twomassid, id, teff, feh = mcallib.loadSampleOfCalibrators(options.inputsample)
Tcal = []
FeHcal = []
ewcal = []
for file in listOfStarSpectra:
spc = Spectrum(file)
objname = spc.object.replace(" ", "").upper()
if options.verbose:
print "Processing spectrum: ", file, objname
if spc.instrument == 'ESPaDOnS' or spc.instrument == 'NARVAL':
spc.resampling(0.01, 4000, 10400)
for i in range(len(id)):
if objname in id[i].upper() or objname in twomassid[i].upper():
spc.equivalentWidths(override=False, verbose=options.verbose)
ewcal_tmp = spc.eqwidths
if not np.any(np.isnan(ewcal_tmp)):
ewcal.append(ewcal_tmp)
Tcal.append(teff[i])
FeHcal.append(feh[i])
print "Selected Calibrator: ", file, objname, twomassid[i], id[
i], teff[i], feh[i]
else:
print "Eq. Widths contain NaNs. Ignoring potential calibrator: ", file, objname
mcallib.calibrate_mcal(ewcal, Tcal, FeHcal, options.outputcalibmatrix)
print 'File with wavelength ranges: ', options.wavemask
spc = Spectrum(options.input,
options.spectype,
options.polar,
options.telluric,
options.helio,
Sort=False)
#spc.binningOrderByOrder(rvsampling_kps=float(options.rvsampling), median=False)
if options.wavemask:
spc.applyMask(options.wavemask)
spc.sortByWavelength()
if options.output.endswith(".fits"):
wlsampling = (float(options.rvsampling) * 1000.0 /
constants.c) * (spc.wl[-1] + spc.wl[0]) / 2.0
spc.resampling(wlsampling)
spc.saveToFile(options.output, format='fits')
elif options.output.endswith(".txt"):
spc.binning(float(options.rvsampling), median=False)
spc.saveToFile(options.output, format='ascii')
else:
spc.printdata(printerrors=False)