From 8669dec9dd9a668fe53ff38d631313bd2191a7eb Mon Sep 17 00:00:00 2001 From: spangly Date: Fri, 27 Jan 2023 14:47:40 +0000 Subject: [PATCH] Fixed the xrange/range screw up --- aotools/functions/zernike.py | 19 ++++++------------- 1 file changed, 6 insertions(+), 13 deletions(-) diff --git a/aotools/functions/zernike.py b/aotools/functions/zernike.py index 6cdfe89..0eba058 100644 --- a/aotools/functions/zernike.py +++ b/aotools/functions/zernike.py @@ -1,13 +1,6 @@ import numpy from . import circle -# xrange just "range" in python3. -# This code means fastest implementation used in 2 and 3 -try: - xrange -except NameError: - xrange = range - def phaseFromZernikes(zCoeffs, size, norm="noll", rot=0): """ Creates an array of the sum of zernike polynomials with specified coefficeints @@ -22,7 +15,7 @@ def phaseFromZernikes(zCoeffs, size, norm="noll", rot=0): """ Zs = zernikeArray(len(zCoeffs), size, norm=norm, rot=rot) phase = numpy.zeros((size, size)) - for z in xrange(len(zCoeffs)): + for z in range(len(zCoeffs)): phase += Zs[z] * zCoeffs[z] return phase @@ -92,7 +85,7 @@ def zernikeRadialFunc(n, m, r): R = numpy.zeros(r.shape) # Can cast the below to "int", n,m are always *both* either even or odd - for i in xrange(0, int((n - m) / 2) + 1): + for i in range(0, int((n - m) / 2) + 1): R += numpy.array(r**(n - 2 * i) * (((-1)**(i)) * numpy.math.factorial(n - i)) / @@ -146,7 +139,7 @@ def zernikeArray(J, N, norm="noll", rot=0): try: nJ = len(J) Zs = numpy.empty((nJ, N, N)) - for i in xrange(nJ): + for i in range(nJ): Zs[i] = zernike_noll(J[i], N, rot) # Else, cast to int and create up to that number @@ -157,16 +150,16 @@ def zernikeArray(J, N, norm="noll", rot=0): Zs = numpy.empty((maxJ, N, N)) - for j in xrange(1, maxJ+1): + for j in range(1, maxJ+1): Zs[j-1] = zernike_noll(j, N, rot) if norm=="p2v": - for z in xrange(len(Zs)): + for z in range(len(Zs)): Zs[z] /= (Zs[z].max()-Zs[z].min()) elif norm=="rms": - for z in xrange(len(Zs)): + for z in range(len(Zs)): # Norm by RMS. Remember only to include circle elements in mean Zs[z] /= numpy.sqrt( numpy.sum(Zs[z]**2)/numpy.sum(circle(N/2., N)))