def waveforms(self, samples, deltat, inittime):
noise = self.synthesize(samples, deltat, inittime)
[hp, hc] = numpy.transpose(
synthlisa.getobs(samples, deltat, [noise.hp, noise.hc], inittime))
return (hp, hc)
sys.exit(1)
elif len(sourceobjects) == 1:
tdi = synthlisa.TDIsignal(lisa, sourceobjects[0])
else:
# print "(proceeding with %s sources)" % len(sourceobjects)
tdi = synthlisa.TDIsignal(lisa, synthlisa.WaveArray(sourceobjects))
if options.rawMeasurements:
[
t, X, Y, Z, y123, y231, y312, y321, y132, y213, z123, z231, z312, z321,
z132, z213
] = numpy.transpose(
synthlisa.getobs(samples,
options.timestep, [
tdi.t, tdi.Xm, tdi.Ym, tdi.Zm, tdi.y123, tdi.y231,
tdi.y312, tdi.y321, tdi.y132, tdi.y213, tdi.z123,
tdi.z231, tdi.z312, tdi.z321, tdi.z132, tdi.z213
],
options.inittime,
display=options.verbose))
obsstr = 't,Xf,Yf,Zf'
else:
# note that choices of options.observables other than 1.5 are not compatible with debugSNR and/or RequestSN
if options.observables == '1.5':
obsset = [tdi.t, tdi.Xm, tdi.Ym, tdi.Zm]
obsstr = 't,Xf,Yf,Zf'
elif options.observables == '2.0':
obsset = [tdi.t, tdi.X1, tdi.X2, tdi.X3]
obsstr = 't,X1f,X2f,X3f'
elif options.observables == 'Sagnac':
obsset = [tdi.alpham, tdi.betam, tdi.gammam, tdi.zetam]
if len(sourceobjects) == 0:
print "!!! Could not find any suitable sources..."
sys.exit(1)
elif len(sourceobjects) == 1:
tdi = synthlisa.TDIsignal(lisa,sourceobjects[0])
else:
# print "(proceeding with %s sources)" % len(sourceobjects)
tdi = synthlisa.TDIsignal(lisa,synthlisa.WaveArray(sourceobjects))
if options.rawMeasurements:
[t,X,Y,Z,
y123,y231,y312,y321,y132,y213,
z123,z231,z312,z321,z132,z213] = numpy.transpose(synthlisa.getobs(samples,options.timestep,
[tdi.t,tdi.Xm,tdi.Ym,tdi.Zm,
tdi.y123,tdi.y231,tdi.y312,tdi.y321,tdi.y132,tdi.y213,
tdi.z123,tdi.z231,tdi.z312,tdi.z321,tdi.z132,tdi.z213],
options.inittime,display=options.verbose))
obsstr = 't,Xf,Yf,Zf'
else:
# note that choices of options.observables other than 1.5 are not compatible with debugSNR and/or RequestSN
if options.observables == '1.5':
obsset = [tdi.t,tdi.Xm,tdi.Ym,tdi.Zm]
obsstr = 't,Xf,Yf,Zf'
elif options.observables == '2.0':
obsset = [tdi.t,tdi.X1,tdi.X2,tdi.X3]
obsstr = 't,X1f,X2f,X3f'
elif options.observables == 'Sagnac':
obsset = [tdi.alpham,tdi.betam,tdi.gammam,tdi.zetam]
obsstr = 'alphaf,betaf,gammaf,zetaf'
2, # norm = 1.0, no filtering, Lagrange-2 interpolation
waveforms.EclipticLatitude,
waveforms.EclipticLongitude,
0) # polarization already encoded in hp,hc
# this hardcodes the standard LISA object for the MLDC...
# lisa = synthlisa.CacheLISA(synthlisa.CircularRotating(0.0,1.5*pi,-1))
lisa = synthlisa.CacheLISA(synthlisa.EccentricInclined(0.0, 1.5 * pi, -1))
tdi = synthlisa.TDIsignal(lisa, source)
samples = int(options.duration / options.timestep + 0.1)
[t, X, Y, Z] = numpy.transpose(
synthlisa.getobs(samples,
options.timestep, [tdi.t, tdi.Xm, tdi.Ym, tdi.Zm],
options.inittime,
display=options.verbose))
# Computing SNR....
# this is |\tilde{h}|^2 * dt/N
sampling = ts.Cadence
hX = synthlisa.spect(X, sampling, 0)
hY = synthlisa.spect(Y, sampling, 0)
hZ = synthlisa.spect(Z, sampling, 0)
# get frequencies, skip DC
fr = hX[1:, 0]
