def generateConfigFiles(self):
try:
teff = numpy.array(self.gridconfig['grid_T'].split(','), dtype=numpy.int)
except:
teff = [self.baseconfig['Teff']]
try:
logg = numpy.array(self.gridconfig['grid_logg'].split(','), dtype=numpy.float)
except:
logg = [self.baseconfig['logg']]
try:
bfield = numpy.array(self.gridconfig['grid_B'].split(','), dtype=numpy.float)
except:
bfield = [self.baseconfig['Bfield']]
filenames = []
for temp in teff:
for grav in logg:
for b in bfield:
configFile = self.baseconfig.copy()
configFile["Teff"] = temp
configFile["logg"] = grav
configFile["Bfield"] = b
filename = self.gridconfig["grid_config_directory"]+'Config_T%d_G%.1f_B%.1f_raw.%s.cfg'%(temp, grav, b, self.flavor)
AstroUtils.write_config(filename, configFile)
filenames.append(filename)
self.filenames = filenames
def __init__(self, configFile, moogInstance):
config = AstroUtils.parse_config(configFile)
self.flavor = ''.join(random.choice(string.ascii_uppercase) for _ in range(4))
self.moogInstance = moogInstance
self.baseconfig = {}
self.gridconfig = {}
for key in config.keys():
if not('grid' in key):
self.baseconfig[key] = config[key]
else:
self.gridconfig[key] = config[key]
self.generateConfigFiles()
def generateConfigFiles(baseConfig, gridConfig):
try:
teff = numpy.array(gridConfig['grid_T'].split(','), dtype = numpy.int)
except:
teff = [baseConfig['Teff']]
try:
logg = numpy.array(gridConfig['grid_logg'].split(','), dtype= numpy.float)
except:
logg = [baseConfig['logg']]
try:
bfield = numpy.array(gridConfig['grid_B'].split(','), dtype=numpy.float)
except:
bfield = [baseConfig['Bfield']]
try:
vsini = numpy.array(gridConfig['grid_vsini'].split(','), dtype=float)
except:
vsini = [baseConfig['vsini']]
filenames = []
for temp in teff:
for grav in logg:
for b in bfield:
for v in vsini:
configFile = baseConfig.copy()
configFile["Teff"] = temp
configFile["logg"] = grav
configFile["Bfield"] = b
configFile["vsini"] = v
filename = 'ConfigFiles/Config_T%d_G%.1f_B%.1f_V%.1f.cfg' % (temp, grav, b, v)
AstroUtils.write_config(filename, configFile)
filenames.append(filename)
return filenames
for grav in logg:
for b in bfield:
for v in vsini:
configFile = baseConfig.copy()
configFile["Teff"] = temp
configFile["logg"] = grav
configFile["Bfield"] = b
configFile["vsini"] = v
filename = 'ConfigFiles/Config_T%d_G%.1f_B%.1f_V%.1f.cfg' % (temp, grav, b, v)
AstroUtils.write_config(filename, configFile)
filenames.append(filename)
return filenames
diffspecConfigFile = sys.argv[1]
config = AstroUtils.parse_config(diffspecConfigFile)
flavor = ''.join(random.choice(string.ascii_uppercase) for _ in range(4))
baseconfig = {}
gridconfig = {}
for key in config.keys():
if not('grid' in key):
baseconfig[key] = config[key]
else:
gridconfig[key] = config[key]
configFiles = generateConfigFiles(baseconfig, gridconfig)
synthesizeSpectra(configFiles, flavor)
import matplotlib.pyplot as pyplot import numpy import scipy import sys import MoogTools import AstroUtils fig = pyplot.figure(0) fig.clear() ax = fig.add_axes([0.1, 0.1, 0.8, 0.8]) baseName = sys.argv[1] arcturusConfig = AstroUtils.parse_config(baseName + "_Solar.cfg") solarConfig = AstroUtils.parse_config(baseName + "_Arcturus.cfg") originalConfig = arcturusConfig.copy() arcturusConfig["applyCorrections"] = True solarConfig["applyCorrections"] = True arcturus = MoogTools.LineList(None, arcturusConfig) solar = MoogTools.LineList(None, solarConfig) original = MoogTools.LineList(None, originalConfig) orig = [] sol = [] arc = [] diff = [] dsol = [] darc = [] species = []
