from astroquery.simbad import Simbad
S = Simbad()
S.add_votable_fields('rv_value')
dir = sys.argv[1]
files = glob.glob(dir + '/*p08.fits')
templates = glob.glob('/home/rajikak/tools/RV_standards/*')
print("*************")
for file in files:
a = pyfits.open(file)
object_name = a[1].header['OBJNAME']
#get RV data on the standard:
#From Vizier table:
result = Vizier.query_object(object_name)
interesting_table = result['J/ApJS/141/503/table1']
object_RV = float(interesting_table[0]['__RV_']) / 1000.
flux_stamp, wave = ps.read_and_find_star_p08(file)
spectrum, sig = ps.weighted_extract_spectrum(flux_stamp)
rv, rv_sig = ps.calc_rv_template(spectrum, wave, sig, templates,
([0, 5400], [6870, 6890]))
rv += a[1].header['RADVEL']
print("object_name: " + object_name)
print("object RV: " + str(object_RV) + "km/s")
print("Retrieved RV from standards: " + str(rv) + "km/s")
print("*************")
else:
sptype = Temp_sptype[ind]
else:
templates = glob.glob(templates_dir + '/*.fits')
Temp_sptype[ind] = ' '
if args.correct_sky == 'True':
#Calculating RV from skylines
if args.absorption == 'False':
spectrum, sig = ps.weighted_extract_spectrum(
sky, var)
snr_val = np.max(spectrum) / np.median(spectrum)
SNR.append(snr_val)
rv_sky, rv_sky_sig, temp_used = ps.calc_rv_template(
spectrum,
wave,
sig,
sky_temp, (sky_intervals),
heliocentric_correction=0.0)
temp_hdu = fits.open('/Users/rajikak/tools/' +
temp_used)
spectrum_interp = np.interp(
wave_template, wave * (1 - (rv_sky) / 2.998e5),
spectrum)
print("Skyline offset= " + str(rv_sky) + ', ' +
str(rv_sky_sig))
if np.isnan(rv_sky) or np.isnan(
rv_sky_sig) or np.abs(rv_sky) > 50.:
print("Could not get reliable sky RV")
rv_sky = 0.0
ccd = hdu[0].header['CCDTEMP']
CCD_Temp.append(ccd)
cam = hdu[0].header['CAMTEMPB']
Cam_Temp.append(cam)
for slit in range(slits):
print("DOING SLIT:", slit)
if args.weight_direction != 'hor':
flux_stamp = flux[:, slit, :]
else:
flux_stamp = flux[slit]
flux_stamp = np.nan_to_num(flux_stamp)
flux_stamp = np.array([flux_stamp])
spectrum,sig = ps.weighted_extract_spectrum(flux_stamp)
template = ['templates/slit_'+str(slit)+'.fits']
rv,rv_sig, temp_used = ps.calc_rv_template(spectrum,wave,sig,template, ([0,5400],[6870,6890]), save_figures=False, save_dir='Images/', heliocentric_correction=0.0)
RV[slit].append(rv)
print('rv =', rv)
RV = np.array(RV)
RV_med = []
RV_std = []
for obs in range(len(RV[0])):
RV_med.append(np.median(RV[np.where(np.isnan(RV[:,obs])==False)[0],obs]))
RV_std.append(np.std(RV[np.where(np.isnan(RV[:,obs])==False)[0],obs]))
print("NOW THAT WE'VE GONE THROUGH ALL THE FILES, LETS PLOT THIS!")
plt.clf()
full_file_path = reduced_dir + file_dir + '/' + file
if os.path.isfile(full_file_path):
hdu = pyfits.open(full_file_path)
h_corr = hdu[0].header['RADVEL']
Hcorr.append(h_corr)
flux, wave, var, sky = ps.read_and_find_star_p08(
full_file_path, sky_rad=5, return_sky=True)
spectrum, sig = ps.weighted_extract_spectrum(flux, var)
if args.absorption != 'False':
if args.all_spectral_types != 'False':
rv_abs, rv_abs_sig, temp_used = ps.calc_rv_template(
spectrum,
wave,
sig,
abs_temps, (abs_bad_ints),
heliocentric_correction=0.0)
print(("ABSORPTION OFFSET= " + str(rv_abs) + ', ' +
str(rv_abs_sig)))
else:
if RV_standard_data[ind][1][0] in abs_corr_spt:
rv_abs, rv_abs_sig, temp_used = ps.calc_rv_template(
spectrum,
wave,
sig,
abs_temps, (abs_bad_ints),
heliocentric_correction=0.0)
print(("ABSORPTION OFFSET= " + str(rv_abs) + ', ' +
str(rv_abs_sig)))
else:
interesting_table = result['J/ApJS/141/503/table1']
object_RV = float(interesting_table[0]['__RV_']) / 1000.