om = 2.0 * pi * fr
source = synthlisa.SampledWave(hp,hc,
ts.Length,ts.Cadence,-ts.TimeOffset, # synthlisa prebuffer is -TimeOffset
1.0,synthlisa.NoFilter(),2, # norm = 1.0, no filtering, Lagrange-2 interpolation
waveforms.EclipticLatitude,
waveforms.EclipticLongitude,0) # polarization already encoded in hp,hc
# this hardcodes the standard LISA object for the MLDC...
# lisa = synthlisa.CacheLISA(synthlisa.CircularRotating(0.0,1.5*pi,-1))
lisa = synthlisa.CacheLISA(synthlisa.EccentricInclined(0.0,1.5*pi,-1))
tdi = synthlisa.TDIsignal(lisa,source)
samples = int( options.duration / options.timestep + 0.1 )
[t,X,Y,Z] = numpy.transpose(synthlisa.getobs(samples,options.timestep,
[tdi.t,tdi.Xm,tdi.Ym,tdi.Zm],
options.inittime,display=options.verbose))
# Computing SNR....
# this is |\tilde{h}|^2 * dt/N
sampling = ts.Cadence
hX = synthlisa.spect(X,sampling,0)
hY = synthlisa.spect(Y,sampling,0)
hZ = synthlisa.spect(Z,sampling,0)
# get frequencies, skip DC
fr = hX[1:,0]
om = 2.0 * pi * fr
elif options.observables == 'Sagnac':
obsset = [tdi.alpham,tdi.betam,tdi.gammam,tdi.zetam]
obsstr = 'alphaf,betaf,gammaf,zetaf'
else:
parser.error("I don't recognize the set of TDI observables!")
# add phase measurements if requested
if options.raw:
obsset += [tdi.t,tdi.y123,tdi.y231,tdi.y312,tdi.y321,tdi.y132,tdi.y213,
tdi.z123,tdi.z231,tdi.z312,tdi.z321,tdi.z132,tdi.z213]
rawstr = 't,y123f,y231f,y312f,y321f,y132f,y213f,z123f,z231f,z312f,z321f,z132f,z213f'
# run synthlisa
samples = int( options.duration / options.timestep + 0.1 )
obsarray = synthlisa.getobs(samples,options.timestep,obsset,options.inittime,display=options.verbose)
# save to XML
if options.raw:
tdiobs = lisaxml.Observable(obsstr,datatype='FractionalFrequency')
tdiobs.TimeSeries = lisaxml.TimeSeries(obsarray[:,0:4],obsstr,Cadence=options.timestep,TimeOffset=options.inittime)
outputXML.TDIData(tdiobs)
tdiraw = lisaxml.Observable(obsstr,datatype='FractionalFrequency')
tdiraw.TimeSeries = lisaxml.TimeSeries(obsarray[:,4: ],rawstr,Cadence=options.timestep,TimeOffset=options.inittime)
outputXML.TDIData(tdiraw)
else:
tdiobs = lisaxml.Observable(obsstr,datatype='FractionalFrequency')
tdiobs.TimeSeries = lisaxml.TimeSeries(obsarray,obsstr,Cadence=options.timestep,TimeOffset=options.inittime)
outputXML.TDIData(tdiobs)
lisa = synthlisa.EccentricInclined(0.0,1.5*math.pi,-1)
proofnoise = [synthlisa.SumSignal(synthlisa.stdproofnoise(lisa,100,2.5e-48,2),
synthlisa.stdproofnoisepink(lisa,1000,2.5e-48,1.0e-4,2))
for i in range(6)]
shotnoise = [synthlisa.stdopticalnoise(lisa,15,1.8e-37,4) for i in range(6)]
lasernoise = [synthlisa.NoSignal() for i in range(6)]
tdi = synthlisa.TDInoise(lisa,proofnoise,shotnoise,lasernoise)
samples = int( options.duration / options.timestep + 0.1 )
[t,X,Y,Z] = numpy.transpose(synthlisa.getobs(samples,options.timestep,
[tdi.t,tdi.Xm,tdi.Ym,tdi.Zm],
options.inittime,display=options.verbose))
tdiobs = lisaxml.Observable('t,Xf,Yf,Zf')
tdiobs.DataType = 'FractionalFrequency'
tdiobs.TimeSeries = lisaxml.TimeSeries([t,X,Y,Z],'t,Xf,Yf,Zf')
tdiobs.TimeSeries.Cadence = options.timestep
tdiobs.TimeSeries.TimeOffset = options.inittime
outputXML = lisaxml.lisaXML(outputfile)
# save the standard LISA...
lisa = lisaxml.LISA('Standard MLDC PseudoLISA')
lisa.TimeOffset = 0; lisa.TimeOffset_Unit = 'Second'
def waveforms(self,samples,deltat,inittime):
noise = self.synthesize(samples,deltat,inittime)
[hp,hc] = numpy.transpose(synthlisa.getobs(samples,deltat,[noise.hp,noise.hc],inittime))
return (hp,hc)