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pyt_VL01_compare_sdssmoc_to_macadamia2.py
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import re
import sys
import time
import datetime
import math
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import matplotlib.colors as mcolors
import scipy
from scipy.stats import norm
from scipy import optimize
import urllib.request
from astropy.table import Table
import glob, os, bz2, subprocess
import os.path
from numpy import linspace
from decimal import *
import statistics
from astroquery.jplsbdb import SBDB
import macadamia_functions as mcd
##### UPDATED 5/6/21 #####
##### FUNCTION DEFINITIONS -- SDSS DATA HANDLING #####
def parse_sdssmoc_table(sdssmoc_filepath,sdssmoc_output_filepath,resolved_sdssmoc_name_log,keep_going,path_logfile,path_errorfile):
if keep_going:
try:
mcd.output_log_entry(path_logfile,'Reading in SDSS MOC data...')
with open(sdssmoc_output_filepath,'w') as of:
of.write('AstNum MJD RA Dec gmag gerr rmag rerr imag ierr zmag zerr\n')
with open(resolved_sdssmoc_name_log,'w') as of:
of.write('Log of resolved SDSS MOC asteroid designations\n')
num_lines = sum(1 for line in open(sdssmoc_filepath))
print('>>> Scanning {:d} lines...'.format(num_lines))
num_objs = 0
print('>>> 0...',end='')
with open(sdssmoc_filepath) as input_file:
#for _ in range(2): #skip first two header lines
# next(input_file)
for line in input_file:
num_objs += 1
if num_objs % 10000 == 0: print('{:d}...'.format(num_objs),end='')
if num_objs % 100000 == 0: print('\n>>> ',end='')
mjd = float(line[46:57])
ra = float(line[58:68])
dec = float(line[70:79])
gmag = float(line[174:179])
gerr = float(line[180:184])
rmag = float(line[185:190])
rerr = float(line[191:195])
imag = float(line[196:201])
ierr = float(line[202:206])
zmag = float(line[207:212])
zerr = float(line[213:217])
flag_id = int(line[242:243])
ast_num = int(line[245:251])
#ast_desig = int(line[245:251])
prov_desig_temp = line[252:264].strip()
if ast_num == 0 and prov_desig_temp != '-':
#with open(resolved_sdssmoc_name_log,'a') as of:
# of.write('{:s} - {:s} ==> {:d}.\n'.format(datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'),prov_desig,ast_num))
prov_desig = ''
for idx in range(0,len(prov_desig_temp)):
if prov_desig_temp[idx] != '_': prov_desig = prov_desig + prov_desig_temp[idx]
else: prov_desig = prov_desig + ' '
sbdb_data = SBDB.query(prov_desig)
if 'object' in sbdb_data:
if sbdb_data['object']['des'].isnumeric():
ast_num = int(sbdb_data['object']['des'])
with open(resolved_sdssmoc_name_log,'a') as of:
of.write('{:s} - {:s} ==> {:d}.\n'.format(datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'),prov_desig,ast_num))
else:
with open(resolved_sdssmoc_name_log,'a') as of:
of.write('{:s} - No numerical designation available for {:s}.\n'.format(datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'),prov_desig))
else:
with open(resolved_sdssmoc_name_log,'a') as of:
of.write('{:s} - JPL look-up of {:s} failed.\n'.format(datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'),prov_desig))
if flag_id == 1 and ast_num != 0:
with open(sdssmoc_output_filepath,'a') as of:
of.write('{:>6d} {:11.5f} {:10.6f} {:10.6f} {:5.2f} {:4.2f} {:5.2f} {:4.2f} {:5.2f} {:4.2f} {:5.2f} {:4.2f}\n'.format(ast_num,mjd,ra,dec,gmag,gerr,rmag,rerr,imag,ierr,zmag,zerr))
#sdssmoc_table.add_row((ast_num,mjd,ra,dec,gmag,gerr,rmag,rerr,imag,ierr,zmag,zerr))
mcd.output_log_entry(path_logfile,'\n Parsing SDSS MOC data complete.')
except Exception as e:
mcd.output_error_log_entry(path_logfile,path_errorfile,'Function failed: parse_sdssmoc_table()')
mcd.output_error_log_entry_nonstring(path_logfile,path_errorfile,e)
keep_going = False
else:
mcd.output_log_entry(path_logfile,'Function skipped: parse_sdssmoc_table()')
return keep_going
def create_sdssmoc_table(sdssmoc_output_filepath,keep_going,path_logfile,path_errorfile):
if keep_going:
try:
mcd.output_log_entry(path_logfile,'Creating SDSS MOC table...')
ast_num = np.genfromtxt(sdssmoc_output_filepath,skip_header=1,usecols=(0))
mjd = np.genfromtxt(sdssmoc_output_filepath,skip_header=1,usecols=(1))
ra = np.genfromtxt(sdssmoc_output_filepath,skip_header=1,usecols=(2))
dec = np.genfromtxt(sdssmoc_output_filepath,skip_header=1,usecols=(3))
gmag = np.genfromtxt(sdssmoc_output_filepath,skip_header=1,usecols=(4))
gerr = np.genfromtxt(sdssmoc_output_filepath,skip_header=1,usecols=(5))
rmag = np.genfromtxt(sdssmoc_output_filepath,skip_header=1,usecols=(6))
rerr = np.genfromtxt(sdssmoc_output_filepath,skip_header=1,usecols=(7))
imag = np.genfromtxt(sdssmoc_output_filepath,skip_header=1,usecols=(8))
ierr = np.genfromtxt(sdssmoc_output_filepath,skip_header=1,usecols=(9))
zmag = np.genfromtxt(sdssmoc_output_filepath,skip_header=1,usecols=(10))
zerr = np.genfromtxt(sdssmoc_output_filepath,skip_header=1,usecols=(11))
mcd.output_log_entry(path_logfile,'>>> SDSS MOC table created with {:d} detections of numbered asteroids...'.format(len(ast_num)))
sdssmoc_table = Table([ast_num,mjd,ra,dec,gmag,gerr,rmag,rerr,imag,ierr,zmag,zerr],
names=('ast_num','mjd','ra','dec','gmag','gerr','rmag','rerr','imag','ierr','zmag','zerr'), \
dtype=('i8','f8','f8','f8','f8','f8','f8','f8','f8','f8','f8','f8'))
sdssmoc_table.sort('ast_num') # sort SDSS MOC table in increasing asteroid numerical designation
mcd.output_log_entry(path_logfile,'Creation of SDSS MOC table complete.')
