import numpy as np
import matplotlib.pyplot as plt
# 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, '-')
# =======================================================================
# Example code: how to compute the three-point correlation function model
# =======================================================================
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"$\theta/\pi$")
# ==========================================================================
# Example code: how to compute the theoretical size function of cosmic voids
# ==========================================================================
# to ensure compatibility in Python versions 2.x and 3.x
from __future__ import print_function
# import the CosmoBolognaLib #
import CosmoBolognaLib as cbl
import numpy as np
# set the CosmoBolognaLib and the current directories
cbl.SetDirs("../../../", "./")
# define a cosmological model, using default parameters #
cosm = cbl.Cosmology()
# Minimum and maximum of effective void radii
R_min = 1.
R_max = 30.
# number of radii at which the size function is computed
n_val = 10
# list of effective void radii with logarithmic binning
RR = np.logspace(np.log10(R_min), np.log10(R_max), n_val, endpoint=True)
# redshift of the sample
zz = 0.
# effective bias of the mass tracers
##########################################################
# Coordinates type selection
if param.findBool('comovingCoordinates'):
coordinates = cbl.CoordinateType__comoving_
else:
coordinates = cbl.CoordinateType__observed_
##########################################################
# define a cosmological model, using parameters from file #
cosm = cbl.Cosmology(param.findDouble('OmM'), param.findDouble('Omb'),
param.findDouble('Omn'), param.findDouble('massless'),
param.findInt('massive'), param.findDouble('OmL'),
param.findDouble('Omr'), param.findDouble('hh'),
param.findDouble('As'), param.findDouble('pivot'),
param.findDouble('ns'), param.findDouble('w0'),
param.findDouble('wa'), param.findDouble('fNL'),
param.findInt('type_NG'), param.findDouble('tau'),
param.findString('model'), param.findBool('unit'))
# set sigma_8 value from file
cosm.set_sigma8(param.findDouble('sigma8'))
##########################################################
# load the input void catalogue
cast = []
clmn = []
attrNames = [
'X_coord', 'Y_coord', 'Z_coord', 'Radius', 'centralDensity',
import numpy as np
print "I'm importing matplotlib..."
import matplotlib.pyplot as plt
### import the CosmoBolognaLib ###
import CosmoBolognaLib as cbl
# set the CosmoBolognaLib and the current directories
cbl.SetDirs("../../../", "./")
### create an object of class Cosmology ###
cosmo = cbl.Cosmology()
### define k and r for the computation of dark matter power spectrum and two point correlation correlation function ###
kk = np.logspace(-3, 0, 100)
rr = np.linspace(1., 100, 50)
### Compute the power spectrum using CAMB ###
PkCAMB = np.asarray(
[cosmo.Pk(kk[i], "CAMB", False, 0.2) for i in range(len(kk))])
### Compute the two point correlation function using CAMB ###
xiCAMB = [
cosmo.xi_DM(rr[i], "CAMB", 0.2, "test", False) for i in range(len(rr))