from __future__ import division, absolute_import, print_function
from ...pipeline_manager.analysis_tasks import AnalysisTask
from ...core.image_processing.filters import UnsharpFilter
from ...core.clustering.connectivity_based.connected_components import ConnectedComponents
from ...core.clustering.cluster_tools import get_cluster_closest_to_position
import numpy as np
__author__ = 'andrea tramacere'
[docs]def do_unsharp_cluster_func(original_cluster,image_bkg_value,cluster_th_level,u=0.8,sigma_factor=1.0,eval=True):
"""
Maps a cluster to circular shape: deprojection
Args:
cluster:
bkg_lvl:
Returns:
"""
image_original,off_set_x,off_set_y,masked_pixels=original_cluster.get_cluster_Image(bkg=image_bkg_value,border=2)
print(original_cluster.flux.min(),original_cluster.flux.max())
#image_resized.show()
#bkg=cluster.flux.min()
#Performs geom transformation of the image
#print("resizing size",size)
unsh=UnsharpFilter(sigma=original_cluster.r_cluster*sigma_factor,k=u)
image_f=image_original.filter(unsh,inplace=False)
x_c=image_f._center_x
y_c=image_f._center_y
#conn=ConnectedComponents(min_size=4)
#conn.run(image_circular.array,bkg_lvl,masked=image_circular.masked)
cluster_th_level=original_cluster.flux.min()
#masked_bg=image_circular.array<cluster_th_level
#masked=np.logical_or(masked_bg,image_circular.masked)
conn=ConnectedComponents(1)
conn.run(image_f.array,cluster_th_level,masked=image_original.masked)
clusters_list=[]
print('|clusters found segmenting unsharp image',len(conn.clusters_list),'with bkg level',cluster_th_level)
central_cluster=get_cluster_closest_to_position(conn.clusters_list,x_c=x_c,y_c=y_c)
# import pylab as plt
# from asterism.plotting.plot_tools import show_image,plot_contour
# fig,(ax1,ax2)=plt.subplots(1,2)
# ax1.imshow(image_original.array,interpolation='nearest')
# ax2.imshow(image_f.array,interpolation='nearest')
# plot_contour(ax1,original_cluster.contour_shape[:,0]-off_set_x,original_cluster.contour_shape[:,1]-off_set_y,'w')
# for cl in conn.clusters_list:
# cl=cl.SourceCluster_factory()
# if hasattr(cl,'contour_shape'):
# if cl.contour_shape is not None:
# plot_contour(ax2,cl.contour_shape[:,0],cl.contour_shape[:,1],'w')
# plt.show()
if central_cluster is not None:
for ID,pos in enumerate(central_cluster.position_array):
central_cluster.weight_array[ID]=image_original.array[np.int(pos[1]),np.int(pos[0])]
print('central cluster cl_size',central_cluster.size)
return central_cluster.SourceCluster_factory(ID=original_cluster.ID,x_off_set=off_set_x,y_off_set=off_set_y)
else:
return original_cluster
[docs]class DoUnsharpCluster(AnalysisTask):
def __init__(self, name='unsharp_cluster', func=do_unsharp_cluster_func, parser=None, process=None):
super(DoUnsharpCluster,self).__init__(name=name,func=func,parser=parser,process=process)
self.parameters_list.add_par('-eval',help=' ',action='store_true')
self.parameters_list.add_par('-u', type=np.float ,help='',default=0.5)
self.parameters_list.add_par('-sigma_factor', type=np.float ,help='',default=1.0)
self.func=func