except Exception as e:
mcd.output_error_log_entry(path_logfile,path_errorfile,'Function failed: create_sdssmoc_table()')
mcd.output_error_log_entry_nonstring(path_logfile,path_errorfile,e)
keep_going = False
else:
mcd.output_log_entry(path_logfile,'Function skipped: create_sdssmoc_table()')
return sdssmoc_table,keep_going
def match_detection(idx_sdss,sdss_filter,mag_sdss,merr_sdss,sdssmoc_table,detection_id_mac,desig_num_mac,exp_start_jd_mac,mag_mac,magerr_mac,path_logfile):
#idx_mac = 0
mac_entry_found = False
idx_mac,mag_diff_sdss_mac,mag_diff_err_sdss_mac = 0,0,0
if sdss_filter == 'g':
for idx_mac in range(0,len(desig_num_mac)):
if desig_num_mac[idx_mac] == sdssmoc_table['ast_num'][idx_sdss]:
if abs((exp_start_jd_mac[idx_mac]-2400000.5)-sdssmoc_table['mjd'][idx_sdss]) < 0.005:
mac_entry_found = True
mcd.output_log_entry(path_logfile,'>> SDSS entry {:d} ({:s}-band) matched to MACADAMIA detection {:d}.'.format(idx_sdss,sdss_filter,int(detection_id_mac[idx_mac])))
if sdssmoc_table['gmag'][idx_sdss] != 99.99:
mag_diff_sdss_mac = mag_mac[idx_mac] - mag_sdss
mag_diff_err_sdss_mac = (magerr_mac[idx_mac]**2 + merr_sdss**2)**0.5
return mac_entry_found,idx_mac,mag_diff_sdss_mac,mag_diff_err_sdss_mac
if sdss_filter == 'r':
for idx_mac in range(0,len(desig_num_mac)):
if desig_num_mac[idx_mac] == sdssmoc_table['ast_num'][idx_sdss]:
if abs((exp_start_jd_mac[idx_mac]-2400000.5)-sdssmoc_table['mjd'][idx_sdss]) < 0.005:
mac_entry_found = True
mcd.output_log_entry(path_logfile,'>> SDSS entry {:d} ({:s}-band) matched to MACADAMIA detection {:d}.'.format(idx_sdss,sdss_filter,int(detection_id_mac[idx_mac])))
if sdssmoc_table['rmag'][idx_sdss] != 99.99:
mag_diff_sdss_mac = mag_mac[idx_mac] - mag_sdss
mag_diff_err_sdss_mac = (magerr_mac[idx_mac]**2 + merr_sdss**2)**0.5
return mac_entry_found,idx_mac,mag_diff_sdss_mac,mag_diff_err_sdss_mac
if sdss_filter == 'i':
for idx_mac in range(0,len(desig_num_mac)):
if desig_num_mac[idx_mac] == sdssmoc_table['ast_num'][idx_sdss]:
if abs((exp_start_jd_mac[idx_mac]-2400000.5)-sdssmoc_table['mjd'][idx_sdss]) < 0.005:
mac_entry_found = True
mcd.output_log_entry(path_logfile,'>> SDSS entry {:d} ({:s}-band) matched to MACADAMIA detection {:d}.'.format(idx_sdss,sdss_filter,int(detection_id_mac[idx_mac])))
if sdssmoc_table['imag'][idx_sdss] != 99.99:
mag_diff_sdss_mac = mag_mac[idx_mac] - mag_sdss
mag_diff_err_sdss_mac = (magerr_mac[idx_mac]**2 + merr_sdss**2)**0.5
return mac_entry_found,idx_mac,mag_diff_sdss_mac,mag_diff_err_sdss_mac
if sdss_filter == 'z':
for idx_mac in range(0,len(desig_num_mac)):
if desig_num_mac[idx_mac] == sdssmoc_table['ast_num'][idx_sdss]:
if abs((exp_start_jd_mac[idx_mac]-2400000.5)-sdssmoc_table['mjd'][idx_sdss]) < 0.005:
mac_entry_found = True
mcd.output_log_entry(path_logfile,'>> SDSS entry {:d} ({:s}-band) matched to MACADAMIA detection {:d}.'.format(idx_sdss,sdss_filter,int(detection_id_mac[idx_mac])))
if sdssmoc_table['zmag'][idx_sdss] != 99.99:
mag_diff_sdss_mac = mag_mac[idx_mac] - mag_sdss
mag_diff_err_sdss_mac = (magerr_mac[idx_mac]**2 + merr_sdss**2)**0.5
return mac_entry_found,idx_mac,mag_diff_sdss_mac,mag_diff_err_sdss_mac
return mac_entry_found,idx_mac,mag_diff_sdss_mac,mag_diff_err_sdss_mac
def create_sdss_macadamia_comparison_files2(sdssmoc_table,macadamia_output_filepath,sdss_vs_macadamia_filepath,keep_going,path_logfile,path_errorfile):
outlier_threshold = 0.3 # maximum allowable abs(mag_macadamia-mag_sdss) for outlier removal
highprecision_threshold = 0.1 # maximum mag err for either SDSS or MACADAMIA photometry for high-precision data selection
if keep_going:
mcd.output_log_entry(path_logfile,'Creating SDSS/MACADAMIA comparison files...')
#mcd.decompress_file_gzip(macadamia_output_filepath)
macadamia_output_g_filepath = macadamia_output_filepath[:-4] + '_g.dat'
macadamia_output_r_filepath = macadamia_output_filepath[:-4] + '_r.dat'
macadamia_output_i_filepath = macadamia_output_filepath[:-4] + '_i.dat'
macadamia_output_z_filepath = macadamia_output_filepath[:-4] + '_z.dat'
sdss_vs_macadamia_filepath_all = sdss_vs_macadamia_filepath[:-4] + '_all.dat'
sdss_vs_macadamia_filepath_notfound = sdss_vs_macadamia_filepath[:-4] + '_notfound.dat'
sdss_vs_macadamia_filepath_g = sdss_vs_macadamia_filepath[:-4] + '_g.dat'
sdss_vs_macadamia_filepath_r = sdss_vs_macadamia_filepath[:-4] + '_r.dat'
sdss_vs_macadamia_filepath_i = sdss_vs_macadamia_filepath[:-4] + '_i.dat'
sdss_vs_macadamia_filepath_z = sdss_vs_macadamia_filepath[:-4] + '_z.dat'
sdss_vs_macadamia_filepath_g_or = sdss_vs_macadamia_filepath[:-4] + '_g_or.dat'
sdss_vs_macadamia_filepath_r_or = sdss_vs_macadamia_filepath[:-4] + '_r_or.dat'
sdss_vs_macadamia_filepath_i_or = sdss_vs_macadamia_filepath[:-4] + '_i_or.dat'
sdss_vs_macadamia_filepath_z_or = sdss_vs_macadamia_filepath[:-4] + '_z_or.dat'
sdss_vs_macadamia_filepath_g_hp = sdss_vs_macadamia_filepath[:-4] + '_g_hp.dat'
sdss_vs_macadamia_filepath_r_hp = sdss_vs_macadamia_filepath[:-4] + '_r_hp.dat'
sdss_vs_macadamia_filepath_i_hp = sdss_vs_macadamia_filepath[:-4] + '_i_hp.dat'
sdss_vs_macadamia_filepath_z_hp = sdss_vs_macadamia_filepath[:-4] + '_z_hp.dat'
mcd.output_log_entry(path_logfile,'Reading in MACADAMIA data...')
mcd.output_log_entry(path_logfile,'Reading in detection IDs...')
detection_id_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(0))
detection_id_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(0))
detection_id_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(0))
detection_id_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(0))
mcd.output_log_entry(path_logfile,'Reading in numerical designations...')
desig_num_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(1))
desig_num_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(1))
desig_num_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(1))
desig_num_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(1))
mcd.output_log_entry(path_logfile,'Reading in exposure start times...')
exp_start_jd_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(10))
exp_start_jd_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(10))
exp_start_jd_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(10))
exp_start_jd_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(10))
mcd.output_log_entry(path_logfile,'Reading in distances to predicted positions...')
dist_pred_postn_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(31))
dist_pred_postn_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(31))
dist_pred_postn_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(31))
dist_pred_postn_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(31))
mcd.output_log_entry(path_logfile,'Reading in measured magnitudes and uncertainties...')
mag_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(34))
mag_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(34))
mag_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(34))
mag_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(34))
magerr_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(35))
magerr_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(35))
magerr_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(35))
magerr_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(35))
mcd.output_log_entry(path_logfile,'Reading in SNRs...')
snr_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(37))
snr_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(37))
snr_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(37))
snr_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(37))
mcd.output_log_entry(path_logfile,'Reading in trail lengths and FWHMs...')
trail_length_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(38))
trail_length_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(38))
trail_length_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(38))
trail_length_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(38))
trail_fwhm_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(39))
trail_fwhm_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(39))
trail_fwhm_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(39))
trail_fwhm_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(39))
trail_len_pred_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(71))
trail_len_pred_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(71))
trail_len_pred_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(71))
trail_len_pred_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(71))
mcd.output_log_entry(path_logfile,'Reading in distances and magnitudes to closest sources...')
