def normaliseContinuum(spec):
"""
Based on example.py
normalize_whole_spectrum_strategy1_ignoring_prefixed_strong_lines function
"""
model = 'Splines'
degree = 2
nknots = None
from_resolution = INSTRUMENT[args.instrument]['RESOLUTION']
# continuum fit
order = 'median+max'
median_wave_range = 0.01
max_wave_range = 1.0
strong_lines = ispec.read_line_regions(strongLines)
continuum_model = ispec.fit_continuum(spec, \
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)
# continuum normalisation
spec_norm = ispec.normalize_spectrum(spec, \
continuum_model, \
consider_continuum_errors=False)
return spec_norm
def normalize_whole_spectrum(spec_id, med_wave, max_wave):
"""
Use the whole spectrum, strategy 'median+max'
"""
star_spectrum = ispec.read_spectrum(spec_id)
#--- Continuum fit -------------------------------------------------------------
model = "Splines" # "Polynomy"
degree = 2
nknots = None # Automatic: 1 spline every 5 nm
from_resolution = 47000
# Strategy: Filter first median values and secondly MAXIMUMs in order to find the continuum
order='median+max'
median_wave_range=med_wave
max_wave_range=max_wave
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)
#--- Continuum normalization ---------------------------------------------------
logging.info("Continuum normalization...")
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")
ispec.write_spectrum(normalized_star_spectrum, spec_id)
def test_normalize_spectrum_in_segments(self):
"""
Fit continuum in each segment independently, strategy 'median+max'
"""
star_spectrum = ispec.read_spectrum(
ispec_dir + "/input/spectra/examples/NARVAL_Sun_Vesta-1.txt.gz")
#--- Continuum fit -------------------------------------------------------------
model = "Splines" # "Polynomy"
degree = 2
nknots = 1
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
segments = ispec.read_segment_regions(
ispec_dir + "/input/regions/fe_lines_segments.txt")
star_continuum_model = ispec.fit_continuum(star_spectrum, from_resolution=from_resolution, \
independent_regions=segments, 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)
#--- Continuum normalization ---------------------------------------------------
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")
np.testing.assert_equal(star_spectrum['waveobs'],
normalized_star_spectrum['waveobs'])
self.assertAlmostEqual(star_spectrum['flux'][0], 0.67077)
self.assertAlmostEqual(star_spectrum['flux'][-1], 2.2169)
self.assertAlmostEqual(star_spectrum['err'][0], 0.0021259)
self.assertAlmostEqual(star_spectrum['err'][-1], 0.0043878)
self.assertAlmostEqual(normalized_star_spectrum['flux'][0], 1.0)
self.assertAlmostEqual(normalized_star_spectrum['flux'][-1], 1.0)
self.assertAlmostEqual(normalized_star_spectrum['err'][0], 0.0)
self.assertAlmostEqual(normalized_star_spectrum['err'][-1], 0.0)
self.assertAlmostEqual(normalized_star_spectrum['flux'][11],
0.9928764307623508)
self.assertAlmostEqual(normalized_star_spectrum['flux'][58288],
0.960387654522309)
self.assertAlmostEqual(normalized_star_spectrum['err'][11],
0.0028468129511384785)
self.assertAlmostEqual(normalized_star_spectrum['err'][58288],
0.0019771951824093786)
self.assertEqual(
len(np.where(normalized_star_spectrum['flux'] != 1.)[0]), 33722)
self.assertTrue(
np.all(star_continuum_model(star_spectrum['waveobs']) == 1))
def test_normalize_spectrum_using_continuum_regions(self):
"""
Consider only continuum regions for the fit, strategy 'median+max'
"""
star_spectrum = ispec.read_spectrum(
ispec_dir + "/input/spectra/examples/NARVAL_Sun_Vesta-1.txt.gz")
#--- 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
continuum_regions = ispec.read_continuum_regions(
ispec_dir + "/input/regions/fe_lines_continuum.txt")
star_continuum_model = ispec.fit_continuum(star_spectrum, from_resolution=from_resolution, \
continuum_regions=continuum_regions, 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)
#--- Continuum normalization ---------------------------------------------------
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")
np.testing.assert_equal(star_spectrum['waveobs'],
normalized_star_spectrum['waveobs'])
self.assertAlmostEqual(star_spectrum['flux'][0], 0.67077)
self.assertAlmostEqual(star_spectrum['flux'][-1], 2.2169)
self.assertAlmostEqual(star_spectrum['err'][0], 0.0021259)
self.assertAlmostEqual(star_spectrum['err'][-1], 0.0043878)
self.assertAlmostEqual(normalized_star_spectrum['flux'][0],
0.7990890725070141)
self.assertAlmostEqual(normalized_star_spectrum['flux'][-1],
0.9887281323707806)
self.assertAlmostEqual(normalized_star_spectrum['err'][0],
0.0025325871151701197)
self.assertAlmostEqual(normalized_star_spectrum['err'][-1],
0.001956940457042046)
self.assertTrue(
