def dedisperse(self,dm,gulp=10000):
"""Dedisperse filterbank to timeseries.
Args:
dm -- Dispersion measure to dedisperse to
gulp -- size of block to read at a time, if chosen gulp
is less than maximum dispersion delay gulp is taken as 2 * max delay.
Returns: TimeSeries instance
"""
chanDelays = self.getDMdelays(dm)
delayPointer = arrayToPointer(chanDelays)
maxDelay = int(chanDelays.max())
gulp = max(2*maxDelay,gulp)
timLen = self.info["nsamples"]-maxDelay
timBuffer = Buffer(timLen,C.c_float)
readBuffer = Buffer(self.info["nchans"]*gulp,self.ctype)
passPlan = ReadPlan(self,readBuffer)
passPlan.readSkipBack(gulp,maxDelay)
for nsamps,ii in passPlan.makePass():
self.lib.dedisperse(readBuffer.Cbuffer,timBuffer.Cbuffer,delayPointer,
maxDelay, self.info["nchans"], nsamps, ii*(gulp-maxDelay))
timInfo = self.info.copy()
timInfo["nsamples"] = timLen
timInfo["refdm"] = dm
return TimeSeries(timInfo,timBuffer)
def fold(self,period,dm,nbins=50,nints=32,nbands=32,gulp=10000):
"""Fold filterbank phase bins, subintegrations and subbands.
Args:
period -- period in seconds to fold with
nbins -- number of phase bins in output
nints -- number of subintegrations in output
Returns: FoldedData instance
"""
nbands = min(nbands,self.info["nchans"])
chanDelays = self.getDMdelays(dm)
delayPointer = arrayToPointer(chanDelays)
maxDelay = int(chanDelays.max())
gulp = max(2*maxDelay,gulp)
foldBuffer = Buffer(nbins*nints*nbands,C.c_float)
countBuffer = Buffer(nbins*nints*nbands,C.c_int)
readBuffer = Buffer(self.info["nchans"]*gulp,self.ctype)
passPlan = ReadPlan(self,readBuffer)
passPlan.readSkipBack(gulp,maxDelay)
for nsamps,ii in passPlan.makePass():
self.lib.foldFil(readBuffer.Cbuffer, foldBuffer.Cbuffer, countBuffer.Cbuffer,
delayPointer, maxDelay, C.c_double(self.info["tsamp"]),
C.c_double(period), gulp, self.info["nchans"], nbins,
nints, nbands, ii*(gulp-maxDelay))
parentInfo = self.info.copy()
return FoldedData(parentInfo,foldBuffer,countBuffer,
period,dm,nbins,nints,nbands)
def dropBits32to8(self,gulp=1024,flag=0,clip=0):
if self.stats is None:
raise AttributeError,"First run getStatistics()"
readBuffer = Buffer(self.info["nchans"]*gulp,self.ctype)
writeBuffer = Buffer(self.info["nchans"]*gulp,C.c_ubyte)
passPlan = ReadPlan(self,readBuffer)
passPlan.readOnce(gulp)
if flag is not 0:
flagBuffer = Buffer(self.info["nchans"]*gulp,C.c_ubyte)
flagMax = flag*self.stats["sigma"].astype("float32")
flagMin = -flag*self.stats["sigma"].astype("float32")
if clip is not 0:
chanMax = numpy.array([min(a,b) for a,b in zip(clip*self.stats["sigma"],self.stats["maxima"])])
chanMin = numpy.array([max(a,b) for a,b in zip(-clip*self.stats["sigma"],self.stats["minima"])])
else:
chanMax = self.stats["maxima"]
chanMin = self.stats["minima"]
chanFactor = ((chanMax-chanMin)/255.)
chanPlus = (chanMin/chanFactor)
outFile = self.prepOutfile("%s_8bit.fil"%(self.basename),(("nbits",8)))
if flag is not 0:
changes = (("nbits",8),("source_name","%s_mask"%(self.info["source_name"].split()[0])))
flagFile = self.prepOutfile("%s_8bit_mask.fil"%(self.basename),changes)
for nsamps,ii in passPlan.makePass():
self.lib.to8bit(readBuffer.Cbuffer,writeBuffer.Cbuffer,
arrayToPointer(chanFactor),arrayToPointer(chanPlus),
nsamps,self.info["nchans"])
outFile.cwrite(writeBuffer)
if flag is not 0:
lib.flagBlock(readBuffer.Cbuffer,flagBuffer.Cbuffer,
arrayToPointer(flagMax),arrayToPointer(flagMin),
nsamps,self.info["nchans"])
flagFile.cwrite(flagBuffer)
if flag is not 0:
return(Filterbank(outFile.name),Filterbank(flagFile.name))
else:
return Filterbank(outFile.name)