import pyfits
import AstroUtils
import matplotlib.pyplot as pyplot
import scipy
import numpy
import SpectralTools
import sys
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)
calcIM = bool(sys.argv[2]=='True')
moogInstance = sys.argv[3]
try:
contFloat = bool(sys.argv[4]== 'True')
except:
contFloat = False
#try:
# rotFloat = bool(sys.argv[5] == 'True')
#except:
# rotFloat = False
f1 = pyplot.figure(0)
f1.clear()
ax1 = f1.add_axes([0.1, 0.1, 0.8, 0.8])
config = AstroUtils.parse_config(configFile)
orchestra = Moog960.Score(directory='../MusicMaker/Convolved/Kband_Convolved_T3*', observed=config["inFile"], suffix='')
#mastered = orchestra.master(selectedLabels=orchestra.convolved_labels, keySignature='CONVOLVED')
#one = mastered[0].Spectrum.copy()
#one.plot(ax=ax1)
#one.nyquistSample(R=45000.0)
#one.plot(ax=ax1)
#mastered[0].Spectrum.plot(ax=ax1)
#f1.show()
#print asdf
if calcIM:
import Moog960
import astropy.io.fits as pyfits
import SpectralTools
import numpy
import sys
import AstroUtils
import glob
#This program reads in an IGRINS spectrum from the .fits files produced by the
#reduction pipeline, and saves it in a Moog960-readable .fits file. It merges
#the spectral orders, weighting by signal-to-noise ratio.
config = AstroUtils.parse_config(sys.argv[1])
datadir = config["datadir"]
outdir = config['outdir']
wlsolfiles = [glob.glob(datadir+'SKY_SDCH*wvlsol_v1.fits')[0], glob.glob(datadir+'SKY_SDCK*wvlsol_v1.fits')[0]]
datafiles = [glob.glob(datadir+'SDCH*spec_a0v.fits')[0], glob.glob(datadir+'SDCK*spec_a0v.fits')[0]]
snfiles = [glob.glob(datadir+'SDCH*sn.fits')[0], glob.glob(datadir+'SDCK*sn.fits')[0]]
varfiles = [glob.glob(datadir+'SDCH*variance.fits')[0], glob.glob(datadir+'SDCK*variance.fits')[0]]
phrases = []
for wlsolfile, datafile, snfile, varfile in zip(wlsolfiles, datafiles, snfiles, varfiles):
wlsol = pyfits.getdata(wlsolfile)
data = pyfits.getdata(datafile)
dataheader = pyfits.getheader(datafile)
snr = pyfits.getdata(datafile)
var = pyfits.getdata(varfile)
import matplotlib.pyplot as pyplot import numpy import scipy import sys import MoogTools import AstroUtils fig = pyplot.figure(0) fig.clear() ax = fig.add_axes([0.1, 0.1, 0.8, 0.8]) baseName = sys.argv[1] arcturusConfig = AstroUtils.parse_config(baseName+"_Solar.cfg") solarConfig = AstroUtils.parse_config(baseName+"_Arcturus.cfg") originalConfig = arcturusConfig.copy() arcturusConfig["applyCorrections"] = True solarConfig["applyCorrections"] = True arcturus = MoogTools.LineList(None, arcturusConfig) solar = MoogTools.LineList(None, solarConfig) original = MoogTools.LineList(None, originalConfig) orig = [] sol = [] arc = [] diff = [] dsol = [] darc = []
def __init__(self, configFile):
self.config = AstroUtils.parse_config(configFile)
self.applyConfigFile()
self.WhosInThePit()
def generateLineList(b_dir, prefix, wl_start, wl_stop, Bfield, **kwargs):
''' This subroutine generates Zeeman-split MOOG line lists (both
strong and weak) '''
staging_dir = 'stage_'+prefix+'/'
print "Feature : ", prefix, ' ', b_dir