np.all(star_continuum_model(star_spectrum['waveobs']) == 1))
def test_normalize_whole_spectrum_ignoring_prefixed_strong_lines(self):
"""
Use the whole spectrum but ignoring some strong lines, strategy 'median+max'
"""
star_spectrum = ispec.read_spectrum(
ispec_dir + "/input/spectra/examples/NARVAL_Sun_Vesta-1.txt.gz")
#--- 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
strong_lines = ispec.read_line_regions(
ispec_dir + "/input/regions/strong_lines/absorption_lines.txt")
star_continuum_model = ispec.fit_continuum(star_spectrum, from_resolution=from_resolution, \
ignore=strong_lines, \
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)
#--- Continuum normalization ---------------------------------------------------
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")
np.testing.assert_equal(star_spectrum['waveobs'],
normalized_star_spectrum['waveobs'])
self.assertAlmostEqual(star_spectrum['flux'][0], 0.67077)
self.assertAlmostEqual(star_spectrum['flux'][-1], 2.2169)
self.assertAlmostEqual(star_spectrum['err'][0], 0.0021259)
self.assertAlmostEqual(star_spectrum['err'][-1], 0.0043878)
self.assertAlmostEqual(normalized_star_spectrum['flux'][0],
0.8005567874185445)
self.assertAlmostEqual(normalized_star_spectrum['flux'][-1],
0.9874528805693361)
self.assertAlmostEqual(normalized_star_spectrum['err'][0],
0.0025372388067043607)
self.assertAlmostEqual(normalized_star_spectrum['err'][-1],
0.0019544164145257493)
self.assertTrue(
np.all(star_continuum_model(star_spectrum['waveobs']) == 1))
def test_normalize_whole_spectrum(self):
"""
Use the whole spectrum, strategy 'median+max'
"""
star_spectrum = ispec.read_spectrum(
ispec_dir + "/input/spectra/examples/NARVAL_Sun_Vesta-1.txt.gz")
#--- 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)
#--- Continuum normalization ---------------------------------------------------
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")
np.testing.assert_equal(star_spectrum['waveobs'],
normalized_star_spectrum['waveobs'])
self.assertAlmostEqual(star_spectrum['flux'][0], 0.67077)
self.assertAlmostEqual(star_spectrum['flux'][-1], 2.2169)
self.assertAlmostEqual(star_spectrum['err'][0], 0.0021259)
self.assertAlmostEqual(star_spectrum['err'][-1], 0.0043878)
self.assertAlmostEqual(normalized_star_spectrum['flux'][0],
0.8052457389161867)
self.assertAlmostEqual(normalized_star_spectrum['flux'][-1],
0.9895767577073404)
self.assertAlmostEqual(normalized_star_spectrum['err'][0],
0.0025520997008839415)
self.assertAlmostEqual(normalized_star_spectrum['err'][-1],
0.0019586200989978207)
self.assertTrue(
np.all(star_continuum_model(star_spectrum['waveobs']) == 1))
def test_normalize_whole_spectrum_with_template(self):
"""
Use a template to normalize the whole spectrum
"""
star_spectrum = ispec.read_spectrum(
ispec_dir + "/input/spectra/examples/NARVAL_Sun_Vesta-1.txt.gz")
synth_spectrum = ispec.read_spectrum(
ispec_dir +
"/input/spectra/templates/Synth.Sun.300_1100nm/template.txt.gz")
#--- Continuum fit -------------------------------------------------------------
model = "Template"
nknots = None # Automatic: 1 spline every 5 nm (in this case, used to apply a gaussian filter)
from_resolution = 80000
median_wave_range = 5.0
#strong_lines = ispec.read_line_regions(ispec_dir + "/input/regions/strong_lines/absorption_lines.txt")
strong_lines = ispec.read_line_regions(
ispec_dir + "/input/regions/relevant/relevant_line_masks.txt")
#strong_lines = None
star_continuum_model = ispec.fit_continuum(star_spectrum, from_resolution=from_resolution, \
ignore=strong_lines, \
nknots=nknots, \
median_wave_range=median_wave_range, \
model=model, \
template=synth_spectrum)
#--- Continuum normalization ---------------------------------------------------
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")
np.testing.assert_equal(star_spectrum['waveobs'],
normalized_star_spectrum['waveobs'])
self.assertAlmostEqual(star_spectrum['flux'][0], 0.67077)
self.assertAlmostEqual(star_spectrum['flux'][-1], 2.2169)
self.assertAlmostEqual(star_spectrum['err'][0], 0.0021259)
self.assertAlmostEqual(star_spectrum['err'][-1], 0.0043878)
self.assertAlmostEqual(normalized_star_spectrum['flux'][0],
0.7964201448878107)
self.assertAlmostEqual(normalized_star_spectrum['flux'][-1],
0.997168332612696)
self.assertAlmostEqual(normalized_star_spectrum['err'][0],
0.002524128368914824)
self.assertAlmostEqual(normalized_star_spectrum['err'][-1],
0.0019736457259407225)
self.assertTrue(
np.all(star_continuum_model(star_spectrum['waveobs']) == 1))
def normalize_spectrum(star_spectrum,
res=80000,
model="Splines",
degree=2,
nknots=None):
'''
Fit continuum ignoring strong lines and using fe lines template,
strategy 'median+max'
