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)
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)
def main():
try:
DATA_PATH = sys.argv[1]
except IndexError:
raise RuntimeError("Pass data path on command line")
TR = 2.5
subjects = get_subjects(DATA_PATH)
for name, subject in subjects.items():
run_fnames = []
for run in subject['functionals']:
run_fnames.append(run['filename'])
print("Realigning subject " + name)
time_space_realign(run_fnames, TR, 'ascending', slice_axis=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
# You need to work out slice times here
subjects = get_subjects(DATA_PATH)
for name, subject in subjects.items():
for run in subject['functionals']:
fname = run['filename']
print("Running slice timing on " + fname)
slice_time_file(fname, slice_times, TR)
def main():
try:
DATA_PATH = sys.argv[1]
except IndexError:
raise RuntimeError("Pass data path on command line")
for name, subject in get_subjects(DATA_PATH).items():
for run in subject['functionals']:
fname = run['filename']
print("Diagnosing functional " + fname)
img = nipy.load_image(fname)
res = screens.screen(img, slice_axis=0)
pth, fname = os.path.split(fname)
froot, ext = os.path.splitext(fname)
if ext in ('.gz', '.bz2'): # discard compressed exts
froot, ext = os.path.splitext(froot)
screens.write_screen_res(res, pth, froot)
def main():
try:
DATA_PATH = sys.argv[1]
except IndexError:
raise RuntimeError("Pass data path on command line")
subjects = get_subjects(DATA_PATH)
for name in sorted(subjects):
subject = subjects[name]
print("Smoothing subject " + name)
for run in subject['functionals']:
fname = run['filename']
pth, fpart = os.path.split(fname)
ra_fname = os.path.join(pth, 'ra' + fpart)
sra_fname = os.path.join(pth, 'sra' + fpart)
img = load_image(ra_fname)
save_image(smooth_image(img, 8.), sra_fname)
def main():
try:
DATA_PATH = sys.argv[1]
except IndexError:
raise RuntimeError("Pass data path on command line")
subjects = get_subjects(DATA_PATH)
for name in sorted(subjects):
subject = subjects[name]
print("Smoothing subject " + name)
for run in subject['functionals']:
fname = run['filename']
pth, fpart = os.path.split(fname)
ra_fname = os.path.join(pth, 'ra' + fpart)
sra_fname = os.path.join(pth, 'sra' + fpart)
img = load_image(ra_fname)
save_image(smooth_image(img, 8.), sra_fname)
def main():
try:
DATA_PATH = sys.argv[1]
except IndexError:
raise RuntimeError("Pass data path on command line")
for name, subject in get_subjects(DATA_PATH).items():
for run in subject['functionals']:
fname = run['filename']
print("Diagnosing functional " + fname)
img = nipy.load_image(fname)
res = screens.screen(img, slice_axis=0)
pth, fname = os.path.split(fname)
froot, ext = os.path.splitext(fname)
if ext in ('.gz', '.bz2'): # discard compressed exts
froot, ext = os.path.splitext(froot)
screens.write_screen_res(res, pth, froot)
def main():
try:
DATA_PATH = sys.argv[1]
except IndexError:
raise RuntimeError("Pass data path on command line")
N_SLICES = 40
TR = 2.5
# You need to work out slice times here
space_to_time = list(range(0, N_SLICES, 2)) + list(range(1, N_SLICES, 2))
time_to_space = np.argsort(space_to_time)
subjects = get_subjects(DATA_PATH)
for name, subject in subjects.items():
run_fnames = []
for run in subject['functionals']:
run_fnames.append(run['filename'])
print("Realigning subject " + name)
time_space_realign(run_fnames, TR, time_to_space, slice_axis=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
# 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
slice_times = space_to_order * time_one_slice + time_one_slice / 2.0
subjects = get_subjects(DATA_PATH)
for name, subject in subjects.items():
for run in subject['functionals']:
fname = run['filename']
print("Running slice timing on " + fname)
slice_time_file(fname, slice_times, TR, slice_axis=0)
def test_big_picture():
subjects = get_subjects(FILEROOT)
assert_equal(len(subjects), 6)
assert_equal(sorted(subjects.keys()), SUBJ_NAMES)
for name, subject in subjects.items():
assert_equal(len(subject['anatomicals']), 1)
assert_equal(subject['tasks'], [1])
if name == 'sub005':
assert_equal(len(subject['functionals']), 11)
else:
assert_equal(len(subject['functionals']), 12)
for i, rundef in enumerate(subject['functionals']):
assert_true(rundef['filename'].endswith('bold.nii.gz'))
assert_equal(rundef['task_no'], 1)
assert_equal(rundef['run_no'], i+1)
assert_true('task001_run%03d' % (i + 1,) in rundef['filename'])
img = nib.load(rundef['filename'])
assert_equal(img.shape, (40, 64, 64, 121))
hdr = img.get_header()
assert_almost_equal(hdr['pixdim'][1:4], (3.5, 3.75, 3.75))
def main():
hash_dict = {}
subjects = get_subjects(sys.argv[1])
for name, subject in subjects.items():
for run in subject['functionals']:
check_store_hash(run['filename'], hash_dict)
import os
import nipy
from nipy.algorithms.diagnostics import screens
from openfmri import get_subjects
for name, subject in get_subjects('ds105').items():
for run in subject['functionals']:
fname = run['filename']
img = nipy.load_image(fname)
res = screens.screen(img, slice_axis=0)
pth, fname = os.path.split(fname)
froot, ext = os.path.splitext(fname)
screens.write_screen_res(res, pth, froot)
import os
import nipy
from nipy.algorithms.diagnostics import screens
from openfmri import get_subjects
for name, subject in get_subjects("ds105").items():
for run in subject["functionals"]:
fname = run["filename"]
img = nipy.load_image(fname)
res = screens.screen(img, slice_axis=0)
pth, fname = os.path.split(fname)
froot, ext = os.path.splitext(fname)
screens.write_screen_res(res, pth, froot)
def main():
hash_dict = {}
subjects = get_subjects(sys.argv[1])
for name, subject in subjects.items():
for run in subject['functionals']:
check_store_hash(run['filename'], hash_dict)