def extract_frommask_component(realigned_file, mask_file):
import os
import nibabel as nb
import numpy as np
from utils import mean_roi_signal
from nipype import logging
iflogger = logging.getLogger('interface')
data = nb.load(realigned_file).get_data().astype('float64')
mask = nb.load(mask_file).get_data().astype('float64')
iflogger.info('Data and mask loaded.')
mask_comp = mean_roi_signal(data, mask.astype('bool'))
components_file = os.path.join(os.getcwd(), 'mask_mean_component.txt')
iflogger.info('Saving components file:' + components_file)
np.savetxt(components_file, mask_comp)
return components_file
def extract_frommask_component(realigned_file, mask_file):
import os
import nibabel as nb
import numpy as np
from utils import mean_roi_signal
from nipype import logging
iflogger = logging.getLogger('interface')
data = nb.load(realigned_file).get_data().astype('float64')
mask = nb.load(mask_file).get_data().astype('float64')
iflogger.info('Data and mask loaded.')
mask_comp = mean_roi_signal(data, mask.astype('bool'))
components_file = os.path.join(os.getcwd(), 'mask_mean_component.txt')
iflogger.info('Saving components file:' + components_file)
np.savetxt(components_file, mask_comp)
return components_file
def extract_global_component(realigned_file):
import os
import nibabel as nb
import numpy as np
from utils import mean_roi_signal
data = nb.load(realigned_file).get_data().astype('float64')
mask = (data != 0).sum(-1) != 0 # Global Mask
print 'Data loaded.'
# Y = data[mask].T
# Yc = Y - np.tile(Y.mean(0), (Y.shape[0], 1))
glb_comp = mean_roi_signal(data, mask)
components_file = os.path.join(os.getcwd(), 'global_component.txt')
print 'Saving components file:', components_file
np.savetxt(components_file, glb_comp)
return components_file
def extract_global_component(realigned_file):
import os
import nibabel as nb
import numpy as np
from utils import mean_roi_signal
data = nb.load(realigned_file).get_data().astype('float64')
mask = (data != 0).sum(-1) != 0 # Global Mask
print 'Data loaded.'
# Y = data[mask].T
# Yc = Y - np.tile(Y.mean(0), (Y.shape[0], 1))
glb_comp = mean_roi_signal(data, mask)
components_file = os.path.join(os.getcwd(), 'global_component.txt')
print 'Saving components file:', components_file
np.savetxt(components_file, glb_comp)
return components_file