dist_src1_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(44))
dist_src1_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(44))
dist_src1_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(44))
dist_src1_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(44))
mag_src1_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(45))
mag_src1_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(45))
mag_src1_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(45))
mag_src1_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(45))
dist_src2_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(50))
dist_src2_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(50))
dist_src2_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(50))
dist_src2_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(50))
mag_src2_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(51))
mag_src2_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(51))
mag_src2_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(51))
mag_src2_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(51))
dist_src3_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(56))
dist_src3_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(56))
dist_src3_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(56))
dist_src3_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(56))
mag_src3_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(57))
mag_src3_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(57))
mag_src3_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(57))
mag_src3_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(57))
mcd.output_log_entry(path_logfile,'Reading in global and local source densities...')
src_density_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(21))
src_density_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(21))
src_density_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(21))
src_density_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(21))
local_srcdn_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(59))
local_srcdn_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(59))
local_srcdn_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(59))
local_srcdn_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(59))
mcd.output_log_entry(path_logfile,'Reading in distances to edges...')
dist_edge_l_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(60))
dist_edge_l_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(60))
dist_edge_l_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(60))
dist_edge_l_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(60))
dist_edge_r_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(61))
dist_edge_r_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(61))
dist_edge_r_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(61))
dist_edge_r_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(61))
dist_edge_b_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(62))
dist_edge_b_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(62))
dist_edge_b_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(62))
dist_edge_b_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(62))
dist_edge_t_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(63))
dist_edge_t_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(63))
dist_edge_t_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(63))
dist_edge_t_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(63))
mcd.output_log_entry(path_logfile,'Reading in zero point parameters...')
zpoint_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(15))
zpoint_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(15))
zpoint_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(15))
zpoint_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(15))
zpt_nstars_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(17))
zpt_nstars_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(17))
zpt_nstars_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(17))
zpt_nstars_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(17))
mcd.output_log_entry(path_logfile,'Reading in limiting magnitudes...')
limit_mag_ps_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(18))
limit_mag_ps_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(18))
limit_mag_ps_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(18))
limit_mag_ps_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(18))
limit_mag_sb_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(19))
limit_mag_sb_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(19))
limit_mag_sb_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(19))
limit_mag_sb_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(19))
mcd.output_log_entry(path_logfile,'Reading in seeing measurements...')
psf_width_mean_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(20))
psf_width_mean_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(20))
psf_width_mean_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(20))
psf_width_mean_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(20))
psf_width_src_mac_g = np.genfromtxt(macadamia_output_g_filepath,skip_header=1,usecols=(36))
psf_width_src_mac_r = np.genfromtxt(macadamia_output_r_filepath,skip_header=1,usecols=(36))
psf_width_src_mac_i = np.genfromtxt(macadamia_output_i_filepath,skip_header=1,usecols=(36))
psf_width_src_mac_z = np.genfromtxt(macadamia_output_z_filepath,skip_header=1,usecols=(36))
num_dets_mac_g = len(detection_id_mac_g)
num_dets_mac_r = len(detection_id_mac_r)
num_dets_mac_i = len(detection_id_mac_i)
num_dets_mac_z = len(detection_id_mac_z)
#mcd.output_log_entry(path_logfile,'Reading in filter names...')
#filter_name_mac = [0 for idx in range(num_dets_mac)]
#idx_mac = 0
#with open(macadamia_output_filepath) as input_file:
# for _ in range(1): #skip first header line
# next(input_file)
# for line in input_file:
# filter_name_mac[idx_mac] = line[125:135].strip()
# idx_mac += 1
header_line = 'detection_id desig_num filt mjd_start mag merr mjd_sdss mag_sdss merr_sdss mag_diff mag_diff_err snr src_density local_srcdn dist_pred_postn trail_predln trail_length trail_fwhm dist_src1 mag_src1 dist_src2 mag_src2 dist_src3 mag_src3 dist_edge zpoint zpt_nstars lim_mag_ps lim_mag_sb mean_seeing src_seeing\n'
with open(sdss_vs_macadamia_filepath_notfound,'w') as of: of.write(header_line)
