def __init__(self,inFoc,outFoc,deltaZ,lbda,pxsize,F,pupilRadius,jmax):
print 'phaseDiversity ...'
#PSF
self.inFoc = inFoc
self.outFoc = outFoc
shapeinFoc = np.shape(self.inFoc)
shapeoutFoc = np.shape(self.outFoc)
if shapeinFoc == shapeoutFoc:
self.shape = shapeinFoc
else:
raise myExceptions.PSFssizeError('the shape of the in/out PSFs is not the same',[shapeinFoc,shapeoutFoc])
if shapeinFoc[0]==shapeinFoc[1] and np.mod(shapeinFoc[0],2)==0:
self.N = shapeinFoc[0]
else:
raise myExceptions.PSFssizeError('Either PSF is not square or mod(N,2) != 0',shapeinFoc)
# properties
self.deltaZ = deltaZ
self.lbda = lbda
self.pxsize = pxsize
self.F = F
self.pupilRadius = pupilRadius
self.dxp = self.F*self.lbda/(self.N*self.pxsize)
self.rad = int(np.ceil(self.pupilRadius/self.dxp))
if 2*self.rad > self.N/2.:
raise myExceptions.PupilSizeError('Npupil (2*rad) is bigger than N/2 which is not correct for the fft computation',[])
self.NyquistCriterion()
self.jmax = jmax
self.oddjs = fs.getOddJs(4,self.jmax)
self.evenjs = fs.getEvenJs(4,self.jmax)
# result computation
self.result = self.retrievePhase()
def __init__(self, inFoc, outFocpos, outFocneg, deltaZ, lbda, pxsize, F,
pupilRadius, jmin, jmax):
#
# input:
# inFoc,outFocpos,outFocneg are the 3 squared PSFs data, (focused, defocused positiv and defocused negative)
# deltaZ is the displacement of the detector to acquire the two defocused PSFs
# lbda is the wavelength of the incoming light
# pxsize is the pixel size of the detector
# F is the focal length of the imaging system
# pupilRadius is the radius of the exit pupil
# jmin and jmax gives the boundary on the js to retrieve
print 'phaseDiversity ...'
#PSF
self.inFoc = inFoc
self.outFocpos = outFocpos
self.outFocneg = outFocneg
shapeinFoc = np.shape(self.inFoc)
shapeoutFocpos = np.shape(self.outFocpos)
shapeoutFocneg = np.shape(self.outFocneg)
if shapeinFoc == shapeoutFocpos and shapeinFoc == shapeoutFocneg:
self.shape = shapeinFoc
else:
raise myExceptions.PSFssizeError(
'the shape of the in/out PSFs is not the same',
[shapeinFoc, shapeoutFocpos])
if shapeinFoc[0] == shapeinFoc[1] and np.mod(shapeinFoc[0], 2) == 0:
self.N = shapeinFoc[0]
else:
raise myExceptions.PSFssizeError(
'Either PSF is not square or mod(N,2) != 0', shapeinFoc)
# properties
self.deltaZ = deltaZ
self.lbda = lbda
self.pxsize = pxsize
self.F = F
self.pupilRadius = pupilRadius
self.dxp = self.F * self.lbda / (self.N * self.pxsize)
self.rad = int(np.ceil(self.pupilRadius / self.dxp))
if 2 * self.rad > self.N / 2.:
raise myExceptions.PupilSizeError(
'Npupil (2*rad) is bigger than N/2 which is not correct for the fft computation',
[])
self.NyquistCriterion()
self.jmin = jmin
self.jmax = jmax
self.oddjs = fs.getOddJs(self.jmin, self.jmax)
self.evenjs = fs.getEvenJs(self.jmin, self.jmax)
# result computation
self.result = self.retrievePhase()
if 4 not in jswth4:
jswth4 = np.append(4, jspresent)
ajswtha4 = np.append(a4dephasing, ajspresent)
else:
ajswtha4[jswth4 == 4] += a4dephasing
PSFinfoc = psf.PSF(jspresent, ajspresent, N, dxp, pupilRadius)
PSFoutfoc = psf.PSF(jswth4, ajswtha4, N, dxp, pupilRadius)
PSFoutfocPerf = psf.PSF([4], [a4dephasing], N, dxp, pupilRadius)
deltaPSFinFoc = PSFinfoc.Sp**2 * PSFinfoc.PSF - PSFinfoc.Sp**2 * PSFinfoc.perfectPSF
deltaPSFoutFoc = PSFoutfoc.Sp**2 * PSFoutfoc.PSF - PSFoutfocPerf.Sp**2 * PSFoutfocPerf.PSF
oddjs = fs.getOddJs(1, jmax)
ajsodd = .0 * oddjs
ajsodd[oddjs == 7] = 10e-9 / lbda * 2 * np.pi
f2j = fs.f2j(j, N, oddjs, ajsodd, deltaphi, dxp, pupilRadius)
y2 = (fs.y2(deltaPSFoutFoc, N, oddjs, ajsodd, deltaphi, dxp,
pupilRadius)).reshape([400, 400])
oddDeltaPSF = fs.getOddPart(deltaPSFoutFoc)
oddPhasor = ph.phasor(oddjs, ajsodd, N, dxp, pupilRadius)
oddPhase = oddPhasor.phase
pupilSin = oddPhasor.pupil * np.sin(deltaphi)
pupilCos = oddPhasor.pupil * np.cos(deltaphi)
FFTPupilSin = fs.scaledfft2(pupilSin, dxp)
FFTPupilCos = fs.scaledfft2(pupilCos, dxp)
lbda = 0.6375e-6
F = 80e-3
pxsize = 5.3e-6
N = 400
dxp = lbda * F / (N * pxsize)
deltaZ = 3.19e-3
jmin = 4
jmax = 30
rmsWFerror = 20.
noiseStdLevels = [1e-3, 2e-3, 5e-3, 1e-2, 2e-2, 5e-2]
PSFinfoc = psf.PSF([1], [0], N, dxp, pupilRadius)
jmin = 4
jmax = 30
oddjs = fs.getOddJs(jmin, jmax)
evenjs = fs.getEvenJs(jmin, jmax)
A1 = np.zeros((N**2, len(oddjs)))
for ij in np.arange(len(oddjs)):
phiJ = fs.f1j(oddjs[ij], N, dxp, pupilRadius)
A1[:, ij] = phiJ
M1 = np.linalg.pinv(A1)
stdErrorOddsAjs = np.sqrt(np.sum(M1**2, 1))
deltaphi = fs.deltaPhi(N, deltaZ, F, 2 * pupilRadius, lbda, dxp)
A2 = np.zeros((N**2, len(evenjs)))
for ij in np.arange(len(evenjs)):
phiJ = fs.f2jeven(evenjs[ij], N, deltaphi, dxp, pupilRadius)
A2[:, ij] = phiJ
M2 = np.linalg.pinv(A2)