def loadSpectra(self):
fileName = self.params['outFileName']
if os.path.exists(fileName):
data = np.load(fileName)
self.spectra = data['cube']
self.frame = data['frame']
self.frameValues = self.frame[~np.isnan(self.frame)]
self.wvlBinEdges = np.array(self.obList[0].flatCalWvlBins)
self.frameIntTime = 300*6
else:
self.spectra,self.wvlBinEdges = self.obList[0].getSpectralCube(weighted=True)
self.frameIntTime = 0
for ob in self.obList[1:]:
print ob.fileName
cube,wvlBinEdges = ob.getSpectralCube(weighted=True)
self.spectra += cube
self.frameIntTime += ob.getFromHeader('exptime')
self.spectra = np.array(self.spectra,dtype=np.float64)
self.frame = np.sum(self.spectra,axis=2)
hotPixMask = hotPixels.findHotPixels(image=self.frame,nsigma=2)['badflag']
self.frame[hotPixMask != 0] = np.nan
self.frame[self.frame == 0] = np.nan
self.frameValues = self.frame[~np.isnan(self.frame)]
np.savez(fileName,cube=self.spectra,frame=self.frame)
def main():
#filenames = ['obs_20121212-033825.h5',
fn = FileName(run='PAL2012',date='20121211',tstamp='20121212-055428').obs()
ob = ObsFile(fn)
frame = ob.getPixelCountImage(0,30,weighted=False)
hotPixMask = hotPixels.findHotPixels(image=frame,firstSec=0,intTime=30,weighted=False)['badflag']
frame[hotPixMask == 1] = 0
def plotFrame(fig,axes):
hMat=axes.matshow(frame,cmap=matplotlib.cm.gnuplot,origin='lower',vmax=np.mean(frame)+3*np.std(frame))
fig.colorbar(hMat)
PopUp(plotFunc=plotFrame)
#d = datetime.date(2012,10,15)#date of table value
#d2 = datetime.date(2012,12,11)#date of observation
#dt=(d2-d).total_seconds()#seconds between obs and table value
##crabtime ephemeris
#nu=29.6957720714 #1/us
#pdot=4.2013878e-13#us/s
#period=(1.0/nu)+pdot*dt#us
#goldstone ephemeris
F0=29.7414493465249770#Hz
deltaF0=0.0000000055983574
F1=-3.669005118205e-10#df0/dt Hz/s
F2=-3.085573120457e-20#d^2f0/dt^2 Hz/s^2
pEpoch = 54781.604891 #Modified Julian Date corresponding to F0
pEpoch = pEpoch+2400000.5#convert mjd to jd
pEpoch *= 24*3600 #in seconds
#obsDate = ob.getFromHeader('jd')
unixEpochJD = 2440587.5
unixSecsInDay = 86400.
headerUnixtime = ob.getFromHeader('unixtime')
obsDate = headerUnixtime/unixSecsInDay+unixEpochJD
startTime = obsDate*24*3600#in seconds
dt = startTime-pEpoch#seconds since pepoch
#freq = F0+F1*dt+F2/2*dt**2
freq = F0+F1*dt
period = 1.0/freq
print 'period=',period,'s'
#period=0.03367660643405371
#period=0.03367664238573182
#period=0.03367662440988317
iRow = 10
iCol = 14
integrationTime = 30
circCol,circRow = circ(iCol,iRow,radius=5)
firstSec = 0
dt = startTime-pEpoch + firstSec
freq = F0+F1*dt
period = 1.0/freq
print 'period=',period,'s'
nPhaseBins = 200
#np.set_printoptions(threshold=np.nan)
jdTimes = np.array([],dtype=np.float64)
times = np.array([])
for i in range(len(circCol)):
iRow = circRow[i]
iCol = circCol[i]
timestamps,peaks,baselines = ob.getTimedPacketList(iRow,iCol,firstSec,integrationTime)
timestamps = np.array(timestamps,dtype=np.float64)
jdTimestamps = obsDate+timestamps /(24.*3600.)
jdTimes = np.append(jdTimes,jdTimestamps)
times = np.append(times,timestamps)
jdTimes -= 2400000.5 #convert to modified jd
np.savetxt('crabOpticalSample-20121212-055428.txt',jdTimes)
periodDays = period/(24.*3600.)
phaseOffset = .2
phases = (jdTimes % periodDays)/periodDays+.2
phases = phases % 1.0
print len(phases)
histPhases,phaseBinEdges = np.histogram(phases,bins=nPhaseBins)
print jdTimes[0:10]
print times[0:10]
plt.plot(phaseBinEdges[0:-1],histPhases)
plt.show()
