# import the CosmoBolognaLib #
import CosmoBolognaLib as cbl
from CosmoBolognaLib import DoubleVector as dv
# set the CosmoBolognaLib and the current directories
cbl.SetDirs("../../", "./")
# set the cosmological model, with default parameters
cosmology = cbl.Cosmology()
# compute the dark matter power spectrum
kk = np.logspace(-4, 2, 200)
Pk = [cosmology.Pk(kk[i], "CAMB", False, 0) for i in range(len(kk))]
# get correlation function from fftlog: dir is the transformation
# direction, mu is the order of the Bessel function (see the
# documentation for other options)
dir = 1
mu = 0
rr = np.linspace(1., 200, 100)
xi = np.array(cbl.transform_FFTlog(dv(rr), dir, dv(kk), dv(Pk), mu))
# plot results
plt.plot(rr, xi * rr * rr)
plt.xlabel(r"$s$ $[$Mpc$h^{-1}]$")
plt.ylabel(r"$\xi(s)\cdot s^2$ $[$Mpc$^2h^{-2}]$")
plt.plot(rr, xi * rr * rr, '-')
plt.show(block=False)
import numpy as np
import matplotlib.pyplot as plt
import CosmoBolognaLib as cbl
from CosmoBolognaLib import DoubleVector as dv
import os
# set the CosmoBolognaLib and the current directories
cbl.SetDirs("../../../", "./")
''' Define the cosmology '''
cosmo = cbl.Cosmology(cbl.CosmologicalModel__Planck15_)
''' Compute Pk '''
redshift = 1
kk = np.logspace(-4, 2, 200)
Pk_DM = np.array([cosmo.Pk(_kk, "CAMB", False, redshift) for _kk in kk])
''' Parameters for 3pt signal '''
rr = dv(np.linspace(1., 300, 200))
theta = np.linspace(0, np.pi, 100)
r1, r2 = 20, 40
''' Slepian model '''
zeta_DM_s = np.array(cosmo.zeta_DM(r1, r2, theta, "Slepian", kk, Pk_DM))
q_DM_s = np.array(cosmo.Q_DM(r1, r2, theta, "Slepian", kk, Pk_DM))
''' Barriga-Gatzagnaga model '''
zeta_DM_bg = np.array(
cosmo.zeta_DM(r1, r2, theta, "BarrigaGatzanaga", kk, Pk_DM))
q_DM_bg = np.array(cosmo.Q_DM(r1, r2, theta, "BarrigaGatzanaga", kk, Pk_DM))
'''Plot the results'''
plt.xlabel(r"$\theta/\pi$")
plt.ylabel(r"$\zeta(r1, r2, \theta)$")
plt.plot(theta / np.pi, zeta_DM_s, '-k', label=r"Slepian et al 2016")
plt.plot(theta / np.pi, zeta_DM_bg, '--r', label=r"Barriga-Gaztanaga 2002")
plt.legend(loc="best")