Galaxies (glass.galaxies)

The glass.galaxies module provides functionality for simulating galaxies as typically observed in a cosmological galaxy survey.

Functions

glass.galaxies.redshifts_from_nz(size, z, nz, *, rng=None)

Generate galaxy redshifts from a source distribution.

Parameters:

sizeint

Number of redshifts to sample.

z, nzarray_like

Source distribution. Leading axes are treated as different galaxy populations.

rngGenerator, optional

Random number generator. If not given, a default RNG will be used.

Returns:

zarray_like

Redshifts sampled from the given source distribution.

poparray_like or None

Index of the galaxy population from the leading axes of nz; or None if there are no galaxy populations.

glass.galaxies.galaxy_shear(lon, lat, eps, kappa, gamma1, gamma2, *, reduced_shear=True)

Observed galaxy shears from weak lensing.

Takes lensing maps for convergence and shear and produces a lensed ellipticity (shear) for each intrinsic galaxy ellipticity.

Parameters:

lon, latarray_like

Arrays for galaxy longitudes and latitudes.

epsarray_like

Array of galaxy ellipticity.

kappa, gamma1, gamma2array_like

HEALPix maps for convergence and two components of shear.

reduced_shearbool, optional

If False, galaxy shears are not reduced by the convergence. Default is True.

Returns:

shearray_like

Array of complex-valued observed galaxy shears (lensed ellipticities).

glass.galaxies.gaussian_phz(z, sigma_0, rng=None)

Photometric redshifts assuming a Gaussian error.

A simple toy model of photometric redshift errors that assumes a Gaussian error with redshift-dependent standard deviation \(\sigma(z) = (1 + z) \sigma_0\) [1].

Parameters:

zarray_like

True redshifts.

sigma_0float

Redshift error in the tomographic binning at zero redshift.

rngGenerator, optional

Random number generator. If not given, a default RNG will be used.

Returns:

phzarray_like

Photometric redshifts assuming Gaussian errors, of the same shape as z.

See also

glass.observations.tomo_nz_gausserr

Create tomographic redshift distributions assuming the same model.

References

[1]

Amara A., Réfrégier A., 2007, MNRAS, 381, 1018. doi:10.1111/j.1365-2966.2007.12271.x

Examples

See the Photometric redshifts example.