Ejemplos de correlation en Python

Ejemplo n.º 1

Archivo: fundamentals.py Proyecto: CVL-dev/StructuralBiology

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)

Ejemplo n.º 2

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)

Ejemplo n.º 3

Archivo: fundamentals.py Proyecto: CVL-dev/StructuralBiology

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)

Ejemplo n.º 4

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)

Ejemplo n.º 5

Archivo: fundamentals.py Proyecto: CVL-dev/StructuralBiology

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)

Ejemplo n.º 6

Archivo: fundamentals.py Proyecto: CVL-dev/StructuralBiology

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)

Ejemplo n.º 7

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)

Ejemplo n.º 8

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)