def loadtemplatespectrum(filename, resolution, telluric_linelist, ccf_mask, velocity_step, wavemask):
spc = Spectrum(filename)
if wavemask :
spc.applyMask(wavemask)
barycentricTime = spc.barycentricTime()
barycentric_vel = barycentric_velocity(spc)
spc.continuumOrderByOrder(binsize = 30, overlap = 10)
spc.normalizeByContinuum(constant=10.0)
spc.binningOrderByOrder(rvsampling_kps=2.4, median=False)
spc.sortByWavelength()
ispectrum = ispec.create_spectrum_structure(spc.wl,spc.flux)
smoothed_spectrum = ispec.convolve_spectrum(ispectrum, resolution)
tel_models, tel_ccf = ispec.cross_correlate_with_mask(smoothed_spectrum, telluric_linelist, \
lower_velocity_limit=-10, upper_velocity_limit=10, \
velocity_step=0.1, mask_depth=0.01, \
fourier = False, only_one_peak = True)
tel_rv = tel_models[0].mu()
min_vel = -30.0
max_vel = +30.0
# Only the 25% of the deepest ones:
dfilter = telluric_linelist['depth'] > np.percentile(telluric_linelist['depth'], 75)
tfilter = ispec.create_filter_for_regions_affected_by_tellurics(smoothed_spectrum['waveobs'], \
telluric_linelist[dfilter], min_velocity=-tel_rv+min_vel, \
max_velocity=-tel_rv+max_vel)
clean_spectrum = smoothed_spectrum[~tfilter]
corrected_spectrum = ispec.correct_velocity(clean_spectrum, tel_rv - barycentric_vel)
models, ccf = ispec.cross_correlate_with_mask(clean_spectrum, ccf_mask, \
lower_velocity_limit=-100, upper_velocity_limit=100, \
velocity_step=velocity_step, mask_depth=0.01, \
fourier=False)
rv = models[0].mu()
clean_corrected_spectrum = ispec.correct_velocity(corrected_spectrum, rv)
return clean_corrected_spectrum
def determine_radial_velocity_with_mask(spec_id):
mu_cas_spectrum = ispec.read_spectrum(spec_id)
#--- Radial Velocity determination with linelist mask --------------------------
logging.info("Radial velocity determination with linelist mask...")
# - Read atomic data
mask_file = ispec_dir + "input/linelists/CCF/Narval.Sun.370_1048nm/mask.lst"
#mask_file = ispec_dir + "input/linelists/CCF/Atlas.Arcturus.372_926nm/mask.lst""
#mask_file = ispec_dir + "input/linelists/CCF/Atlas.Sun.372_926nm/mask.lst"
#mask_file = ispec_dir + "input/linelists/CCF/HARPS_SOPHIE.A0.350_1095nm/mask.lst"
#mask_file = ispec_dir + "input/linelists/CCF/HARPS_SOPHIE.F0.360_698nm/mask.lst"
#mask_file = ispec_dir + "input/linelists/CCF/HARPS_SOPHIE.G2.375_679nm/mask.lst"
#mask_file = ispec_dir + "input/linelists/CCF/HARPS_SOPHIE.K0.378_679nm/mask.lst"
#mask_file = ispec_dir + "input/linelists/CCF/HARPS_SOPHIE.K5.378_680nm/mask.lst"
#mask_file = ispec_dir + "input/linelists/CCF/HARPS_SOPHIE.M5.400_687nm/mask.lst"
#mask_file = ispec_dir + "input/linelists/CCF/Synthetic.Sun.350_1100nm/mask.lst"
#mask_file = ispec_dir + "input/linelists/CCF/VALD.Sun.300_1100nm/mask.lst"
ccf_mask = ispec.read_cross_correlation_mask(mask_file)
models, ccf = ispec.cross_correlate_with_mask(mu_cas_spectrum, ccf_mask, \
lower_velocity_limit=-200, upper_velocity_limit=200, \
velocity_step=1.0, mask_depth=0.01, \
fourier=False)
# Number of models represent the number of components
components = len(models)
# First component:
rv = np.round(models[0].mu(), 2) # km/s
rv_err = np.round(models[0].emu(), 2) # km/s
# Applying correction
logging.info("Applying radial velocity correction...")
#rv = -96.40 # km/s
mu_cas_spectrum = ispec.correct_velocity(mu_cas_spectrum, rv)
ispec.write_spectrum(mu_cas_spectrum, spec_id)
def lmfit_func(pars, normed_spectra, O2_spectra, return_model=False):
model = ispec.correct_velocity(np.copy(normed_spectra), pars['rv'])
model['flux'] = pars['zp'] * model['flux']
o2_model = 1 - (1 - np.copy(O2_spectra['flux'])) * pars['strength']
if return_model: return model, o2_model
else:
return np.interp(O2_spectra['waveobs'], model['waveobs'],
model['flux']) - o2_model
def test_correct_radial_velocity(self):
mu_cas_spectrum = ispec.read_spectrum(
ispec_dir + "/input/spectra/examples/NARVAL_muCas.txt.gz")
#--- Radial Velocity correction ------------------------------------------------
rv = -96.40 # km/s
mu_cas_spectrum = ispec.correct_velocity(mu_cas_spectrum, rv)
self.assertAlmostEqual(mu_cas_spectrum['waveobs'][0], 480.15547196)
self.assertAlmostEqual(mu_cas_spectrum['flux'][0], 0.19076)
self.assertAlmostEqual(mu_cas_spectrum['err'][0], 0.00095993)
def align_with_O2(spectra, O2_spectra, R=5000):
# Convert to ispec structures
spectra = ispec.create_spectrum_structure(spectra.T[0], spectra.T[1],
spectra.T[2])
O2_spectra = ispec.create_spectrum_structure(O2_spectra.T[0],
O2_spectra.T[1],
O2_spectra.T[2])
# Now normalise
normed_spectra, spectra_continuum_model = normalize_whole_spectrum(spectra)
#wfilter = ispec.create_wavelength_filter(normed_spectra, wave_base=np.min(O2_spectra['waveobs']) - 3, wave_top=np.max(O2_spectra['waveobs']) + 3)
wfilter = ispec.create_wavelength_filter(normed_spectra,
wave_base=684,
wave_top=690)
normed_spectra = normed_spectra[wfilter]
params = Parameters()
params.add('rv', value=0, min=-100, max=100)
params.add('strength', value=1, min=0.7, max=1.3)
params.add('zp', value=1., min=0.9, max=1.1, vary=False)
mini = Minimizer(lmfit_func,
params,
fcn_args=(np.copy(normed_spectra), np.copy(O2_spectra),
False))
lmfit_minimize_result = mini.minimize()
printfuncs.report_fit(lmfit_minimize_result, min_correl=0.5)
corrected_spectra, o2_model = lmfit_func(lmfit_minimize_result.params,
normed_spectra,
O2_spectra,
return_model=True)
f = plt.figure()
plt.plot(normed_spectra['waveobs'], normed_spectra['flux'], 'k', alpha=0.3)
plt.plot(corrected_spectra['waveobs'],
corrected_spectra['flux'],
'k',
label='Corrected solution')
plt.plot(O2_spectra['waveobs'], O2_spectra['flux'], 'r', alpha=0.3)
plt.plot(O2_spectra['waveobs'], o2_model, 'r', label='O2 model')
plt.gca().set(title='RV = {:.3f} +- {:.3f}'.format(
lmfit_minimize_result.params['rv'].value,
lmfit_minimize_result.params['rv'].stderr),
xlabel='Wavelength [nm]',
ylabel='Normalized flux')
plt.legend()
plt.xlim(685, 690)
corrected = ispec.correct_velocity(
np.copy(spectra), lmfit_minimize_result.params['rv'].value)
return f, np.array(
[corrected['waveobs'], corrected['flux'],
corrected['err']]).T, lmfit_minimize_result.params[
'rv'].value, lmfit_minimize_result.params['rv'].stderr
def test_determine_loggf_line_by_line_using_synth_spectra(self):
code = "spectrum"
star_spectrum = ispec.read_spectrum(
ispec_dir + "/input/spectra/examples/NARVAL_Sun_Vesta-1.txt.gz")
#--- Radial Velocity determination with template -------------------------------
# - Read synthetic template
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Arcturus.372_926nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Sun.372_926nm/template.txt.gz")
template = ispec.read_spectrum(
ispec_dir +
"/input/spectra/templates/NARVAL.Sun.370_1048nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Synth.Sun.300_1100nm/template.txt.gz")
models, ccf = ispec.cross_correlate_with_template(star_spectrum, template, \
lower_velocity_limit=-200, upper_velocity_limit=200, \
velocity_step=1.0, fourier=False)
# Number of models represent the number of components
components = len(models)
# First component:
rv = np.round(models[0].mu(), 2) # km/s
rv_err = np.round(models[0].emu(), 2) # km/s
#--- Radial Velocity correction ------------------------------------------------
star_spectrum = ispec.correct_velocity(star_spectrum, rv)
