def n_chi(chi):
"""Vectorized."""
# Invert the distance redshift relation by interpolating.
c = Cosmology()
redshifts_s = np.linspace(0.01, 3, 50)
chi_s = c.comoving_distance(redshifts_s)
redshift_interp = interpolate.interp1d(chi_s, redshifts_s, kind='cubic')
redshifts = redshift_interp(chi)
# Calculate the source density at both redshifts.
dL = c.luminosity_distance(redshifts)
dL_star = c.luminosity_distance(Z_STAR)
# Minimum detectable L/L*
x_min = (dL / dL_star)**2
# Get source density by integrating the luminocity function.
n = []
dndL_fun = lambda x : x**ALPHA * np.exp(-x)
for x_m in x_min:
this_n, err = integrate.quad(dndL_fun, x_m, np.inf)
n.append(this_n)
n = np.array(n)
return n
def interpolator():
c = Cosmology()
chi = c.comoving_distance(REDSHIFTS)
interpolator = interpolate.interp2d(K, chi, DATA, kind='cubic')
return interpolator