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 = []