#--- Resolution degradation ----------------------------------------------------
# NOTE: The line selection was built based on a solar spectrum with R ~ 47,000 and GES/VALD atomic linelist.
from_resolution = 80000
to_resolution = 47000
star_spectrum = ispec.convolve_spectrum(star_spectrum, to_resolution,
from_resolution)
#--- Continuum fit -------------------------------------------------------------
model = "Splines" # "Polynomy"
degree = 2
nknots = None # Automatic: 1 spline every 5 nm
from_resolution = to_resolution
# Strategy: Filter first median values and secondly MAXIMUMs in order to find the continuum
order = 'median+max'
median_wave_range = 0.05
max_wave_range = 1.0
star_continuum_model = ispec.fit_continuum(star_spectrum, from_resolution=from_resolution, \
nknots=nknots, degree=degree, \
median_wave_range=median_wave_range, \
max_wave_range=max_wave_range, \
model=model, order=order, \
automatic_strong_line_detection=True, \
strong_line_probability=0.5, \
use_errors_for_fitting=True)
#--- Normalize -------------------------------------------------------------
normalized_star_spectrum = ispec.normalize_spectrum(
star_spectrum,
star_continuum_model,
consider_continuum_errors=False)
# Use a fixed value because the spectrum is already normalized
star_continuum_model = ispec.fit_continuum(star_spectrum,
fixed_value=1.0,
model="Fixed value")
#--- Model spectra ----------------------------------------------------------
# Parameters
initial_teff = 5771.0
initial_logg = 4.44
initial_MH = 0.00
initial_alpha = 0.00
initial_vmic = ispec.estimate_vmic(initial_teff, initial_logg,
initial_MH)
initial_vmac = ispec.estimate_vmac(initial_teff, initial_logg,
initial_MH)
initial_vsini = 1.60 # Sun
initial_limb_darkening_coeff = 0.6
initial_R = to_resolution
initial_vrad = 0
max_iterations = 6
# Selected model amtosphere, linelist and solar abundances
#model = ispec_dir + "/input/atmospheres/MARCS/"
model = ispec_dir + "/input/atmospheres/MARCS.GES/"
#model = ispec_dir + "/input/atmospheres/MARCS.APOGEE/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.APOGEE/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Castelli/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Kurucz/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Kirby/"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/VALD.300_1100nm/atomic_lines.tsv"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/VALD.1100_2400nm/atomic_lines.tsv"
atomic_linelist_file = ispec_dir + "/input/linelists/transitions/GESv6_atom_hfs_iso.420_920nm/atomic_lines.tsv"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/GESv6_atom_nohfs_noiso.420_920nm/atomic_lines.tsv"
if "ATLAS" in model:
solar_abundances_file = ispec_dir + "/input/abundances/Grevesse.1998/stdatom.dat"
else:
# MARCS
solar_abundances_file = ispec_dir + "/input/abundances/Grevesse.2007/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Asplund.2005/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Asplund.2009/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Anders.1989/stdatom.dat"
isotope_file = ispec_dir + "/input/isotopes/SPECTRUM.lst"
# Load chemical information and linelist
atomic_linelist = ispec.read_atomic_linelist(
atomic_linelist_file,
wave_base=np.min(star_spectrum['waveobs']),
wave_top=np.max(star_spectrum['waveobs']))
atomic_linelist = atomic_linelist[
atomic_linelist['theoretical_depth'] >=
0.01] # Select lines that have some minimal contribution in the sun
isotopes = ispec.read_isotope_data(isotope_file)
# Load model atmospheres
modeled_layers_pack = ispec.load_modeled_layers_pack(model)
# Load SPECTRUM abundances
solar_abundances = ispec.read_solar_abundances(solar_abundances_file)
# Free parameters
#free_params = ["teff", "logg", "MH", "vmic", "vmac", "vsini", "R", "vrad", "limb_darkening_coeff"]
#free_params = ["vrad"]
free_params = []
# Free individual element abundance (WARNING: it should be coherent with the selected line regions!)
chemical_elements_file = ispec_dir + "/input/abundances/chemical_elements_symbols.dat"
chemical_elements = ispec.read_chemical_elements(
chemical_elements_file)
# Line regions
line_regions_with_atomic_data = ispec.read_line_regions(
ispec_dir +
"/input/regions/47000_GES/{}_synth_good_for_params_all_extended.txt"
.format(code))
#line_regions_with_atomic_data = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/{}_synth_good_for_params_all_extended.txt".format(code))
# Select only the lines to get abundances from
line_regions_with_atomic_data = line_regions_with_atomic_data[:5]
line_regions_with_atomic_data = ispec.adjust_linemasks(
normalized_star_spectrum,
line_regions_with_atomic_data,
max_margin=0.5)
output_dirname = "example_loggf_line_by_line_%s" % (code, )
#ispec.mkdir_p(output_dirname)
for i, line in enumerate(line_regions_with_atomic_data):
# Directory and file names
#element_name = "_".join(line['element'].split())
element_name = "_".join(line['note'].split())
common_filename = "example_" + code + "_individual_" + element_name + "_%.4f" % line[
'wave_peak']
# Free individual element abundance (WARNING: it should be coherent with the selected line regions!)
free_abundances = None
# Line by line
individual_line_regions = line_regions_with_atomic_data[
i:i + 1] # Keep recarray structure
linelist_free_loggf = line_regions_with_atomic_data[
i:i + 1] # Keep recarray structure
# Filter the line that we want to determine the loggf from the global atomic linelist
lfilter = atomic_linelist['element'] == linelist_free_loggf[
'element'][0]
for key in [
'wave_nm', 'lower_state_eV', 'loggf', 'stark', 'rad',
'waals'
]:
lfilter = np.logical_and(
lfilter,
np.abs(atomic_linelist[key] - linelist_free_loggf[key][0])
< 1e-9)
# Segment
segments = ispec.create_segments_around_lines(
individual_line_regions, margin=0.25)
wfilter = ispec.create_wavelength_filter(
normalized_star_spectrum,
regions=segments) # Only use the segment
obs_spec, modeled_synth_spectrum, params, errors, abundances_found, loggf_found, status, stats_linemasks = \
ispec.model_spectrum(normalized_star_spectrum[wfilter], star_continuum_model, \
modeled_layers_pack, atomic_linelist[~lfilter], isotopes, solar_abundances, free_abundances, linelist_free_loggf, initial_teff, \
initial_logg, initial_MH, initial_alpha, initial_vmic, initial_vmac, initial_vsini, \
initial_limb_darkening_coeff, initial_R, initial_vrad, free_params, segments=segments, \
linemasks=individual_line_regions, \
enhance_abundances=True, \
use_errors = True, \
vmic_from_empirical_relation = False, \
vmac_from_empirical_relation = False, \
max_iterations=max_iterations, \
tmp_dir = None, \
code=code)
self.assertAlmostEqual(loggf_found['loggf'][0],
-1.0743873027191777)
self.assertAlmostEqual(loggf_found['eloggf'][0],
0.11414696354921147)
self.assertEqual(len(loggf_found['loggf']), 1)
self.assertEqual(individual_line_regions['lower_state_eV'][0],
loggf_found['linelist']['lower_state_eV'][0])
break
def test_determine_astrophysical_parameters_using_synth_spectra(self):
code = "spectrum"
star_spectrum = ispec.read_spectrum(
ispec_dir + "/input/spectra/examples/NARVAL_Sun_Vesta-1.txt.gz")
#--- Radial Velocity determination with template -------------------------------
# - Read synthetic template
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Arcturus.372_926nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Sun.372_926nm/template.txt.gz")
template = ispec.read_spectrum(
ispec_dir +
"/input/spectra/templates/NARVAL.Sun.370_1048nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Synth.Sun.300_1100nm/template.txt.gz")
models, ccf = ispec.cross_correlate_with_template(star_spectrum, template, \
lower_velocity_limit=-200, upper_velocity_limit=200, \
velocity_step=1.0, fourier=False)
# Number of models represent the number of components
components = len(models)
# First component:
rv = np.round(models[0].mu(), 2) # km/s
rv_err = np.round(models[0].emu(), 2) # km/s
#--- Radial Velocity correction ------------------------------------------------
star_spectrum = ispec.correct_velocity(star_spectrum, rv)
#--- Resolution degradation ----------------------------------------------------
# NOTE: The line selection was built based on a solar spectrum with R ~ 47,000 and GES/VALD atomic linelist.
from_resolution = 80000
to_resolution = 47000
star_spectrum = ispec.convolve_spectrum(star_spectrum, to_resolution,
from_resolution)
#--- Continuum fit -------------------------------------------------------------
model = "Splines" # "Polynomy"
degree = 2
nknots = None # Automatic: 1 spline every 5 nm
from_resolution = to_resolution
# Strategy: Filter first median values and secondly MAXIMUMs in order to find the continuum
order = 'median+max'
median_wave_range = 0.05
max_wave_range = 1.0
star_continuum_model = ispec.fit_continuum(star_spectrum, from_resolution=from_resolution, \
nknots=nknots, degree=degree, \
median_wave_range=median_wave_range, \
max_wave_range=max_wave_range, \
model=model, order=order, \
automatic_strong_line_detection=True, \
strong_line_probability=0.5, \
use_errors_for_fitting=True)
#--- Normalize -------------------------------------------------------------
normalized_star_spectrum = ispec.normalize_spectrum(
star_spectrum,
star_continuum_model,
consider_continuum_errors=False)
# Use a fixed value because the spectrum is already normalized
star_continuum_model = ispec.fit_continuum(star_spectrum,
fixed_value=1.0,
model="Fixed value")
#--- Model spectra ----------------------------------------------------------
# Parameters
initial_teff = 5750.0
initial_logg = 4.5
initial_MH = 0.00
initial_alpha = ispec.determine_abundance_enchancements(initial_MH)
initial_vmic = ispec.estimate_vmic(initial_teff, initial_logg,
initial_MH)
initial_vmac = ispec.estimate_vmac(initial_teff, initial_logg,
initial_MH)
initial_vsini = 2.0
initial_limb_darkening_coeff = 0.6
initial_R = to_resolution
initial_vrad = 0
max_iterations = 6
# Selected model amtosphere, linelist and solar abundances
#model = ispec_dir + "/input/atmospheres/MARCS/"
model = ispec_dir + "/input/atmospheres/MARCS.GES/"
#model = ispec_dir + "/input/atmospheres/MARCS.APOGEE/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.APOGEE/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Castelli/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Kurucz/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Kirby/"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/VALD.300_1100nm/atomic_lines.tsv"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/VALD.1100_2400nm/atomic_lines.tsv"
atomic_linelist_file = ispec_dir + "/input/linelists/transitions/GESv6_atom_hfs_iso.420_920nm/atomic_lines.tsv"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/GESv6_atom_nohfs_noiso.420_920nm/atomic_lines.tsv"
if "ATLAS" in model:
solar_abundances_file = ispec_dir + "/input/abundances/Grevesse.1998/stdatom.dat"
else:
# MARCS
solar_abundances_file = ispec_dir + "/input/abundances/Grevesse.2007/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Asplund.2005/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Asplund.2009/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Anders.1989/stdatom.dat"
isotope_file = ispec_dir + "/input/isotopes/SPECTRUM.lst"
# Load chemical information and linelist
atomic_linelist = ispec.read_atomic_linelist(
atomic_linelist_file,
wave_base=np.min(star_spectrum['waveobs']),
wave_top=np.max(star_spectrum['waveobs']))
atomic_linelist = atomic_linelist[
atomic_linelist['theoretical_depth'] >=
0.01] # Select lines that have some minimal contribution in the sun
isotopes = ispec.read_isotope_data(isotope_file)
# Load model atmospheres
modeled_layers_pack = ispec.load_modeled_layers_pack(model)
# Load SPECTRUM abundances
solar_abundances = ispec.read_solar_abundances(solar_abundances_file)
# Free parameters
#free_params = ["teff", "logg", "MH", "vmic", "vmac", "vsini", "R", "vrad", "limb_darkening_coeff"]
free_params = ["teff", "logg", "MH", "vmic", "R"]
# Free individual element abundance
free_abundances = None
linelist_free_loggf = None
# Line regions
line_regions = ispec.read_line_regions(
ispec_dir +
"/input/regions/47000_GES/{}_synth_good_for_params_all.txt".format(
code))
#line_regions = ispec.read_line_regions(ispec_dir + "/input/regions/47000_GES/{}_synth_good_for_params_all_extended.txt".format(code))
#line_regions = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/{}_synth_good_for_params_all.txt".format(code))
#line_regions = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/{}_synth_good_for_params_all_extended.txt".format(code))
## Select only some lines to speed up the execution (in a real analysis it is better not to do this)
line_regions = line_regions[np.logical_or(
line_regions['note'] == 'Ti 1', line_regions['note'] == 'Ti 2')]
line_regions = ispec.adjust_linemasks(normalized_star_spectrum,
line_regions,
max_margin=0.5)