except:
object_RV = float(data['RV_VALUE'])
Actual_RV.append(object_RV)
else:
h_corr = hdu[0].header['RADVEL']
ind = RV_standard.index(Obj_name)
pref_temp = Temp_to_use[ind]
flux, wave = ps.read_and_find_star_p08(file)
spectrum, sig = ps.weighted_extract_spectrum(flux)
rv, rv_sig, temp_used = ps.calc_rv_template(
spectrum,
wave,
sig, [pref_temp], ([0, 5400], [6870, 6890]),
save_figures=False,
heliocentric_correction=h_corr)
Delta_RV = Actual_RV[ind] - rv
Time_line[ind].append(MJD)
RV_variation[ind].append(Delta_RV)
for sit in range(len(RV_standard)):
plt.clf()
plt.plot(Time_line[sit], RV_variation[sit], 'o')
plt.axhline(y=0.0)
plt.xlabel('MJD')
plt.ylabel('RV Variation')
plt.title(RV_standard[sit] + '_RV_' + str(Actual_RV[sit]))
"""
Determine radial velocities
How is template determined?
"""
import process_stellar as ps
ps.calc_rv_template(spect,wave,sig, template_dir,bad_intervals,smooth_distance=101, \
gaussian_offset=1e-4,nwave_log=1e4,oversamp=1,fig_fn='',convolve_template=True,\
starnumber=0, plotit=False, save_figures=False, save_dir='./', heliocentric_correction=0.)
"""Compute a radial velocity based on an best fitting template spectrum.
Teff is estimated at the same time.
Parameters
----------
spect: array-like
The reduced WiFeS spectrum
wave: array-like
The wavelengths corresponding to the reduced WiFeS spectrum
template_conv_dir: string
The directory containing template spectra convolved to 0.1 Angstrom resolution
bad_intervals:
List of wavelength intervals where e.g. telluric absorption is bad.
smooth_distance: float
Distance to smooth for "continuum" correction
SNR.append(snr_val)
if snr_val >= 3.0:
rv,rv_sig, temp_used = ps.calc_rv_template(spectrum,wave,sig,templates, (bad_intervals), save_figures=False, save_dir='Images/', heliocentric_correction=0.0, fig_fn='Images/xcorr_slit_'+str(slit))
else:
rv = np.nan
RV_slits[slit].append(rv)
'''
spectrum, sig = ps.weighted_extract_spectrum(sky)
snr_val = np.max(spectrum) / np.median(spectrum)
SNR.append(snr_val)
if snr_val >= 5.0:
rv, rv_sig, temp_used = ps.calc_rv_template(
spectrum,
wave,
sig,
templates, (bad_intervals),
save_figures=True,
save_dir='Images/',
heliocentric_correction=0.0,
fig_fn='Images/xcorr_' + file.split('-')[-1].split('.')[0])
'''
spectrum_interp = np.interp(wave_template,wave[100:-100]*(1 - (0.0 - 0.0)/2.998e5),spectrum[100:-100])
sky_templates.append(spectrum_interp)
'''
#ps.make_wifes_p08_template(file, 'templates/', rv=0.0, )
else:
print("SNR TOO LOW")
rv = np.nan
rv_sig = np.nan
RV.append(rv)
RV_sig.append(rv_sig)
spectrum,sig = ps.weighted_extract_spectrum(flux)
templates = glob.glob('/Users/rajikak/tools/templates/*') + glob.glob('/Users/rajikak/tools/self_templates/*')
for temp in templates:
if Obj_name in temp and ''.join(Obs_date.split('-')) not in temp and use_self == True:
templates = [temp]
print("Observed before so will compare with itself")
break
else:
templates = glob.glob('/Users/rajikak/tools/templates/*')
if len(templates) >1:
print("Using RV standards")
#templates = glob.glob('/Users/rajikak/tools/self_templates/*')
#templates = glob.glob('/Users/rajikak/Observational_Data/Reduced_Wifes_Obs/20140622/*-0030*')
'''
for temp in templates:
if Obj_name in temp and ''.join(Obs_date.split('-')) in temp:
templates.remove(temp)
print "removed template:", temp
'''
#PLOT TEMPLATE SPECTRA VS REAL DATA AND PLOT CROSS_CORRELATION FUNCTIONS WITH RV
rv,rv_sig, temp_used = ps.calc_rv_template(spectrum,wave,sig,templates, ([0,5400],[6870,6890]), save_figures=True, save_dir=temp_dir, heliocentric_correction=h_corr)
write_string = Obj_name+','+RA+','+DEC+','+str(Obs_date)+','+str(rv)+','+str(rv_sig)+','+str(h_corr)+','+str(temp_used)+'\n'
print(write_string)
f.write(write_string)
f.close()
#MAKE LATEX
f.close()