with open(sdss_vs_macadamia_filepath_all,'w') as of: of.write(header_line)
with open(sdss_vs_macadamia_filepath_g,'w') as of: of.write(header_line)
with open(sdss_vs_macadamia_filepath_r,'w') as of: of.write(header_line)
with open(sdss_vs_macadamia_filepath_i,'w') as of: of.write(header_line)
with open(sdss_vs_macadamia_filepath_z,'w') as of: of.write(header_line)
with open(sdss_vs_macadamia_filepath_g_or,'w') as of: of.write(header_line)
with open(sdss_vs_macadamia_filepath_r_or,'w') as of: of.write(header_line)
with open(sdss_vs_macadamia_filepath_i_or,'w') as of: of.write(header_line)
with open(sdss_vs_macadamia_filepath_z_or,'w') as of: of.write(header_line)
with open(sdss_vs_macadamia_filepath_g_hp,'w') as of: of.write(header_line)
with open(sdss_vs_macadamia_filepath_r_hp,'w') as of: of.write(header_line)
with open(sdss_vs_macadamia_filepath_i_hp,'w') as of: of.write(header_line)
with open(sdss_vs_macadamia_filepath_z_hp,'w') as of: of.write(header_line)
outliers_g,outliers_r,outliers_i,outliers_z = 0,0,0,0
higherr_g,higherr_r,higherr_i,higherr_z = 0,0,0,0
for idx_sdss in range(0,len(sdssmoc_table)):
try:
mcd.output_log_entry(path_logfile,'Matching asteroid {:d} at {:.5f} (SDSS entry {:d})...'.format(int(sdssmoc_table['ast_num'][idx_sdss]),sdssmoc_table['mjd'][idx_sdss],idx_sdss))
sdss_filters = ['g','r','i','z']
for sdss_filter in sdss_filters:
#print(' >>> {:s}-band...'.format(sdss_filter))
#log_file.write(' >>> {:s}-band...\n'.format(sdss_filter))
if sdss_filter == 'g':
mag_sdss = sdssmoc_table['gmag'][idx_sdss]
merr_sdss = sdssmoc_table['gerr'][idx_sdss]
if sdss_filter == 'r':
mag_sdss = sdssmoc_table['rmag'][idx_sdss]
merr_sdss = sdssmoc_table['rerr'][idx_sdss]
if sdss_filter == 'i':
mag_sdss = sdssmoc_table['imag'][idx_sdss]
merr_sdss = sdssmoc_table['ierr'][idx_sdss]
if sdss_filter == 'z':
mag_sdss = sdssmoc_table['zmag'][idx_sdss]
merr_sdss = sdssmoc_table['zerr'][idx_sdss]
#idx_mac = 0
#mac_entry_found = False
if sdss_filter == 'g':
mac_entry_found,idx_mac,mag_diff_sdss_mac,mag_diff_err_sdss_mac = match_detection(idx_sdss,sdss_filter,mag_sdss,merr_sdss,sdssmoc_table,detection_id_mac_g,desig_num_mac_g,exp_start_jd_mac_g,mag_mac_g,magerr_mac_g,path_logfile)
if sdss_filter == 'r':
mac_entry_found,idx_mac,mag_diff_sdss_mac,mag_diff_err_sdss_mac = match_detection(idx_sdss,sdss_filter,mag_sdss,merr_sdss,sdssmoc_table,detection_id_mac_r,desig_num_mac_r,exp_start_jd_mac_r,mag_mac_r,magerr_mac_r,path_logfile)
if sdss_filter == 'i':
mac_entry_found,idx_mac,mag_diff_sdss_mac,mag_diff_err_sdss_mac = match_detection(idx_sdss,sdss_filter,mag_sdss,merr_sdss,sdssmoc_table,detection_id_mac_i,desig_num_mac_i,exp_start_jd_mac_i,mag_mac_i,magerr_mac_i,path_logfile)
if sdss_filter == 'z':
mac_entry_found,idx_mac,mag_diff_sdss_mac,mag_diff_err_sdss_mac = match_detection(idx_sdss,sdss_filter,mag_sdss,merr_sdss,sdssmoc_table,detection_id_mac_z,desig_num_mac_z,exp_start_jd_mac_z,mag_mac_z,magerr_mac_z,path_logfile)
if mac_entry_found:
if sdss_filter == 'g':
# find distance to nearest chip edge
dist_edge_mac = dist_edge_l_mac_g[idx_mac]
if dist_edge_r_mac_g[idx_mac] < dist_edge_mac: dist_edge_mac = dist_edge_r_mac_g[idx_mac]
if dist_edge_t_mac_g[idx_mac] < dist_edge_mac: dist_edge_mac = dist_edge_t_mac_g[idx_mac]
if dist_edge_b_mac_g[idx_mac] < dist_edge_mac: dist_edge_mac = dist_edge_b_mac_g[idx_mac]
# write detection data to sdss vs. macadamia output file
output_line = '{:>12d} {:>9d} {:1s} {:11.5f} {:5.2f} {:5.2f} {:11.5f} {:5.2f} {:5.2f} {:5.2f} {:5.2f} {:7.1f} {:11.3f} {:11.3f} {:15.3f} {:12.3f} {:12.3f} {:10.3f} {:9.3f} {:8.3f} {:9.3f} {:8.3f} {:9.3f} {:8.3f} {:9.1f} {:6.3f} {:>10d} {:10.3f} {:10.3f} {:11.3f} {:10.3f}\n'.format(int(detection_id_mac_g[idx_mac]),int(desig_num_mac_g[idx_mac]),'g',exp_start_jd_mac_g[idx_mac],mag_mac_g[idx_mac],magerr_mac_g[idx_mac],sdssmoc_table['mjd'][idx_sdss],mag_sdss,merr_sdss,mag_diff_sdss_mac,mag_diff_err_sdss_mac,snr_mac_g[idx_mac],src_density_mac_g[idx_mac],local_srcdn_mac_g[idx_mac],dist_pred_postn_mac_g[idx_mac],trail_len_pred_mac_g[idx_mac],trail_length_mac_g[idx_mac],trail_fwhm_mac_g[idx_mac],dist_src1_mac_g[idx_mac],mag_src1_mac_g[idx_mac],dist_src2_mac_g[idx_mac],mag_src2_mac_g[idx_mac],dist_src3_mac_g[idx_mac],mag_src3_mac_g[idx_mac],dist_edge_mac,zpoint_mac_g[idx_mac],int(zpt_nstars_mac_g[idx_mac]),limit_mag_ps_mac_g[idx_mac],limit_mag_sb_mac_g[idx_mac],psf_width_mean_mac_g[idx_mac],psf_width_src_mac_g[idx_mac])
if snr_mac_g[idx_mac] != -999:
with open(sdss_vs_macadamia_filepath_all,'a') as of:
of.write(output_line)
with open(sdss_vs_macadamia_filepath_g,'a') as of:
of.write(output_line)
if abs(mag_mac_g[idx_mac] - mag_sdss) < outlier_threshold:
with open(sdss_vs_macadamia_filepath_g_or,'a') as of:
of.write(output_line)
else:
outliers_g += 1
if magerr_mac_g[idx_mac] < highprecision_threshold and merr_sdss < highprecision_threshold:
with open(sdss_vs_macadamia_filepath_g_hp,'a') as of:
of.write(output_line)
else:
higherr_g += 1
if sdss_filter == 'r':
# find distance to nearest chip edge
dist_edge_mac = dist_edge_l_mac_r[idx_mac]
if dist_edge_r_mac_r[idx_mac] < dist_edge_mac: dist_edge_mac = dist_edge_r_mac_r[idx_mac]
if dist_edge_t_mac_r[idx_mac] < dist_edge_mac: dist_edge_mac = dist_edge_t_mac_r[idx_mac]
if dist_edge_b_mac_r[idx_mac] < dist_edge_mac: dist_edge_mac = dist_edge_b_mac_r[idx_mac]
# write detection data to sdss vs. macadamia output file
output_line = '{:>12d} {:>9d} {:1s} {:11.5f} {:5.2f} {:5.2f} {:11.5f} {:5.2f} {:5.2f} {:5.2f} {:5.2f} {:7.1f} {:11.3f} {:11.3f} {:15.3f} {:12.3f} {:12.3f} {:10.3f} {:9.3f} {:8.3f} {:9.3f} {:8.3f} {:9.3f} {:8.3f} {:9.1f} {:6.3f} {:>10d} {:10.3f} {:10.3f} {:11.3f} {:10.3f}\n'.format(int(detection_id_mac_r[idx_mac]),int(desig_num_mac_r[idx_mac]),'r',exp_start_jd_mac_r[idx_mac],mag_mac_r[idx_mac],magerr_mac_r[idx_mac],sdssmoc_table['mjd'][idx_sdss],mag_sdss,merr_sdss,mag_diff_sdss_mac,mag_diff_err_sdss_mac,snr_mac_r[idx_mac],src_density_mac_r[idx_mac],local_srcdn_mac_r[idx_mac],dist_pred_postn_mac_r[idx_mac],trail_len_pred_mac_r[idx_mac],trail_length_mac_r[idx_mac],trail_fwhm_mac_r[idx_mac],dist_src1_mac_r[idx_mac],mag_src1_mac_r[idx_mac],dist_src2_mac_r[idx_mac],mag_src2_mac_r[idx_mac],dist_src3_mac_r[idx_mac],mag_src3_mac_r[idx_mac],dist_edge_mac,zpoint_mac_r[idx_mac],int(zpt_nstars_mac_r[idx_mac]),limit_mag_ps_mac_r[idx_mac],limit_mag_sb_mac_r[idx_mac],psf_width_mean_mac_g[idx_mac],psf_width_src_mac_r[idx_mac])
if snr_mac_r[idx_mac] != -999:
