def loadSpectra(self):
self.wave = []
self.flux = []
for i, good in zip(range(self.nSpectra), self.inWlRange):
if good:
data = pyfits.getdata(self.datafile, ext=i+1)
if self.resolvingPower != None:
wave, flux = SpectralTools.resample(data.field('Wavelength'),
data.field('Stokes_I'), self.resolvingPower)
self.wave.append(wave)
self.flux.append(flux)
else:
self.wave.append(data.field('Wavelength'))
self.flux.append(data.field('Stokes_I'))
else:
self.wave.append([])
self.flux.append([])
#self.wave, self.flux = SpectralTools.resample(data[0], data[1],
# self.resolvingPower)
self.wave = numpy.array(self.wave)
self.flux = numpy.array(self.flux)
def calculateCM(SynthObj, nominalWave, nominalSpectrum):
solarWl = SynthObj.solarSpectrum.wave
solarFl = SynthObj.solarSpectrum.flux
resolution = 45000.0
nLines = SynthObj.lineList.numLines
nModes = 2 * nLines + 3
nFilt = nLines
IM = numpy.zeros((nModes, len(solarWl)))
stroke = numpy.ones(nModes)
factor = numpy.ones(nModes)
stroke[-1] = 0.005 # Continuum Shift
stroke[-2] = 0.1 # WL Shift
stroke[-3] = 0.01 # Smoothing
for i in range(nLines):
SynthObj.lineList.writeLineLists(i)
wave, flux = SynthObj.run()
stroke[i] = SynthObj.lineList.getGf(i) / 5.0
stroke[i + nLines] = 0.1
"""
while ((factor[i] < 0.9) | (factor[i] > 1.1)):
stroke[i] *= factor[i]
SynthObj.lineList.perturbGf(i, stroke[i])
SynthObj.lineList.writeLineLists(i,partial=True)
wave, plus = SynthObj.run()
wave, plus = SpectralTools.resample(wave, plus, resolution)
SynthObj.lineList.perturbGf(i, -2.0*stroke[i])
SynthObj.lineList.writeLineLists(i,partial=True)
wave, minus = SynthObj.run()
wave, minus = SpectralTools.resample(wave, minus, resolution)
SynthObj.lineList.perturbGf(i, stroke[i])
factor[i] = numpy.abs(target[i]/(numpy.min(plus)-numpy.min(minus)))
print factor[i]
raw_input()
#"""
for i in range(nLines):
# log gf
SynthObj.lineList.perturbGf(i, stroke[i])
SynthObj.lineList.writeLineLists(i)
wave, plus = SynthObj.run()
newWave, plus = SpectralTools.resample(wave, plus, resolution)
SynthObj.lineList.perturbGf(i, -2.0 * stroke[i])
SynthObj.lineList.writeLineLists(i)
wave, minus = SynthObj.run()
newWave, minus = SpectralTools.resample(wave, minus, resolution)
SynthObj.lineList.perturbGf(i, stroke[i])
IM[i, :] = SpectralTools.interpolate_spectrum(newWave,
solarWl, (plus - minus) /
(2.0 * stroke[i]),
pad=0.0)
factor[i] = numpy.max(numpy.abs(IM[i, :]))
IM[i, :] /= factor[i]
# damping
SynthObj.lineList.perturbVdW(i, stroke[i + nLines])
SynthObj.lineList.writeLineLists(i)
wave, plus = SynthObj.run()
newWave, plus = SpectralTools.resample(wave, plus, resolution)
SynthObj.lineList.perturbVdW(i, -2.0 * stroke[i + nLines])
SynthObj.lineList.writeLineLists(i)
wave, minus = SynthObj.run()
newWave, minus = SpectralTools.resample(wave, minus, resolution)
SynthObj.lineList.perturbVdW(i, stroke[i + nLines])
IM[i + nLines, :] = SpectralTools.interpolate_spectrum(
newWave,
solarWl, (plus - minus) / (2.0 * stroke[i + nLines]),
pad=0.0)
factor[i + nLines] = numpy.max(numpy.abs(IM[i + nLines, :]))
IM[i + nLines, :] /= factor[i + nLines]
#Continuum Level
plus = nominalSpectrum + stroke[-1]
newWave, plus = SpectralTools.resample(nominalWave, plus, resolution)
