def qap_functional_temporal(
func_motion_correct,
func_brain_mask,
coord_xfm_matrix,
subject_id,
session_id,
scan_id,
site_name=None,
motion_threshold=1.0,
):
import sys
from qap.temporal_qc import (
mean_dvars_wrapper,
summarize_fd,
mean_outlier_timepoints,
mean_quality_timepoints,
global_correlation,
)
# DVARS
mean_dvars = mean_dvars_wrapper(func_motion_correct, func_brain_mask)
# Mean FD (Jenkinson)
(mean_fd, num_fd, percent_fd) = summarize_fd(coord_xfm_matrix, threshold=motion_threshold)
# 3dTout
mean_outlier = mean_outlier_timepoints(func_motion_correct, func_brain_mask)
# 3dTqual
mean_quality = mean_quality_timepoints(func_motion_correct)
# new thing
gcor = global_correlation(func_motion_correct, func_brain_mask)
# Compile
qc = {
"subject": subject_id,
"session": session_id,
"scan": scan_id,
"dvars": mean_dvars,
"mean_fd": mean_fd,
"num_fd": num_fd,
"perc_fd": percent_fd,
"outlier": mean_outlier,
"quality": mean_quality,
"gcor": gcor,
}
if site_name:
qc["site"] = site_name
return qc
def test_summarize_fd_threshold_01():
import os
import pickle
import pkg_resources as p
from qap.temporal_qc import summarize_fd
coord_xfm = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"coordinate_transformation", \
"rest_calc_tshift_resample.aff12.1D"))
out_tuple = summarize_fd(coord_xfm, threshold=0.1)
assert out_tuple == (0.050015007171052638, 14.0, 9.15032679738562)
def test_summarize_fd_threshold_01():
import os
import pickle
import pkg_resources as p
from qap.temporal_qc import summarize_fd
coord_xfm = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"coordinate_transformation", \
"rest_calc_tshift_resample.aff12.1D"))
out_tuple = summarize_fd(coord_xfm, threshold=0.1)
assert out_tuple == (0.050015007171052638, 14.0, 9.15032679738562)
