def ccf(e, f, center=True): """ Return the circulant cross-correlation function of images e and f. Input images may be real or complex. Output image is real. 1-D, 2-D, or 3-D images supported. """ from EMAN2 import correlation, fp_flag return correlation(e,f,fp_flag.CIRCULANT, center)
def ccfnpl(e, f, center=True): """ Name ccfnpl - calculate the normalized cross-correlation function between two images Input e: input image (real) ref: second input image (real) center: if set to True (default), the origin of the result is at the center """ from EMAN2 import correlation, fp_flag return correlation(e,f,fp_flag.PADDED_NORMALIZED_LAG, center)
def ccfp(e, f, center=True): """ Name ccfp - calculate the cross-correlation function between two images Input e: input image (real) ref: second input image (real) center: if set to True (default), the origin of the result is at the center Output cross-correlation function between image and ref. Real. """ from EMAN2 import correlation, fp_flag return correlation(e,f,fp_flag.PADDED, center)
def ccfn(e, f, center=True): """ Name ccfn - calculate the normalized circulant cross-correlation function between two images. Input e: input image (real) ref: second input image (real) (in the alignment problems, it should be the reference image). center: if set to True (default), the origin of the result is at the center Output normalized circulant cross-correlation function between image and ref. Real. """ from EMAN2 import correlation, fp_flag return correlation(e,f,fp_flag.CIRCULANT_NORMALIZED, center)