##^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^Lance Simms, Stanford University 2009 ##ExaminePersistenceNoise.py ## ##PURPOSE: ## To examine the noise in the core-halo structure of the persistence in ## the HxRG detectors and determine whether it follows poisson statistics. ## ## The same star will be followed in a series of dithers and centered. ## ## 1) Make radial plots around a center spot and show the corresponding ## images ## For this mode, XCen, YCen, and BoxSize must be defined ## ##INPUTS: ## DetStr - 'H1RG-022','H2RG-32-147', or 'H4RG-10-007' ## ElecSt - 'ASIC' or 'LEACH' ## Date - A string containing the date in the path (ex. '07Nov16') ## ObjectName - A string containing the name of the object under study ## Filter - A string designating the filter used: 'G,I,Y' ## NReads - A string with the number of reads in the dark images ## ##KEYWORDS: ## FirstFile: int ## The index of the first read to be plotted ## LastFile: int ## The index of the last read to be plotted ## UseRef: int ## A Boolean; 0-Don't subtract reference 1-Do subtract ## PlotMode: int ## 0 - Plot ramps individually, clearing plot each time ## 1 - Plot all the ramps over each other ## DarkSub: int ## 0 - Don't subtract a dark ## 1 - Subtract a median dark with the same NReads ## FileList: string ## Optionally, all of the files to be examined can ## be specified in this file, one per line ## DoCentroid: int ## 0 - Don't center image around intenisty peak ## 1 - Center the image around intensity ## XCen: int ## X center coordinate for region of interest ## YCen: int ## Y center coordinate for region of interest ## BoxSize: int ## Size of box centered around (XCen, YCen) ## CenSize: int ## Size of box used to do centroid ## TvFlag: int ## 0 - Don't plot ## 1 - Plot ## TrackStar: int ## 0 - Look at the noise in the actual star ## 1 - Look at the noise in the persistence ## AllReads: int ## 0 - Collect data only for read specified by ReadNum ## 1 - Collect data for all reads in all exposures ## ReadNum: int ## The read for which the data will be collected for all ## files in FileList ## ##CALLING SEQUENCE: ## run ExaminePersistenceNoise.py.py [DetStr] [ElecSt] [Date] [ObjectName] [NReads] [Filter] ## ##EXAMPLES: ## ##H2RG_Mars ## ##run ExaminePersistenceNoise.py 'H2RG-32-147' 'ASIC' '07Dec17' 15 'I' 'ForwardBiasedDiodes' --FileList='/nfs/slac/g/ki/ki03/lances/H2RG-32-147/NegPersistence/NGC2683_I_Slopes.lst' --XCen=912 --YCen=1010 --BoxSize=40 --DoCentroid=0 --UseRef=1 ##run ExaminePersistenceNoise.py 'H2RG-32-147' 'ASIC' '07Dec17' 15 'I' 'ForwardBiasedDiodes' --FileList='/nfs/slac/g/ki/ki03/lances/H2RG-32-147/NegPersistence/NGC2683_I_Slopes.lst' --XCen=1555 --YCen=1326 --BoxSize=40 --DoCentroid=0 --UseRef=1 ## ##run ExaminePersistenceNoise.py 'H2RG-32-147' 'ASIC' '07Dec17' 15 'I' 'ForwardBiasedDiodes' --FileList='/nfs/slac/g/ki/ki03/lances/H2RG-32-147/NegPersistence/NGC2683_I_Slopes.lst' --XCen=1555 --YCen=1326 --BoxSize=30 --DoCentroid=1 --UseRef=1 --TvFlag=0 --CenSize=5 ##//////////////////////////////////////////////////////////////////////// ##SETUP execfile('/afs/slac/u/ki/lances/python/python_HxRG/HxRG_Setup.py') execfile('/afs/slac/u/ki/lances/python/SPIEPlotSettings.py') from HxRG_Class import * from ReturnCentroid import * from ReturnRadialAvg import * import TableIO import csv import pdb import asciidata #Get the filename and options from command line DetStr = sys.argv[1] ElecStr = sys.argv[2] Date = sys.argv[3] ObjectName = sys.argv[4] NReads = sys.argv[5] Filter = sys.argv[6] ##INITIAL SETUP HxRG = HxRG_C(DetStr=DetStr, ElecStr=ElecStr, ObjectName=ObjectName) ##PARSE KEYWORDS keywords = ['FirstFile=','LastFile=','UseRef=','DarkSub=','PlotMode=',\ 'FileList=','DoCentroid=','XCen=', 'YCen=', 'BoxSize=',\ 'CenSize=','TvFlag=', 'TrackStar=', 'AllReads=', 'ReadNum='] FirstFile = 0 LastFile = 0 UseRef = 0 DarkSub = 0 PlotMode = 0 FileList = '' DoCentroid = 1 XCen = 100 YCen = 100 BoxSize = 50 CenSize = 8 TvFlag = 0 TrackStar = 0 AllReads = 0 ReadNum = 0 opts, extraparams = getopt.getopt(sys.argv[7:],'',keywords) for o,p in opts: if o in ['--FirstFile']: