def findv1(self):
populationMax=2000
ySum = np.zeros(populationMax)
frameSum = 'none'
seq5 = self.s['seq5'].split()
for seq in seq5:
print "seq=",seq
outfileName = "cosmicTimeList-"+seq+".pkl"
if not os.path.exists(outfileName):
fn = FileName(self.s['run'],
self.s['sundownDate'],
self.s['obsDate']+"-"+str(seq))
cosmic = Cosmic(fn,
beginTime=self.s['beginTime'],
endTime=self.s['endTime'],
loggingLevel = logging.INFO)
fc = cosmic.findCosmics(stride=int(self.s['stride']),
threshold=int(self.s['threshold']),
populationMax=populationMax,
nSigma=float(self.s['nSigma']))
outfile = open(outfileName, "wb")
pickle.dump(fc['cosmicTimeList'],outfile)
pickle.dump(fc['binContents'],outfile)
outfile.close()
cfn = "cosmicMask-%s.h5"%seq
ObsFile.writeCosmicIntervalToFile(fc['interval'],1.0e6, cfn,
self.s['beginTime'],
self.s['endTime'],
int(self.s['stride']),
int(self.s['threshold']),
float(self.s['nSigma']),
populationMax)
del cosmic
#cosmic = Cosmic(fn, endTime='exptime')
cosmic = Cosmic(fn, beginTime=0)
fc = cosmic.findCosmics(stride=stride,
threshold=threshold,
populationMax=populationMax,
nSigma=nSigma)
if frameSum == 'none':
frameSum = fc['frameSum']
else:
frameSum += fc['frameSum']
outfile = open("cosmicTimeList-"+seq+".pkl", "wb")
pickle.dump(fc['cosmicTimeList'],outfile)
pickle.dump(fc['binContents'],outfile)
outfile.close()
cfn = "cosmicMax-%s.h5"%seq
ObsFile.writeCosmicIntervalToFile(fc['interval'],1.0e6, cfn)
populationHg = fc['populationHg']
yPlot = populationHg[0].astype(np.float)
ySum += yPlot
norm = yPlot.sum()
yPlot /= norm
yPlot[yPlot==0] = 1e-3/norm
xPlot = 0.5*(populationHg[1][1:]+populationHg[1][:-1])
plt.clf()
plt.plot(xPlot,yPlot,'-')
plt.yscale('log')
plt.ylim(ymin=0.5/norm)
plt.xlim(1,populationMax)
plt.xscale('log')
#poisson = []
#xValues = populationHg[1][1:]-0.5
def findCosmics(self, stride=10, threshold=100,
populationMax=2000, nSigma=5, writeCosmicMask=False,
ppsStride=10000):
"""
Find cosmics ray suspects. Histogram the number of photons
recorded at each timeStamp. When the number of photons in a
group of stride timeStamps is greater than threshold in second
iSec, add (iSec,timeStamp) to cosmicTimeLists. Also keep
track of the histogram of the number of photons per stride
timeStamps.
return a dictionary of 'populationHg', 'cosmicTimeLists',
'binContents', 'timeHgValues', 'interval', 'frameSum', and 'pps'
populationHg is a histogram of the number of photons in each time bin.
This is a poisson distribution with a long tail due to cosmic events
cosmicTimeLists is a numpy array of all the sequences that are
suspects for cosmic rays
binContents corresponds to cosmicTimeLists. For each time in
cosmicTimeLists, binContents is the number of photons detected
at that time.
timeHgValues is a histogram of the number of photons in each time
interval
frameSum is a two dimensional numpy array of the number of photons
detected by each pixel
interval is the interval of data to be masked out
pps is photons per second, calculated every ppsStride bins.
"""
self.logger.info("findCosmics: begin stride=%d threshold=%d populationMax=%d nSigma=%d writeCosmicMask=%s"%(stride,threshold,populationMax,nSigma,writeCosmicMask))
exptime = self.endTime-self.beginTime
nBins = int(np.round(self.file.ticksPerSec*exptime+1))
bins = np.arange(0, nBins, 1)
timeHgValues,frameSum = self.getTimeHgAndFrameSum(self.beginTime,self.endTime)
remainder = len(timeHgValues)%ppsStride
if remainder > 0:
temp = timeHgValues[:-remainder]
else:
temp = timeHgValues
ppsTime = (ppsStride*self.file.tickDuration)
pps = np.sum(temp.reshape(-1, ppsStride), axis=1)/ppsTime
self.logger.info("findCosmics: call populationFromTimeHgValues")
pfthgv = Cosmic.populationFromTimeHgValues\
(timeHgValues,populationMax,stride,threshold)
#now build up all of the intervals in seconds
self.logger.info("findCosmics: build up intervals: nCosmicTime=%d"%len(pfthgv['cosmicTimeList']))
i = interval()
iCount = 0
secondsPerTick = self.file.tickDuration
for cosmicTime in pfthgv['cosmicTimeList']:
#t0 = max(0,self.beginTime+(cosmicTime-50)/1.e6)
#t1 = min(self.endTime,self.beginTime+(cosmicTime+50)/1.e6)
#intTime = t1-t0
t0 = self.beginTime+cosmicTime*secondsPerTick
dt = stride*secondsPerTick
t1 = t0+dt
left = max(self.beginTime, t0-nSigma*dt)
right = min(self.endTime, t1+2*nSigma*dt)
i = i | interval[left,right]
self.logger.debug("findCosmics: iCount=%d t0=%f t1=%f left=%f right=%f"%(iCount,t0,t1,left,right))
iCount+=1
tMasked = Cosmic.countMaskedBins(i)
ppmMasked = 1000000*tMasked/(self.endTime-self.beginTime)
retval = {}
retval['timeHgValues'] = timeHgValues
retval['populationHg'] = pfthgv['populationHg']
retval['cosmicTimeList'] = pfthgv['cosmicTimeList']
retval['binContents'] = pfthgv['binContents']
retval['frameSum'] = frameSum
retval['interval'] = i
retval['ppmMasked'] = ppmMasked
retval['pps'] = pps
retval['ppsTime'] = ppsTime
if writeCosmicMask:
cfn = self.fn.cosmicMask()
self.logger.info("findCosmics: write masks to =%s"%cfn)
ObsFile.writeCosmicIntervalToFile(i, self.file.ticksPerSec,
cfn,self.beginTime, self.endTime,
stride, threshold, nSigma, populationMax)
self.logger.info("findCosmics: end with ppm masked=%d"%ppmMasked)
return retval