Perturbation AUF Fortran Subroutines

Description

This module provides the Fortran code for the handling of the creation of perturbation component of the Astrometric Uncertainty Function.

Quick access

Routines:

fit_skew(), fourier_transform(), get_density(), histogram1d_dp(), ipos_dp(), perturb_aufs(), psf_perturb(), scatter_perturbers(), xval_dp()

Variables

  • perturbation_auf_fortran/dp [integer,parameter=kind(0.0d0)]
  • perturbation_auf_fortran/pi [real,parameter=4.0_dp*atan(1.0_dp)]

Subroutines and functions

subroutine  perturbation_auf_fortran/get_density(a_ax1, a_ax2, b_ax1, b_ax2, maxdist, counts)

Calculate the number of sources in a given catalogue within a specified radius of each source.

Parameters:

  • a_ax1 (*) [real,in]

  • a_ax2 (*) [real,in]

  • b_ax1 (*) [real,in]

  • b_ax2 (*) [real,in]

  • maxdist [real,in]

  • counts (size(a_ax1) [integer,out]

Call to:

haversine()

subroutine  perturbation_auf_fortran/perturb_aufs(narray, magarray, r, dr, rbins, j0s, mag_d, dmag_d, ds, n_norm, num_int, dmcut, psfr, psfsig, lentrials, seed, dd_params, l_cut, algorithm_type, fracgrid, fluxav, fouriergrid, rgrid, intrgrid)

Fortran wrapper for the perturbation AUF component calculation for a set of density-magnitude combinations, creating the various parameters needed to use the distribution of perturbations.

Parameters:

  • narray (*) [real,in]

  • magarray (*) [real,in]

  • r (*) [real,in]

  • dr (*) [real,in]

  • rbins (*) [real,in]

  • j0s (,) [real,in]

  • mag_d (*) [real,in]

  • dmag_d (*) [real,in]

  • ds (*) [real,in]

  • n_norm [real,in]

  • num_int (*) [integer,in]

  • dmcut (*) [real,in]

  • psfr [real,in]

  • psfsig [real,in]

  • lentrials [integer,in]

  • seed (,) [integer,in]

  • dd_params (,,*) [real,in]

  • l_cut (*) [real,in]

  • algorithm_type [character,in]

  • fracgrid (size(dmcut,size(narray) [real,out]

  • fluxav (size(narray) [real,out]

  • fouriergrid (size(j0s, 2,size(narray) [real,out]

  • rgrid (size(r,size(narray) [real,out]

  • intrgrid (size(r,size(narray) [real,out]

Call to:

scatter_perturbers(), histogram1d_dp(), fourier_transform()

subroutine  perturbation_auf_fortran/scatter_perturbers(dns, dms, psfr, maxk, dmcut, psfsig, offsets, fraccontam, fluxcontam, dd_params, l_cut, ddms, algorithm_type, lentrials, seed)

Given a set of average numbers of sources per PSF circle for a series of relative fluxes, populate a bright, central source’s PSF with randomly placed sources, and calculate the flux brightening and expected PSF centroid shift.

Parameters:

  • dns (*) [real,in]

  • dms (*) [real,in]

  • psfr [real,in]

  • maxk [integer,in]

  • dmcut (*) [real,in]

  • psfsig [real,in]

  • offsets (lentrials) [real,out]

  • fraccontam (size(dmcut) [real,out]

  • fluxcontam (lentrials) [real,out]

  • dd_params (,,*) [real,in]

  • l_cut (*) [real,in]

  • ddms (*) [real,in]

  • algorithm_type [character,in]

  • lentrials [integer,in]

  • seed (*) [integer,in]

Called from:

perturb_aufs()

Call to:

psf_perturb()

subroutine  perturbation_auf_fortran/psf_perturb(x, y, r, fs, dd_params, flux, psfsig, l_cut, xav, yav)

For a set of cartesian coordinates and relative fluxes for perturbers, depending on the flux of the objects, calculate different perturbation offsets based on Gaussian PSF model fits with constant background noise.

Parameters:

  • x (*) [real,in]

  • y (*) [real,in]

  • r (*) [real,in]

  • fs (*) [real,in]

  • dd_params (,,*) [real,in]

  • flux [real,in]

  • psfsig [real,in]

  • l_cut (*) [real,in]

  • xav [real,out]

  • yav [real,out]

Called from:

scatter_perturbers()

Call to:

fit_skew()

subroutine  perturbation_auf_fortran/fit_skew(params, x, l, y)

Calculate the skew-normal perturber effect, evaluated at some perturber separation x.

Parameters:

  • params (*) [real,in]

  • x [real,in]

  • l [real,in]

  • y [real,out]

Called from:

psf_perturb()

subroutine  perturbation_auf_fortran/xval_dp(xmin, xmax, i, nbin, xval)

Find central value of a bin for a regular histogram

Parameters:

  • xmin [real,in]

  • xmax [real,in]

  • i [integer,in]

  • nbin [integer,in]

  • xval [real,out]

Called from:

histogram1d_dp()

subroutine  perturbation_auf_fortran/ipos_dp(xmin, xmax, x, nbin, ipos)

Find bin a value falls in for a regular histogram

Parameters:

  • xmin [real,in]

  • xmax [real,in]

  • x [real,in]

  • nbin [integer,in]

  • ipos [integer,out]

Called from:

histogram1d_dp()

subroutine  perturbation_auf_fortran/histogram1d_dp(array, xmin, xmax, nbin, hist_x, hist_y[, mask[, weights]])

Bin 1D array of values into 1D regular histogram

Parameters:

  • array (*) [real,in]

  • xmin [real,in]

  • xmax [real,in]

  • nbin [integer,in]

  • hist_x (nbin) [real,out]

  • hist_y (nbin) [real,out]

  • mask (*) [logical,in,]

  • weights (*) [real,in,]

Called from:

perturb_aufs()

Call to:

ipos_dp(), xval_dp()

subroutine  perturbation_auf_fortran/fourier_transform(pr, r, dr, j0s, g)

Calculates the Fourier-Bessel transform, or Hankel transform of zeroth order, of a function. This is equivalent to a two-dimensional Fourier transform in the limiting case of circular symmetry.

Parameters:

  • pr (*) [real,in]

  • r (*) [real,in]

  • dr (*) [real,in]

  • j0s (,) [real,in]

  • g (size(j0s, 2) [real,out]

Called from:

perturb_aufs()