Example cluster fit¶
⚠️🔴 ONLY FOR ADVANCE USERS 🔴⚠️
Example of how multiple stars in a cluster can be fitted together
Create a star_param dictionary which stores the necessary parameters (e.g. filters_to_drop, wavelength_range_A, model_name, r_limit…)
Plots are not shown in the notebook (
show_plot=False) to reduce clutter
Cluster and stellar parameters¶
import src.binary_sed_fitting as bsf
import importlib
importlib.reload(bsf)
import warnings
warnings.filterwarnings("ignore")
################################################################################
distance = 831. # pc
e_distance = 11. # pc
optical_IR_wave_range = [3000,1_000_000_000]
all_wave_range = [1,1_000_000_000]
star_params = {'WOCS2002':{'filters_to_drop':['KPNO/Mosaic.I'],
'wavelength_range_A':optical_IR_wave_range,
'wavelength_range_B':all_wave_range,
},
'Y1168':{'filters_to_drop':['2MASS/2MASS.J', '2MASS/2MASS.H', '2MASS/2MASS.Ks',
'WISE/WISE.W1','WISE/WISE.W2'],
'wavelength_range_A':[2000,10_000_000],
'wavelength_range_B':all_wave_range,
},
'WOCS1007' :{'filters_to_drop':[],
'wavelength_range_A':optical_IR_wave_range,
'wavelength_range_B':all_wave_range,
}}
Fitting single SEDs¶
bsf.console.setLevel(bsf.logging.WARNING)
refit = False
run_name = '0'
for name in star_params.keys():
file_name = 'data/extinction_corrected_flux_files/%s.csv'%name
data = bsf.load_data(file_name, mode='csv')
################################################################################
if name == 'Y1168':
model_name = 'koester'
limits = {'Te' : [5000, 80000],
'logg' : [ 6.5, 9.5]}
else:
model_name = 'kurucz'
limits = {'Te' : [3500, 9000],
'logg' : [ 3, 5],
'MH' : [ 0.0, 0.0],
'alpha': [ 0.0, 0.0]}
model = bsf.Model(model_name, limits=limits)
################################################################################
star = bsf.Star(name=name,
distance=distance,
e_distance=e_distance,
filters_to_drop=star_params[name]['filters_to_drop'],
wavelength_range=star_params[name]['wavelength_range_A'],
data=data,
model=model,
r_limits='blackbody',
run_name=run_name)
################################################################################
star.fit_chi2(refit=refit)
star.fit_noisy_chi2(refit=refit)
################################################################################
star.plot_public(add_noisy_seds=False,
show_plot=False,
folder='plots/M67/',
FR_cutoff=0.5)
star.save_summary()
22:37:55 ----- WARNING ----- calculate_chi2
Give "refit=True" if you want to rerun the fitting process.
22:37:55 ----- WARNING ----- get_parameters_from_chi2_minimization
Based on chi2, I recommend removal of following filters: ['GAIA/GAIA3.Grvs']; chi2=[19.2204403]
22:37:55 ----- WARNING ----- calculate_noisy_chi2
Give "refit=True" if you want to rerun the fitting process.
22:37:55 ----- WARNING ----- calculate_chi2
Give "refit=True" if you want to rerun the fitting process.
22:37:55 ----- WARNING ----- calculate_noisy_chi2
Give "refit=True" if you want to rerun the fitting process.
22:37:55 ----- WARNING ----- get_realistic_errors_from_iterations
logg_A : The best fit value is at upper limit of the model.
22:37:56 ----- WARNING ----- calculate_chi2
Give "refit=True" if you want to rerun the fitting process.
22:37:56 ----- WARNING ----- calculate_noisy_chi2
Give "refit=True" if you want to rerun the fitting process.
Identifying stars with UV excess¶
Manually
stars_with_uv_excess = ['WOCS2002', 'WOCS1007']
Fitting double SEDs¶
bsf.console.setLevel(bsf.logging.WARNING)
refit = False
run_name = '0'
for name in stars_with_uv_excess:
file_name = 'data/extinction_corrected_flux_files/%s.csv'%name
data = bsf.load_data(file_name, mode='csv')
################################################################################
model_name = 'kurucz_uvblue'
limits = {'Te' : [3500, 9000],
'logg' : [ 3, 5],
'MH' : [ 0.0, 0.0]}
model_A = bsf.Model(model_name, limits=limits)
model_name = 'koester'
limits = {'Te' : [5000, 80000],
'logg' : [ 6.5, 9.5]}
model_B = bsf.Model(model_name, limits=limits)
################################################################################
star_system = bsf.System(name=name,
distance=distance,
e_distance=e_distance,
data=data,
run_name=run_name,
filters_to_drop=star_params[name]['filters_to_drop'])
################################################################################
star_system.setup_A_component(model=model_A,
wavelength_range=star_params[name]['wavelength_range_A'],
r_limits='blackbody')
star_system.A.fit_chi2(refit=refit)
star_system.A.fit_noisy_chi2(refit=refit)
################################################################################
star_system.create_residual_star(component='B',
model=model_B,
wavelength_range=star_params[name]['wavelength_range_B'],
r_limits=[0.001,1.0])
star_system.B.fit_chi2(refit=refit)
star_system.B.fit_noisy_chi2(refit=refit)
################################################################################
star_system.plot(add_noisy_seds=False,
FR_cutoff=0.5,
folder='plots/',
show_plot=False)
star_system.save_summary()
22:37:56 ----- WARNING ----- calculate_chi2
Give "refit=True" if you want to rerun the fitting process.
22:37:56 ----- WARNING ----- calculate_noisy_chi2
Give "refit=True" if you want to rerun the fitting process.
22:37:56 ----- WARNING ----- get_realistic_errors_from_iterations
logg_A : The best fit value is at upper limit of the model.
22:37:56 ----- WARNING ----- calculate_chi2
Give "refit=True" if you want to rerun the fitting process.
22:37:56 ----- WARNING ----- get_parameters_from_chi2_minimization
Based on chi2, I recommend removal of following filters: ['GALEX/GALEX.NUV']; chi2=[2582.21594585]
22:37:56 ----- WARNING ----- calculate_noisy_chi2
Give "refit=True" if you want to rerun the fitting process.
22:37:56 ----- WARNING ----- get_realistic_errors_from_iterations
logg_B : The best fit value is at upper limit of the model.
22:37:56 ----- WARNING ----- get_parameters_from_noisy_chi2_minimization
Te_B (14750) != Te_median_B (14500) : Proceed with caution!
22:37:57 ----- WARNING ----- calculate_chi2
Give "refit=True" if you want to rerun the fitting process.
22:37:57 ----- WARNING ----- calculate_noisy_chi2
Give "refit=True" if you want to rerun the fitting process.
22:37:57 ----- WARNING ----- get_realistic_errors_from_iterations
logg_A : The best fit value is at lower limit of the model.
22:37:58 ----- WARNING ----- calculate_chi2
Give "refit=True" if you want to rerun the fitting process.
22:37:58 ----- WARNING ----- get_parameters_from_chi2_minimization
Based on chi2, I recommend removal of following filters: ['GALEX/GALEX.NUV']; chi2=[754.58954018]
22:37:58 ----- WARNING ----- calculate_noisy_chi2
Give "refit=True" if you want to rerun the fitting process.
22:37:58 ----- WARNING ----- get_realistic_errors_from_iterations
Te_B : The best fit value is at upper limit of the model.