def main():
parser = ArgumentParser(description=DESCRIP,
epilog=EPILOG,
formatter_class=RawDescriptionHelpFormatter)
parser.add_argument('filename', type=str,
help='4D image filename')
parser.add_argument('--out-path', type=str,
help='path for output image files')
parser.add_argument('--out-fname-label', type=str,
help='mid part of output image filenames')
parser.add_argument('--ncomponents', type=int, default=10,
help='number of PCA components to write')
# parse the command line
args = parser.parse_args()
# process inputs
filename = args.filename
out_path = args.out_path
out_root = args.out_fname_label
ncomps = args.ncomponents
# collect extension for output images
froot, ext, gz = splitext_addext(filename)
pth, fname = os.path.split(froot)
if out_path is None:
out_path = pth
if out_root is None:
out_root = fname
img = nipy.load_image(filename)
res = nads.screen(img, ncomps)
nads.write_screen_res(res, out_path, out_root, ext + gz)
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")
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)
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_visits
for name, visit in get_visits('ds105').items():
for functional in visit['functionals']:
filename = functional['filename']
img = nipy.load_image(filename)
res = screens.screen(img, slice_axis=0)
pth, fname = os.path.split(filename)
froot, ext = os.path.splitext(fname)
screens.write_screen_res(res, pth, froot)
