Module: denclue_deblending

Overview

This module provides the implementation of the Table

Classes and Inheritance Structure

mary::

Table

Summary

DoDENCLUEDeblendingTask	Methods
do_denclue_deblending	This function implements the top-level algorithm for the Denclue-based deblending: * each parent cluster in the cluster_list is partitioned by the do_denclue_of_cluster() function.
do_denclue_of_cluster	This function sets-up the parameters for the DENCLUE partitioning of the parent clusters.
gauss_laplace_down_sampling	Performs the down sampling of the target coordinates to use in the Denclue.

Module API

class DoDENCLUEDeblendingTask(name='denclue_deblending', func=<function do_denclue_deblending>, parser=None, process=None)

Bases: asterism.pipeline_manager.analysis_tasks.AnalysisTask

Methods

add_par(name, \*\*kwargs)
get_par_value(name)
list_parameters()
run([extra_message])
set_par(name, \*\*kwargs)
set_pars_from_parser(args, argv, args_dict)
start_message([extra_message])
stop_message()

denclue_plot(denclue_debl, parent_cluster, target_coordinates=None, target_coordinates_w_array=None)

do_denclue_deblending(clusters_list, eps=0.1, h_frac=0.2, h_min=1.0, h_max=None, kernel='gauss', gl_downsampling=False, h_grid=3, gl_th_rel=0.1, attr_dbs_eps=1.0, attr_dbs_K=4.0, min_size=9, mask_unchanged=0.5, k_table_size=None, R_max_frac=1.0, R_max_kern_th=None, plot=False, verbose=False, digitize_attractors=False)

This function implements the top-level algorithm for the Denclue-based deblending:

• each parent cluster in the cluster_list is partitioned by the do_denclue_of_cluster() function.
• the parent cluster with his children clusters are used to build DeblendedProducts object
• a list of class:DeblendedProducts object is returned

Parameters:

clusters_list

eps

h_frac

kernel

gl_downsampling

attr_dbs_eps

attr_dbs_K

children_min_frac_integ_flux

children_min_frac_peak_flux

children_min_frac_size

children_bright_frac_peak_flux

min_size

mask_unchanged

k_table_size

R_max_frac

R_max_kern_th

plot

denclue_catalog

verbose

do_denclue_deblending

out_catalog

digitize_attractors

do_denclue_of_cluster(parent_cluster, min_size, kernel, eps, h_frac, h_min, attr_dbs_K, attr_dbs_eps, mask_unchanged, k_table_size, R_max_frac, R_max_kern_th, gl_th_rel=0.1, h_max=None, plot=False, digitize_attractors=False, gl_downsampling=False, h_grid=3, verbose=False)

This function sets-up the parameters for the DENCLUE partitioning of the parent clusters. The following features are

Parameters:

parent_cluster

min_size

kernel

eps

h_frac

attr_dbs_K

attr_dbs_eps

mask_unchanged

k_table_size

R_max_frac

R_max_kern_th

plot

digitize_attractors

gl_downsampling

gauss_laplace_down_sampling(parent_cluster, h, verbose=False, gl_th_rel=0.1, h_grid=3)

Performs the down sampling of the target coordinates to use in the Denclue.

• the cluster image is extracted

• local maxima are extracted using the BlobDetectionGaussLaplace

• if number of local maxima is leq 1 then

  • target_coordinates are set to None
  • target_coordinates_w_array are set to None

• if number of local maxima is geq 2 then

  • target_coordinates are obtained from a grid with size = max(1,h*0.5)
  • target_coordinates_w_array are obtained from the image flux at grid coordinates
  • coordinates and w_array corresponding to local maxima are added to the target arrays

Parameters:

parent_cluster :

h : float

sets the side of the grid and the max_sigma=h, and min_sigma=h*0.5 used in the BlobDetectionGaussLaplace

Returns:

target_coordinates :

target_coordinates_w_array :

get_pixel_matching_gauss_laplace_lm(parent_cluster, h, local_maxima_xy, off_x, off_y)

plot_final_clusters(parent_cluster, deblended_clusters_list)