#!/usr/bin/env python
# coding: utf-8

# In[ ]:


# import necessary modules
from classy import Class
from math import pi
get_ipython().run_line_magic('matplotlib', 'inline')
import matplotlib
import matplotlib.pyplot as plt


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#############################################
#
# Cosmological parameters and other CLASS parameters
#
common_settings = {# LambdaCDM parameters
                   'h':0.67810,
                   'omega_b':0.02238280,
                   'omega_cdm':0.1201075,
                   'A_s':2.100549e-09,
                   'n_s':0.9660499,
                   'tau_reio':0.05430842 ,
                   # output and precision parameters
                   'output':'tCl,pCl,lCl',
                   'lensing':'yes',
                   'l_max_scalars':5000}
#
M = Class()
#
###############
#    
# call CLASS for the total Cl's and then for each contribution
#
###############
#
M.set(common_settings)
M.compute()
cl_tot = M.raw_cl(3000)
cl_lensed = M.lensed_cl(3000)
M.empty()           # reset input
#
M.set(common_settings) # new input
M.set({'temperature contributions':'tsw'}) 
M.compute()
cl_tsw = M.raw_cl(3000) 
M.empty()
#
M.set(common_settings)
M.set({'temperature contributions':'eisw'})
M.compute()
cl_eisw = M.raw_cl(3000) 
M.empty()
#
M.set(common_settings)
M.set({'temperature contributions':'lisw'})
M.compute()
cl_lisw = M.raw_cl(3000) 
M.empty()
#
M.set(common_settings)
M.set({'temperature contributions':'dop'})
M.compute()
cl_dop = M.raw_cl(3000) 
M.empty()


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#################
#
# start plotting
#
#################
#
plt.xlim([2,3000])
plt.xlabel(r"$\ell$")
plt.ylabel(r"$\ell (\ell+1) C_l^{TT} / 2 \pi \,\,\, [\times 10^{10}]$")
plt.grid()
#
ell = cl_tot['ell']
factor = 1.e10*ell*(ell+1.)/2./pi
plt.semilogx(ell,factor*cl_tsw['tt'],'c-',label=r'$\mathrm{T+SW}$')
plt.semilogx(ell,factor*cl_eisw['tt'],'r-',label=r'$\mathrm{early-ISW}$')
plt.semilogx(ell,factor*cl_lisw['tt'],'y-',label=r'$\mathrm{late-ISW}$')
plt.semilogx(ell,factor*cl_dop['tt'],'g-',label=r'$\mathrm{Doppler}$')
plt.semilogx(ell,factor*cl_tot['tt'],'r-',label=r'$\mathrm{total}$')
plt.semilogx(ell,factor*cl_lensed['tt'],'k-',label=r'$\mathrm{lensed}$')
#
plt.legend(loc='right',bbox_to_anchor=(1.4, 0.5))
plt.savefig('cltt_terms.pdf',bbox_inches='tight')