####
#### ASSUMING DEFAULT VALUES FOR:
#### RESOLUTION, MODEL FOR CONTINUUM, DEGREE OF MODEL, NKNOTS!!!!
#### TAKE CARE!!!!
####
returns normalized star spectrum object and continumm model
'''
from_resolution = res #define 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
# read continuum regions from Fe lines and strong lines
continuum_regions = ispec.read_continuum_regions(\
ispec_dir + "/input/regions/fe_lines_continuum.txt")
strong_lines = ispec.read_line_regions(\
ispec_dir + "/input/regions/strong_lines/absorption_lines.txt")
star_continuum_model = ispec.fit_continuum(star_spectrum,\
from_resolution=from_resolution, ignore=strong_lines,\
continuum_regions=continuum_regions, 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)
#--- Continuum normalization -----------------------------------------------
logging.info("Continuum normalization...")
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
#you need continuum model to be able to synt or interpolate params from grid
star_continuum_model = ispec.fit_continuum(star_spectrum, \
fixed_value=1.0, model="Fixed value")
return normalized_star_spectrum, star_continuum_model
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_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_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 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 _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 determine_parameters(spec_id, lines_id):
#code = "synthe"
code = "spectrum"
star_spectrum = ispec.read_spectrum(spec_id)
# 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")
normalized_star_spectrum = ispec.normalize_spectrum(star_spectrum, star_continuum_model, consider_continuum_errors=False)
#--- Model spectra ----------------------------------------------------------
params = []
with open('config.txt', 'r') as cfile:
for line in cfile:
params.append(float(str(line)[:-1]))
# Parameters
initial_teff = params[0]
initial_logg = params[1]
initial_MH = params[2]
initial_vmic = params[3]
initial_vmac = params[4]
initial_vsini = params[5]
initial_limb_darkening_coeff = params[6]
initial_R = params[7]
initial_vrad = params[8]
max_iterations = params[9]
# Selected model amtosphere, linelist and solar abundances
#model = ispec_dir + "/input/atmospheres/MARCS/modeled_layers_pack.dump"
model = ispec_dir + "/input/atmospheres/MARCS.GES/modeled_layers_pack.dump"
#model = ispec_dir + "/input/atmospheres/MARCS.APOGEE/modeled_layers_pack.dump"
#model = ispec_dir + "/input/atmospheres/ATLAS9.APOGEE/modeled_layers_pack.dump"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Castelli/modeled_layers_pack.dump"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Kurucz/modeled_layers_pack.dump"
#model = ispec_dir + "/input/atmospheres/ATLAS9.Kirby/modeled_layers_pack.dump"
#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/GESv5_atom_hfs_iso.420_920nm/atomic_lines.tsv"
#atomic_linelist_file = ispec_dir + "/input/linelists/transitions/GESv5_atom_nohfs_noiso.420_920nm/atomic_lines.tsv"
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/Grevesse.1998/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", "vmac", "vsini"]
# Free individual element abundance
free_abundances = None
linelist_free_loggf = None
# Line regions
line_regions = ispec.read_line_regions(lines_id)
#line_regions = ispec.read_line_regions(ispec_dir + "/input/regions/47000_VALD/spectrum_synth_turbospectrum_synth_sme_synth_moog_synth_synthe_synth_good_for_params_all_extended.txt")
# 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)
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_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)
##--- Save results -------------------------------------------------------------
logging.info("Saving results...")
#dump_file = "example_results_synth_%s.dump" % (code)
#ispec.save_results(dump_file, (params, errors, abundances_found, loggf_found, status, stats_linemasks))
# If we need to restore the results from another script:
#params, errors, abundances_found, loggf_found, status, stats_linemasks = ispec.restore_results(dump_file)
#logging.info("Saving synthetic spectrum...")
#synth_filename = "example_modeled_synth_%s.fits" % (code)
#ispec.write_spectrum(modeled_synth_spectrum, synth_filename)
parameters = "\n" + str(params)
parameter_errors = "\n" + str(errors)
file_id = spec_id + "_info.txt"
with open(file_id, "w") as savefile:
savefile.write(parameters)
savefile.write(parameter_errors)
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_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)
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)