PSFinfoc = psf.PSF(js,ajstrues[i,:],N,dxp,pupilRadius)
noiseMean = 0.
noiseStd = np.max(PSFinfoc.PSF)*noiseStdLevel
whiteNoise = fsApd.generateWhiteNoise((PSFinfoc.PSF).shape,noiseMean,noiseStd)
PSFinfocWthNoise = PSFinfoc.PSF+whiteNoise
PSFoutfoc = psf.PSF(jswth4,ajswtha4,N,dxp,pupilRadius)
whiteNoise = fsApd.generateWhiteNoise((PSFoutfoc.PSF).shape,noiseMean,noiseStd)
PSFoutfocWthNoise = PSFoutfoc.PSF+whiteNoise
phaseDivWthNoise = PD.phaseDiversity(PSFinfocWthNoise,PSFoutfocWthNoise,deltaZ,lbda,pxsize,F,pupilRadius,jmax)
jsretrieved = phaseDivWthNoise.result['js']
ajsretrieveds[i,:] = phaseDivWthNoise.result['ajs']
rmse[i] = fs.RMSE(ajsretrieveds[i,:]*1e9*lbda/2/np.pi,ajstrues[i,:]*1e9*lbda/2/np.pi)
rmsWFerrorsRetrieved[i] = fs.RMSwavefrontError(jsretrieved,ajsretrieveds[i,:]*1e9*lbda/2/np.pi)
plt.figure()
plt.hold(True)
plt.plot(noiseStdLevels,rmsWFerrorsRetrieved,label='$\sigma_{WF,rms}$ retrieved')
plt.plot(noiseStdLevels,rmsWFerrorsTrue,linewidth=2,c='grey',label='$\sigma_{WF,rms}$ true')
plt.xlabel('noise Std level of PSF/PSF max')
plt.ylabel('$\sigma_{WF,rms}$ retrieved [nm]')
plt.grid()
plt.figure()
plt.plot(noiseStdLevels,rmse)
plt.xlabel('noise Std level of PSF/PSF max')
plt.ylabel('RMSE [nm]')
else:
ajswtha4pos[jswth4 == 4] += a4dephasing
ajswtha4neg[jswth4 == 4] -= a4dephasing
PSFinfoc = psf.PSF(js, ajstrue, N, dxp, pupilRadius)
PSFoutfocpos = psf.PSF(jswth4, ajswtha4pos, N, dxp, pupilRadius)
PSFoutfocneg = psf.PSF(jswth4, ajswtha4neg, N, dxp, pupilRadius)
phaseDiv = PD.phaseDiversity3PSFs(PSFinfoc.PSF, PSFoutfocpos.PSF,
PSFoutfocneg.PSF, deltaZ, lbda, pxsize,
F, pupilRadius, jmin, jmax)
jsretrieved = phaseDiv.result['js']
ajsretrieved = phaseDiv.result['ajs']
rmse[i] = fs.RMSE(ajsretrieved * 1e9 * lbda / 2 / np.pi,
ajstrue * 1e9 * lbda / 2 / np.pi)
rmsWFerrorsRetrieved[i] = fs.RMSwavefrontError(
jsretrieved, ajsretrieved * 1e9 * lbda / 2 / np.pi)
rmsWFerrorMax = np.max(np.append(rmsWFerrors, rmsWFerrorsRetrieved))
rmsWFerrorMin = np.min(np.append(rmsWFerrors, rmsWFerrorsRetrieved))
fnamerms = '../../../fig/PDDev/test/rmsWFerrorsretrieved_rmsWFe%s'
fnamermse = '../../../fig/PDDev/test/rmse_rmsWFe%s'
fig = plt.figure()
plt.hold(True)
plt.plot(rmsWFerrors, rmsWFerrorsRetrieved)
plt.plot([rmsWFerrorMin, rmsWFerrorMax], [rmsWFerrorMin, rmsWFerrorMax],
linewidth=2,
c='grey')