with open(sdss_vs_macadamia_filepath_all,'a') as of:
of.write(output_line)
with open(sdss_vs_macadamia_filepath_r,'a') as of:
of.write(output_line)
if abs(mag_mac_r[idx_mac] - mag_sdss) < outlier_threshold:
with open(sdss_vs_macadamia_filepath_r_or,'a') as of:
of.write(output_line)
else:
outliers_r += 1
if magerr_mac_r[idx_mac] < highprecision_threshold and merr_sdss < highprecision_threshold:
with open(sdss_vs_macadamia_filepath_r_hp,'a') as of:
of.write(output_line)
else:
higherr_r += 1
if sdss_filter == 'i':
# find distance to nearest chip edge
dist_edge_mac = dist_edge_l_mac_i[idx_mac]
if dist_edge_r_mac_i[idx_mac] < dist_edge_mac: dist_edge_mac = dist_edge_r_mac_i[idx_mac]
if dist_edge_t_mac_i[idx_mac] < dist_edge_mac: dist_edge_mac = dist_edge_t_mac_i[idx_mac]
if dist_edge_b_mac_i[idx_mac] < dist_edge_mac: dist_edge_mac = dist_edge_b_mac_i[idx_mac]
# write detection data to sdss vs. macadamia output file
output_line = '{:>12d} {:>9d} {:1s} {:11.5f} {:5.2f} {:5.2f} {:11.5f} {:5.2f} {:5.2f} {:5.2f} {:5.2f} {:7.1f} {:11.3f} {:11.3f} {:15.3f} {:12.3f} {:12.3f} {:10.3f} {:9.3f} {:8.3f} {:9.3f} {:8.3f} {:9.3f} {:8.3f} {:9.1f} {:6.3f} {:>10d} {:10.3f} {:10.3f} {:11.3f} {:10.3f}\n'.format(int(detection_id_mac_i[idx_mac]),int(desig_num_mac_i[idx_mac]),'i',exp_start_jd_mac_i[idx_mac],mag_mac_i[idx_mac],magerr_mac_i[idx_mac],sdssmoc_table['mjd'][idx_sdss],mag_sdss,merr_sdss,mag_diff_sdss_mac,mag_diff_err_sdss_mac,snr_mac_i[idx_mac],src_density_mac_i[idx_mac],local_srcdn_mac_i[idx_mac],dist_pred_postn_mac_i[idx_mac],trail_len_pred_mac_i[idx_mac],trail_length_mac_i[idx_mac],trail_fwhm_mac_i[idx_mac],dist_src1_mac_i[idx_mac],mag_src1_mac_i[idx_mac],dist_src2_mac_i[idx_mac],mag_src2_mac_i[idx_mac],dist_src3_mac_i[idx_mac],mag_src3_mac_i[idx_mac],dist_edge_mac,zpoint_mac_i[idx_mac],int(zpt_nstars_mac_i[idx_mac]),limit_mag_ps_mac_i[idx_mac],limit_mag_sb_mac_i[idx_mac],psf_width_mean_mac_i[idx_mac],psf_width_src_mac_i[idx_mac])
if snr_mac_i[idx_mac] != -999:
with open(sdss_vs_macadamia_filepath_all,'a') as of:
of.write(output_line)
with open(sdss_vs_macadamia_filepath_i,'a') as of:
of.write(output_line)
if abs(mag_mac_i[idx_mac] - mag_sdss) < outlier_threshold:
with open(sdss_vs_macadamia_filepath_i_or,'a') as of:
of.write(output_line)
else:
outliers_i += 1
if magerr_mac_i[idx_mac] < highprecision_threshold and merr_sdss < highprecision_threshold:
with open(sdss_vs_macadamia_filepath_i_hp,'a') as of:
of.write(output_line)
else:
higherr_i += 1
if sdss_filter == 'z':
# find distance to nearest chip edge
dist_edge_mac = dist_edge_l_mac_z[idx_mac]
if dist_edge_r_mac_z[idx_mac] < dist_edge_mac: dist_edge_mac = dist_edge_r_mac_z[idx_mac]
if dist_edge_t_mac_z[idx_mac] < dist_edge_mac: dist_edge_mac = dist_edge_t_mac_z[idx_mac]
if dist_edge_b_mac_z[idx_mac] < dist_edge_mac: dist_edge_mac = dist_edge_b_mac_z[idx_mac]
# write detection data to sdss vs. macadamia output file
output_line = '{:>12d} {:>9d} {:1s} {:11.5f} {:5.2f} {:5.2f} {:11.5f} {:5.2f} {:5.2f} {:5.2f} {:5.2f} {:7.1f} {:11.3f} {:11.3f} {:15.3f} {:12.3f} {:12.3f} {:10.3f} {:9.3f} {:8.3f} {:9.3f} {:8.3f} {:9.3f} {:8.3f} {:9.1f} {:6.3f} {:>10d} {:10.3f} {:10.3f} {:11.3f} {:10.3f}\n'.format(int(detection_id_mac_z[idx_mac]),int(desig_num_mac_z[idx_mac]),'z',exp_start_jd_mac_z[idx_mac],mag_mac_z[idx_mac],magerr_mac_z[idx_mac],sdssmoc_table['mjd'][idx_sdss],mag_sdss,merr_sdss,mag_diff_sdss_mac,mag_diff_err_sdss_mac,snr_mac_z[idx_mac],src_density_mac_z[idx_mac],local_srcdn_mac_z[idx_mac],dist_pred_postn_mac_z[idx_mac],trail_len_pred_mac_z[idx_mac],trail_length_mac_z[idx_mac],trail_fwhm_mac_z[idx_mac],dist_src1_mac_z[idx_mac],mag_src1_mac_z[idx_mac],dist_src2_mac_z[idx_mac],mag_src2_mac_z[idx_mac],dist_src3_mac_z[idx_mac],mag_src3_mac_z[idx_mac],dist_edge_mac,zpoint_mac_z[idx_mac],int(zpt_nstars_mac_z[idx_mac]),limit_mag_ps_mac_z[idx_mac],limit_mag_sb_mac_z[idx_mac],psf_width_mean_mac_z[idx_mac],psf_width_src_mac_z[idx_mac])
if snr_mac_z[idx_mac] != -999:
with open(sdss_vs_macadamia_filepath_all,'a') as of:
of.write(output_line)
with open(sdss_vs_macadamia_filepath_z,'a') as of:
of.write(output_line)
if abs(mag_mac_z[idx_mac] - mag_sdss) < outlier_threshold:
with open(sdss_vs_macadamia_filepath_z_or,'a') as of:
of.write(output_line)
else:
outliers_z += 1
if magerr_mac_z[idx_mac] < highprecision_threshold and merr_sdss < highprecision_threshold:
with open(sdss_vs_macadamia_filepath_z_hp,'a') as of:
of.write(output_line)
else:
higherr_z += 1
else:
mcd.output_error_log_entry(path_logfile,path_errorfile,'>> MACADAMIA match for SDSS entry {:d} ({:s}-band) not found.'.format(idx_sdss,sdss_filter))
if mag_sdss != 99.99:
with open(sdss_vs_macadamia_filepath_notfound,'a') as of:
of.write(output_line)
except Exception as e:
mcd.output_error_log_entry(path_logfile,path_errorfile,'Matching asteroid {:d} at {:.5f} (SDSS entry {:d}) failed.'.format(int(sdssmoc_table['ast_num'][idx_sdss]),sdssmoc_table['mjd'][idx_sdss],idx_sdss))
mcd.output_error_log_entry_nonstring(path_logfile,path_errorfile,e)
mcd.output_log_entry(path_logfile,"{:d} outliers (dev > {:1f} mag) removed from g'-band photometry.".format(outliers_g,outlier_threshold))
mcd.output_log_entry(path_logfile,"{:d} outliers (dev > {:1f} mag) removed from r'-band photometry.".format(outliers_r,outlier_threshold))
mcd.output_log_entry(path_logfile,"{:d} outliers (dev > {:1f} mag) removed from i'-band photometry.".format(outliers_i,outlier_threshold))
mcd.output_log_entry(path_logfile,"{:d} outliers (dev > {:1f} mag) removed from z'-band photometry.".format(outliers_z,outlier_threshold))
mcd.output_log_entry(path_logfile,"{:d} low-precision data points (magerr_mcdm or magerr_sdss > {:1f} mag) removed from g'-band photometry.".format(higherr_g,highprecision_threshold))
mcd.output_log_entry(path_logfile,"{:d} low-precision data points (magerr_mcdm or magerr_sdss > {:1f} mag) removed from r'-band photometry.".format(higherr_g,highprecision_threshold))
mcd.output_log_entry(path_logfile,"{:d} low-precision data points (magerr_mcdm or magerr_sdss > {:1f} mag) removed from i'-band photometry.".format(higherr_g,highprecision_threshold))
mcd.output_log_entry(path_logfile,"{:d} low-precision data points (magerr_mcdm or magerr_sdss > {:1f} mag) removed from z'-band photometry.".format(higherr_g,highprecision_threshold))
#mcd.compress_file_gzip(macadamia_output_filepath)
mcd.output_log_entry(path_logfile,'Creation of SDSS/MACADAMIA comparison files complete.')
