In [1]:
%pylab inline
import numpy as np
import matplotlib.pyplot as plt
import theoryLyaP3D as tP3D
In [2]:
# create theory object
theory=tP3D.TheoryLyaP3D()
In [3]:
# compute P3D at z=3, in the parallel (mu=0) and transverse (mu=1) directions
z=3.0
k=np.logspace(-4,0.9,1000)
pk_0=theory.FluxP3D_hMpc(z,k,np.zeros_like(k))
pk_1=theory.FluxP3D_hMpc(z,k,np.ones_like(k))
# compute also P3D ignoring non-linear corrections (Kaiser only)
pk_0_lin=theory.FluxP3D_hMpc(z,k,np.zeros_like(k),linear=True)
pk_1_lin=theory.FluxP3D_hMpc(z,k,np.ones_like(k),linear=True)
In [4]:
# something related to fonts in the plot
plt.rc('text', usetex=True)
plt.rcParams['text.latex.preamble'] = [
r'\usepackage{siunitx}', # i need upright \micro symbols, but you need
r'\sisetup{detect-all}', # this to force siunitx to actually use your fonts
r'\usepackage{helvet}', # set the normal font here
r'\usepackage{sansmath}', # load up the sansmath so that math -> helvet
r'\sansmath' # <- tricky! -- gotta actually tell tex to use!
]
plt.rc('xtick', labelsize=15)
plt.rc('ytick', labelsize=15)
In [5]:
plt.ylim(1e0,2e3)
plt.xlim(1e-3,1e0)
plt.xlabel(r'k [h $\rm{Mpc}^{-1}$]',fontsize=15)
plt.ylabel(r'$\rm{P}_{\rm{F}}(k)$ [$\rm{Mpc}^3 \rm{h}^{-3}$]',fontsize=15)
plt.title(r'3D flux power at z='+str(z),fontsize=15)
plt.loglog(k,pk_0,label=r'$\mu=0$')
plt.loglog(k,pk_1,label=r'$\mu=1$')
plt.loglog(k,pk_0_lin,label=r'$\mu=0$, lin')
plt.loglog(k,pk_1_lin,label=r'$\mu=1$, lin')
plt.legend(loc='lower left',fontsize=12)
plt.show()
In [6]:
p1d = theory.FluxP1D_hMpc(z,k,0.01,0.01)
p1d_TH = theory.FluxP1D_hMpc(z,k,0.01,1.0)
p1d_G = theory.FluxP1D_hMpc(z,k,1.0,0.01)
In [7]:
plt.ylim(1e-5,1)
plt.xlabel(r'k [h $\rm{Mpc}^{-1}$]',fontsize=15)
plt.ylabel(r'k $\rm{P}^{1D}_{\rm{F}}(k) / \pi $',fontsize=15)
plt.title(r'1D flux power at z='+str(z),fontsize=15)
plt.loglog(k,k*p1d/np.pi,label='no smoothing')
plt.loglog(k,k*p1d_TH/np.pi,label='Gaussian smoothing')
plt.loglog(k,k*p1d_G/np.pi,label='Top hat smoothing')
plt.legend(loc='upper left',fontsize=12)
Out[7]: