Created on Mar 27, 2019 author: Joerg Herbel
Bases: BasePlugin
Apply a potentially redshift-dependent shear from input shear maps specified by ctx.parameters.path_shear_map. Only first-order effects due to gamma are applied, kappa is completely ignored. There are three options: 1) The path is None, which will result in zero shear. 2) The path is a file readable by healpy. The file is then assumed to contain 3
healpix maps (kappa, gamma1, gamma2).
The path is and hdf5-file containing multiple, kappa-, gamma1- and gamma2-maps at given redshifts. The shear values are computed by interpolating linearly between the maps.
Evaluate hdf5 shear maps given at multiple redshifts for given redshifts and angular positions. :param path: path to hdf5 file containing shear maps; assumes that this file
contains four datasets: - z: redshifts of maps - kappa: kappa-maps - gamma1: gamma1-maps - gamma2: gamma2-maps
ra – right ascensions where maps will be evaluated
dec – declinations where maps will be evaluated
z – redshifts to which maps will be interpolated
kappa, gamma1 and gamma2
Reads in a healpix map and evaluates it at given positions. :param path: path where map is stored, assumes that file contains three maps (kappa,
gamma1, gamma2)
ra – right ascension where map is evaluated
dec – declinations where map is evaluated
kappa, gamma1 and gamma2 evaluated at input positions
Linearly interpolate to input redshifts between healpix maps at given redshifts. :param z_maps: redshifts of input maps, assumed to be ordered :param maps: input maps corresponding to z_maps, type: hdf5-dataset or numpy-array :param z: redshifts to which maps will be interpolated, assumed to be sorted :param pixel_ind: indices indicating pixels of input maps to interpolate, same size
as z
ind_intervals – indices splitting up z into chunks that lie between the maps
interpolated values
Linearly interpolate to input redshifts between healpix maps at given redshifts. :param z_maps: redshifts of input maps, assumed to be ordered :param maps: input maps corresponding to z_maps, type: hdf5-dataset or numpy-array :param z: redshifts to which maps will be interpolated, assumed to be sorted :param pixel_ind: indices indicating pixels of input maps to interpolate, same size
as z
ind_intervals – indices splitting up z into chunks that lie between the maps
interpolated values
Vectorized linear interpolation between two data points. :param x0: x-coordinates of first data points :param y0: y-coordinates of first data points :param x1: x-coordinates of second data points :param y1: y-coordinates of second data points :param x: positions where interpolation is evaluated :return: interpolated values
Created on Aug 2021 author: Tomasz Kacprzak
Created on Aug 2021 author: Tomasz Kacprzak
Created on Mar 5, 2018 author: Joerg Herbel
Created 2021 author: Tomasz Kacprzak
Created on Mar 5, 2018 author: Joerg Herbel
Bases: object
Class that gives extinction values for positions
Bases: BasePlugin
Generate a random catalog of galaxies with magnitudes in multiple bands.
Interface to direct magnitude calculation
Created on Aug 2021 author: Tomasz Kacprzak
Created on Aug 2021 author: Tomasz Kacprzak