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plot_xy_power.py
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import math
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import xy_power
import time
def beam_transfer_function (ell, cl, fwhm) :
#convert fwhm from arcmin to radian
fwhm *= (np.pi/180.0)/60.0
sigma = fwhm / (np.sqrt(8.0*np.log(2.0)))
bl = np.exp(-ell**2 * sigma**2/2.0)
return bl
def power (ell, theta, clump=True) :
eps_f = theta[0]
eps_DM = theta[1]
f_star = theta[2]
S_star = theta[3]
A_C = theta[4]
alpha0 = theta[5]
n_nt = theta[6]
beta = theta[7]
gamma_mod0 = theta[8]
gamma_mod_zslope = theta[9]
x_break = theta[10]
x_smooth = theta[11]
n_nt_mod = theta[12]
clump0 = theta[13]
clump_zslope = theta[14]
x_clump = theta[15]
alpha_clump1 = theta[16]
alpha_clump2 = theta[17]
xy_power.set_Flender_params(alpha0, n_nt, beta, eps_f*1e-6, eps_DM, f_star, S_star, A_C, gamma_mod0, gamma_mod_zslope, x_break, x_smooth, n_nt_mod, clump0, clump_zslope, x_clump, alpha_clump1, alpha_clump2)
model = xy_power.return_xy_power(ell) # [erg cm^-2 s^-1 str^-1]^2
return model
def read_data (filename) :
ell = []
cl = []
var = []
with open(filename,'r') as f:
f.readline()
for line in f:
cols = line.split(' ')
ell.append(float(cols[0]))
cl.append(float(cols[1]))
var.append(float(cols[2]))
ell = np.array(ell)
cl = np.array(cl)
var = np.array(var)
return ell, cl, var
def main ():
# set cosmology and linear power spectrum
H0=70.0
Omega_M=0.279000
Omega_b=0.046100
w0=-1.000000
Omega_k=0.000000
n_s=0.972000
inputPk="../input_pk/wmap9_fid_matterpower_z0.dat"
nH = 2.4e+20
xy_power.init_cosmology(H0, Omega_M, Omega_b, w0, Omega_k, n_s, nH, inputPk, 1)
shot_noise = 3.e-22
ell = 10.**np.linspace(np.log10(1.),np.log10(3.e4), 1000)
theta_fid = [4.0, 3.e-5 ,0.026000,0.120000,1.000000,0.180000,0.800000,0.500000,0.100000,1.720000,0.195000,0.010000,0.800000,0.670000,0.730000,1.230000,0.880000, 3.85000]
param_ind_dict = {'eps_f':0, 'eps_DM':1, 'f_star':2, 'S_star':3, 'A_C':4, 'alpha_nt':5, 'n_nt':6, 'beta_nt':7, 'gamma_mod0':8, 'gamma_mod_zslope':9, 'x_break':10, 'x_smooth':11, 'n_nt_mod':12, 'clump0':13, 'clump_zslope':14, 'x_clump':15, 'alpha_clump1':16, 'alpha_clump2':17}
param_label_dict = {'eps_f':r'$\epsilon_f$', 'eps_DM':r'$\epsilon_{DM}$', 'f_star':r'$f_\star$', 'S_star':r'$S_\star$', 'A_C':r'$A_C$','alpha_nt':r'$\alpha_{nt}$', 'n_nt':r'$n_{nt}$', 'beta_nt':r'$\beta_{nt}$', 'gamma_mod0':r'$\Gamma_0$', 'gamma_mod_zslope':r'$\beta_\Gamma$', 'n_nt_mod':'$n_{nt,mod}$', 'clump0':r'$C_0$', 'clump_zslope':r'$\beta_C$','x_clump':r'$x_{C}$', 'alpha_clump1':r'$\alpha_{C1}$', 'alpha_clump2':r'$\alpha_{C2}$'}
#rosat_ell, rosat_cl, rosat_var = read_data("../ROSAT/rosat_R6_planck_mask_hfi_R2_small_ell.txt")
#rosat_cl *= rosat_ell*(rosat_ell+1.)/(2.0*math.pi)
#rosat_cl_err = np.sqrt(rosat_var)*rosat_ell*(rosat_ell+1.)/(2.0*math.pi)
params = [ 'eps_f', 'f_star', 'S_star', 'alpha_nt', 'n_nt', 'beta_nt', 'gamma_mod0', 'gamma_mod_zslope', 'clump0', 'clump_zslope', 'x_clump', 'alpha_clump1', 'alpha_clump2' ]
for param in params :
param_ind = param_ind_dict[param]
param_fid = theta_fid[param_ind]
print(param_fid)
param_val_list = []
color_list = ['C0', 'C1', 'C2', 'C3', 'C4']
for i in [0.1,0.5,1.0,1.5,2.0]:
param_val = param_fid * i
param_val_list.append(param_val)
f = plt.figure( figsize=(5,5) )
ax = f.add_axes([0.18,0.16,0.75,0.75])
cl_list = []
for counter ,param_val in enumerate(param_val_list) :
theta = theta_fid.copy()
theta[param_ind] = param_val
start = time.time()
cl = power (ell, theta)
end = time.time()
print("Elapsed time: %s" % (end - start))
cl *= ell*(ell+1)/(2.0*math.pi)
#psn = np.full(ell.shape, shot_noise, dtype = np.float64)
#psn *= ell*(ell+1)/(2.0*math.pi)
#total = cl + psn
cl_list.append(cl)
label_str = param_label_dict[param]+'$= %.3f $'% (param_val)
if param == 'eps_f' :
label_str = param_label_dict[param]+r'$= %.1f \times 10^{-6}$'% (param_val)
#ax.plot (ell, total, ls = '-', color=color_list[counter], label = label_str)
ax.plot (ell, cl, ls = '-', color=color_list[counter], label = label_str)
#ax.plot (ell, psn, ls = ':', color=color_list[counter])
#ax.errorbar(rosat_ell, rosat_cl, yerr = rosat_cl_err, color='k', label=r"data")
ax.set_xlim ( 10, 3e3 )
#ax.set_ylim ( 1e-19, 1e-13)
ax.set_xlabel(r'$\ell$')
ax.set_ylabel(r'$\ell(\ell+1)C_{\ell}^{xy}/2\pi\,[{\rm erg^{2}s^{-2}cm^{-4}str^{-2}}]$')
ax.set_xscale('log')
ax.set_yscale('log')
ax.legend(loc='best')
outname = '../plots/'+param+'_xy_power.pdf'
f.savefig(outname)
f.clf()
if __name__ == "__main__" :
main()