rmsWFeIDLtrue[i] = (((ajsIDLFile[i]).replace('.', '_')).split('_'))[-2]
jsajsTrue = np.loadtxt(ajsTrueFolderPath + '\\' + ajsTrueFile[i])
jsTrue[i, :] = jsajsTrue[0, :]
ajsTrue[i, :] = jsajsTrue[1, :] * 1e9 * lbda / 2 / np.pi
jsajsIDL = np.loadtxt(ajsIDLFolderPath + '\\' + ajsIDLFile[i],
delimiter=',',
skiprows=1)
jsIDL[i, :] = jsajsIDL[:, 0]
ajsIDLmodal[i, :] = jsajsIDL[:, 1] * 1000
ajsIDLzonal[i, :] = jsajsIDL[:, 2] * 1000
rmsWFeIDLmodalretrieved[i] = fs.RMSwavefrontError(jsIDL[i, :],
ajsIDLmodal[i, :])
rmsemodal[i] = fs.RMSE(ajsIDLmodal[i, :], ajsTrue[i, :])
rmsWFeIDLzonalretrieved[i] = fs.RMSwavefrontError(jsIDL[i, :],
ajsIDLzonal[i, :])
rmsezonal[i] = fs.RMSE(ajsIDLzonal[i, :], ajsTrue[i, :])
rmsWFefolderPath = 'C:\\Users\\Jojo\\Desktop\\PdM-HEIG\\Science\\data\\devPD\\PSFforIDLtreatment\\PSFs'
rmsWFerrorFolderPaths = os.listdir(rmsWFefolderPath)
NrmsWFe = len(rmsWFerrorFolderPaths)
rmsePy = np.zeros(NrmsWFe)
rmsWFerrorsPyRetrieved = np.zeros(NrmsWFe)
rmsWFeTruePy = np.zeros(NrmsWFe)
jsretrieved = np.zeros([NrmsWFe, jmax - jmin + 1])
ajsretrieved = np.zeros([NrmsWFe, jmax - jmin + 1])
for irms, rmsWFdir in enumerate(rmsWFerrorFolderPaths):
#noiseStd = np.max(PSFoutfocneg.PSF)*noiseStdLevel
#whiteNoise = fsApd.generateWhiteNoise((PSFoutfocneg.PSF).shape,noiseMean,noiseStd)
#PSFoutfocnegWthNoise = PSFoutfocneg.PSF+whiteNoise
phaseDivWoutNoise = PD.phaseDiversity3PSFs(PSFinfoc.PSF,PSFoutfocpos.PSF,PSFoutfocneg.PSF,deltaZ,lbda,pxsize,F,pupilRadius,jmin,jmax)
#phaseDivWthNoise = PD.phaseDiversity3PSFs(PSFinfocWthNoise,PSFoutfocposWthNoise,PSFoutfocnegWthNoise,deltaZ,lbda,pxsize,F,pupilRadius,jmin,jmax)
#print phaseDiv.result['ajs']*1e9*lbda/2/np.pi
#print ajstrue*1e9*lbda/2/np.pi
plt.figure()
plt.hold(True)
plt.plot(jscomplete,ajscomplete*1e9*lbda/2/np.pi,'b-',label='true, $\sigma_{WF,rms}$ = %5.3f nm' %(fs.RMSwavefrontError(js,ajstrue*1e9*lbda/2/np.pi)))
plt.errorbar(phaseDivWoutNoise.result['js'],phaseDivWoutNoise.result['ajs']*1e9*lbda/2/np.pi,yerr=phaseDivWoutNoise.result['ajsSte']*1e9*lbda/2/np.pi
,color = 'red',lineStyle='-',label='retrieved wout noise, $\sigma_{WF,rms}$ = %5.3f nm, RMSE = %5.3f nm'
%(fs.RMSwavefrontError(phaseDivWoutNoise.result['js'],phaseDivWoutNoise.result['ajs']*1e9*lbda/2/np.pi)
,fs.RMSE(phaseDivWoutNoise.result['ajs']*1e9*lbda/2/np.pi,ajscomplete*1e9*lbda/2/np.pi)))
