def test_qap_functional_spatial():
import os
import pkg_resources as p
from qap.qap_workflows_utils import qap_functional_spatial
mean_func = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"mean_functional", \
"rest_calc_tshift_resample_volreg_" \
"tstat.nii.gz"))
func_mask = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"functional_brain_mask", \
"rest_calc_tshift_resample_volreg_" \
"mask.nii.gz"))
subject = "1019436"
session = "session_1"
scan = "rest_1"
direction = "y"
qc = qap_functional_spatial(mean_func, func_mask, direction, subject, \
session, scan)
assert (len(qc.keys()) == 17) and (None not in qc.values())
def test_qap_functional_spatial():
import os
import pkg_resources as p
from qap.qap_workflows_utils import qap_functional_spatial
mean_func = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"mean_functional", \
"rest_calc_tshift_resample_volreg_" \
"tstat.nii.gz"))
func_mask = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"functional_brain_mask", \
"rest_calc_tshift_resample_volreg_" \
"mask.nii.gz"))
subject = "1019436"
session = "session_1"
scan = "rest_1"
direction = "y"
qc = qap_functional_spatial(mean_func, func_mask, direction, subject, \
session, scan)
assert (len(qc.keys()) == 17) and (None not in qc.values())
subjectdir = os.path.join(args.outdir, args.subjectid)
if not os.path.isdir(subjectdir):
os.mkdir(subjectdir)
if args.erase:
shutil.rmtree(subjectdir)
os.mkdir(subjectdir)
"""
QAP spatial
"""
# out_vox: output the FWHM as # of voxels (otherwise as mm)
# direction: used to compute signal present outside the brain due to
# acquisition in the phase encoding direction
# > compute functional spatial scores from QAP library
qc = qap_functional_spatial(args.meanrealign, args.maskrealign,
args.direction,
args.subjectid, "mysession", "myscan",
site_name="mysite", out_vox=True)
# > save scores as a Json file
scores_json = os.path.join(subjectdir, "qap_functional_spatial.json")
qc.pop("session")
qc.pop("scan")
qc.pop("site")
for key, value in qc.items():
if isinstance(value, numpy.double) or isinstance(value, numpy.single):
qc[key] = float(value)
if isinstance(value, numpy.core.memmap):
if value.dtype == numpy.single or value.dtype == numpy.double:
qc[key] = float(value)
elif value.dtype == numpy.int:
qc[key] = int(value)
time_axis=-1,
slice_axis=-2,
mvt_thr=50,
rot_thr=50,
volumes_to_ignore=args.crop)
"""
QAP spatial
"""
# out_vox: output the FWHM as # of voxels (otherwise as mm)
# direction: used to compute signal present outside the brain due to
# acquisition in the phase encoding direction
# > compute functional spatial scores from QAP library
qc = qap_functional_spatial(args.meanrealign,
args.maskrealign,
args.direction,
args.subjectid,
"mysession",
"myscan",
site_name="mysite",
out_vox=True)
# > save scores as a Json file
scores_json = os.path.join(subjectdir, "qap_functional_spatial.json")
qc.pop("session")
qc.pop("scan")
qc.pop("site")
for key, value in qc.items():
if isinstance(value, numpy.double) or isinstance(value, numpy.single):
qc[key] = float(value)
if isinstance(value, numpy.core.memmap):
if value.dtype == numpy.single or value.dtype == numpy.double:
qc[key] = float(value)
