ler.utils.cosmological_conversions

Module Contents

Functions

generate_mixed_grid(x_min, x_max, resolution[, ...])	Generalized mixed spacing grid generator. Safely handles negative ranges.
luminosity_distance([z, z_min, z_max, cosmo, ...])	Function to create a lookup table for luminosity distance as a function of redshift.
differential_comoving_volume([z, z_min, z_max, cosmo, ...])	Create a FunctionConditioning object for the differential comoving volume dVc/dz.
comoving_distance([z, z_min, z_max, cosmo, directory, ...])	Create a FunctionConditioning object for the comoving distance.
angular_diameter_distance([z, z_min, z_max, cosmo, ...])	Create a FunctionConditioning object for the angular diameter distance.
angular_diameter_distance_z1z2([z1, z2, z_min, z_max, ...])	Create a FunctionConditioning object for the angular diameter distance between two redshifts.

ler.utils.cosmological_conversions.generate_mixed_grid(x_min, x_max, resolution, power_law_part='lower', geomspace_part=False, spacing_trend='increasing', power=2.3, value_transition_fraction=0.6, num_transition_fraction=0.8, auto_match_slope=True)

Generalized mixed spacing grid generator. Safely handles negative ranges.

Parameters:

x_minfloat

Minimum value of the grid.

x_maxfloat

Maximum value of the grid.

resolutionint

Total number of grid points.

power_law_partstr, optional

Which part of the grid should follow the power-law spacing. Options: ‘lower’ or ‘upper’. Default is ‘lower’.

geomspace_partbool or str, optional

If False, keep the existing linear + power-law behavior. If ‘lower’ or ‘upper’, replace that segment with geometric spacing while keeping the other segment linear. Geometric spacing is only used when the selected segment endpoints are strictly positive; otherwise the function falls back to the standard mixed-grid construction. Default is False.

spacing_trendstr, optional

Whether the power-law spacing should be increasing or decreasing. Options: ‘increasing’ or ‘decreasing’. Default is ‘increasing’.

powerfloat, optional

The power-law exponent. Higher values lead to more extreme spacing. Default is 2.3.

value_transition_fractionfloat, optional

The fraction of the total value range at which to transition from linear to power-law spacing. Must be between 0 and 1. Default is 0.6.

num_transition_fractionfloat, optional

The fraction of the total number of points at which to transition from linear to power-law spacing. Must be between 0 and 1. Default is 0.8.

auto_match_slopebool, optional

Whether to automatically adjust the power-law exponent to match the slope of the linear spacing at the transition point. Default is True. This is ignored for the geometric-spacing segment when geomspace_part is used.

Returns:

numpy.ndarray

The generated grid points.

Examples

>>> from ler.utils import generate_mixed_grid
>>> resolution = 20
>>> x = generate_mixed_grid(
...     x_min=0.0,
...     x_max=10.0,
...     resolution=resolution,
...     power_law_part='upper',
...     spacing_trend='decreasing',
...     power=2.5,
...     value_transition_fraction=0.6,
...     num_transition_fraction=0.3,
... )

ler.utils.cosmological_conversions.luminosity_distance(z=None, z_min=0.001, z_max=10.0, cosmo=LambdaCDM(H0=70, Om0=0.3, Ode0=0.7, Tcmb0=0.0, Neff=3.04, m_nu=None, Ob0=0.0), directory='./interpolator_json', create_new=False, resolution=500, get_attribute=True)

Function to create a lookup table for luminosity distance as a function of redshift.

The interpolated quantity is

\[D_L(z) = (1+z) D_C(z),\]

as returned by astropy.cosmology for the supplied cosmology.

Parameters:

znumpy.ndarray or float

Source redshifts

z_minfloat

Minimum redshift of the source population

z_maxfloat

Maximum redshift of the source population

Attributes:

z_to_luminosity_distanceler.utils.FunctionConditioning

Object of FunctionConditioning class containing luminosity distance as a function of redshift.

ler.utils.cosmological_conversions.differential_comoving_volume(z=None, z_min=0.001, z_max=10.0, cosmo=LambdaCDM(H0=70, Om0=0.3, Ode0=0.7, Tcmb0=0.0, Neff=3.04, m_nu=None, Ob0=0.0), directory='./interpolator_json', create_new=False, resolution=500, get_attribute=True)

Create a FunctionConditioning object for the differential comoving volume dVc/dz.