else:
mcd.output_log_entry(path_logfile,'Function skipped: create_sdss_macadamia_comparison_files()')
return keep_going
def create_sdss_macadamia_comparison_plots(sdss_vs_macadamia_filepath,dataset,keep_going,path_logfile,path_errorfile):
if dataset == 'outliers_removed': filename_suffix = '_or'
elif dataset == 'high_precision': filename_suffix = '_hp'
else: filename_suffix = ''
if keep_going:
try:
sdss_vs_macadamia_dev_vs_snr_all_filepath = sdss_vs_macadamia_filepath[:-4] + '_dev_vs_snr_all.pdf'
sdss_vs_macadamia_dev_vs_snr_griz_filepath = sdss_vs_macadamia_filepath[:-4] + '_dev_vs_snr_griz.pdf'
sdss_vs_macadamia_dev_vs_mag_all_filepath = sdss_vs_macadamia_filepath[:-4] + '_dev_vs_mag_all.pdf'
sdss_vs_macadamia_dev_vs_mag_griz_filepath = sdss_vs_macadamia_filepath[:-4] + '_dev_vs_mag_griz.pdf'
merr_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(5))
merr_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(5))
merr_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(5))
merr_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(5))
sdss_mags_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(7))
sdss_mags_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(7))
sdss_mags_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(7))
sdss_mags_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(7))
sdss_merr_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(8))
sdss_merr_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(8))
sdss_merr_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(8))
sdss_merr_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(8))
mag_diffs_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(9))
mag_diffs_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(9))
mag_diffs_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(9))
mag_diffs_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(9))
mag_diff_errs_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(10))
mag_diff_errs_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(10))
mag_diff_errs_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(10))
mag_diff_errs_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(10))
snrs_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(11))
snrs_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(11))
snrs_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(11))
snrs_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(11))
src_density_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(12))
src_density_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(12))
src_density_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(12))
src_density_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(12))
dist_predpstn_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(13))
dist_predpstn_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(13))
dist_predpstn_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(13))
dist_predpstn_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(13))
trail_length_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(14))
trail_length_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(14))
trail_length_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(14))
trail_length_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(14))
trail_fwhm_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(15))
trail_fwhm_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(15))
trail_fwhm_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(15))
trail_fwhm_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(15))
dist_src1_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(16))
dist_src1_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(16))
dist_src1_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(16))
dist_src1_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(16))
mag_src1_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(17))
mag_src1_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(17))
mag_src1_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(17))
mag_src1_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(17))
dist_src2_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(18))
dist_src2_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(18))
dist_src2_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(18))
dist_src2_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(18))
mag_src2_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(19))
mag_src2_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(19))
mag_src2_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(19))
mag_src2_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(19))
dist_src3_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(20))
dist_src3_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(20))
dist_src3_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(20))
dist_src3_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(20))
mag_src3_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(21))
mag_src3_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(21))
mag_src3_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(21))
mag_src3_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(21))
dist_edge_g = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_g'+filename_suffix+'.dat',skip_header=1,usecols=(22))
dist_edge_r = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_r'+filename_suffix+'.dat',skip_header=1,usecols=(22))
dist_edge_i = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_i'+filename_suffix+'.dat',skip_header=1,usecols=(22))
dist_edge_z = np.genfromtxt(sdss_vs_macadamia_filepath[:-4]+'_z'+filename_suffix+'.dat',skip_header=1,usecols=(22))
#keep_going,log_file = create_histogram_all(mag_diffs_all,sdss_vs_macadamia_filepath[:-4]+'_histogram_all.pdf',keep_going,log_file)
#keep_going,log_file = create_dev_vs_mag_all(mag_diffs_all,mags_all,sdss_vs_macadamia_filepath[:-4]+'_dev_vs_mag_all.pdf',keep_going,log_file)
#keep_going,log_file = create_dev_vs_snr_all(mag_diffs_all,snrs_all,sdss_vs_macadamia_filepath[:-4]+'_dev_vs_snr_all.pdf',keep_going,log_file)
keep_going = create_err_histograms_griz(merr_g,merr_r,merr_i,merr_z,sdss_merr_g,sdss_merr_r,sdss_merr_i,sdss_merr_z,sdss_vs_macadamia_filepath[:-4]+'_err_histogram_griz'+filename_suffix+'.pdf',keep_going,path_logfile,path_errorfile)
keep_going = create_diff_histograms_griz(mag_diffs_g,mag_diffs_r,mag_diffs_i,mag_diffs_z,sdss_vs_macadamia_filepath[:-4]+'_histogram_griz'+filename_suffix+'.pdf',keep_going,path_logfile,path_errorfile)