# Read segments if we have them or...
#segments = ispec.read_segment_regions(ispec_dir + "/input/regions/fe_lines_segments.txt")
# ... or we can create the segments on the fly:
segments = ispec.create_segments_around_lines(line_regions,
margin=0.25)
### Add also regions from the wings of strong lines:
## H beta
#hbeta_lines = ispec.read_line_regions(ispec_dir + "input/regions/wings_Hbeta.txt")
#hbeta_segments = ispec.read_segment_regions(ispec_dir + "input/regions/wings_Hbeta_segments.txt")
#line_regions = np.hstack((line_regions, hbeta_lines))
#segments = np.hstack((segments, hbeta_segments))
## H alpha
#halpha_lines = ispec.read_line_regions(ispec_dir + "input/regions/wings_Halpha.txt")
#halpha_segments = ispec.read_segment_regions(ispec_dir + "input/regions/wings_Halpha_segments.txt")
#line_regions = np.hstack((line_regions, halpha_lines))
#segments = np.hstack((segments, halpha_segments))
## Magnesium triplet
#mgtriplet_lines = ispec.read_line_regions(ispec_dir + "input/regions/wings_MgTriplet.txt")
#mgtriplet_segments = ispec.read_segment_regions(ispec_dir + "input/regions/wings_MgTriplet_segments.txt")
#line_regions = np.hstack((line_regions, mgtriplet_lines))
#segments = np.hstack((segments, mgtriplet_segments))
obs_spec, modeled_synth_spectrum, params, errors, abundances_found, loggf_found, status, stats_linemasks = \
ispec.model_spectrum(normalized_star_spectrum, star_continuum_model, \
modeled_layers_pack, atomic_linelist, isotopes, solar_abundances, free_abundances, linelist_free_loggf, initial_teff, \
initial_logg, initial_MH, initial_alpha, initial_vmic, initial_vmac, initial_vsini, \
initial_limb_darkening_coeff, initial_R, initial_vrad, free_params, segments=segments, \
linemasks=line_regions, \
enhance_abundances=True, \
use_errors = True, \
vmic_from_empirical_relation = False, \
vmac_from_empirical_relation = True, \
max_iterations=max_iterations, \
tmp_dir = None, \
code=code)
expected_params = {
'teff': 5696.144535300913,
'logg': 4.35386512625295,
'MH': -0.117924251886487,
'alpha': 0.047169700754594805,
'vmic': 1.1383979614486783,
'vmac': 4.04,
'vsini': 2.0,
'limb_darkening_coeff': 0.6,
'R': 49936.32725781359
}
for k, v in list(expected_params.items()):
self.assertAlmostEqual(params[k], v)
expected_errors = {
'teff': 66.38643184730074,
'logg': 0.10101410057739481,
'MH': 0.07728877921624414,
'alpha': 0.0,
'vmic': 0.10922339131594937,
'vmac': 0.0,
'vsini': 0.0,
'limb_darkening_coeff': 0.0,
'R': 3496.439438356713
}
for k, v in list(expected_errors.items()):
self.assertAlmostEqual(errors[k], v)
self.assertEqual(len(stats_linemasks), 30)
def test_determine_astrophysical_parameters_using_grid(self):
star_spectrum = ispec.read_spectrum(
ispec_dir + "/input/spectra/examples/NARVAL_Sun_Vesta-1.txt.gz")
#star_spectrum = ispec.read_spectrum(ispec_dir + "/input/spectra/examples/NARVAL_Arcturus.txt.gz")
#star_spectrum = ispec.read_spectrum(ispec_dir + "/input/spectra/examples/NARVAL_muCas.txt.gz")
#star_spectrum = ispec.read_spectrum(ispec_dir + "/input/spectra/examples/NARVAL_muLeo.txt.gz")
#star_spectrum = ispec.read_spectrum(ispec_dir + "/input/spectra/examples/HARPS.GBOG_Procyon.txt.gz")
#--- Radial Velocity determination with template -------------------------------
# - Read synthetic template
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Arcturus.372_926nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Sun.372_926nm/template.txt.gz")
template = ispec.read_spectrum(
ispec_dir +
"/input/spectra/templates/NARVAL.Sun.370_1048nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Synth.Sun.300_1100nm/template.txt.gz")
models, ccf = ispec.cross_correlate_with_template(star_spectrum, template, \
lower_velocity_limit=-200, upper_velocity_limit=200, \
velocity_step=1.0, fourier=False)
# Number of models represent the number of components
components = len(models)
# First component:
rv = np.round(models[0].mu(), 2) # km/s
rv_err = np.round(models[0].emu(), 2) # km/s
#--- Radial Velocity correction ------------------------------------------------
star_spectrum = ispec.correct_velocity(star_spectrum, rv)
#--- Resolution degradation ----------------------------------------------------
# NOTE: The line selection was built based on a solar spectrum with R ~ 47,000 and GES/VALD atomic linelist.
from_resolution = 80000
to_resolution = 47000
star_spectrum = ispec.convolve_spectrum(star_spectrum, to_resolution,
from_resolution)
#--- Continuum fit -------------------------------------------------------------
model = "Splines" # "Polynomy"
degree = 2
nknots = None # Automatic: 1 spline every 5 nm
from_resolution = to_resolution
# Strategy: Filter first median values and secondly MAXIMUMs in order to find the continuum
order = 'median+max'
median_wave_range = 0.05
max_wave_range = 1.0
star_continuum_model = ispec.fit_continuum(star_spectrum, from_resolution=from_resolution, \
nknots=nknots, degree=degree, \
median_wave_range=median_wave_range, \
max_wave_range=max_wave_range, \
model=model, order=order, \
automatic_strong_line_detection=True, \
strong_line_probability=0.5, \
use_errors_for_fitting=True)
#--- Normalize -------------------------------------------------------------
normalized_star_spectrum = ispec.normalize_spectrum(
star_spectrum,
star_continuum_model,
consider_continuum_errors=False)
# Use a fixed value because the spectrum is already normalized
star_continuum_model = ispec.fit_continuum(star_spectrum,
fixed_value=1.0,
model="Fixed value")
#--- Model spectra ----------------------------------------------------------
# Parameters
initial_teff = 5750.0
initial_logg = 4.5
initial_MH = 0.00
initial_alpha = 0.00
initial_vmic = ispec.estimate_vmic(initial_teff, initial_logg,
initial_MH)
initial_vmac = ispec.estimate_vmac(initial_teff, initial_logg,
initial_MH)
initial_vsini = 2.0
initial_limb_darkening_coeff = 0.6
initial_R = to_resolution
initial_vrad = 0
max_iterations = 20
code = "grid"
precomputed_grid_dir = ispec_dir + "/input/grid/SPECTRUM_MARCS.GES_GESv6_atom_hfs_iso.480_680nm_light/"
atomic_linelist = None
isotopes = None
modeled_layers_pack = None
solar_abundances = None
free_abundances = None
linelist_free_loggf = None
# Free parameters (vmic cannot be used as a free parameter when using a spectral grid)
#free_params = ["teff", "logg", "MH", "alpha", "vmic", "vmac", "vsini", "R", "vrad", "limb_darkening_coeff"]
free_params = ["teff", "logg", "MH", "alpha", "vmic", "R"]
# Line regions
line_regions = ispec.read_line_regions(
ispec_dir +
"/input/regions/47000_GES/{}_synth_good_for_params_all.txt".format(
code))
#line_regions = ispec.read_line_regions(ispec_dir + "/input/regions/47000_GES/{}_synth_good_for_params_all_extended.txt".format(code))
#line_regions = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/{}_synth_good_for_params_all.txt".format(code))
#line_regions = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/{}_synth_good_for_params_all_extended.txt".format(code))
## Select only some lines to speed up the execution (in a real analysis it is better not to do this)
#line_regions = line_regions[np.logical_or(line_regions['note'] == 'Ti 1', line_regions['note'] == 'Ti 2')]
#line_regions = ispec.adjust_linemasks(normalized_star_spectrum, line_regions, max_margin=0.5)
# Read segments if we have them or...
#segments = ispec.read_segment_regions(ispec_dir + "/input/regions/fe_lines_segments.txt")
# ... or we can create the segments on the fly:
segments = ispec.create_segments_around_lines(line_regions,
margin=0.25)
## Add also regions from the wings of strong lines:
# H beta
hbeta_lines = ispec.read_line_regions(ispec_dir +
"input/regions/wings_Hbeta.txt")
hbeta_segments = ispec.read_segment_regions(
ispec_dir + "input/regions/wings_Hbeta_segments.txt")
line_regions = np.hstack((line_regions, hbeta_lines))
segments = np.hstack((segments, hbeta_segments))
# H alpha
halpha_lines = ispec.read_line_regions(
ispec_dir + "input/regions/wings_Halpha.txt")
halpha_segments = ispec.read_segment_regions(
ispec_dir + "input/regions/wings_Halpha_segments.txt")
line_regions = np.hstack((line_regions, halpha_lines))
segments = np.hstack((segments, halpha_segments))
# Magnesium triplet
mgtriplet_lines = ispec.read_line_regions(
ispec_dir + "input/regions/wings_MgTriplet.txt")
mgtriplet_segments = ispec.read_segment_regions(
ispec_dir + "input/regions/wings_MgTriplet_segments.txt")
line_regions = np.hstack((line_regions, mgtriplet_lines))
segments = np.hstack((segments, mgtriplet_segments))
obs_spec, modeled_synth_spectrum, params, errors, abundances_found, loggf_found, status, stats_linemasks = \
ispec.model_spectrum(normalized_star_spectrum, star_continuum_model, \
modeled_layers_pack, atomic_linelist, isotopes, solar_abundances, free_abundances, linelist_free_loggf, initial_teff, \
initial_logg, initial_MH, initial_alpha, initial_vmic, initial_vmac, initial_vsini, \
initial_limb_darkening_coeff, initial_R, initial_vrad, free_params, segments=segments, \
linemasks=line_regions, \
enhance_abundances=False, \
use_errors = True, \
vmic_from_empirical_relation = False, \
vmac_from_empirical_relation = True, \
max_iterations=max_iterations, \
tmp_dir = None, \
code=code, precomputed_grid_dir=precomputed_grid_dir)
expected_params = {
'teff': 5848.516352941799,
'logg': 4.47140586507073,
'MH': 0.021745200217247945,
'alpha': 0.0,
'vmic': 0.5617098008018283,
'vmac': 4.5,
'vsini': 2.0,
'limb_darkening_coeff': 0.6,
'R': 78395.52968455742
}
for k, v in list(expected_params.items()):
self.assertAlmostEqual(params[k], v)
expected_errors = {
'teff': 16.061649602869444,
'logg': 0.028408456932473077,
'MH': 0.007324730574204324,
'alpha': 0.007733907152934892,
'vmic': 0.043996803165640905,
'vmac': 0.0,
'vsini': 0.0,
'limb_darkening_coeff': 0.0,
'R': 3898.724894322937
}
for k, v in list(expected_errors.items()):
self.assertAlmostEqual(errors[k], v)
self.assertEqual(len(stats_linemasks), 337)
def test_determine_abundances_using_synth_spectra(self):
code = "spectrum"
star_spectrum = ispec.read_spectrum(
ispec_dir + "/input/spectra/examples/NARVAL_Sun_Vesta-1.txt.gz")
#--- Radial Velocity determination with template -------------------------------
# - Read synthetic template
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Arcturus.372_926nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Sun.372_926nm/template.txt.gz")
template = ispec.read_spectrum(
ispec_dir +
"/input/spectra/templates/NARVAL.Sun.370_1048nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Synth.Sun.300_1100nm/template.txt.gz")
models, ccf = ispec.cross_correlate_with_template(star_spectrum, template, \
lower_velocity_limit=-200, upper_velocity_limit=200, \
velocity_step=1.0, fourier=False)
# Number of models represent the number of components
components = len(models)
# First component:
rv = np.round(models[0].mu(), 2) # km/s
rv_err = np.round(models[0].emu(), 2) # km/s
#--- Radial Velocity correction ------------------------------------------------
star_spectrum = ispec.correct_velocity(star_spectrum, rv)
