti1Image
from os.path import join 
from glob import glob

datadir = join('d:\\', 'home', 'Alexis', 'data', 'remy')
I = Image(load(join(datadir, '2_axial_FL_AD_ROI.nii')))

defmodes = glob(join(datadir, 'NEW_SDF', 'SDF_*.nii'))
data = np.zeros(list(I.shape)+[len(defmodes)])
for i in range(len(defmodes)):
    print('image: %d (%s)' % (i, defmodes[i]))
    m = Image(load(defmodes[i]))
    mm = m.transform(np.eye(4), reference=I)
    data[:,:,:,i] = mm.data

save(asNifti1Image(Image(data, I.affine)), join(datadir, 'deformation_modes.nii'))