import math # mathematical functions import subprocess # calling to the terminal from astropy.io import fits # Open and Reading FITS Files usign astropy import random # pseudo-random generator import seaborn as sns # Improvements for statistical-plots from WL_Utils import sex_caller from Class_CrossMatching import CrossMatching from Class_CatalogReader import CatalogReader # Get first catalogs # sex_caller('lhn1n1_2010apr_r_stack_fc_fix.fits', 'lhn1n1_2010apr_r_stack_fc_fix') # sex_caller('lhn1n1_2010dec_z_stack_fc_fix.fits', 'lhn1n1_2010dec_z_stack_fc_fix') # Read catalogs catag_r = CatalogReader("lhn1n1_2010apr_r_stack_fc_fix.cat") catag_r.read() catag_z = CatalogReader("lhn1n1_2010dec_z_stack_fc_fix.cat") catag_z.read() # Give value to the cross-matching radius r = 3 # Create object for cross-matching crossmatching = CrossMatching(catag_r.fcat, catag_z.fcat) crossmatching.kdtree(n=r * 1e-06) crossmatching.catalog_writter("lhn1n1_crossmatching_1to2", compare="1to2") print "\n" crossmatching.catalog_writter("lhn1n1_crossmatching_2to1", compare="2to1")
mag_output_wayback = [] mag_output_error_sex = [] mag_output_error_wayback = [] flux_input = [] flux_output = [] flux_output_error = [] flux_output_max = [] flux_output_max_error = [] number_lost_objects = [] # Call Source Extractor catalog_name = sex_caller("{}.fits".format(PICTURE), "{}_{}".format(PICTURE, FILTER)) # Read catalog catag = CatalogReader(catalog_name) catag.read() # Create object for simulation simulation = ObjectCreator(catag.fcat) simulation.general_histograms(catag.fcat) print "\nMasking . . . {}\n" # For-loop for 1 to 30 mag for mag in mag_input: simulation.matrix_data = [] simulation.masking_matrix("{}.fits".format(PICTURE)) print "\nRound {}\n".format(mag) simulation.packing_percentage(number_objects=4000) simulation.out_mag = []