#--- Resolution degradation ----------------------------------------------------
# NOTE: The line selection was built based on a solar spectrum with R ~ 47,000 and GES/VALD atomic linelist.
from_resolution = 80000
to_resolution = 47000
star_spectrum = ispec.convolve_spectrum(star_spectrum, to_resolution,
from_resolution)
#--- Continuum fit -------------------------------------------------------------
model = "Splines" # "Polynomy"
degree = 2
nknots = None # Automatic: 1 spline every 5 nm
from_resolution = to_resolution
# Strategy: Filter first median values and secondly MAXIMUMs in order to find the continuum
order = 'median+max'
median_wave_range = 0.05
max_wave_range = 1.0
star_continuum_model = ispec.fit_continuum(star_spectrum, from_resolution=from_resolution, \
nknots=nknots, degree=degree, \
median_wave_range=median_wave_range, \
max_wave_range=max_wave_range, \
model=model, order=order, \
automatic_strong_line_detection=True, \
strong_line_probability=0.5, \
use_errors_for_fitting=True)
#--- Normalize -------------------------------------------------------------
normalized_star_spectrum = ispec.normalize_spectrum(
star_spectrum,
star_continuum_model,
consider_continuum_errors=False)
# Use a fixed value because the spectrum is already normalized
star_continuum_model = ispec.fit_continuum(star_spectrum,
fixed_value=1.0,
model="Fixed value")
#--- Model spectra ----------------------------------------------------------
# Parameters
initial_teff = 5771.0
initial_logg = 4.44
initial_MH = 0.00
initial_alpha = 0.00
initial_vmic = ispec.estimate_vmic(initial_teff, initial_logg,
initial_MH)
initial_vmac = ispec.estimate_vmac(initial_teff, initial_logg,
initial_MH)
initial_vsini = 1.60 # Sun
initial_limb_darkening_coeff = 0.6
initial_R = to_resolution
initial_vrad = 0
max_iterations = 6
# Selected model amtosphere, linelist and solar abundances
#model = ispec_dir + "/input/atmospheres/MARCS/"
model = ispec_dir + "/input/atmospheres/MARCS.GES/"
#model = ispec_dir + "/input/atmospheres/MARCS.APOGEE/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.APOGEE/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Castelli/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Kurucz/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Kirby/"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/VALD.300_1100nm/atomic_lines.tsv"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/VALD.1100_2400nm/atomic_lines.tsv"
atomic_linelist_file = ispec_dir + "/input/linelists/transitions/GESv6_atom_hfs_iso.420_920nm/atomic_lines.tsv"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/GESv6_atom_nohfs_noiso.420_920nm/atomic_lines.tsv"
if "ATLAS" in model:
solar_abundances_file = ispec_dir + "/input/abundances/Grevesse.1998/stdatom.dat"
else:
# MARCS
solar_abundances_file = ispec_dir + "/input/abundances/Grevesse.2007/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Asplund.2005/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Asplund.2009/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Anders.1989/stdatom.dat"
isotope_file = ispec_dir + "/input/isotopes/SPECTRUM.lst"
# Load chemical information and linelist
atomic_linelist = ispec.read_atomic_linelist(
atomic_linelist_file,
wave_base=np.min(star_spectrum['waveobs']),
wave_top=np.max(star_spectrum['waveobs']))
atomic_linelist = atomic_linelist[
atomic_linelist['theoretical_depth'] >=
0.01] # Select lines that have some minimal contribution in the sun
isotopes = ispec.read_isotope_data(isotope_file)
# Load model atmospheres
modeled_layers_pack = ispec.load_modeled_layers_pack(model)
# Load SPECTRUM abundances
solar_abundances = ispec.read_solar_abundances(solar_abundances_file)
# Free parameters
#free_params = ["teff", "logg", "MH", "vmic", "vmac", "vsini", "R", "vrad", "limb_darkening_coeff"]
free_params = ["vrad"]
#free_params = []
# Free individual element abundance (WARNING: it should be coherent with the selected line regions!)
chemical_elements_file = ispec_dir + "/input/abundances/chemical_elements_symbols.dat"
chemical_elements = ispec.read_chemical_elements(
chemical_elements_file)
element_name = "Ca"
free_abundances = ispec.create_free_abundances_structure(
[element_name], chemical_elements, solar_abundances)
free_abundances['Abund'] += initial_MH # Scale to metallicity
linelist_free_loggf = None
# Line regions
line_regions = ispec.read_line_regions(
ispec_dir +
"/input/regions/47000_GES/{}_synth_good_for_params_all.txt".format(
code))
#line_regions = ispec.read_line_regions(ispec_dir + "/input/regions/47000_GES/{}_synth_good_for_params_all_extended.txt".format(code))
#line_regions = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/{}_synth_good_for_params_all.txt".format(code))
#line_regions = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/{}_synth_good_for_params_all_extended.txt".format(code))
# Select only the lines to get abundances from
line_regions = line_regions[np.logical_or(
line_regions['note'] == element_name + ' 1',
line_regions['note'] == element_name + ' 2')]
line_regions = ispec.adjust_linemasks(normalized_star_spectrum,
line_regions,
max_margin=0.5)
# Read segments if we have them or...
#segments = ispec.read_segment_regions(ispec_dir + "/input/regions/fe_lines_segments.txt")
# ... or we can create the segments on the fly:
segments = ispec.create_segments_around_lines(line_regions,
margin=0.25)
obs_spec, modeled_synth_spectrum, params, errors, abundances_found, loggf_found, status, stats_linemasks = \
ispec.model_spectrum(normalized_star_spectrum, star_continuum_model, \
modeled_layers_pack, atomic_linelist, isotopes, solar_abundances, free_abundances, linelist_free_loggf, initial_teff, \
initial_logg, initial_MH, initial_alpha, initial_vmic, initial_vmac, initial_vsini, \
initial_limb_darkening_coeff, initial_R, initial_vrad, free_params, segments=segments, \
linemasks=line_regions, \
enhance_abundances=True, \
use_errors = True, \
vmic_from_empirical_relation = False, \
vmac_from_empirical_relation = False, \
max_iterations=max_iterations, \
tmp_dir = None, \
code=code)
expected_params = {
'teff': 5771.0,
'logg': 4.44,
'MH': 0.0,
'alpha': 0.0,
'vmic': 1.07,
'vmac': 4.19,
'vsini': 1.6,
'limb_darkening_coeff': 0.6,
'R': 47000.0,
'vrad0000': -0.009293697395991595,
'vrad0001': -0.06018526081728252,
'vrad0002': -0.015666491320596353,
'vrad0003': -0.055193632795656256,
'vrad0004': -0.1567689404172516,
'vrad0005': -0.22508061064189286,
'vrad0006': -0.20359311863771612,
'vrad0007': -0.16078450322612126
}
for k, v in list(expected_params.items()):
self.assertAlmostEqual(params[k], v)
expected_errors = {
'teff': 0.0,
'logg': 0.0,
'MH': 0.0,
'alpha': 0.0,
'vmic': 0.0,
'vmac': 0.0,
'vsini': 0.0,
'limb_darkening_coeff': 0.0,
'R': 0.0,
'vrad0000': 2.2914331925224816,
'vrad0001': 0.6770488621090028,
'vrad0002': 0.2767472596825708,
'vrad0003': 1.0820599330375968,
'vrad0004': 0.47734411482243877,
'vrad0005': 0.2585031799872256,
'vrad0006': 0.46187116575854853,
'vrad0007': 0.23921192411257394
}
for k, v in list(expected_errors.items()):
self.assertAlmostEqual(errors[k], v)
self.assertEqual(len(stats_linemasks), 8)
self.assertEqual(abundances_found['element'][0], 'Ca')
self.assertAlmostEqual(abundances_found['[X/H]'][0],
-0.0020078068382556324)
self.assertAlmostEqual(abundances_found['[X/Fe]'][0],
-0.0020078068382556324)
self.assertAlmostEqual(abundances_found['e[X/H]'][0],
0.027149612080779945)
self.assertAlmostEqual(abundances_found['e[X/Fe]'][0],
0.027149612080779945)
def _determine_abundances_from_ew(self, code):
use_ares = False
star_spectrum = ispec.read_spectrum(
ispec_dir + "/input/spectra/examples/NARVAL_Sun_Vesta-1.txt.gz")
#--- Radial Velocity determination with template -------------------------------
# - Read synthetic template
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Arcturus.372_926nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Sun.372_926nm/template.txt.gz")
template = ispec.read_spectrum(
ispec_dir +
"/input/spectra/templates/NARVAL.Sun.370_1048nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Synth.Sun.300_1100nm/template.txt.gz")
models, ccf = ispec.cross_correlate_with_template(star_spectrum, template, \
lower_velocity_limit=-200, upper_velocity_limit=200, \
velocity_step=1.0, fourier=False)
# Number of models represent the number of components
components = len(models)
# First component:
rv = np.round(models[0].mu(), 2) # km/s
rv_err = np.round(models[0].emu(), 2) # km/s
#--- Radial Velocity correction ------------------------------------------------
star_spectrum = ispec.correct_velocity(star_spectrum, rv)
#--- Telluric velocity shift determination from spectrum --------------------------
# - Telluric
telluric_linelist_file = ispec_dir + "/input/linelists/CCF/Synth.Tellurics.500_1100nm/mask.lst"
telluric_linelist = ispec.read_telluric_linelist(
telluric_linelist_file, minimum_depth=0.0)
models, ccf = ispec.cross_correlate_with_mask(star_spectrum, telluric_linelist, \
lower_velocity_limit=-100, upper_velocity_limit=100, \
velocity_step=0.5, mask_depth=0.01, \
fourier = False,
only_one_peak = True)