keep_going = create_dev_vs_mag_griz(mag_diffs_g,mag_diffs_r,mag_diffs_i,mag_diffs_z,mags_g,mags_r,mags_i,mags_z,sdss_vs_macadamia_filepath[:-4]+'_dev_vs_mag_griz'+filename_suffix+'.pdf',keep_going,path_logfile,path_errorfile)
keep_going = create_dev_vs_snr_griz(mag_diffs_g,mag_diffs_r,mag_diffs_i,mag_diffs_z,snrs_g,snrs_r,snrs_i,snrs_z,sdss_vs_macadamia_filepath[:-4]+'_dev_vs_snr_griz'+filename_suffix+'.pdf',keep_going,path_logfile,path_errorfile)
except Exception as e:
mcd.output_error_log_entry(path_logfile,path_errorfile,'Function failed: create_sdss_macadamia_comparison_plots()')
mcd.output_error_log_entry_nonstring(path_logfile,path_errorfile,e)
keep_going = False
else:
mcd.output_log_entry(path_logfile,'Function skipped: create_sdss_macadamia_comparison_plots()')
return keep_going
def gaussian(x,amplitude,mean,stddev):
return amplitude * np.exp(-((x-mean)**2)/(2*stddev**2))
def create_err_histograms_griz(merr_g,merr_r,merr_i,merr_z,sdss_merr_g,sdss_merr_r,sdss_merr_i,sdss_merr_z,plot_filepath,keep_going,path_logfile,path_errorfile):
if keep_going:
try:
rect_plot_1a = [0.12,0.63,0.35,0.20]
rect_plot_1b = [0.12,0.40,0.35,0.20]
rect_plot_2a = [0.12,0.32,0.35,0.20]
rect_plot_2b = [0.12,0.12,0.35,0.20]
rect_plot_3a = [0.55,0.63,0.35,0.20]
rect_plot_3b = [0.55,0.40,0.35,0.20]
rect_plot_4a = [0.55,0.32,0.35,0.20]
rect_plot_4b = [0.55,0.12,0.35,0.20]
plt.figure(1,figsize=(12,12))
axPlot_g1 = plt.axes(rect_plot_1a)
axPlot_g2 = plt.axes(rect_plot_1b)
axPlot_r1 = plt.axes(rect_plot_2a)
axPlot_r2 = plt.axes(rect_plot_2b)
axPlot_i1 = plt.axes(rect_plot_3a)
axPlot_i2 = plt.axes(rect_plot_3b)
axPlot_z1 = plt.axes(rect_plot_4a)
axPlot_z2 = plt.axes(rect_plot_4b)
n_mag_err_bins = 20
#mag_diff_min = np.amin(mag_diffs)
#mag_diff_max = np.amax(mag_diffs)
#n_mag_diff_bins = 401
mag_err_min = 0
mag_err_max = 1
mag_err_bins = np.arange(mag_err_min,mag_err_max,(mag_err_max-mag_err_min)/n_mag_err_bins)
#mu_g,sigma_g = norm.fit(mag_diffs_g)
#mu_r,sigma_r = norm.fit(mag_diffs_r)
#mu_i,sigma_i = norm.fit(mag_diffs_i)
#mu_z,sigma_z = norm.fit(mag_diffs_z)
x_g1,bins_g1,p_g1 = axPlot_g1.hist(merr_g,bins=mag_err_bins,histtype='bar',density=True,edgecolor='black',color='#2077b4',zorder=2)
x_r1,bins_r1,p_r1 = axPlot_r1.hist(merr_r,bins=mag_err_bins,histtype='bar',density=True,edgecolor='black',color='#2077b4',zorder=2)
x_i1,bins_i1,p_i1 = axPlot_i1.hist(merr_i,bins=mag_err_bins,histtype='bar',density=True,edgecolor='black',color='#2077b4',zorder=2)
x_z1,bins_z1,p_z1 = axPlot_z1.hist(merr_z,bins=mag_err_bins,histtype='bar',density=True,edgecolor='black',color='#2077b4',zorder=2)
x_g2,bins_g2,p_g2 = axPlot_g2.hist(sdss_merr_g,bins=mag_err_bins,histtype='bar',density=True,edgecolor='black',color='#2077b4',zorder=2)
x_r2,bins_r2,p_r2 = axPlot_r2.hist(sdss_merr_r,bins=mag_err_bins,histtype='bar',density=True,edgecolor='black',color='#2077b4',zorder=2)
x_i2,bins_i2,p_i2 = axPlot_i2.hist(sdss_merr_i,bins=mag_err_bins,histtype='bar',density=True,edgecolor='black',color='#2077b4',zorder=2)
x_z2,bins_z2,p_z2 = axPlot_z2.hist(sdss_merr_z,bins=mag_err_bins,histtype='bar',density=True,edgecolor='black',color='#2077b4',zorder=2)
major_xticks = np.arange(-2,2,0.2)
minor_xticks = np.arange(-2,2,0.1)
#major_xticks = np.arange(-12,12,2)
#minor_xticks = np.arange(-12,12,0.5)
major_yticks = np.arange(-2,2,0.1)
minor_yticks = np.arange(-2,2,0.05)
axPlot_g1.tick_params(axis='both',which='major',labelsize=13)
axPlot_g1.tick_params(axis='both',which='minor',labelsize=0)
axPlot_r1.tick_params(axis='both',which='major',labelsize=13)
axPlot_r1.tick_params(axis='both',which='minor',labelsize=0)
axPlot_i1.tick_params(axis='both',which='major',labelsize=13)
axPlot_i1.tick_params(axis='both',which='minor',labelsize=0)
axPlot_z1.tick_params(axis='both',which='major',labelsize=13)
axPlot_z1.tick_params(axis='both',which='minor',labelsize=0)
axPlot_g2.tick_params(axis='both',which='major',labelsize=13)
axPlot_g2.tick_params(axis='both',which='minor',labelsize=0)
axPlot_r2.tick_params(axis='both',which='major',labelsize=13)
axPlot_r2.tick_params(axis='both',which='minor',labelsize=0)
axPlot_i2.tick_params(axis='both',which='major',labelsize=13)
axPlot_i2.tick_params(axis='both',which='minor',labelsize=0)
axPlot_z2.tick_params(axis='both',which='major',labelsize=13)
axPlot_z2.tick_params(axis='both',which='minor',labelsize=0)
axPlot_g1.set_xticks(major_xticks)
axPlot_g1.set_xticks(minor_xticks,minor=True)
axPlot_r1.set_xticks(major_xticks)
axPlot_r1.set_xticks(minor_xticks,minor=True)
axPlot_i1.set_xticks(major_xticks)
axPlot_i1.set_xticks(minor_xticks,minor=True)
axPlot_z1.set_xticks(major_xticks)
axPlot_z1.set_xticks(minor_xticks,minor=True)
axPlot_g2.set_xticks(major_xticks)
axPlot_g2.set_xticks(minor_xticks,minor=True)
axPlot_r2.set_xticks(major_xticks)
axPlot_r2.set_xticks(minor_xticks,minor=True)
axPlot_i2.set_xticks(major_xticks)
axPlot_i2.set_xticks(minor_xticks,minor=True)
axPlot_z2.set_xticks(major_xticks)
axPlot_z2.set_xticks(minor_xticks,minor=True)
axPlot_g1.set_yticks(major_yticks)
axPlot_g1.set_yticks(minor_yticks,minor=True)
axPlot_r1.set_yticks(major_yticks)
axPlot_r1.set_yticks(minor_yticks,minor=True)
axPlot_i1.set_yticks(major_yticks)
axPlot_i1.set_yticks(minor_yticks,minor=True)
axPlot_z1.set_yticks(major_yticks)
axPlot_z1.set_yticks(minor_yticks,minor=True)
axPlot_g2.set_yticks(major_yticks)
axPlot_g2.set_yticks(minor_yticks,minor=True)
axPlot_r2.set_yticks(major_yticks)
axPlot_r2.set_yticks(minor_yticks,minor=True)
axPlot_i2.set_yticks(major_yticks)
axPlot_i2.set_yticks(minor_yticks,minor=True)
axPlot_z2.set_yticks(major_yticks)
axPlot_z2.set_yticks(minor_yticks,minor=True)
axPlot_g1.tick_params(which='both',direction='in')
axPlot_r1.tick_params(which='both',direction='in')
axPlot_i1.tick_params(which='both',direction='in')
axPlot_z1.tick_params(which='both',direction='in')
axPlot_g2.tick_params(which='both',direction='in')
axPlot_r2.tick_params(which='both',direction='in')
axPlot_i2.tick_params(which='both',direction='in')
axPlot_z2.tick_params(which='both',direction='in')
axPlot_g1.set_xlim([-0.1,0.9])
axPlot_r1.set_xlim([-0.1,0.9])
axPlot_i1.set_xlim([-0.1,0.9])
axPlot_z1.set_xlim([-0.1,0.9])
axPlot_g2.set_xlim([-0.1,0.9])
axPlot_r2.set_xlim([-0.1,0.9])
axPlot_i2.set_xlim([-0.1,0.9])
axPlot_z2.set_xlim([-0.1,0.9])
#axPlot_g.set_xlim([-1,1])
#axPlot_r.set_xlim([-1,1])
#axPlot_i.set_xlim([-1,1])
#axPlot_z.set_xlim([-1,1])
axPlot_g1.set_ylim([0,0.45])
axPlot_r1.set_ylim([0,0.45])
axPlot_i1.set_ylim([0,0.45])
