import numpy
import math
import correlation
import os
path = '/home/rabrahm/Desktop/spec2/'
spectra = os.listdir(path)
cant = len(spectra)
m = 0
Tv = numpy.zeros(cant, float)
Gv = numpy.zeros(cant, float)
Zv = numpy.zeros(cant, float)
Vv = numpy.zeros(cant, float)
"""print spectra"""
m = 5
print spectra
while m < cant:
Tv[m], Gv[m], Zv[m], Vv[m] = correlation.CCF(path, spectra[m])
m = m + 1
m = 0
while m < cant:
print spectra[m], Tv[m], Gv[m], Zv[m], Vv[m]
m = m + 1
hdu = GLOBALutils.update_header(hdu, 'HIERARCH SIMBAD SPTYP',
sp_type_query)
pars_file = dirout + fsim.split('/')[-1][:-4] + '_stellar_pars.txt'
if os.access(pars_file, os.F_OK) == False or force_stellar_pars:
print "\t\t\tEstimating atmospheric parameters:"
Rx = np.around(1. / np.sqrt(1. / 40000.**2 - 1. / ref_RES**2))
spec2 = spec.copy()
for i in range(spec.shape[1]):
IJ = np.where(spec[5, i] != 0.)[0]
spec2[5, i,
IJ] = GLOBALutils.convolve(spec[0, i, IJ],
spec[5, i, IJ], Rx)
T_eff, logg, Z, vsini, vel0, ccf = correlation.CCF(
spec2, model_path=models_path, npools=npools)
line = "%6d %4.1f %4.1f %8.1f %8.1f\n" % (T_eff, logg, Z,
vsini, vel0)
f = open(pars_file, 'w')
f.write(line)
f.close()
else:
print "\t\t\tAtmospheric parameters loaded from file:"
T_eff, logg, Z, vsini, vel0 = np.loadtxt(pars_file,
unpack=True)
print "\t\t\t\tT_eff=", T_eff, "log(g)=", logg, "Z=", Z, "vsin(i)=", vsini, "vel0", vel0
else:
T_eff, logg, Z, vsini, vel0 = -999, -999, -999, -999, -999
import correlation
dire = '/home/rabrahm/Desktop/spec2/'
mods = os.listdir(dire)
t = []
g = []
z = []
r = []
v = []
nam = []
mods = mods[:-5]
for fits in mods:
print fits
sc = pyfits.getdata(dire + fits)
L, F = sc[0], sc[1]
Ln, Fn = continuum.NORM2(L, F)
Tfin, Gfin, Zfin, rot, velo2 = correlation.CCF(Ln, Fn)
t.append(Tfin)
g.append(Gfin)
z.append(Zfin)
r.append(rot)
v.append(velo2)
nam.append(fits)
cant = len(t)
o = 0
while o < cant:
print nam[o], t[o], g[o], z[o], r[o], v[o]
o += 1