minus = nominalSpectrum - stroke[-1]
newWave, minus = SpectralTools.resample(nominalWave, minus, resolution)
IM[-1, :] = SpectralTools.interpolate_spectrum(newWave,
solarWl, (plus - minus) /
(2.0 * stroke[-1]),
pad=0.0)
factor[-1] = numpy.max(numpy.abs(IM[-1, :]))
IM[-1, :] /= factor[-1]
#Wavelength Shift
plus = SpectralTools.interpolate_spectrum(wave,
wave - stroke[-2],
nominalSpectrum,
pad=True)
newWave, plus = SpectralTools.resample(wave, plus, resolution)
minus = SpectralTools.interpolate_spectrum(wave,
wave + stroke[-2],
nominalSpectrum,
pad=True)
newWave, minus = SpectralTools.resample(wave, minus, resolution)
IM[-2, :] = SpectralTools.interpolate_spectrum(newWave,
solarWl, (plus - minus) /
(2.0 * stroke[-2]),
pad=0.0)
factor[-2] = numpy.max(numpy.abs(IM[-2, :]))
IM[-2, :] /= factor[-2]
#"""
#Instrumental Smoothing
wavePlus, plus = SpectralTools.resample(wave, nominalSpectrum,
resolution * (1.0 + stroke[-3]))
waveMinus, minus = SpectralTools.resample(wave, nominalSpectrum,
resolution * (1.0 - stroke[-3]))
diffx, diffy = SpectralTools.diff_spectra(wavePlus,
plus,
waveMinus,
minus,
pad=True)
IM[-3, :] = SpectralTools.interpolate_spectrum(diffx,
solarWl,
diffy / (2.0 * stroke[-3]),
pad=0.0)
factor[-3] = numpy.max(numpy.abs(IM[-3, :]))
IM[-3, :] /= factor[-3]
#"""
hdu = pyfits.PrimaryHDU(IM)
hdu.writeto("InteractionMatrix.fits", clobber=True)
#nFilt = Synth.lineList.numLines-2
dims = IM.shape
U, S, V = scipy.linalg.svd(IM)
D = 1.0 / S
#D = 1.0/(S[0:-nFilt])
#S[-nFilt:] = 0.0
newS = numpy.zeros((dims[0], dims[1]))
I = [i for i in range(dims[1])]
for i in range(len(D)):
newS[i][i] = D[i]
S = newS.copy()
CM = numpy.array(scipy.matrix(V.T.dot(S.T.dot(U.T)),
dtype=numpy.float32)).T
fig = pyplot.figure(0)
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])
ax.plot(S)
hdu = pyfits.PrimaryHDU(CM)
hdu.writeto('CommandMatrix.fits', clobber=True)
hdu = pyfits.PrimaryHDU(factor)
hdu.writeto('scalingfactor.fits', clobber=True)
diffplot = False
Synth = MoogTools.Moog(configFile)
Synth.lineList.writeLineLists()
Synth.parameterFile.writeParFile()
solarWave = Synth.solarSpectrum.wave + 0.1
solarFlux = Synth.solarSpectrum.flux + 0.001 + numpy.random.randn(
len(solarWave)) * 0.001
continuum = 0.0
wlOffset = 0.0
resolution = 45000
nominalWavelength, nominalSpectrum = Synth.run()
wave, spectrum = SpectralTools.resample(nominalWavelength, nominalSpectrum,
resolution)
if True:
calculateCM(Synth, nominalWavelength, nominalSpectrum)
CM = pyfits.getdata("CommandMatrix.fits")
factor = pyfits.getdata("scalingfactor.fits")
f1 = pyplot.figure(0)
f1.clear()
ax1 = f1.add_axes([0.1, 0.1, 0.8, 0.8])
cb = ax1.matshow(CM, aspect='auto')
blah = pyplot.colorbar(cb)
f1.show()
edges = (plus != 0) & (minus != 0)
IM[-2, edges] = (plus[edges] - minus[edges]) / (0.2)
nFilt = Synth.lineList.numLines - 10
dims = IM.shape
U, S, V = scipy.linalg.svd(IM)
D = 1.0 / (S[0:-nFilt])
S[-nFilt:] = 0.0
newS = numpy.zeros((dims[0], dims[1]))
I = [i for i in range(dims[1])]
for i in range(len(D)):
newS[i][i] = D[i]
S = newS.copy()
CM = numpy.array(scipy.matrix(V.T.dot(S.T.dot(U.T)),
dtype=numpy.float32)).T
hdu = pyfits.PrimaryHDU(CM)
