Redshift¶

Setup for the redshift distributions

class redshift.nz_dist(zmin: float = None, zmax: float = None, nzmax: int = None)[source]¶

Bases: object

nz_gaussian(z0: float, sigma: float) → numpy.ndarray[source]¶

Gaussian n(z) distribution for the tomographic bin

$n(z)=\frac{1}{2\pi\sigma}\text{exp}(-\frac{1}{2}\frac{(z-z_{0})^{2}}{\sigma^{2}})$

nz_model_1(zm: float) → numpy.ndarray[source]¶

Calculate the analytic function

$n(z)=z^{2}\text{exp}(-\frac{z}{z_{0}})$

nz_model_2(z0: float, alpha: float = 2, beta: float = 1.5)[source]¶

Calculate the analytic function

$n(z)=z^{\alpha}\text{exp}(-(\frac{z}{z_{0}})^{\beta})$