vel_telluric = np.round(models[0].mu(), 2) # km/s
vel_telluric_err = np.round(models[0].emu(), 2) # km/s
#--- Resolution degradation ----------------------------------------------------
# NOTE: The line selection was built based on a solar spectrum with R ~ 47,000 and GES/VALD atomic linelist.
from_resolution = 80000
to_resolution = 47000
star_spectrum = ispec.convolve_spectrum(star_spectrum, to_resolution,
from_resolution)
#--- Continuum fit -------------------------------------------------------------
model = "Splines" # "Polynomy"
degree = 2
nknots = None # Automatic: 1 spline every 5 nm
#from_resolution = 80000
from_resolution = to_resolution
# Strategy: Filter first median values and secondly MAXIMUMs in order to find the continuum
order = 'median+max'
median_wave_range = 0.05
max_wave_range = 1.0
star_continuum_model = ispec.fit_continuum(star_spectrum, from_resolution=from_resolution, \
nknots=nknots, degree=degree, \
median_wave_range=median_wave_range, \
max_wave_range=max_wave_range, \
model=model, order=order, \
automatic_strong_line_detection=True, \
strong_line_probability=0.5, \
use_errors_for_fitting=True)
#--- Normalize -------------------------------------------------------------
normalized_star_spectrum = ispec.normalize_spectrum(
star_spectrum,
star_continuum_model,
consider_continuum_errors=False)
# Use a fixed value because the spectrum is already normalized
star_continuum_model = ispec.fit_continuum(star_spectrum,
fixed_value=1.0,
model="Fixed value")
#telluric_linelist_file = ispec_dir + "/input/linelists/CCF/Synth.Tellurics.500_1100nm/mask.lst"
#telluric_linelist = ispec.read_telluric_linelist(telluric_linelist_file, minimum_depth=0.01)
#vel_telluric = 17.79 # km/s
#telluric_linelist = None
#vel_telluric = None
#--- Read lines and adjust them ------------------------------------------------
if code in ['width', 'moog']:
line_regions_with_atomic_data = ispec.read_line_regions(
ispec_dir +
"/input/regions/47000_GES/{}_ew_ispec_good_for_params_all_extended.txt"
.format(code))
#line_regions_with_atomic_data = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/{}_ew_ispec_good_for_params_all_extended.txt".format(code))
else:
line_regions_with_atomic_data = ispec.read_line_regions(
ispec_dir +
"/input/regions/47000_GES/{}_synth_good_for_params_all_extended.txt"
.format(code))
#line_regions_with_atomic_data = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/{}_synth_good_for_params_all_extended.txt".format(code))
# Select only iron lines
line_regions_with_atomic_data = line_regions_with_atomic_data[
np.logical_or(line_regions_with_atomic_data['note'] == "Fe 1",
line_regions_with_atomic_data['note'] == "Fe 2")]
smoothed_star_spectrum = ispec.convolve_spectrum(
star_spectrum, 2 * to_resolution)
line_regions_with_atomic_data = ispec.adjust_linemasks(
smoothed_star_spectrum,
line_regions_with_atomic_data,
max_margin=0.5)
#--- Fit the lines but do NOT cross-match with any atomic linelist since they already have that information
linemasks = ispec.fit_lines(line_regions_with_atomic_data, normalized_star_spectrum, star_continuum_model, \
atomic_linelist = None, \
max_atomic_wave_diff = 0.005, \
telluric_linelist = telluric_linelist, \
check_derivatives = False, \
vel_telluric = vel_telluric, discard_gaussian=False, \
smoothed_spectrum=None, \
discard_voigt=True, \
free_mu=True, crossmatch_with_mu=False, closest_match=False)
# Discard bad masks
flux_peak = normalized_star_spectrum['flux'][linemasks['peak']]
flux_base = normalized_star_spectrum['flux'][linemasks['base']]
flux_top = normalized_star_spectrum['flux'][linemasks['top']]
bad_mask = np.logical_or(
linemasks['wave_peak'] <= linemasks['wave_base'],
linemasks['wave_peak'] >= linemasks['wave_top'])
bad_mask = np.logical_or(bad_mask, flux_peak >= flux_base)
bad_mask = np.logical_or(bad_mask, flux_peak >= flux_top)
linemasks = linemasks[~bad_mask]
# Exclude lines with EW equal to zero
rejected_by_zero_ew = (linemasks['ew'] == 0)
linemasks = linemasks[~rejected_by_zero_ew]
# Exclude lines that may be affected by tellurics
rejected_by_telluric_line = (linemasks['telluric_wave_peak'] != 0)
linemasks = linemasks[~rejected_by_telluric_line]
linemasks = linemasks[:20]
if use_ares:
# Replace the measured equivalent widths by the ones computed by ARES
old_linemasks = linemasks.copy()
### Different rejection parameters (check ARES papers):
## - http://adsabs.harvard.edu/abs/2007A%26A...469..783S
## - http://adsabs.harvard.edu/abs/2015A%26A...577A..67S
#linemasks = ispec.update_ew_with_ares(normalized_star_spectrum, linemasks, rejt="0.995", tmp_dir=None, verbose=0)
#linemasks = ispec.update_ew_with_ares(normalized_star_spectrum, linemasks, rejt="3;5764,5766,6047,6052,6068,6076", tmp_dir=None, verbose=0)
snr = 50
linemasks = ispec.update_ew_with_ares(normalized_star_spectrum,
linemasks,
rejt="%s" % (snr),
tmp_dir=None,
verbose=0)
#--- Determining abundances by EW of the previously fitted lines ---------------
# Parameters
teff = 5777.0
logg = 4.44
MH = 0.00
alpha = 0.00
microturbulence_vel = 1.0
# Selected model amtosphere and solar abundances
#model = ispec_dir + "/input/atmospheres/MARCS/"
model = ispec_dir + "/input/atmospheres/MARCS.GES/"
#model = ispec_dir + "/input/atmospheres/MARCS.APOGEE/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.APOGEE/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Castelli/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Kurucz/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Kirby/"
if "ATLAS" in model:
solar_abundances_file = ispec_dir + "/input/abundances/Grevesse.1998/stdatom.dat"
else:
# MARCS
solar_abundances_file = ispec_dir + "/input/abundances/Grevesse.2007/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Asplund.2005/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Asplund.2009/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Anders.1989/stdatom.dat"
# Load model atmospheres
modeled_layers_pack = ispec.load_modeled_layers_pack(model)
# Load SPECTRUM abundances
solar_abundances = ispec.read_solar_abundances(solar_abundances_file)
# Validate parameters
if not ispec.valid_atmosphere_target(modeled_layers_pack, {
'teff': teff,
'logg': logg,
'MH': MH,
'alpha': alpha
}):
msg = "The specified effective temperature, gravity (log g) and metallicity [M/H] \
fall out of theatmospheric models."
print(msg)
# Prepare atmosphere model
atmosphere_layers = ispec.interpolate_atmosphere_layers(
modeled_layers_pack, {
'teff': teff,
'logg': logg,
'MH': MH,
'alpha': alpha
},
code=code)
spec_abund, normal_abund, x_over_h, x_over_fe = ispec.determine_abundances(atmosphere_layers, \
teff, logg, MH, alpha, linemasks, solar_abundances, microturbulence_vel = microturbulence_vel, \
verbose=1, code=code)
return linemasks, x_over_h
def correctBarycentricVelocity(spectrum, barycentric_velocity):
"""
Correct the spectrum to the barycentre
"""
return ispec.correct_velocity(spectrum, barycentric_velocity)
def test_determine_astrophysical_parameters_from_ew(self):
code = "moog"
use_ares = False
star_spectrum = ispec.read_spectrum(
ispec_dir + "/input/spectra/examples/NARVAL_Sun_Vesta-1.txt.gz")
#--- Radial Velocity determination with template -------------------------------
# - Read synthetic template
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Arcturus.372_926nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Sun.372_926nm/template.txt.gz")
template = ispec.read_spectrum(
ispec_dir +
"/input/spectra/templates/NARVAL.Sun.370_1048nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Synth.Sun.300_1100nm/template.txt.gz")
models, ccf = ispec.cross_correlate_with_template(star_spectrum, template, \
lower_velocity_limit=-200, upper_velocity_limit=200, \
velocity_step=1.0, fourier=False)
# Number of models represent the number of components
components = len(models)
# First component:
rv = np.round(models[0].mu(), 2) # km/s
rv_err = np.round(models[0].emu(), 2) # km/s
#--- Radial Velocity correction ------------------------------------------------
star_spectrum = ispec.correct_velocity(star_spectrum, rv)
#--- Telluric velocity shift determination from spectrum --------------------------
# - Telluric
telluric_linelist_file = ispec_dir + "/input/linelists/CCF/Synth.Tellurics.500_1100nm/mask.lst"
telluric_linelist = ispec.read_telluric_linelist(
telluric_linelist_file, minimum_depth=0.0)
models, ccf = ispec.cross_correlate_with_mask(star_spectrum, telluric_linelist, \
lower_velocity_limit=-100, upper_velocity_limit=100, \
velocity_step=0.5, mask_depth=0.01, \
fourier = False,
only_one_peak = True)
