def __init__(self):
# Lya P3D defined at this redshift
self.zref=2.25
# Cosmological model
self.cosmo = cCAMB.Cosmology(self.zref)
# Lya P3D theory
self.LyaP3D = P3D.TheoryLyaP3D(self.cosmo)
# quasar luminosity function
self.QLF = qLF.QuasarLF()
# spectrograph
self.spec = sp.Spectrograph(band='g')
# survey (should probably be its own object at some point...)
self.area_deg2 = 14000.0
# each mini-survey will cover only (lmin,lmax)
self.lmin = 3501.0
self.lmax = 3701.0
# quasar redshift range
self.zq_min = 2.0
self.zq_max = 4.0
# magnitude range
self.mag_min = 16.5
self.mag_max = 23.0
# pixel width and resolution in km/s (for now)
self.pix_kms = 50.0
self.res_kms = 70.0
# definition of forest (lrmin,lrmax)
self.lrmin = 985.0
self.lrmax = 1200.0
# S/N weights evaluated at this Fourier mode
self.kt_w_deg=7.0 # ~ 0.1 h/Mpc
self.kp_w_kms=0.001 # ~ 0.1 h/Mpc
# verbosity level
self.verbose = 1
def __init__(self, cosmo=None):
"""cosmo is an optional cosmoCAMB.Cosmology object"""
if cosmo:
self.cosmo = cosmo
self.zref = cosmo.pk_zref
else:
self.zref = 2.25
self.cosmo = cCAMB.Cosmology(self.zref)
# get linear power spectrum
self.kmin = 1.e-4
self.kmax = 1.e1
self.linPk = self.cosmo.LinPk_hMpc(self.kmin, self.kmax, 1000)
def __init__(self, cosmo=None):
"""
cosmo is an optional cosmoCAMB.Cosmology object
since our LyA reference values are at redshift 2.4, we set z_ref = 2.4
"""
if cosmo:
self.cosmo = cosmo
self.zref = cosmo.pk_zref
else:
self.zref = 2.4
self.cosmo = cCAMB.Cosmology(self.zref)
# get linear power spectrum
self.kmin = 1.e-4
self.kmax = 1.e1
self.linPk = self.cosmo.LinPk_hMpc(self.kmin, self.kmax, 1000)
z = 2.4 #redshift value
headFile = "run89" #subfolder of "output" to write fitting results to
# make the output folder if it does not already exist
if not os.path.exists('../output/' + headFile):
os.makedirs('../output/' + headFile)
######################################################################
## Define fiducial parameter values and the 1D power spectrum model ##
######################################################################
q1_f, q2_f, kp_f, kvav_f, av_f, bv_f = getFiducialValues(z)
p0 = [q1_f, q2_f, kp_f, kvav_f, av_f, bv_f]
ndims = len(p0)
cosmo = cCAMB.Cosmology(z)
th = tLyA.TheoryLya(cosmo)
dkMz = th.cosmo.dkms_dhMpc(z)
data = npd.LyA_P1D(z)
k_vals = data.k
P = data.Pk
Perr = data.Pk_stat
k_res = k_vals * dkMz
def model(k, q1, q2, kp, kvav, av, bv):
m = th.FluxP1D_hMpc(
z, k * dkMz, q1=q1, q2=q2, kp=kp, kvav=kvav, av=av, bv=bv) * dkMz
return m
import numpy as np
import matplotlib.pyplot as plt
import cosmoCAMB as cCAMB
# setup cosmological model
zref = 2.25
cosmo = cCAMB.Cosmology(zref)
# compute linear power at zref
kmin = 1.e-4
kmax = 1.e1
linPk = cosmo.LinPk_hMpc(kmin, kmax, 1000)
# plot power
k = np.logspace(np.log10(kmin), np.log10(0.99 * kmax), 1000)
plt.loglog(k, linPk(k))
plt.xlim(1.e-4, 1.0)
plt.ylim(ymin=10.0)
plt.xlabel('k [h/Mpc]')
plt.ylabel('P(k) [Mpc/h]')
plt.title('Linear density power at z =' + str(zref))
plt.show()