def xi(self, r=0., z1=0.0, R1=8., z2=0.0, R2=8.):
"""return the smoothed two-point correlation function (of two subvolumes of size R1 and R2), r apart
"""
fac = self.gfratio(z1)*self.gfratio(z2)/(2.*np.power(np.pi, 2.0))
integrand = lambda q: q*q*top_hat(q, R1)*top_hat(q, R2)*BesselJ(0, q*r)*self.power_spectrumz(q, z=0)
results = integrate.quad(integrand, 0.0, 20./min(R1, R2))
return fac*results[0]
def xi_camb(self, r=0., z1=0.0, R1=8., z2=0.0, R2=8.):
"""return the smoothed two-point correlation function
using the non-linear matter spectrum from camb
make sure to run get_nonlin_power using z=0
"""
fac = self.gfratio(z1)*self.gfratio(z2)/(2.*np.power(np.pi, 2.0))
integrand = lambda q: q*q*top_hat(q, R1)*top_hat(q, R2)*BesselJ(0, q*r)*self.camb_power_nonlin(q)
results = integrate.quad(integrand, 2E-5, 20./min(R1, R2), limit=300)
return fac*results[0]
def sigmaR(self, R):
"""
compute sigma_R by integrating;
now use the CAMB power spectrum
"""
#fac = 1./(2.*np.power(np.pi, 2.0))
integrand = lambda q: np.power(top_hat(q, R)*self.alpha(q), 2.0)*self.primordial_power(self.A, q, self.k0)/q
#integrand = lambda q: q*q*np.power(top_hat(q, R), 2.0)*self.camb_power_lin(q)
results = integrate.quad(integrand, 0.0, 20./R, limit=80)
return np.sqrt(results[0])
def sigma_sq_integrand(self, k, R):
return k*k/(2.0*np.pi**2.0)*self.power_spectrum0(self.A, k)*top_hat(k,R)**2.0