vel_telluric = np.round(models[0].mu(), 2) # km/s
vel_telluric_err = np.round(models[0].emu(), 2) # km/s
#--- Resolution degradation ----------------------------------------------------
# NOTE: The line selection was built based on a solar spectrum with R ~ 47,000 and GES/VALD atomic linelist.
from_resolution = 80000
to_resolution = 47000
star_spectrum = ispec.convolve_spectrum(star_spectrum, to_resolution,
from_resolution)
#--- Continuum fit -------------------------------------------------------------
model = "Splines" # "Polynomy"
degree = 2
nknots = None # Automatic: 1 spline every 5 nm
#from_resolution = 80000
from_resolution = to_resolution
# Strategy: Filter first median values and secondly MAXIMUMs in order to find the continuum
order = 'median+max'
median_wave_range = 0.05
max_wave_range = 1.0
star_continuum_model = ispec.fit_continuum(star_spectrum, from_resolution=from_resolution, \
nknots=nknots, degree=degree, \
median_wave_range=median_wave_range, \
max_wave_range=max_wave_range, \
model=model, order=order, \
automatic_strong_line_detection=True, \
strong_line_probability=0.5, \
use_errors_for_fitting=True)
#--- Normalize -------------------------------------------------------------
normalized_star_spectrum = ispec.normalize_spectrum(
star_spectrum,
star_continuum_model,
consider_continuum_errors=False)
# Use a fixed value because the spectrum is already normalized
star_continuum_model = ispec.fit_continuum(star_spectrum,
fixed_value=1.0,
model="Fixed value")
#telluric_linelist_file = ispec_dir + "/input/linelists/CCF/Synth.Tellurics.500_1100nm/mask.lst"
#telluric_linelist = ispec.read_telluric_linelist(telluric_linelist_file, minimum_depth=0.01)
#vel_telluric = 17.79 # km/s
#telluric_linelist = None
#vel_telluric = None
#--- Read lines and adjust them ------------------------------------------------
if code in ['width', 'moog']:
line_regions_with_atomic_data = ispec.read_line_regions(
ispec_dir +
"/input/regions/47000_GES/{}_ew_ispec_good_for_params_all_extended.txt"
.format(code))
#line_regions_with_atomic_data = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/{}_ew_ispec_good_for_params_all_extended.txt".format(code))
else:
line_regions_with_atomic_data = ispec.read_line_regions(
ispec_dir +
"/input/regions/47000_GES/{}_synth_good_for_params_all_extended.txt"
.format(code))
#line_regions_with_atomic_data = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/{}_synth_good_for_params_all_extended.txt".format(code))
# Select only iron lines
line_regions_with_atomic_data = line_regions_with_atomic_data[
np.logical_or(line_regions_with_atomic_data['note'] == "Fe 1",
line_regions_with_atomic_data['note'] == "Fe 2")]
smoothed_star_spectrum = ispec.convolve_spectrum(
star_spectrum, 2 * to_resolution)
line_regions_with_atomic_data = ispec.adjust_linemasks(
smoothed_star_spectrum,
line_regions_with_atomic_data,
max_margin=0.5)
#--- Fit the lines but do NOT cross-match with any atomic linelist since they already have that information
linemasks = ispec.fit_lines(line_regions_with_atomic_data, normalized_star_spectrum, star_continuum_model, \
atomic_linelist = None, \
max_atomic_wave_diff = 0.005, \
telluric_linelist = telluric_linelist, \
check_derivatives = False, \
vel_telluric = vel_telluric, discard_gaussian=False, \
smoothed_spectrum=None, \
discard_voigt=True, \
free_mu=True, crossmatch_with_mu=False, closest_match=False)
# Discard bad masks
flux_peak = normalized_star_spectrum['flux'][linemasks['peak']]
flux_base = normalized_star_spectrum['flux'][linemasks['base']]
flux_top = normalized_star_spectrum['flux'][linemasks['top']]
bad_mask = np.logical_or(
linemasks['wave_peak'] <= linemasks['wave_base'],
linemasks['wave_peak'] >= linemasks['wave_top'])
bad_mask = np.logical_or(bad_mask, flux_peak >= flux_base)
bad_mask = np.logical_or(bad_mask, flux_peak >= flux_top)
linemasks = linemasks[~bad_mask]
# Exclude lines with EW equal to zero
rejected_by_zero_ew = (linemasks['ew'] == 0)
linemasks = linemasks[~rejected_by_zero_ew]
# Exclude lines that may be affected by tellurics
rejected_by_telluric_line = (linemasks['telluric_wave_peak'] != 0)
linemasks = linemasks[~rejected_by_telluric_line]
if use_ares:
# Replace the measured equivalent widths by the ones computed by ARES
old_linemasks = linemasks.copy()
### Different rejection parameters (check ARES papers):
## - http://adsabs.harvard.edu/abs/2007A%26A...469..783S
## - http://adsabs.harvard.edu/abs/2015A%26A...577A..67S
#linemasks = ispec.update_ew_with_ares(normalized_star_spectrum, linemasks, rejt="0.995", tmp_dir=None, verbose=0)
#linemasks = ispec.update_ew_with_ares(normalized_star_spectrum, linemasks, rejt="3;5764,5766,6047,6052,6068,6076", tmp_dir=None, verbose=0)
snr = 50
linemasks = ispec.update_ew_with_ares(normalized_star_spectrum,
linemasks,
rejt="%s" % (snr),
tmp_dir=None,
verbose=0)
#--- Model spectra from EW --------------------------------------------------
# Parameters
initial_teff = 5777.0
initial_logg = 4.44
initial_MH = 0.00
initial_alpha = 0.00
initial_vmic = ispec.estimate_vmic(initial_teff, initial_logg,
initial_MH)
max_iterations = 10
# Selected model amtosphere, linelist and solar abundances
#model = ispec_dir + "/input/atmospheres/MARCS/"
model = ispec_dir + "/input/atmospheres/MARCS.GES/"
#model = ispec_dir + "/input/atmospheres/MARCS.APOGEE/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.APOGEE/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Castelli/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Kurucz/"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Kirby/"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/VALD.300_1100nm/atomic_lines.tsv"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/VALD.1100_2400nm/atomic_lines.tsv"
atomic_linelist_file = ispec_dir + "/input/linelists/transitions/GESv6_atom_hfs_iso.420_920nm/atomic_lines.tsv"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/GESv6_atom_nohfs_noiso.420_920nm/atomic_lines.tsv"
if "ATLAS" in model:
solar_abundances_file = ispec_dir + "/input/abundances/Grevesse.1998/stdatom.dat"
else:
# MARCS
solar_abundances_file = ispec_dir + "/input/abundances/Grevesse.2007/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Asplund.2005/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Asplund.2009/stdatom.dat"
#solar_abundances_file = ispec_dir + "/input/abundances/Anders.1989/stdatom.dat"
# Load model atmospheres
modeled_layers_pack = ispec.load_modeled_layers_pack(model)
# Load SPECTRUM abundances
solar_abundances = ispec.read_solar_abundances(solar_abundances_file)
# Validate parameters
if not ispec.valid_atmosphere_target(
modeled_layers_pack, {
'teff': initial_teff,
'logg': initial_logg,
'MH': initial_MH,
'alpha': initial_alpha
}):
msg = "The specified effective temperature, gravity (log g) and metallicity [M/H] \
fall out of theatmospheric models."
print(msg)
# Reduced equivalent width
# Filter too weak/strong lines
# * Criteria presented in paper of GALA
#efilter = np.logical_and(linemasks['ewr'] >= -5.8, linemasks['ewr'] <= -4.65)
efilter = np.logical_and(linemasks['ewr'] >= -6.0,
linemasks['ewr'] <= -4.3)
# Filter high excitation potential lines
# * Criteria from Eric J. Bubar "Equivalent Width Abundance Analysis In Moog"
efilter = np.logical_and(efilter, linemasks['lower_state_eV'] <= 5.0)
efilter = np.logical_and(efilter, linemasks['lower_state_eV'] >= 0.5)
## Filter also bad fits
efilter = np.logical_and(efilter, linemasks['rms'] < 1.00)
# no flux
noflux = normalized_star_spectrum['flux'][linemasks['peak']] < 1.0e-10
efilter = np.logical_and(efilter, np.logical_not(noflux))
unfitted = linemasks['fwhm'] == 0
efilter = np.logical_and(efilter, np.logical_not(unfitted))
results = ispec.model_spectrum_from_ew(linemasks[efilter], modeled_layers_pack, \
solar_abundances, initial_teff, initial_logg, initial_MH, initial_alpha, initial_vmic, \
free_params=["teff", "logg", "vmic"], \
adjust_model_metalicity=True, \
max_iterations=max_iterations, \
enhance_abundances=True, \
#outliers_detection = "robust", \
#outliers_weight_limit = 0.90, \
outliers_detection = "sigma_clipping", \
#sigma_level = 3, \
tmp_dir = None, \
code=code)
params, errors, status, x_over_h, selected_x_over_h, fitted_lines_params, used_linemasks = results
expected_params = {
'teff': 5825.366401775263,
'logg': 4.3929210834771535,
'MH': 0.03500000000000014,
'alpha': 0.0,
'vmic': 1.1670939448402673
}
for k, v in list(expected_params.items()):
self.assertAlmostEqual(params[k], v)
expected_errors = {
'teff': 59.030776466850426,
'logg': 0.08775700534919817,
'MH': 0.0606561589029185,
'alpha': 0.0,
'vmic': 0.03900548810240552
}
for k, v in list(expected_errors.items()):
self.assertAlmostEqual(errors[k], v)
#--- Cleaning telluric regions -------------------------------------------
if options.verbose: print "Cleaning telluric regions ..."
min_vel = -30.0
max_vel = +30.0
# Only the 25% of the deepest ones:
dfilter = telluric_linelist['depth'] > np.percentile(telluric_linelist['depth'], 75)
tfilter = ispec.create_filter_for_regions_affected_by_tellurics(smoothed_star_spectrum['waveobs'], \
telluric_linelist[dfilter], min_velocity=-tel_rv+min_vel, \
max_velocity=-tel_rv+max_vel)
clean_spectrum = smoothed_star_spectrum[~tfilter]
#-----
#--- Correcting telluric shift -------------------------------------------
if options.verbose: print "Correcting RV shift calculated from telluric lines ..."
corrected_spectrum = ispec.correct_velocity(clean_spectrum, tel_rv)
#-----
#--- Correcting barycentric velocity -------------------------------------------
if options.verbose: print "Correcting barycentric velocity ..."
corrected_spectrum = ispec.correct_velocity(corrected_spectrum, -barycentric_vel)
#-----
#--- Calculating cross-correlation for RV measurements ------------------------
if options.template :
if options.verbose: print "Calculating radial velocity by cross-correlation with template spectrum ..."
