def calc_VeilingSED(Thot, Tint, Tcool, fi_fh, fc_fh):
wave = numpy.arange(1.0, 2.5, 0.01)
bm = numpy.argsort(abs(wave-2.2))[0]
Bhot = SpectralTools.blackBody(wl = wave/10000.0, T=Thot,
outUnits='Energy')
Bint = SpectralTools.blackBody(wl = wave/10000.0, T=Tint,
outUnits='Energy')*fi_fh
Bcool = SpectralTools.blackBody(wl = wave/10000.0, T=Tcool,
outUnits='Energy')*fc_fh
composite = Bhot+Bint+Bcool
composite /= composite[bm]
return scipy.interpolate.interp1d(wave*10000.0, composite)
def calc_VeilingSED(Thot, Tint, Tcool, fi_fh, fc_fh):
wave = numpy.arange(1.0, 2.5, 0.01)
bm = numpy.argsort(abs(wave - 2.2))[0]
Bhot = SpectralTools.blackBody(wl=wave / 10000.0,
T=Thot,
outUnits='Energy')
Bint = SpectralTools.blackBody(
wl=wave / 10000.0, T=Tint, outUnits='Energy') * fi_fh
Bcool = SpectralTools.blackBody(
wl=wave / 10000.0, T=Tcool, outUnits='Energy') * fc_fh
composite = Bhot + Bint + Bcool
composite /= composite[bm]
return scipy.interpolate.interp1d(wave * 10000.0, composite)
def calculateCM(SynthObj, solarWl, rebinnedSpectrum, nominalWave,
nominalSpectrum):
IM = numpy.zeros((SynthObj.lineList.numLines + 2, len(solarWl)))
for i in range(SynthObj.lineList.numLines):
SynthObj.lineList.perturbLine(i, 0.3)
wave, flux = SynthObj.run()
plus = SpectralTools.binSpectrum(flux, wave, solarWl)
SynthObj.lineList.perturbLine(i, -0.3)
wave, flux = SynthObj.run()
minus = SpectralTools.binSpectrum(flux, wave, solarWl)
IM[i, :] = (plus - minus) / 0.6
#Continuum Level
plus = rebinnedSpectrum.copy() + 0.005
minus = rebinnedSpectrum.copy() - 0.005
IM[-1, :] = (plus - minus) / 0.01
plus = SpectralTools.binSpectrum(nominalSpectrum, nominalWave + 0.1,
solarWl)
minus = SpectralTools.binSpectrum(nominalSpectrum, nominalWave - 0.1,
solarWl)
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)
def calculateCM(SynthObj, solarWl, rebinnedSpectrum, nominalWave, nominalSpectrum):
IM = numpy.zeros((SynthObj.lineList.numLines+2, len(solarWl)))
for i in range(SynthObj.lineList.numLines):
SynthObj.lineList.perturbLine(i, 0.3)
wave, flux = SynthObj.run()
plus = SpectralTools.binSpectrum(flux, wave, solarWl)
SynthObj.lineList.perturbLine(i, -0.3)
wave, flux = SynthObj.run()
minus = SpectralTools.binSpectrum(flux, wave, solarWl)
IM[i,:] = (plus - minus)/0.6
#Continuum Level
plus = rebinnedSpectrum.copy()+ 0.005
minus = rebinnedSpectrum.copy()- 0.005
IM[-1, :] = (plus-minus)/0.01
plus = SpectralTools.binSpectrum(nominalSpectrum, nominalWave+0.1, solarWl)
minus = SpectralTools.binSpectrum(nominalSpectrum, nominalWave-0.1, solarWl)
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)
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()
def main(fname, binsize=5, interactive_mode=False, bin_range=None, limits=None, plot=False):
# load the fits file
data = fits.getdata(fname)
hdr = fits.getheader(fname)
try:
# Gasgano reduction
I = data["Extracted_OPT"]
I = np.array(I, dtype="float64")
except:
# Dracs reduction
try:
I = data["Extracted_DRACS"]
print(type(I))
I = np.array(I, dtype="float64")
print(type(I))
except:
I = data
try:
wl = data["Wavelength"]
xscale = "nm"
except:
# no wavelength values so use pixel positions
wl = range(len(I))
xscale = "pixel"
if interactive_mode:
# do interactve mode stuff
pass
elif limits:
limited_wl, limited_flux = s_tools.fast_wav_selector(wl, I, limits[0], limits[1])
limit_snr = snr(limited_flux)
print("SNR of the spectra between the given limits {0}-{1} is {2}".format(limits[0], limits[1], limit_snr))
if plot:
simple_plot(wl, I, label="Spectra", xscale=xscale)
else:
# Default to scan mode
binsize = int(binsize)
snr_list = snrscan(I, binsize)
print("snr list", snr_list)
# Try using stride on np.array
plt.hist(snr_list)
plt.show()
# striding
if bin_range:
bins = np.arange(bin_range[0], bin_range[1], bin_range[2]) # TODO ability for less than 3 args?
