def inter_calc_dynamic():
# print(os.getcwd())
corrcoef_path = os.path.join(os.getcwd(),'bold_net')
nii_path = os.path.join(path.curparent(), 'pBOLD.nii')
outfolder = os.path.join(os.getcwd(), OUTFOLDER_INTER)
json_path = path.fullfile("inter_attr_dynamic.json")
# print(outfolder)
# print(corrcoef_path)
if not os.path.isdir(outfolder):
os.mkdir(outfolder)
inter_ac = InterAttrCalcDynamic(nii_path,corrcoef_path,outfolder,json_path)
inter_ac.calc()
def intra_calc():
print(os.getcwd())
atlasobj = path.curatlas()
volumename = '3mm'
nii_path = os.path.join(path.curparent(), 'pBOLD.nii')
outfolder = os.path.join(os.getcwd(), 'bold_net_attr_zzl')
json_path = path.fullfile("intra_attr.json")
print(nii_path)
print(outfolder)
if not os.path.isdir(outfolder):
os.mkdir(outfolder)
intra_ac = IntraAttrCalc(nii_path, atlasobj, outfolder, json_path)
intra_ac.calc()
def intra_calc_dynamic():
# print(os.getcwd())
atlasobj = path.curatlas()
volumename = '3mm'
nii_path = os.path.join(path.curparent(), 'pBOLD.nii')
outfolder = os.path.join(os.getcwd(), OUTFOLDER_INTRA)
json_path = path.fullfile("intra_attr_dynamic.json")
# print(nii_path)
# print(outfolder)
if not os.path.isdir(outfolder):
os.mkdir(outfolder)
intra_ac = IntraAttrCalcDynamic(nii_path,atlasobj,outfolder,json_path)
intra_ac.calc()
import os import numpy as np import nibabel as nib from mmdps.proc import atlas # from mmdps.util.loadsave import load_nii, save_csvmat from mmdps.util import path from mmdps.proc import job if __name__ == '__main__': atlasobj = path.curatlas() volumename = '3mm' print(os.path.join(path.curparent(), 'pBOLD.nii')) print(os.getcwd()) outfolder = os.path.join(os.getcwd(), 'bold_net_attr_zzl') print(outfolder)
def gen_timeseries(self):
data = self.img.get_data()
atdata = self.atlasimg.get_data()
timepoints = data.shape[3]
timeseries = np.empty((self.atlasobj.count, timepoints))
for i, region in enumerate(self.atlasobj.regions):
regiondots = data[atdata == region, :]
regionts = np.mean(regiondots, axis=0)
timeseries[i, :] = regionts
return timeseries
def gen_net(self):
ts = self.gen_timeseries()
save_csvmat(self.outpath('timeseries.csv'), ts)
tscorr = np.corrcoef(ts)
save_csvmat(self.outpath('corrcoef.csv'), tscorr)
def run(self):
self.gen_net()
if __name__ == '__main__':
atlasobj = path.curatlas()
volumename = '3mm'
img = load_nii(os.path.join(path.curparent(), 'pBOLD.nii'))
outfolder = 'bold_net'
c = Calc(atlasobj, volumename, img, outfolder)
c.run()