Exemplo n.º 1
0
def main():
    try:
        DATA_PATH = sys.argv[1]
    except IndexError:
        raise RuntimeError("Pass data path on command line")
    N_SLICES = 40
    TR = 2.5
    SLICE_AXIS = 0

    # Figure out slice times.
    slice_order = np.array(range(0, N_SLICES, 2) + range(1, N_SLICES, 2))
    space_to_order = np.argsort(slice_order)
    time_one_slice = TR / N_SLICES
    # This time, don't add half a slice - nifti won't accept it.
    slice_times = space_to_order * time_one_slice

    subjects = get_subjects(DATA_PATH)
    for name, subject in subjects.items():
        for run in subject['functionals']:
            fname = run['filename']
            print("Fixing functional " + fname)
            fixnifti.fixup_nifti_file(fname, 'f', TR, SLICE_AXIS,
                                      slice_times)  # changed filename to fname
        for anat_fname in subject['anatomicals']:
            print("Fixing anatomical " + anat_fname)
            fixnifti.fixup_nifti_file(anat_fname)
Exemplo n.º 2
0
def main():
    try:
        DATA_PATH = sys.argv[1]
    except IndexError:
        raise RuntimeError("Pass data path on command line")
    N_SLICES = 40
    TR = 2.5
    SLICE_AXIS=0

    # Figure out slice times.
    slice_order = np.array(range(0, N_SLICES, 2) + range(1, N_SLICES, 2))
    space_to_order = np.argsort(slice_order)
    time_one_slice = TR / N_SLICES
    # This time, don't add half a slice - nifti won't accept it.
    slice_times = space_to_order * time_one_slice

    subjects = get_subjects(DATA_PATH)
    for name, subject in subjects.items():
        for run in subject['functionals']:
            fname = run['filename']
            print("Fixing functional " + fname)
            fixnifti.fixup_nifti_file(fname, 'f', TR, SLICE_AXIS, slice_times)
        for anat_fname in subject['anatomicals']:
            print("Fixing anatomical " + anat_fname)
            fixnifti.fixup_nifti_file(anat_fname)
Exemplo n.º 3
0
def test_fixup_nifti_file():
    # Test fixup_nifti_file function
    data = np.arange(24).reshape((2, 3, 4))
    img = nib.Nifti1Image(data, None)
    hdr = img.get_header()
    assert_equal(hdr['pixdim'][4], 1)
    assert_equal(hdr.get_dim_info(), (None, None, None))
    def_aff = img.get_header().get_best_affine()
    tmpdir = tempfile.mkdtemp()
    try:
        fname = os.path.join(tmpdir, 'test.nii')
        new_fname = os.path.join(tmpdir, 'ftest.nii')
        nib.save(img, fname)
        # Just running without params sets the affine
        fixup_nifti_file(fname)
        img2 = nib.load(new_fname)
        assert_almost_equal(img2.get_affine(), def_aff)
        hdr2 = img2.get_header()
        assert_almost_equal(hdr2.get_sform(), def_aff)
        assert_almost_equal(hdr2.get_qform(), def_aff)
        # set prefix
        fixup_nifti_file(fname, 'pre')
        img2 = nib.load(os.path.join(tmpdir, 'pretest.nii'))
        assert_almost_equal(img2.get_affine(), def_aff)
        # Set TR
        fixup_nifti_file(fname, 'f', 2.1)
        img2 = nib.load(new_fname)
        hdr2 = img2.get_header()
        assert_almost_equal(hdr2['pixdim'][4], 2.1, 6)
        # Set slice axis
        fixup_nifti_file(fname, 'f', None, 1)
        img2 = nib.load(new_fname)
        hdr2 = img2.get_header()
        assert_equal(hdr2.get_dim_info(), (None, None, 1))
        # And slice times
        times = np.array([0, 1, 2]) * 3 / 2.1
        fixup_nifti_file(fname, 'f', 2.1, 1, times)
        img2 = nib.load(new_fname)
        hdr2 = img2.get_header()
        assert_almost_equal(hdr2.get_slice_times(), times)
        del img, img2
    finally:
        shutil.rmtree(tmpdir)
Exemplo n.º 4
0
def test_fixup_nifti_file():
    # Test fixup_nifti_file function
    data = np.arange(24).reshape((2, 3, 4))
    img = nib.Nifti1Image(data, None)
    hdr = img.get_header()
    assert_equal(hdr['pixdim'][4], 1)
    assert_equal(hdr.get_dim_info(), (None, None, None))
    def_aff = img.get_header().get_best_affine()
    tmpdir = tempfile.mkdtemp()
    try:
        fname = os.path.join(tmpdir, 'test.nii')
        new_fname = os.path.join(tmpdir, 'ftest.nii')
        nib.save(img, fname)
        # Just running without params sets the affine
        fixup_nifti_file(fname)
        img2 = nib.load(new_fname)
        assert_almost_equal(img2.get_affine(), def_aff)
        hdr2 = img2.get_header()
        assert_almost_equal(hdr2.get_sform(), def_aff)
        assert_almost_equal(hdr2.get_qform(), def_aff)
        # set prefix
        fixup_nifti_file(fname, 'pre')
        img2 = nib.load(os.path.join(tmpdir, 'pretest.nii'))
        assert_almost_equal(img2.get_affine(), def_aff)
        # Set TR
        fixup_nifti_file(fname, 'f', 2.1)
        img2 = nib.load(new_fname)
        hdr2 = img2.get_header()
        assert_almost_equal(hdr2['pixdim'][4], 2.1, 6)
        # Set slice axis
        fixup_nifti_file(fname, 'f', None, 1)
        img2 = nib.load(new_fname)
        hdr2 = img2.get_header()
        assert_equal(hdr2.get_dim_info(), (None, None, 1))
        # And slice times
        times = np.array([0, 1, 2]) * 3 / 2.1
        fixup_nifti_file(fname, 'f', 2.1, 1, times)
        img2 = nib.load(new_fname)
        hdr2 = img2.get_header()
        assert_almost_equal(hdr2.get_slice_times(), times)
        del img, img2
    finally:
        shutil.rmtree(tmpdir)
import os, os.path as op
import glob
from nipype.utils.filemanip import split_filename
import os.path as op
import nipype.interfaces.ants as ants
import fixnifti # Borrowed from https://github.com/practical-neuroimaging/pna-utils

list_to_reg = glob.glob("p0*_maths_rl.nii")
for in_file in list_to_reg:
    path, name, ext = split_filename(in_file)
    fixnifti.fixup_nifti_file(in_file)