hopper = 1
print("itemsize", I.itemsize, "dtype", I.dtype)
store_list = []
for i, b in enumerate(bins):
store_list.append(strided_snr(I, b, hop_length=hopper))
# pandas dataframe (not nessesary)
df_list = pd.DataFrame(store_list, index=bins, columns=np.round(wl,2))
# ploting heatmap
plt.subplot(221)
plt.plot(wl, I, label="spectra")
plt.ylabel("Flux")
plt.xlabel("Wavelength")
plt.title("Spectra of {0}".format(fname))
plt.subplot(212)
sns.set()
cmap = sns.diverging_palette(220, 10, as_cmap=True)
#ax = sns.heatmap(store_list, cmap=cmap, xticklabels=200, vmax=300, vmin=10)
ax = sns.heatmap(df_list, cmap=cmap, xticklabels=200, vmax=300, vmin=0)
#ax = sns.heatmap(df_list)
#plt.xticks(np.arange(int(np.min(wl)), int(np.max(wl)+1), 1.0))
ax.set(ylabel="Binsize", xlabel="Wavelength")
plt.title("SNR")
plt.show()
import numpy
configFile = sys.argv[1]
config = AstroUtils.parse_config(configFile)
watched_dir = config['watched_dir']
wlStart = config['wlStart']
wlStop = config['wlStop']
parameters = {}
parameters["TEFF"] = []
parameters["LOGG"] = []
parameters["BFIELD"] = []
parameters, waves, fluxes = SpectralTools.winnow_MoogStokes_Spectra(watched_dir, wlStart, wlStop, trackedParams=parameters)
EWs = []
teff = numpy.array(parameters["TEFF"])
logg = numpy.array(parameters["LOGG"])
bfield = numpy.array(parameters["BFIELD"])
temps = numpy.unique(teff)
gravs = numpy.unique(logg)
bs = numpy.unique(bfield)
for w, f in zip(waves, fluxes):
EWs.append(SpectralTools.calc_EW(w, f, wlStart, wlStop))
EWs = numpy.array(EWs)
fig = pyplot.figure(0)
Name = dataheader.get('OBJECT')
headerKWs['OBJECT'] = Name
headerKWs["DATE-OBS"] = dataheader.get('DATE-OBS')
headerKWs["INSTRUMENT"] = dataheader.get('INSTRUME')
headerKWs["OBSERVER"] = dataheader.get('OBSERVER')
headerKWs["EXPTIME"] = dataheader.get('EXPTIME')
Score = Moog960.Score()
Melody = Moog960.ObservedMelody(Score=Score, name=Name)
for wl, I, sn, v in zip(wlsol, data, snr, var):
header = pyfits.Header()
header.set('NAME', Name)
header.set("WLSTART", numpy.min(wl))
header.set("WLSTOP", numpy.max(wl))
Melody.addPhrase(Moog960.ObservedPhrase(observedData=[SpectralTools.Spectrum(wl=wl,
I=I, dI=I/sn, header=header, spectrum_type="OBSERVED")], Melody=Melody))
ID = Melody.phrases[-1].ID
parameters = {}
parameters["PHRASE"] = ID
parameters["MELODY"] = Melody.ID
parameters["SCORE"] = Melody.Score.ID
parameters["WLSTART"] = header.get('WLSTART')
parameters["WLSTOP"] = header.get('WLSTOP')
parameters["SELECTED"] = False
if not(Melody.ID in Melody.Score.observed_labels.keys()):
Melody.Score.observed_labels[Melody.ID] = {}
Melody.Score.observed_labels[Melody.ID][ID] = []
Melody.Score.observed_labels[Melody.ID][ID].append(Moog960.Label(parameters,
reference=Melody.phrases[-1].observedData[-1], Phrase=Melody.phrases[-1],
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)
continuum *= float(raw_input("Enter multiplicative continuum factor : "))
elif choice == 'v':
veiling = float(raw_input("Enter new Veiling :"))
elif choice == 's':
outfile = raw_input("Enter the name of the file you wish to save")
fig.savefig(outfile)
Ensemble = Orchestra.getEnsemble()
ax1.clear()
ax2.clear()
wave = Orchestra.observed.wave+wlOffset
flux = Orchestra.observed.flux*continuum
ax1.plot(wave, flux, label='TW Hydra')
ax2.plot([Orchestra.wlStart, Orchestra.wlStop], [0.0, 0.0])
for spectra, l in zip(Ensemble[0], Ensemble[1]):
newSpec = (SpectralTools.binSpectrum(spectra[1], spectra[0], wave)+veiling)/(1.0+veiling)
difference = flux - newSpec
ax1.plot(wave, newSpec, label=l)
ax2.plot(wave, difference)
ax1.set_xbound(lower = Orchestra.wlStart, upper=Orchestra.wlStop)
ax1.set_ybound(lower = 0.0, upper = 1.5)
ax2.set_xbound(lower = Orchestra.wlStart, upper=Orchestra.wlStop)
ax2.set_ybound(lower = -0.15, upper = 0.15)
ax1.set_xticklabels([])
params = ax1.text(0.1, 0.8, "wlShift = %.1f A\nContinuum Scaling = %.2f\nVeiling = %.2f"
% (wlOffset, continuum, veiling), transform = ax1.transAxes, fontsize=19.0)
ax1.legend(loc=3)
fig.show()
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()
headerKWs["OBSERVER"] = dataheader.get('OBSERVER')
headerKWs["EXPTIME"] = dataheader.get('EXPTIME')
Score = Moog960.Score()
Melody = Moog960.ObservedMelody(Score=Score, name=Name)
for wl, I, sn, v in zip(wlsol, data, snr, var):
header = pyfits.Header()
header.set('NAME', Name)
header.set("WLSTART", numpy.min(wl))
header.set("WLSTOP", numpy.max(wl))
Melody.addPhrase(
Moog960.ObservedPhrase(observedData=[
SpectralTools.Spectrum(wl=wl,
I=I,
dI=I / sn,
header=header,
spectrum_type="OBSERVED")
],
Melody=Melody))
ID = Melody.phrases[-1].ID
parameters = {}
parameters["PHRASE"] = ID
parameters["MELODY"] = Melody.ID
parameters["SCORE"] = Melody.Score.ID
parameters["WLSTART"] = header.get('WLSTART')
parameters["WLSTOP"] = header.get('WLSTOP')
parameters["SELECTED"] = False
if not (Melody.ID in Melody.Score.observed_labels.keys()):
Melody.Score.observed_labels[Melody.ID] = {}