#plt.errorbar(phaseDivWthNoise.result['js'],phaseDivWthNoise.result['ajs']*1e9*lbda/2/np.pi,yerr=phaseDivWthNoise.result['ajsSte']*1e9*lbda/2/np.pi
# ,color = 'green',lineStyle='-',label='retrieved wth noise, $\sigma_{WF,rms}$ = %5.3f nm, RMSE = %5.3f nm'
# %(fs.RMSwavefrontError(phaseDivWthNoise.result['js'],phaseDivWthNoise.result['ajs']*1e9*lbda/2/np.pi)
# ,fs.RMSE(phaseDivWthNoise.result['ajs']*1e9*lbda/2/np.pi,ajscomplete*1e9*lbda/2/np.pi)))
plt.xlabel('j')
plt.ylabel('aj [nm]')
plt.xlim([jscomplete[0],jscomplete[-1]])
plt.legend(loc='upper center')
plt.grid()
fnameajsjs = '../../../fig/PDDev/test/ajs_js_jmax_%d_WoutN_rmsWFe_%d%s'
plt.savefig(fnameajsjs % (jmax,rmsWFerror,'.png'), dpi=300)
plt.savefig(fnameajsjs % (jmax,rmsWFerror,'.pdf'), dpi=300)
plt.figure()
# %(jm,fs.RMSwavefrontError(phaseDivWoutNoise[ij].result['js'],phaseDivWoutNoise[ij].result['ajs']*1e9*lbda/2/np.pi)
# ,fs.RMSE((phaseDivWoutNoise[ij].result['ajs'])[0:jmax[2]-3]*1e9*lbda/2/np.pi,ajscomplete*1e9*lbda/2/np.pi)))
# else :
plt.errorbar(
phaseDivWoutNoise[ij].result['js'],
phaseDivWoutNoise[ij].result['ajs'] * 1e9 * lbda / 2 / np.pi,
yerr=phaseDivWoutNoise[ij].result['ajsSte'] * 1e9 * lbda / 2 / np.pi,
lineStyle='-',
label=
'retrieved jmax = %d, $\sigma_{WF,rms}$ = %5.3f nm, RMSE = %5.3f nm' %
(jm,
fs.RMSwavefrontError(
phaseDivWoutNoise[ij].result['js'],
phaseDivWoutNoise[ij].result['ajs'] * 1e9 * lbda / 2 / np.pi),
fs.RMSE(
(phaseDivWoutNoise[ij].result['ajs']) * 1e9 * lbda / 2 / np.pi,
ajscomplete[0:jm - 3] * 1e9 * lbda / 2 / np.pi)))
#plt.errorbar(phaseDivWthNoise.result['js'],phaseDivWthNoise.result['ajs']*1e9*lbda/2/np.pi,yerr=phaseDivWthNoise.result['ajsSte']*1e9*lbda/2/np.pi
# ,color = 'green',lineStyle='-',label='retrieved wth noise, $\sigma_{WF,rms}$ = %5.3f nm, RMSE = %5.3f nm'
# %(fs.RMSwavefrontError(phaseDivWthNoise.result['js'],phaseDivWthNoise.result['ajs']*1e9*lbda/2/np.pi)
# ,fs.RMSE(phaseDivWthNoise.result['ajs']*1e9*lbda/2/np.pi,ajscomplete*1e9*lbda/2/np.pi)))
plt.xlabel('j')
plt.ylabel('aj [nm]')
plt.xlim([np.min(jmax), np.max(jmax)])
plt.legend(loc='best', fontsize=16)
plt.grid()
fnameajsjs = '../../../fig/PDDev/test/ajs_js_jmaxstudy_WoutN_rmsWFe_%d%s'
#plt.savefig(fnameajsjs % (rmsWFerror,'.png'), dpi=300)
#plt.savefig(fnameajsjs % (rmsWFerror,'.pdf'), dpi=300)
PSFoutfoc = psf.PSF(jswth4,ajswtha4,N,dxp,pupilRadius)
noiseMean = 0.