try:
os.makedirs(os.path.join(staging_dir,'Parfiles',b_dir))
os.makedirs(os.path.join(staging_dir,'Output', b_dir))
os.makedirs(os.path.join(staging_dir,'Linelists', b_dir))
except:
pass
MoogTools.write_par_file(wl_start, wl_stop, staging_dir, b_dir, prefix,
mode='gridstokes', strongLines=True, **kwargs)
# Load in configuration file
config = AstroUtils.parse_config('counterpoint.cfg')
weak_file = config['weak_file']
strong_file = config['strong_file']
molecules = config['molecules']
VALD_list = config['VALD_file']
gf_corrections = config['gf_file']
strongLines, weakLines = MoogTools.parse_VALD(VALD_list, strong_file,
wl_start, wl_stop, Bfield, gf_corrections)
# CO
weakLines = numpy.append(weakLines, MoogTools.parse_HITRAN(
molecules+'05_HITEMP2010new.par', wl_start, wl_stop, Bfield,
gf_corrections, weedout=2.5))
# OH
weakLines = numpy.append(weakLines, MoogTools.parse_HITRAN(
molecules+'13_HITEMP2010.par', wl_start, wl_stop, Bfield,
gf_corrections))
# CN
weakLines = numpy.append(weakLines, MoogTools.parse_Plez_CN(
molecules+'CN_Plez_linelist.dat', wl_start, wl_stop, Bfield,
gf_corrections))
sfn = os.path.join(staging_dir, 'Linelists', b_dir,
prefix+'_strong_linelist.stokes')
outfile = open(sfn, 'w')
for strongLine in strongLines:
strongLine.dump(out=outfile, mode='MOOGSTOKES')
outfile.close()
sort_file(sfn)
wfn = os.path.join(staging_dir, 'Linelists', b_dir,
prefix+'_weak_linelist.stokes')
weakfile = open(wfn, 'w')
for weakLine in weakLines:
weakLine.dump(out=weakfile, mode='MOOGSTOKES')
weakfile.close()
sort_file(wfn, weak=True)
if Bfield==0.0:
MoogTools.write_par_file(wl_start, wl_stop, staging_dir, b_dir,
prefix, mode='gridsyn', strongLines=True, **kwargs)
sfn = os.path.join(staging_dir, 'Linelists', b_dir,
prefix+'_strong_linelist.scalar')
outfile = open(sfn, 'w')
for strongLine in strongLines:
strongLine.dump(out=outfile, mode='MOOGSCALAR')
outfile.close()
sort_file(sfn)
wfn = os.path.join(staging_dir, 'Linelists', b_dir,
prefix+'_weak_linelist.scalar')
outfile = open(wfn, 'w')
for weakLine in weakLines:
weakLine.dump(out=outfile, mode='MOOGSCALAR')
outfile.close()
sort_file(wfn, weak=True)
for strongLine in strongLines:
strongLine.dump(out=outfile, mode='MOOGSCALAR')
outfile.close()
sort_file(sfn)
wfn = os.path.join(staging_dir, 'Linelists', b_dir,
prefix+'_weak_linelist.scalar')
outfile = open(wfn, 'w')
for weakLine in weakLines:
weakLine.dump(out=outfile, mode='MOOGSCALAR')
outfile.close()
sort_file(wfn, weak=True)
parameters = AstroUtils.parse_config(sys.argv[-1])
if type(parameters["BFields"])==str:
Bfields = numpy.array(parameters["BFields"].split(','), dtype = float).tolist()
else:
Bfields = numpy.array(parameters["BFields"]).tolist().tolist()
prefixes = numpy.array(parameters["prefixes"].split(','), dtype=str)
if type(parameters["wl_starts"])== str:
wl_starts = numpy.array(parameters["wl_starts"].split(','), dtype=float)
wl_stops = numpy.array(parameters["wl_stops"].split(','), dtype=float)
else:
wl_starts = numpy.array([parameters["wl_starts"]], dtype=float)
wl_stops = numpy.array([parameters["wl_stops"]], dtype=float)
if type(parameters["temps"])==str:
temps = numpy.array(parameters["temps"].split(','), dtype=int).tolist()
else:
temps = numpy.array([parameters["temps"]]).tolist()