def metric_register(pclow, pchigh, do_phasecorr=True, smooth_sigma=1.15, block_size=(128,128), maxregshift=0.1, maxregshiftNR=5):
ops = {
'num_workers': -1,
'snr_thresh': 1.25,
'nonrigid': True,
'num_workers': -1,
'block_size': np.array(block_size),
'maxregshiftNR': np.array(maxregshiftNR),
'maxregshift': np.array(maxregshift),
'subpixel': 10,
'do_phasecorr': do_phasecorr,
'smooth_sigma': smooth_sigma
}
nPC, ops['Ly'], ops['Lx'] = pclow.shape
X = np.zeros((nPC,3))
ops = make_blocks(ops)
for i in range(nPC):
refImg = pclow[i]
Img = pchigh[i][np.newaxis, :, :]
#Img = np.tile(Img, (1,1,1))
maskMul, maskOffset, cfRefImg = register.prepare_masks(refImg, ops)
maskMulNR, maskOffsetNR, cfRefImgNR = nonrigid.prepare_masks(refImg, ops)
refAndMasks = [maskMul, maskOffset, cfRefImg, maskMulNR, maskOffsetNR, cfRefImgNR]
dwrite, ymax, xmax, cmax, yxnr = register.phasecorr(Img, refAndMasks, ops)
X[i,1] = np.mean((yxnr[0]**2 + yxnr[1]**2)**.5)
X[i,0] = np.mean((ymax[0]**2 + xmax[0]**2)**.5)
X[i,2] = np.amax((yxnr[0]**2 + yxnr[1]**2)**.5)
return X
def pc_register_worker(inputs):
ops, refImg, Img = inputs
maskMul, maskOffset, cfRefImg = register.prepare_masks(refImg, ops)
maskMulNR, maskOffsetNR, cfRefImgNR = nonrigid.prepare_masks(refImg, ops)
refAndMasks = [maskMul, maskOffset, cfRefImg, maskMulNR, maskOffsetNR, cfRefImgNR]
dwrite, ymax, xmax, cmax, yxnr = register.register_and_shift(Img, refAndMasks, ops)
X = np.zeros((3,))
X[1] = np.mean((yxnr[0]**2 + yxnr[1]**2)**.5)
X[0] = np.mean((ymax[0]**2 + xmax[0]**2)**.5)
X[2] = np.amax((yxnr[0]**2 + yxnr[1]**2)**.5)
return X