noiseStd = np.max(PSFoutfoc.PSF)*noiseStdLevel
whiteNoise = fsApd.generateWhiteNoise((PSFoutfoc.PSF).shape,noiseMean,noiseStd)
PSFoutfocWthNoise = PSFoutfoc.PSF+whiteNoise
phaseDivWoutNoise = PD.phaseDiversity(PSFinfoc.PSF,PSFoutfoc.PSF,deltaZ,lbda,pxsize,F,pupilRadius,jmax)
phaseDivWthNoise = PD.phaseDiversity(PSFinfocWthNoise,PSFoutfocWthNoise,deltaZ,lbda,pxsize,F,pupilRadius,jmax)
#print phaseDiv.result['ajs']*1e9*lbda/2/np.pi
#print ajstrue*1e9*lbda/2/np.pi
plt.figure()
plt.hold(True)
plt.plot(js,ajstrue*1e9*lbda/2/np.pi,'b-',label='true, $\sigma_{WF,rms}$ = %5.3f nm' %(fs.RMSwavefrontError(js,ajstrue*1e9*lbda/2/np.pi)))
plt.xlim([js[0],js[-1]])
plt.hold(True)
plt.plot(phaseDivWoutNoise.result['js'],phaseDivWoutNoise.result['ajs']*1e9*lbda/2/np.pi
,'r-',label='retrieved wout noise, $\sigma_{WF,rms}$ = %5.3f nm, RMSE = %5.3f nm'
%(fs.RMSwavefrontError(phaseDivWoutNoise.result['js'],phaseDivWoutNoise.result['ajs']*1e9*lbda/2/np.pi)
,fs.RMSE(phaseDivWoutNoise.result['ajs']*1e9*lbda/2/np.pi,ajstrue*1e9*lbda/2/np.pi)))
plt.plot(phaseDivWthNoise.result['js'],phaseDivWthNoise.result['ajs']*1e9*lbda/2/np.pi
,'g-',label='retrieved wth noise, $\sigma_{WF,rms}$ = %5.3f nm, RMSE = %5.3f nm'
%(fs.RMSwavefrontError(phaseDivWthNoise.result['js'],phaseDivWthNoise.result['ajs']*1e9*lbda/2/np.pi)
,fs.RMSE(phaseDivWthNoise.result['ajs']*1e9*lbda/2/np.pi,ajstrue*1e9*lbda/2/np.pi)))
plt.xlabel('j')
plt.ylabel('aj [nm]')
plt.legend(loc='best')
plt.grid()
lbda, pxsize, F, pupilRadius,
jmin, jmax)
ajss[irmsWFe, iNretrieve, :] = phaseDivWthNoise.result['ajs']
ajsSte[irmsWFe, iNretrieve, :] = phaseDivWthNoise.result['ajsSte']
fnameajsjsWthe = '../../../fig/PDDev/test/ajs_js_WthE_rmsWFe_%d%s'
fnameajsjsWoute = '../../../fig/PDDev/test/ajs_js_WoutE_rmsWFe_%d%s'
fnamebxpajsjs = '../../../fig/PDDev/test/bxp_ajs_js_rmsWFe_%d%s'
plt.ioff()
for irmsWFe, rmsWFerror in enumerate(rmsWFerrors):
meanAjsRetrieved = np.mean(ajss[irmsWFe, :, :], 0) * 1e9 * lbda / 2 / np.pi
meanrmsWFerror = fs.RMSwavefrontError(jscomplete, meanAjsRetrieved)
meanRMSE = fs.RMSE(meanAjsRetrieved, ajscomplete * 1e9 * lbda / 2 / np.pi)
#Plot all the result
fig = plt.figure()
plt.title(
'Nretrieval = %d, $\sigma_{wf,rms}$ = %3.1fnm, noiseStdLevel = %4.3f [maxPSF]'
% (Nretrieve, rmsWFerror, noiseStdLevel))
plt.hold(True)
for iNretrieve in np.arange(Nretrieve - 1):
plt.errorbar(jscomplete,
ajss[irmsWFe, iNretrieve, :] * 1e9 * lbda / 2 / np.pi,
yerr=ajsSte[irmsWFe, iNretrieve, :] * 1e9 * lbda / 2 /
np.pi,
linewidth=0.5,
color='red')
plt.errorbar(
jscomplete,