| #!/usr/bin/env python | |
| # coding: utf-8 | |
| # In[ ]: | |
| # import necessary modules | |
| # uncomment to get plots displayed in notebook#%matplotlib inline | |
| import matplotlib | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| from classy import Class | |
| from scipy.optimize import fsolve | |
| from scipy.interpolate import interp1d | |
| import math | |
| # In[ ]: | |
| common_settings = {'output' : 'tCl', | |
| # LambdaCDM parameters | |
| 'h':0.6781, | |
| 'omega_b':0.02238280, | |
| 'omega_cdm':0.1201075, | |
| 'A_s':2.100549e-09, | |
| 'n_s':0.9660499, | |
| 'tau_reio':0.05430842, | |
| 'thermodynamics_verbose':1 | |
| } | |
| ############## | |
| # | |
| # call CLASS | |
| # | |
| ############### | |
| M = Class() | |
| M.set(common_settings) | |
| M.compute() | |
| derived = M.get_current_derived_parameters(['tau_rec','conformal_age','conf_time_reio']) | |
| thermo = M.get_thermodynamics() | |
| print (thermo.keys()) | |
| # In[ ]: | |
| tau = thermo['conf. time [Mpc]'] | |
| g = thermo['g [Mpc^-1]'] | |
| # to make the reionisation peak visible, rescale g by 100 for late times | |
| g[:500] *= 100 | |
| ################# | |
| # | |
| # start plotting | |
| # | |
| ################# | |
| # | |
| plt.xlim([1.e2,derived['conformal_age']]) | |
| plt.xlabel(r'$\tau \,\,\, \mathrm{[Mpc]}$') | |
| plt.ylabel(r'$\mathrm{visibility} \,\,\, g \,\,\, [\mathrm{Mpc}^{-1}]$') | |
| plt.axvline(x=derived['tau_rec'],color='k') | |
| plt.axvline(x=derived['conf_time_reio'],color='k') | |
| # | |
| plt.semilogx(tau,g,'r',label=r'$\psi$') | |
| plt.savefig('thermo.pdf',bbox_inches='tight') | |