Module: denclue_watershed_deblending

class DoDenclueWatershedDeblendingTask(name='guass_laplace_watershed_deblending', func=<function do_denclue_watershed_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()

do_cluster_denclue_watershed_segmentation(parent_cluster, kernel, eps, min_size, h_frac, attr_dbs_eps, attr_dbs_K, h_min=None, h_max=None, h_grid=3.0, gl_th_rel=0.1, R_max_frac=1.0, R_max_kern_th=None, plot=False, verbose=False)

This function implements the cluster image segmentation based

• GaussLaplace local maxima (BlobDetectionGaussLaplace)
• watershed segmentation on the corresponding local maxima (watershed())

Parameters:

parent_cluster :n

min_size :

h_frac :

h_min :

th_rel :

plot :

Returns:

deblended_cluster_list

off_x

off_y

do_denclue_watershed_deblending(clusters_list, kernel, eps, attr_dbs_eps, attr_dbs_K, gl_th_rel=0.1, h_frac=0.1, h_min=1.0, h_max=None, h_grid=3.0, min_size=9, R_max_frac=1.0, R_max_kern_th=None, plot=False, verbose=False)

This function implements the top level algorithm for the denclue_watershed_deblending:

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

Parameters:

clusters_list

h_frac

h_min

th_rel

min_size

plot

verbose

Returns:

deblended_prod_list : list of DeblendedProducts objects

test_plot(parent_cluster_image, parent_cluster, denclue_attr_cl_centre, deblended_cluster_list, target_coordinates=None, dx=None, dy=None)