upsample)# x_convolved = ndimage.convolve1d(image,xkernel,mode='mirror',axis=1)# both_convolved = ndimage.convolve1d(x_convolved,thetakernel,mode='mirror',axis=0)x_convolved = ndimage.convolve1d(image,xkernel,mode='constant',axis=1)
defconvolve(sequence, rule, **kwds):"""Wrapper around scipy.ndimage.convolve1dthat allows complex input."""dtype = np.result_type(float, np.ravel(sequence)[0]) seq = np.asarray(sequence, dtype=dtype)ifnp.iscomplexobj(seq):return(convolve1d(seq.real, rule, **kwds) +1j*convolve1d(se...