return mean_inv_Sigma_crit
def calc_gammmat(self):
rp, DeltaSigma = self.calc_DeltaSigma()
zh = 0.5 * (self.zh_min + self.zh_max)
mean_inv_Sigma_crit = self.mean_inv_Sigma_crit(zh)
gammat_avg = DeltaSigma * mean_inv_Sigma_crit #* (1e-12)
chi_l = self.chi(zh).value
theta = rp / chi_l
return theta, gammat_avg
if __name__ == "__main__":
co = CosmoParameters(OmegaM=0.286, sigma8=0.82, h=0.7, OmegaDE=0.714)
nu = NuisanceParameters(sigma_lambda=1e-5, lgM0=0, alpha_M=1,
lambda0=1) #1-1,no scatter
su = Survey(zs_min=0.508, zs_max=0.574)
lp = LensingProfiles(co=co,
nu=nu,
su=su,
zh_min=0.155,
zh_max=0.323,
Mmin=1e+14,
Mmax=1e+16)
theta, gammat = lp.calc_gammmat()
plt.plot(theta, gammat)
plt.xscale('log')
plt.yscale('log')
plt.show()