FirstFile = int(p) elif o in ['--LastFile']: LastFile = int(p) elif o in ['--UseRef']: UseRef = int(p) elif o in ['--DarkSub']: DarkSub = int(p) elif o in ['--PlotMode']: PlotMode= int(p) elif o in ['--FileList']: FileList=p elif o in ['--DoCentroid']: DoCentroid=int(p) elif o in ['--XCen']: XCen =int(p) elif o in ['--YCen']: YCen =int(p) elif o in ['--BoxSize']: BoxSize = int(p) elif o in ['--CenSize']: CenSize = int(p) elif o in ['--TvFlag']: TvFlag = int(p) elif o in ['--TrackStar']: TrackStar = int(p) elif o in ['--AllReads']: AllReads = int(p) elif o in ['--ReadNum']: ReadNum = int(p) #Determine coordinates XStart=XCen-BoxSize/2 ; XStop=XCen+BoxSize/2 YStart=YCen-BoxSize/2 ; YStop=YCen+BoxSize/2 #Form the class that will contain the necessary info HxRG = HxRG_C(DetStr=DetStr, ElecStr=ElecStr, ObjectName=ObjectName, \ Filter=Filter, Date=Date, UseRef=UseRef, NReads=NReads) HxRG.Get_Date(Date) PlotDir = HxRG.DataDir+HxRG.DetStr+'/Plots/NegPersistence/' ##FIND THE MATCHING DARK if DarkSub == 1: HxRG.Get_Median_Dark(HxRG.NReads) DarkHDU = pyfits.open(HxRG.DarkName) ##Take the files in along with the offsets if FileList!='': Columns = asciidata.open(FileList) NumFiles = Columns.nrows ##GO THROUGH THE FILES AND PLOT THE PERSISTENCE mplot.close('all') RadFig = mplot.figure(0) ##USE THESE SYMBOLS AND COLORS PSyms = ['r+','b+','g+','m+','c+','orange+'] PlotHandles = [] LegendLabs = [] LegendSyms = [] FiltersArr = [] FiltersStr = '' ##Get Some Data from the first file FitsFileName = Columns[0][0] FitsHDU = pyfits.open(FitsFileName) HxRG = HxRG_C(FitsFileName=FitsFileName) HxRG.Get_Raw_Header(FitsFileName) ##Setup arrays for holding values if AllReads == 1: if TrackStar == 1: IntArr = zeros([BoxSize,BoxSize,HxRG.NAxis3,NumFiles],dtype=float32) else: IntArr = zeros([BoxSize,BoxSize,HxRG.NAxis3,NumFiles-1],dtype=float32) else: if TrackStar == 1: IntArr = zeros([BoxSize,BoxSize,NumFiles],dtype=float32) else: IntArr = zeros([BoxSize,BoxSize,NumFiles-1],dtype=float32) ##Starting from SECOND FILE, so initially keep offsets at 0 XOff = 0 ; YOff = 0 ##GO THROUGH THE FILES IN SEQUENCE for FileNum in range(Columns.nrows): print 'FileNum: '+str(FileNum) FitsFileName = Columns[0][FileNum] FitsHDU = pyfits.open(FitsFileName) HxRG = HxRG_C(FitsFileName=FitsFileName, ObjectName=ObjectName) HxRG.Get_Raw_Header(FitsFileName) #Get the offsets from the .lst file if TrackStar != 1 and FileNum > 0: XOff = Columns[1][FileNum-1] YOff = Columns[2][FileNum-1] else: XOff = Columns[1][FileNum] YOff = Columns[2][FileNum] #Get Offsets for this file ThisXStart = XStart+XOff; ThisXStop = XStop+XOff ThisYStart = YStart+YOff; ThisYStop = YStop+YOff #Get the image Im = FitsHDU[0].section[HxRG.NAxis3-1,:,:] Im0 = FitsHDU[0].section[0,:,:] #Subtract Reference Pixels if necessary if UseRef==1: Im = ReturnRSFrame(Im,Im0, HxRG.CFac,BadCols=HxRG.BadCols) Im0 = ReturnRSFrame(Im0,Im0, HxRG.CFac,BadCols=HxRG.BadCols) Im = Im-Im0 #Obtain the centroid to align the images if DoCentroid==1: ThisCen = ReturnCentroid(Im, ThisXStart, ThisXStop,\ ThisYStart, ThisYStop, TvFlag=TvFlag,\ CenSize=CenSize) ThisXStart = ThisCen[0]; ThisXStop = ThisCen[1] ThisYStart = ThisCen[2]; ThisYStop = ThisCen[3] #Go through all files and get the reads if AllReads == 1: for ReadNum in arange(HxRG.NAxis3): Im = FitsHDU[0].section[ReadNum,:,:] if UseRef==1: Im = ReturnRSFrame(Im,Im0, HxRG.CFac,BadCols=HxRG.BadCols) Im = Im-Im0 SubIm = Im[ThisYStart:ThisYStop, ThisXStart:ThisXStop] if TrackStar !=1 and FileNum > 0: IntArr[:,:,ReadNum,FileNum-1] = SubIm else: IntArr[:,:,ReadNum,FileNum] = SubIm else: Im = FitsHDU[0].section[ReadNum,:,:] if UseRef==1: Im = ReturnRSFrame(Im,Im0, HxRG.CFac,BadCols=HxRG.BadCols) Im = Im-Im0 SubIm = Im[ThisYStart:ThisYStop, ThisXStart:ThisXStop] if TrackStar !=1 and FileNum > 0: IntArr[:,:,FileNum-1] = SubIm else: IntArr[:,:,FileNum] = SubIm if AllReads == 1: StdArr = IntArr.std(axis=3) MeanArr = IntArr.mean(axis=3) else: StdArr = IntArr.std(axis=2) MeanArr = IntArr.mean(axis=2) RadFig.add_axes([0.05,0.05,.4,.85]) mplot.imshow(StdArr) RadFig.add_axes([.5,0.05,.4,.85]) mplot.imshow(MeanArr)