# Plot Response vs Frequency for 1st and 2nd stages
def f(fig, ax):
ax.plot(freqListMHz, freqResponsePfbDb, label="FFT bin")
# ax.plot(freqListMHz,freqResponseFftDb)
# ax.plot(freqListMHz,freqResponseLpfDb)
ax.plot(freqListMHz, freqResponseDb, label="final channel")
ax.axvline(resFreq / 1.0e6, color=".5", label="resonant freq")
ax.axvline(resFreq2 / 1.0e6, color=".8")
ax.axvline(resFreq3 / 1.0e6, color=".8")
ax.set_ylim(-50, 0)
ax.set_ylabel("response (dB)")
ax.set_xlabel("frequency (MHz)")
ax.legend(loc="lower left")
pop(plotFunc=lambda fig, axes: f(fig=fig, ax=axes))
# Plot Response vs Phase for 1st and 2nd stages
def f(fig, ax):
ax.plot(freqListMHz, phaseResponse, label="overall")
ax.plot(freqListMHz, phaseResponseLpf, label="LPF")
ax.plot(freqListMHz, phaseResponsePfb, label="FFT")
ax.axvline(resFreq / 1.0e6, color=".5", label="resonant freq")
ax.axvline(resFreq2 / 1.0e6, color=".8")
ax.axvline(resFreq3 / 1.0e6, color=".8")
ax.set_ylabel("phase response ($^\circ$)")
ax.set_xlabel("frequency (MHz)")
ax.legend(loc="best")
pop(plotFunc=lambda fig, axes: f(fig=fig, ax=axes))
print 'illumination corrected sigma', illumFwhm['sigma'],
print '{:.1f}%'.format(illumFwhmPercent)
print 'flatfield corrected sigma', flatFwhm['sigma'],
print '{:.1f}%'.format(flatFwhmPercent)
print 'shot noise sigma',shotNoiseSigma,'{:.1f}%'.format(shotPercent)
print 'noise ratio',flatToShotNoiseRatio
# Plot
def plotFunc(fig,axes):
axes.set_title('Distribution of pixel counts')
axes.plot(rawHistEdges[0:-1],rawHist,color='k',label='raw')
axes.plot(illumHistEdges[0:-1],illumHist,color='b',label='illum')
axes.plot(flatHistEdges[0:-1],flatHist,'r',label='flatfield')
axes.set_xlabel('Counts')
axes.set_ylabel('Num of Pixels')
axes.legend()
pop(plotFunc=plotFunc)
plotDict = {'rawHistEdges':rawHistEdges,'rawHist':rawHist,'illumHistEdges':illumHistEdges,'illumHist':illumHist,'flatHistEdges':flatHistEdges,'flatHist':flatHist,'flatLabel':flatLabel,'lowerWvlCut':lowerWvlCut,'upperWvlCut':upperWvlCut,'imgFilename':outfilename,'obsDate':date,'obsTimestamp':obsTimestamp,'bClippedImgs':bClipData,'nBins':nBins}
pickle.dump(plotDict,open( 'flatHist.pickle', 'wb' ))
#outfile.write('{}\t{}\t{:.1f}\t{:.1f}\t{:.1f}\t{:.1f}\t{:.2f}\t{}\n'.format(obsTimestamp,avgCounts,rawFwhmPercent,illumFwhmPercent,flatFwhmPercent,shotPercent,flatToShotNoiseRatio,exptime))