The stored table is full-sky:

\[\frac{dV_c}{dz} = 4\pi \frac{dV_c}{dz\,d\Omega}.\]

Parameters:

zfloat or numpy.ndarray or None

Redshift(s) at which to evaluate. If None, returns the FunctionConditioning object.

z_minfloat

Minimum redshift. default: 0.001

z_maxfloat

Maximum redshift. default: 10.0

cosmoastropy.cosmology

Cosmology object. default: LambdaCDM(H0=70, Om0=0.3, Ode0=0.7)

directorystr

Directory for storing interpolator JSON files. default: ‘./interpolator_json’

create_newbool

If True, create new interpolator. default: False

resolutionint

Number of grid points for the interpolator. default: 500

get_attributebool

If True, return the FunctionConditioning object. default: True

Returns:

differential_comoving_volumeFunctionConditioning or numpy.ndarray

dVc/dz in Mpc^3 sr^-1 (multiplied by 4*pi for full sky).

ler.utils.cosmological_conversions.comoving_distance(z=None, z_min=0.001, z_max=10.0, cosmo=LambdaCDM(H0=70, Om0=0.3, Ode0=0.7, Tcmb0=0.0, Neff=3.04, m_nu=None, Ob0=0.0), directory='./interpolator_json', create_new=False, resolution=500, get_attribute=True)

Create a FunctionConditioning object for the comoving distance.

\[D_C(z) = c \int_0^z \frac{dz'}{H(z')}.\]

Parameters:

zfloat or numpy.ndarray or None

Redshift(s) at which to evaluate. If None, returns the FunctionConditioning object.

z_minfloat

Minimum redshift. default: 0.001

z_maxfloat

Maximum redshift. default: 10.0

cosmoastropy.cosmology

Cosmology object. default: LambdaCDM(H0=70, Om0=0.3, Ode0=0.7)

directorystr

Directory for storing interpolator JSON files. default: ‘./interpolator_json’

create_newbool

If True, create new interpolator. default: False

resolutionint

Number of grid points for the interpolator. default: 500

get_attributebool

If True, return the FunctionConditioning object. default: True

Returns:

comoving_distanceFunctionConditioning or numpy.ndarray

Comoving distance in Mpc.

ler.utils.cosmological_conversions.angular_diameter_distance(z=None, z_min=0.001, z_max=10.0, cosmo=LambdaCDM(H0=70, Om0=0.3, Ode0=0.7, Tcmb0=0.0, Neff=3.04, m_nu=None, Ob0=0.0), directory='./interpolator_json', create_new=False, resolution=500, get_attribute=True)

Create a FunctionConditioning object for the angular diameter distance.

\[D_A(z) = \frac{D_C(z)}{1+z}.\]

Parameters:

zfloat or numpy.ndarray or None

Redshift(s) at which to evaluate. If None, returns the FunctionConditioning object.

z_minfloat

Minimum redshift. default: 0.001

z_maxfloat

Maximum redshift. default: 10.0

cosmoastropy.cosmology

Cosmology object. default: LambdaCDM(H0=70, Om0=0.3, Ode0=0.7)

directorystr

Directory for storing interpolator JSON files. default: ‘./interpolator_json’

create_newbool

If True, create new interpolator. default: False

resolutionint

Number of grid points for the interpolator. default: 500

get_attributebool

If True, return the FunctionConditioning object. default: True

Returns:

angular_diameter_distanceFunctionConditioning or numpy.ndarray

Angular diameter distance in Mpc.

ler.utils.cosmological_conversions.angular_diameter_distance_z1z2(z1=None, z2=None, z_min=0.001, z_max=10.0, cosmo=LambdaCDM(H0=70, Om0=0.3, Ode0=0.7, Tcmb0=0.0, Neff=3.04, m_nu=None, Ob0=0.0), directory='./interpolator_json', create_new=False, resolution=500, get_attribute=True)

Create a FunctionConditioning object for the angular diameter distance between two redshifts.

Uses the relation

\[D_A(z_1, z_2) = \frac{D_A(z_2)(1+z_2) - D_A(z_1)(1+z_1)}{1+z_2}.\]

Parameters:

z1float or numpy.ndarray or None

Lens redshift(s).

z2float or numpy.ndarray or None

Source redshift(s).

z_minfloat

Minimum redshift. default: 0.001

z_maxfloat

Maximum redshift. default: 10.0

cosmoastropy.cosmology

Cosmology object. default: LambdaCDM(H0=70, Om0=0.3, Ode0=0.7)

directorystr

Directory for storing interpolator JSON files. default: ‘./interpolator_json’

create_newbool

If True, create new interpolator. default: False

resolutionint

Number of grid points for the interpolator. default: 500

get_attributebool

If True, return the FunctionConditioning object. default: True

Returns:

angular_diameter_distance_z1z2FunctionConditioning or numpy.ndarray

Angular diameter distance between z1 and z2 in Mpc.