hdu.writeto('CommandMatrix_new.fits', clobber=True)
configFile = 'CMTeacher.cfg'
Synth = MoogTools.Moog(configFile)
Synth.lineList.writeLineLists()
Synth.parameterFile.writeParFile()
wavelengths, nominalSpectrum = Synth.run()
newWave, newFlux = SpectralTools.resample(wavelengths, nominalSpectrum, 40000)
SpectralTools.write_2col_spectrum("observed.dat", newWave, newFlux)
edges = (plus !=0) & (minus != 0)
IM[-2, edges] = (plus[edges]-minus[edges])/(0.2)
nFilt = Synth.lineList.numLines-10
dims = IM.shape
U,S,V = scipy.linalg.svd(IM)
D = 1.0/(S[0:-nFilt])
S[-nFilt:] = 0.0
newS = numpy.zeros((dims[0], dims[1]))
I = [i for i in range(dims[1])]
for i in range(len(D)):
newS[i][i] = D[i]
S = newS.copy()
CM = numpy.array(scipy.matrix(V.T.dot(S.T.dot(U.T)),dtype=numpy.float32)).T
hdu = pyfits.PrimaryHDU(CM)
hdu.writeto('CommandMatrix_new.fits', clobber=True)
configFile = 'CMTeacher.cfg'
Synth = MoogTools.Moog(configFile)
Synth.lineList.writeLineLists()
Synth.parameterFile.writeParFile()
wavelengths, nominalSpectrum = Synth.run()
newWave, newFlux = SpectralTools.resample(wavelengths, nominalSpectrum, 40000)
SpectralTools.write_2col_spectrum("observed.dat", newWave, newFlux)
def calculateCM(SynthObj, nominalWave, nominalSpectrum):
solarWl = SynthObj.solarSpectrum.wave
solarFl = SynthObj.solarSpectrum.flux
resolution = 45000.0
nLines = SynthObj.lineList.numLines
nModes = 2*nLines+3
nFilt = nLines
IM = numpy.zeros((nModes, len(solarWl)))
stroke = numpy.ones(nModes)
factor = numpy.ones(nModes)
stroke[-1] = 0.005 # Continuum Shift
stroke[-2] = 0.1 # WL Shift
stroke[-3] = 0.01 # Smoothing
for i in range(nLines):
SynthObj.lineList.writeLineLists(i)
wave, flux = SynthObj.run()
stroke[i] = SynthObj.lineList.getGf(i)/5.0
stroke[i+nLines] = 0.1
"""
while ((factor[i] < 0.9) | (factor[i] > 1.1)):
stroke[i] *= factor[i]
SynthObj.lineList.perturbGf(i, stroke[i])
SynthObj.lineList.writeLineLists(i,partial=True)
wave, plus = SynthObj.run()
wave, plus = SpectralTools.resample(wave, plus, resolution)
SynthObj.lineList.perturbGf(i, -2.0*stroke[i])
SynthObj.lineList.writeLineLists(i,partial=True)
wave, minus = SynthObj.run()
wave, minus = SpectralTools.resample(wave, minus, resolution)
SynthObj.lineList.perturbGf(i, stroke[i])
factor[i] = numpy.abs(target[i]/(numpy.min(plus)-numpy.min(minus)))
print factor[i]
raw_input()
#"""
for i in range(nLines):
# log gf
SynthObj.lineList.perturbGf(i, stroke[i])
SynthObj.lineList.writeLineLists(i)
wave, plus = SynthObj.run()
newWave, plus = SpectralTools.resample(wave, plus, resolution)
SynthObj.lineList.perturbGf(i, -2.0*stroke[i])
SynthObj.lineList.writeLineLists(i)
wave, minus = SynthObj.run()
newWave, minus = SpectralTools.resample(wave, minus, resolution)
SynthObj.lineList.perturbGf(i, stroke[i])
IM[i,:] = SpectralTools.interpolate_spectrum(newWave, solarWl,
(plus - minus)/(2.0*stroke[i]), pad=0.0)
factor[i] = numpy.max(numpy.abs(IM[i,:]))
IM[i,:] /= factor[i]
# damping
SynthObj.lineList.perturbVdW(i, stroke[i+nLines])
SynthObj.lineList.writeLineLists(i)
wave, plus = SynthObj.run()
newWave, plus = SpectralTools.resample(wave, plus, resolution)
SynthObj.lineList.perturbVdW(i, -2.0*stroke[i+nLines])
