flip.covariance.contraction

flip.covariance.contraction#

Attributes#

log

Classes#

Contraction

Functions#

compute_contraction_coordinates(coord_1, coord_2, ...)

contract_covariance(model_name, model_kind, ...[, ...])

Module Contents#

flip.covariance.contraction.log#
class flip.covariance.contraction.Contraction(model_name=None, model_kind=None, contraction_dict=None, coordinates_dict=None, basis_definition=None, redshift_dict=None, variant=None)#
model_name = None#
model_kind = None#
contraction_dict = None#
coordinates_dict = None#
basis_definition = None#
redshift_dict = None#
variant = None#
classmethod init_from_flip(model_name, model_kind, power_spectrum_dict, coord_1, coord_2, coord_1_reference, coord_2_reference, coordinate_type='rprt', additional_parameters_values=None, basis_definition='bisector', redshift=None, variant=None, **kwargs)#
property type#

The type function is used to determine the type of covariance model that will be computed. The options are:

  • velocity: The covariance model is computed for velocity only.

  • density: The covariance model is computed for density only.

  • density_velocity: The covariance model is computed for both velocity and density, without cross-term (i.e., the covariances between velocities and densities are zero). This option should be used when computing a full 3D tomography in which we want to compute a separate 1D tomography along each axis (x, y, z

Parameters:

self – Represent the instance of the class

Returns:

The type of the model

compute_contraction_sum(parameter_values_dict)#
The compute_contraction_sum function computes the sum of all the contractions

for a given model type and parameter values.

Parameters:

  • self – Make the function a method of the class

  • parameter_values_dict – Get the coefficients for each of the covariances

:param : Get the coefficients of the model

Returns:

A dictionary of contraction_covariance_sum

flip.covariance.contraction.compute_contraction_coordinates(coord_1, coord_2, coord_1_reference, coord_2_reference, coordinate_type, basis_definition)#
flip.covariance.contraction.contract_covariance(model_name, model_kind, power_spectrum_dict, coord_1, coord_2, coord_1_reference, coord_2_reference, coordinate_type='rprt', additional_parameters_values=None, basis_definition='bisector', redshift=None, number_worker=8, hankel=True)#
Contents