make_test_data

#!/usr/bin/env python3

import nibabel as nib
import argh
import os.path
import numpy as np
import cosgen.models as models
from scipy.ndimage.filters import gaussian_filter1d

def main(source, destination, sequence, hrf, voxels, scale=1000, saturation=2, highpass_sigma=225, lowpass_sigma=2):  #saturation/scale is the value at which the activation saturates
	seq = np.load(sequence)
	hrf = np.load(hrf)
	hrf = hrf/float(hrf.max())/scale
	#conv = models.squashing_function(np.convolve(seq,hrf),max=float(saturation/scale))
	conv = np.convolve(seq,hrf)
	roi = nib.load(voxels)
	vox = np.nonzero(roi.get_data())
	img = nib.load(os.path.expanduser(source))
	data = img.get_data()
	func_data = gaussian_filter1d(models.gaussian_highpass(conv[0:img.shape[3]],sigma=highpass_sigma),sigma=lowpass_sigma)
	data[vox] += func_data
	nib.save(img,os.path.expanduser(destination))

if __name__ == '__main__':
	argh.dispatch_command(main)