SynthObj.lineList.writeLineLists(i)
wave, minus = SynthObj.run()
newWave, minus = SpectralTools.resample(wave, minus, resolution)
SynthObj.lineList.perturbVdW(i, stroke[i+nLines])
IM[i+nLines,:] = SpectralTools.interpolate_spectrum(newWave, solarWl,
(plus-minus)/(2.0*stroke[i+nLines]), pad=0.0)
factor[i+nLines] = numpy.max(numpy.abs(IM[i+nLines,:]))
IM[i+nLines,:] /= factor[i+nLines]
#Continuum Level
plus = nominalSpectrum + stroke[-1]
newWave, plus = SpectralTools.resample(nominalWave, plus, resolution)
minus = nominalSpectrum - stroke[-1]
newWave, minus = SpectralTools.resample(nominalWave, minus, resolution)
IM[-1, :] = SpectralTools.interpolate_spectrum(newWave, solarWl,
(plus-minus)/(2.0*stroke[-1]), pad=0.0)
factor[-1] = numpy.max(numpy.abs(IM[-1,:]))
IM[-1,:] /= factor[-1]
#Wavelength Shift
plus = SpectralTools.interpolate_spectrum(wave, wave-stroke[-2], nominalSpectrum,
pad=True)
newWave, plus = SpectralTools.resample(wave, plus, resolution)
minus = SpectralTools.interpolate_spectrum(wave, wave+stroke[-2], nominalSpectrum,
pad=True)
newWave, minus = SpectralTools.resample(wave, minus, resolution)
IM[-2, :] = SpectralTools.interpolate_spectrum(newWave, solarWl,
(plus-minus)/(2.0*stroke[-2]), pad=0.0)
factor[-2] = numpy.max(numpy.abs(IM[-2,:]))
IM[-2,:] /= factor[-2]
#"""
#Instrumental Smoothing
wavePlus, plus = SpectralTools.resample(wave, nominalSpectrum, resolution*(1.0+stroke[-3]))
waveMinus, minus = SpectralTools.resample(wave, nominalSpectrum, resolution*(1.0-stroke[-3]))
diffx, diffy = SpectralTools.diff_spectra(wavePlus, plus, waveMinus, minus, pad=True)
IM[-3,:] = SpectralTools.interpolate_spectrum(diffx, solarWl, diffy/(2.0*stroke[-3]), pad=0.0)
factor[-3] = numpy.max(numpy.abs(IM[-3,:]))
IM[-3,:] /= factor[-3]
#"""
hdu = pyfits.PrimaryHDU(IM)
hdu.writeto("InteractionMatrix.fits", clobber=True)
#nFilt = Synth.lineList.numLines-2
dims = IM.shape
U,S,V = scipy.linalg.svd(IM)
D = 1.0/S
#D = 1.0/(S[0:-nFilt])
#S[-nFilt:] = 0.0
newS = numpy.zeros((dims[0], dims[1]))
I = [i for i in range(dims[1])]
for i in range(len(D)):
newS[i][i] = D[i]
S = newS.copy()
CM = numpy.array(scipy.matrix(V.T.dot(S.T.dot(U.T)),dtype=numpy.float32)).T
fig = pyplot.figure(0)
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])
ax.plot(S)
hdu = pyfits.PrimaryHDU(CM)
hdu.writeto('CommandMatrix.fits', clobber=True)
hdu = pyfits.PrimaryHDU(factor)
hdu.writeto('scalingfactor.fits', clobber=True)
diffplot = False
Synth = MoogTools.Moog(configFile)
Synth.lineList.writeLineLists()
Synth.parameterFile.writeParFile()
solarWave = Synth.solarSpectrum.wave+0.1
solarFlux = Synth.solarSpectrum.flux+0.001+ numpy.random.randn(len(solarWave))*0.001
continuum = 0.0
wlOffset = 0.0
resolution = 45000
nominalWavelength, nominalSpectrum = Synth.run()
wave, spectrum = SpectralTools.resample(nominalWavelength, nominalSpectrum, resolution)
if True:
calculateCM(Synth, nominalWavelength, nominalSpectrum)
CM = pyfits.getdata("CommandMatrix.fits")
factor = pyfits.getdata("scalingfactor.fits")
f1 = pyplot.figure(0)
f1.clear()
ax1 = f1.add_axes([0.1, 0.1, 0.8, 0.8])
cb = ax1.matshow(CM, aspect='auto')
blah = pyplot.colorbar(cb)
f1.show()