models, ccf = ispec.cross_correlate_with_template(corrected_spectrum, templatespectrum, \
lower_velocity_limit=-100, upper_velocity_limit=100, \
velocity_step=velocity_step, fourier=False)
else :
def test_fit_lines_already_crossmatched_with_atomic_data_and_determine_ew(self):
use_ares = False
star_spectrum = ispec.read_spectrum(ispec_dir + "/input/spectra/examples/NARVAL_Sun_Vesta-1.txt.gz")
#--- Radial Velocity determination with template -------------------------------
# - Read synthetic template
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Arcturus.372_926nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Sun.372_926nm/template.txt.gz")
template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/NARVAL.Sun.370_1048nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Synth.Sun.300_1100nm/template.txt.gz")
models, ccf = ispec.cross_correlate_with_template(star_spectrum, template, \
lower_velocity_limit=-200, upper_velocity_limit=200, \
velocity_step=1.0, fourier=False)
# Number of models represent the number of components
components = len(models)
# First component:
rv = np.round(models[0].mu(), 2) # km/s
rv_err = np.round(models[0].emu(), 2) # km/s
#--- Radial Velocity correction ------------------------------------------------
star_spectrum = ispec.correct_velocity(star_spectrum, rv)
#--- Telluric velocity shift determination from spectrum --------------------------
# - Telluric
telluric_linelist_file = ispec_dir + "/input/linelists/CCF/Synth.Tellurics.500_1100nm/mask.lst"
telluric_linelist = ispec.read_telluric_linelist(telluric_linelist_file, minimum_depth=0.0)
models, ccf = ispec.cross_correlate_with_mask(star_spectrum, telluric_linelist, \
lower_velocity_limit=-100, upper_velocity_limit=100, \
velocity_step=0.5, mask_depth=0.01, \
fourier = False,
only_one_peak = True)
vel_telluric = np.round(models[0].mu(), 2) # km/s
vel_telluric_err = np.round(models[0].emu(), 2) # km/s
#--- Resolution degradation ----------------------------------------------------
# NOTE: The line selection was built based on a solar spectrum with R ~ 47,000 and GES/VALD atomic linelist.
from_resolution = 80000
to_resolution = 47000
star_spectrum = ispec.convolve_spectrum(star_spectrum, to_resolution, from_resolution)
#--- Continuum fit -------------------------------------------------------------
model = "Splines" # "Polynomy"
degree = 2
nknots = None # Automatic: 1 spline every 5 nm
from_resolution = to_resolution
# Strategy: Filter first median values and secondly MAXIMUMs in order to find the continuum
order='median+max'
median_wave_range=0.05
max_wave_range=1.0
star_continuum_model = ispec.fit_continuum(star_spectrum, from_resolution=from_resolution, \
nknots=nknots, degree=degree, \
median_wave_range=median_wave_range, \
max_wave_range=max_wave_range, \
model=model, order=order, \
automatic_strong_line_detection=True, \
strong_line_probability=0.5, \
use_errors_for_fitting=True)
#--- Normalize -------------------------------------------------------------
normalized_star_spectrum = ispec.normalize_spectrum(star_spectrum, star_continuum_model, consider_continuum_errors=False)
# Use a fixed value because the spectrum is already normalized
star_continuum_model = ispec.fit_continuum(star_spectrum, fixed_value=1.0, model="Fixed value")
#--- Read lines with atomic data ------------------------------------------------
line_regions_with_atomic_data = ispec.read_line_regions(ispec_dir + "/input/regions/47000_GES/moog_synth_good_for_params_all_extended.txt")
#line_regions_with_atomic_data = ispec.read_line_regions(ispec_dir + "/input/regions/47000_GES/width_synth_good_for_params_all_extended.txt")
#line_regions_with_atomic_data = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/moog_synth_good_for_params_all_extended.txt")
#line_regions_with_atomic_data = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/width_synth_good_for_params_all_extended.txt")
smoothed_star_spectrum = ispec.convolve_spectrum(star_spectrum, 2*to_resolution)
line_regions_with_atomic_data = ispec.adjust_linemasks(smoothed_star_spectrum, line_regions_with_atomic_data, max_margin=0.5)
#telluric_linelist_file = ispec_dir + "/input/linelists/CCF/Synth.Tellurics.500_1100nm/mask.lst"
#telluric_linelist = ispec.read_telluric_linelist(telluric_linelist_file, minimum_depth=0.01)
#vel_telluric = 17.79 # km/s
#telluric_linelist = None
#vel_telluric = None
#--- Fit the lines but do NOT cross-match with any atomic linelist since they already have that information
linemasks = ispec.fit_lines(line_regions_with_atomic_data, normalized_star_spectrum, star_continuum_model, \
atomic_linelist = None, \
max_atomic_wave_diff = 0.005, \
telluric_linelist = telluric_linelist, \
check_derivatives = False, \
vel_telluric = vel_telluric, discard_gaussian=False, \
smoothed_spectrum=None, \
discard_voigt=True, \
free_mu=True, crossmatch_with_mu=False, closest_match=False)
# Discard bad masks
flux_peak = normalized_star_spectrum['flux'][linemasks['peak']]
flux_base = normalized_star_spectrum['flux'][linemasks['base']]
flux_top = normalized_star_spectrum['flux'][linemasks['top']]
bad_mask = np.logical_or(linemasks['wave_peak'] <= linemasks['wave_base'], linemasks['wave_peak'] >= linemasks['wave_top'])
bad_mask = np.logical_or(bad_mask, flux_peak >= flux_base)
bad_mask = np.logical_or(bad_mask, flux_peak >= flux_top)
linemasks = linemasks[~bad_mask]
# Exclude lines with EW equal to zero
rejected_by_zero_ew = (linemasks['ew'] == 0)
linemasks = linemasks[~rejected_by_zero_ew]
# Exclude lines that may be affected by tellurics
rejected_by_telluric_line = (linemasks['telluric_wave_peak'] != 0)
linemasks = linemasks[~rejected_by_telluric_line]
if use_ares:
# Replace the measured equivalent widths by the ones computed by ARES
old_linemasks = linemasks.copy()
### Different rejection parameters (check ARES papers):
## - http://adsabs.harvard.edu/abs/2007A%26A...469..783S
## - http://adsabs.harvard.edu/abs/2015A%26A...577A..67S
#linemasks = ispec.update_ew_with_ares(normalized_star_spectrum, linemasks, rejt="0.995", tmp_dir=None, verbose=0)
#linemasks = ispec.update_ew_with_ares(normalized_star_spectrum, linemasks, rejt="3;5764,5766,6047,6052,6068,6076", tmp_dir=None, verbose=0)
snr = 50
linemasks = ispec.update_ew_with_ares(normalized_star_spectrum, linemasks, rejt="%s" % (snr), tmp_dir=None, verbose=0)
self.assertEqual(len(linemasks), 281)
self.assertAlmostEqual(linemasks['ew'][0], 68.62459244466727)
self.assertAlmostEqual(linemasks['ew'][-3], 46.23135207295078)
self.assertEqual(linemasks['element'][0], 'Fe 1')
self.assertEqual(linemasks['element'][-3], 'Si 1')
self.assertAlmostEqual(linemasks['loggf'][0], -1.028)
self.assertAlmostEqual(linemasks['loggf'][-3], -1.062)
def test_fit_lines_determine_ew_and_crossmatch_with_atomic_data(self):
use_ares = False
star_spectrum = ispec.read_spectrum(ispec_dir + "/input/spectra/examples/NARVAL_Sun_Vesta-1.txt.gz")
#--- Radial Velocity determination with template -------------------------------
# - Read synthetic template
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Arcturus.372_926nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Sun.372_926nm/template.txt.gz")
template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/NARVAL.Sun.370_1048nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Synth.Sun.300_1100nm/template.txt.gz")
models, ccf = ispec.cross_correlate_with_template(star_spectrum, template, \
lower_velocity_limit=-200, upper_velocity_limit=200, \
velocity_step=1.0, fourier=False)
# Number of models represent the number of components
components = len(models)
# First component:
rv = np.round(models[0].mu(), 2) # km/s
rv_err = np.round(models[0].emu(), 2) # km/s
#--- Radial Velocity correction ------------------------------------------------
star_spectrum = ispec.correct_velocity(star_spectrum, rv)
#--- Telluric velocity shift determination from spectrum --------------------------
# - Telluric
telluric_linelist_file = ispec_dir + "/input/linelists/CCF/Synth.Tellurics.500_1100nm/mask.lst"
telluric_linelist = ispec.read_telluric_linelist(telluric_linelist_file, minimum_depth=0.0)
models, ccf = ispec.cross_correlate_with_mask(star_spectrum, telluric_linelist, \
lower_velocity_limit=-100, upper_velocity_limit=100, \
velocity_step=0.5, mask_depth=0.01, \
fourier = False,
only_one_peak = True)
