comparison dmri.py @ 39:24c3ca0fd7fa draft

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38:b054adc68274

import shutil

from dipy.core.gradients import gradient_table
from dipy.data import fetch_stanford_hardi, fetch_stanford_t1, read_stanford_labels
from dipy.io import read_bvals_bvecs
from matplotlib import pyplot

import nibabel

parser = argparse.ArgumentParser()

    pyplot.imshow(data[:, :, axial_middle, 0].T, cmap='gray', origin='lower')
    pyplot.subplot(1, 2, 2).set_axis_off()
    pyplot.imshow(data[:, :, axial_middle, 10].T, cmap='gray', origin='lower')
pyplot.savefig('data.png', bbox_inches='tight')
shutil.move('data.png', args.output_png)
# Load the b-values and b-vectors.
bvals, bvecs = read_bvals_bvecs(fbval, fbvec)
gtab = gradient_table(bvals, bvecs)
# gtab can be used to tell what part of the data is the S0
# volumes (volumes which correspond to b-values of 0).
S0s = data[:, :, :, gtab.b0s_mask]
# Save this in a new Nifti file.
nibabel.save(nibabel.Nifti1Image(S0s, img.affine), 'output.nii')
shutil.move('output.nii', args.output_nifti1)
# Move the entire contents of input_dir to output_nifti1_extra_files.
move_directory_files(input_dir, args.output_nifti1_extra_files)

39:24c3ca0fd7fa

import shutil

from dipy.core.gradients import gradient_table
from dipy.data import fetch_stanford_hardi, fetch_stanford_t1, read_stanford_labels
from dipy.io import read_bvals_bvecs
from dipy.io.image import save_nifti
from matplotlib import pyplot

import nibabel

parser = argparse.ArgumentParser()

    pyplot.imshow(data[:, :, axial_middle, 0].T, cmap='gray', origin='lower')
    pyplot.subplot(1, 2, 2).set_axis_off()
    pyplot.imshow(data[:, :, axial_middle, 10].T, cmap='gray', origin='lower')
pyplot.savefig('data.png', bbox_inches='tight')
shutil.move('data.png', args.output_png)

if args.drmi_dataset == 'stanford_hardi':
    # Load the b-values and b-vectors.
    bvals, bvecs = read_bvals_bvecs(fbval, fbvec)
    gtab = gradient_table(bvals, bvecs)
    # gtab can be used to tell what part of the data is the S0
    # volumes (volumes which correspond to b-values of 0).
    S0s = data[:, :, :, gtab.b0s_mask]
    # Save this in a new Nifti file.
    nibabel.save(nibabel.Nifti1Image(S0s, img.affine), 'output.nii')
else:
    save_nifti('output.nii', data, img.affine)

shutil.move('output.nii', args.output_nifti1)
# Move the entire contents of input_dir to output_nifti1_extra_files.
move_directory_files(input_dir, args.output_nifti1_extra_files)