vel_telluric = np.round(models[0].mu(), 2) # km/s
vel_telluric_err = np.round(models[0].emu(), 2) # km/s
#--- Resolution degradation ----------------------------------------------------
# NOTE: The line selection was built based on a solar spectrum with R ~ 47,000 and GES/VALD atomic linelist.
from_resolution = 80000
to_resolution = 47000
star_spectrum = ispec.convolve_spectrum(star_spectrum, to_resolution, from_resolution)
#--- Continuum fit -------------------------------------------------------------
model = "Splines" # "Polynomy"
degree = 2
nknots = None # Automatic: 1 spline every 5 nm
from_resolution = 80000
# Strategy: Filter first median values and secondly MAXIMUMs in order to find the continuum
order='median+max'
median_wave_range=0.05
max_wave_range=1.0
star_continuum_model = ispec.fit_continuum(star_spectrum, from_resolution=from_resolution, \
nknots=nknots, degree=degree, \
median_wave_range=median_wave_range, \
max_wave_range=max_wave_range, \
model=model, order=order, \
automatic_strong_line_detection=True, \
strong_line_probability=0.5, \
use_errors_for_fitting=True)
#--- Normalize -------------------------------------------------------------
normalized_star_spectrum = ispec.normalize_spectrum(star_spectrum, star_continuum_model, consider_continuum_errors=False)
# Use a fixed value because the spectrum is already normalized
star_continuum_model = ispec.fit_continuum(star_spectrum, fixed_value=1.0, model="Fixed value")
#--- Fit lines -----------------------------------------------------------------
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/VALD.300_1100nm/atomic_lines.tsv"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/VALD.1100_2400nm/atomic_lines.tsv"
atomic_linelist_file = ispec_dir + "/input/linelists/transitions/GESv6_atom_hfs_iso.420_920nm/atomic_lines.tsv"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/GESv6_atom_nohfs_noiso.420_920nm/atomic_lines.tsv"
# Read
atomic_linelist = ispec.read_atomic_linelist(atomic_linelist_file, wave_base=np.min(star_spectrum['waveobs']), wave_top=np.max(star_spectrum['waveobs']))
atomic_linelist = atomic_linelist[atomic_linelist['theoretical_depth'] >= 0.01] # Select lines that have some minimal contribution in the sun
#telluric_linelist_file = ispec_dir + "/input/linelists/CCF/Synth.Tellurics.500_1100nm/mask.lst"
#telluric_linelist = ispec.read_telluric_linelist(telluric_linelist_file, minimum_depth=0.01)
#vel_telluric = 17.79 # km/s
#telluric_linelist = None
#vel_telluric = None
line_regions = ispec.read_line_regions(ispec_dir + "/input/regions/47000_GES/moog_synth_good_for_params_all.txt")
#line_regions = ispec.read_line_regions(ispec_dir + "/input/regions/47000_GES/width_synth_good_for_params_all.txt")
#line_regions = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/moog_synth_good_for_params_all.txt")
#line_regions = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/width_synth_good_for_params_all.txt")
line_regions = ispec.adjust_linemasks(normalized_star_spectrum, line_regions, max_margin=0.5)
linemasks = ispec.fit_lines(line_regions, normalized_star_spectrum, star_continuum_model, \
atomic_linelist = atomic_linelist, \
#max_atomic_wave_diff = 0.005, \
max_atomic_wave_diff = 0.00, \
telluric_linelist = telluric_linelist, \
smoothed_spectrum = None, \
check_derivatives = False, \
vel_telluric = vel_telluric, discard_gaussian=False, \
discard_voigt=True, \
free_mu=True, crossmatch_with_mu=False, closest_match=False)
# Discard lines that are not cross matched with the same original element stored in the note
linemasks = linemasks[linemasks['element'] == line_regions['note']]
# Exclude lines that have not been successfully cross matched with the atomic data
# because we cannot calculate the chemical abundance (it will crash the corresponding routines)
rejected_by_atomic_line_not_found = (linemasks['wave_nm'] == 0)
linemasks = linemasks[~rejected_by_atomic_line_not_found]
# Exclude lines with EW equal to zero
rejected_by_zero_ew = (linemasks['ew'] == 0)
linemasks = linemasks[~rejected_by_zero_ew]
# Exclude lines that may be affected by tellurics
rejected_by_telluric_line = (linemasks['telluric_wave_peak'] != 0)
linemasks = linemasks[~rejected_by_telluric_line]
if use_ares:
# Replace the measured equivalent widths by the ones computed by ARES
old_linemasks = linemasks.copy()
### Different rejection parameters (check ARES papers):
## - http://adsabs.harvard.edu/abs/2007A%26A...469..783S
## - http://adsabs.harvard.edu/abs/2015A%26A...577A..67S
#linemasks = ispec.update_ew_with_ares(normalized_star_spectrum, linemasks, rejt="0.995", tmp_dir=None, verbose=0)
#linemasks = ispec.update_ew_with_ares(normalized_star_spectrum, linemasks, rejt="3;5764,5766,6047,6052,6068,6076", tmp_dir=None, verbose=0)
snr = 50
linemasks = ispec.update_ew_with_ares(normalized_star_spectrum, linemasks, rejt="%s" % (snr), tmp_dir=None, verbose=0)
self.assertEqual(len(linemasks), 281)
self.assertAlmostEqual(linemasks['ew'][0], 68.48284589709996)
self.assertAlmostEqual(linemasks['ew'][-3], 46.17583047097995)
self.assertEqual(linemasks['element'][0], 'Fe 1')
self.assertEqual(linemasks['element'][-3], 'Si 1')
self.assertAlmostEqual(linemasks['loggf'][0], -1.028)
self.assertAlmostEqual(linemasks['loggf'][-3], -1.062)
def test_find_linemasks(self):
star_spectrum = ispec.read_spectrum(
ispec_dir + "/input/spectra/examples/NARVAL_Sun_Vesta-1.txt.gz")
#--- Radial Velocity determination with template -------------------------------
# - Read synthetic template
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Arcturus.372_926nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Atlas.Sun.372_926nm/template.txt.gz")
template = ispec.read_spectrum(
ispec_dir +
"/input/spectra/templates/NARVAL.Sun.370_1048nm/template.txt.gz")
#template = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/Synth.Sun.300_1100nm/template.txt.gz")
models, ccf = ispec.cross_correlate_with_template(star_spectrum, template, \
lower_velocity_limit=-200, upper_velocity_limit=200, \
velocity_step=1.0, fourier=False)
# Number of models represent the number of components
components = len(models)
# First component:
rv = np.round(models[0].mu(), 2) # km/s
rv_err = np.round(models[0].emu(), 2) # km/s
#--- Radial Velocity correction ------------------------------------------------
star_spectrum = ispec.correct_velocity(star_spectrum, rv)
#--- Telluric velocity shift determination from spectrum --------------------------
# - Telluric
telluric_linelist_file = ispec_dir + "/input/linelists/CCF/Synth.Tellurics.500_1100nm/mask.lst"
telluric_linelist = ispec.read_telluric_linelist(
telluric_linelist_file, minimum_depth=0.0)
models, ccf = ispec.cross_correlate_with_mask(star_spectrum, telluric_linelist, \
lower_velocity_limit=-100, upper_velocity_limit=100, \
velocity_step=0.5, mask_depth=0.01, \
fourier = False,
only_one_peak = True)
vel_telluric = np.round(models[0].mu(), 2) # km/s
vel_telluric_err = np.round(models[0].emu(), 2) # km/s
#--- Continuum fit -------------------------------------------------------------
model = "Splines" # "Polynomy"
degree = 2
nknots = None # Automatic: 1 spline every 5 nm
from_resolution = 80000
# Strategy: Filter first median values and secondly MAXIMUMs in order to find the continuum
order = 'median+max'
median_wave_range = 0.05
max_wave_range = 1.0
star_continuum_model = ispec.fit_continuum(star_spectrum, from_resolution=from_resolution, \
nknots=nknots, degree=degree, \
median_wave_range=median_wave_range, \
max_wave_range=max_wave_range, \
model=model, order=order, \
automatic_strong_line_detection=True, \
strong_line_probability=0.5, \
use_errors_for_fitting=True)
#--- Find linemasks ------------------------------------------------------------
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/VALD.300_1100nm/atomic_lines.tsv"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/VALD.1100_2400nm/atomic_lines.tsv"
atomic_linelist_file = ispec_dir + "/input/linelists/transitions/GESv6_atom_hfs_iso.420_920nm/atomic_lines.tsv"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/GESv6_atom_nohfs_noiso.420_920nm/atomic_lines.tsv"
telluric_linelist_file = ispec_dir + "/input/linelists/CCF/Synth.Tellurics.500_1100nm/mask.lst"
# Read
atomic_linelist = ispec.read_atomic_linelist(
atomic_linelist_file,
wave_base=np.min(star_spectrum['waveobs']),
wave_top=np.max(star_spectrum['waveobs']))
atomic_linelist = atomic_linelist[
atomic_linelist['theoretical_depth'] >=
0.01] # Select lines that have some minimal contribution in the sun
#telluric_linelist = ispec.read_telluric_linelist(telluric_linelist_file, minimum_depth=0.01)
#vel_telluric = 17.79 # km/s
#telluric_linelist = None
#vel_telluric = None
resolution = 80000
smoothed_star_spectrum = ispec.convolve_spectrum(
star_spectrum, resolution)
min_depth = 0.05
max_depth = 1.00
star_linemasks = ispec.find_linemasks(star_spectrum, star_continuum_model, \
atomic_linelist=atomic_linelist, \
max_atomic_wave_diff = 0.005, \
telluric_linelist=telluric_linelist, \
vel_telluric=vel_telluric, \
minimum_depth=min_depth, maximum_depth=max_depth, \
smoothed_spectrum=smoothed_star_spectrum, \
check_derivatives=False, \
discard_gaussian=False, discard_voigt=True, \
closest_match=False)
# Exclude lines that have not been successfully cross matched with the atomic data
# because we cannot calculate the chemical abundance (it will crash the corresponding routines)
rejected_by_atomic_line_not_found = (star_linemasks['wave_nm'] == 0)
star_linemasks = star_linemasks[~rejected_by_atomic_line_not_found]
# Exclude lines with EW equal to zero
rejected_by_zero_ew = (star_linemasks['ew'] == 0)
star_linemasks = star_linemasks[~rejected_by_zero_ew]
# Select only iron lines
iron = star_linemasks['element'] == "Fe 1"
iron = np.logical_or(iron, star_linemasks['element'] == "Fe 2")
iron_star_linemasks = star_linemasks[iron]
self.assertEqual(len(star_linemasks), 1732)
self.assertEqual(len(iron_star_linemasks), 883)
self.assertAlmostEqual(iron_star_linemasks['ew'][0], 15.82970157775808)
self.assertAlmostEqual(iron_star_linemasks['ew'][-1],
15.545342323635188)
self.assertAlmostEqual(iron_star_linemasks['ew_err'][0],
1.1187509030236669)
self.assertAlmostEqual(iron_star_linemasks['ew_err'][-1],
1.3221015426240295)
tmp_filename = tempfile.mktemp()
# Write regions with masks limits, cross-matched atomic data and fit data
ispec.write_line_regions(star_linemasks, tmp_filename, extended=True)
recover_star_linemasks = ispec.read_line_regions(tmp_filename)
os.remove(tmp_filename)
# Write regions with masks limits and cross-matched atomic data (fit data fields are zeroed)
zeroed_star_linemasks = ispec.reset_fitted_data_fields(star_linemasks)
np.testing.assert_almost_equal(star_linemasks['wave_nm'],
recover_star_linemasks['wave_nm'])
np.testing.assert_almost_equal(star_linemasks['ew'],
recover_star_linemasks['ew'],
decimal=1)
np.testing.assert_almost_equal(star_linemasks['wave_base'],
recover_star_linemasks['wave_base'],
decimal=4)
np.testing.assert_almost_equal(star_linemasks['wave_top'],
recover_star_linemasks['wave_top'],
decimal=4)
np.testing.assert_almost_equal(star_linemasks['wave_peak'],
recover_star_linemasks['wave_peak'],
decimal=4)
self.assertTrue(np.all(zeroed_star_linemasks['ew'] == 0))
rv_err = np.round(models[0].emu(), 3) # km/s
print components, rv, rv_err
'''
suntemplate = ispec.read_spectrum(ispec_dir + "/input/spectra/templates/NARVAL.Sun.370_1048nm/template.txt.gz")
smoothed_suntemplate = ispec.convolve_spectrum(suntemplate, resolution)
models2, ccf2 = ispec.cross_correlate_with_template(smoothed_star_spectrum, smoothed_suntemplate, \
lower_velocity_limit=-50, upper_velocity_limit=50, \
velocity_step=0.1, fourier=False)
components2 = len(models2)
# First component:
rv2 = np.round(models2[0].mu(), 2) # km/s
rv_err2 = np.round(models2[0].emu(), 2) # km/s
print components2, rv2, rv_err2
'''
smoothed_star_spectrum = ispec.correct_velocity(smoothed_star_spectrum, rv)
velocity = ccf['x']
xcorr = ccf['y']
xcorr_err = ccf['err']
#ispec.plot_spectra([smoothed_star_spectrum, smoothed_suntemplate])
plt.plot(velocity, xcorr)
plt.show()
def correct_radial_velocity(star_spectrum, rv):
''' correct radial velocity'''
logging.info("Radial velocity correction...")
#rv = -96.40 # km/s
return ispec.correct_velocity(star_spectrum, rv)