axPlot_z1.set_ylim([0,0.45])
axPlot_g2.set_ylim([0,0.45])
axPlot_r2.set_ylim([0,0.45])
axPlot_i2.set_ylim([0,0.45])
axPlot_z2.set_ylim([0,0.45])
axPlot_g1.xaxis.set_ticks_position('both')
axPlot_r1.xaxis.set_ticks_position('both')
axPlot_i1.xaxis.set_ticks_position('both')
axPlot_z1.xaxis.set_ticks_position('both')
axPlot_g1.yaxis.set_ticks_position('both')
axPlot_r1.yaxis.set_ticks_position('both')
axPlot_i1.yaxis.set_ticks_position('both')
axPlot_z1.yaxis.set_ticks_position('both')
axPlot_g2.xaxis.set_ticks_position('both')
axPlot_r2.xaxis.set_ticks_position('both')
axPlot_i2.xaxis.set_ticks_position('both')
axPlot_z2.xaxis.set_ticks_position('both')
axPlot_g2.yaxis.set_ticks_position('both')
axPlot_r2.yaxis.set_ticks_position('both')
axPlot_i2.yaxis.set_ticks_position('both')
axPlot_z2.yaxis.set_ticks_position('both')
for item in p_g1:
item.set_height(item.get_height()/sum(x_g1))
for item in p_r1:
item.set_height(item.get_height()/sum(x_r1))
for item in p_i1:
item.set_height(item.get_height()/sum(x_i1))
for item in p_z1:
item.set_height(item.get_height()/sum(x_z1))
for item in p_g2:
item.set_height(item.get_height()/sum(x_g2))
for item in p_r2:
item.set_height(item.get_height()/sum(x_r2))
for item in p_i2:
item.set_height(item.get_height()/sum(x_i2))
for item in p_z2:
item.set_height(item.get_height()/sum(x_z2))
max_hist_g1,max_hist_r1,max_hist_i1,max_hist_z1 = 0,0,0,0
for item in p_g1:
if item.get_height() > max_hist_g1: max_hist_g1 = item.get_height()
for item in p_r1:
if item.get_height() > max_hist_r1: max_hist_r1 = item.get_height()
for item in p_i1:
if item.get_height() > max_hist_i1: max_hist_i1 = item.get_height()
for item in p_z1:
if item.get_height() > max_hist_z1: max_hist_z1 = item.get_height()
max_hist_g2,max_hist_r2,max_hist_i2,max_hist_z2 = 0,0,0,0
for item in p_g2:
if item.get_height() > max_hist_g2: max_hist_g2 = item.get_height()
for item in p_r2:
if item.get_height() > max_hist_r2: max_hist_r2 = item.get_height()
for item in p_i2:
if item.get_height() > max_hist_i2: max_hist_i2 = item.get_height()
for item in p_z2:
if item.get_height() > max_hist_z2: max_hist_z2 = item.get_height()
#print(max_hist_g,max_hist_r,max_hist_i,max_hist_z)
num_histbars_g1 = len(p_g1)
num_histbars_r1 = len(p_r1)
num_histbars_i1 = len(p_i1)
num_histbars_z1 = len(p_z1)
num_histbars_g2 = len(p_g2)
num_histbars_r2 = len(p_r2)
num_histbars_i2 = len(p_i2)
num_histbars_z2 = len(p_z2)
height_histbars_g1 = [0 for idx in range(num_histbars_g1)]
height_histbars_r1 = [0 for idx in range(num_histbars_r1)]
height_histbars_i1 = [0 for idx in range(num_histbars_i1)]
height_histbars_z1 = [0 for idx in range(num_histbars_z1)]
height_histbars_g2 = [0 for idx in range(num_histbars_g2)]
height_histbars_r2 = [0 for idx in range(num_histbars_r2)]
height_histbars_i2 = [0 for idx in range(num_histbars_i2)]
height_histbars_z2 = [0 for idx in range(num_histbars_z2)]
idx = 0
for item in p_g1:
height_histbars_g1[idx] = item.get_height()
idx += 1
idx = 0
for item in p_r1:
height_histbars_r1[idx] = item.get_height()
idx += 1
idx = 0
for item in p_i1:
height_histbars_i1[idx] = item.get_height()
idx += 1
idx = 0
for item in p_z1:
height_histbars_z1[idx] = item.get_height()
idx += 1
idx = 0
for item in p_g2:
height_histbars_g2[idx] = item.get_height()
idx += 1
idx = 0
for item in p_r2:
height_histbars_r2[idx] = item.get_height()
idx += 1
idx = 0
for item in p_i2:
height_histbars_i2[idx] = item.get_height()
idx += 1
idx = 0
for item in p_z2:
height_histbars_z2[idx] = item.get_height()
idx += 1
x_hist_g1 = [0 for idx in range(len(bins_g1)-1)]
x_hist_r1 = [0 for idx in range(len(bins_r1)-1)]
x_hist_i1 = [0 for idx in range(len(bins_i1)-1)]
x_hist_z1 = [0 for idx in range(len(bins_z1)-1)]
x_hist_g2 = [0 for idx in range(len(bins_g2)-1)]
x_hist_r2 = [0 for idx in range(len(bins_r2)-1)]
x_hist_i2 = [0 for idx in range(len(bins_i2)-1)]
x_hist_z2 = [0 for idx in range(len(bins_z2)-1)]
for idx in range(0,len(x_hist_g1)):
x_hist_g1[idx] = (bins_g1[idx] + bins_g1[idx+1])/2
for idx in range(0,len(x_hist_r1)):
x_hist_r1[idx] = (bins_r1[idx] + bins_r1[idx+1])/2
for idx in range(0,len(x_hist_i)):
x_hist_i1[idx] = (bins_i1[idx] + bins_i1[idx+1])/2
for idx in range(0,len(x_hist_z)):
x_hist_z1[idx] = (bins_z1[idx] + bins_z1[idx+1])/2
for idx in range(0,len(x_hist_g2)):
x_hist_g2[idx] = (bins_g2[idx] + bins_g2[idx+1])/2
for idx in range(0,len(x_hist_r2)):
x_hist_r2[idx] = (bins_r2[idx] + bins_r2[idx+1])/2
for idx in range(0,len(x_hist_i2)):
x_hist_i2[idx] = (bins_i2[idx] + bins_i2[idx+1])/2
for idx in range(0,len(x_hist_z2)):
x_hist_z2[idx] = (bins_z2[idx] + bins_z2[idx+1])/2
props1 = dict(boxstyle='round',facecolor='white', alpha=1.0,edgecolor='0.00')
props2 = dict(boxstyle='round,pad=0.05',facecolor='white',alpha=1.0,edgecolor='white')
props3 = dict(boxstyle='round,pad=0.20',facecolor='white',alpha=1.0,edgecolor='black')
axPlot_g1.text(0.915,0.89,"g'",fontsize=16,transform=axPlot_g1.transAxes,bbox=props1)
axPlot_r1.text(0.925,0.89,"r'",fontsize=16,transform=axPlot_r1.transAxes,bbox=props1)
axPlot_i1.text(0.930,0.89,"i'",fontsize=16,transform=axPlot_i1.transAxes,bbox=props1)
axPlot_z1.text(0.922,0.89,"z'",fontsize=16,transform=axPlot_z1.transAxes,bbox=props1)
#axPlot_g.text(0.045,0.80,r'$\mu={:.4f}$'.format(mu_g)+'\n'+r'$\sigma={:.4f}$'.format(sigma_g),fontsize=11,transform=axPlot_g.transAxes,bbox=props2)
#axPlot_r.text(0.045,0.80,r'$\mu={:.4f}$'.format(mu_r)+'\n'+r'$\sigma={:.4f}$'.format(sigma_r),fontsize=11,transform=axPlot_r.transAxes,bbox=props2)
#axPlot_i.text(0.045,0.80,r'$\mu={:.4f}$'.format(mu_i)+'\n'+r'$\sigma={:.4f}$'.format(sigma_i),fontsize=11,transform=axPlot_i.transAxes,bbox=props2)
#axPlot_z.text(0.045,0.80,r'$\mu={:.4f}$'.format(mu_z)+'\n'+r'$\sigma={:.4f}$'.format(sigma_z),fontsize=11,transform=axPlot_z.transAxes,bbox=props2)
axPlot_g1.set_xlabel(r'$\delta m_{\rm SDSS}$',fontsize=14)
axPlot_r1.set_xlabel(r'$\delta m_{\rm SDSS}$',fontsize=14)
axPlot_i1.set_xlabel(r'$\delta m_{\rm SDSS}$',fontsize=14)
axPlot_z1.set_xlabel(r'$\delta m_{\rm SDSS}$',fontsize=14)
axPlot_g2.set_xlabel(r'$\delta m_{\rm Mcdm}$',fontsize=14)
axPlot_r2.set_xlabel(r'$\delta m_{\rm Mcdm}$',fontsize=14)
axPlot_i2.set_xlabel(r'$\delta m_{\rm Mcdm}$',fontsize=14)
axPlot_z2.set_xlabel(r'$\delta m_{\rm Mcdm}$',fontsize=14)
axPlot_g1.set_ylabel('Sample fraction',fontsize=14,labelpad=9)
axPlot_r1.set_ylabel('Sample fraction',fontsize=14,labelpad=9)
axPlot_i1.set_ylabel('Sample fraction',fontsize=14,labelpad=9)
axPlot_z1.set_ylabel('Sample fraction',fontsize=14,labelpad=9)
axPlot_g2.set_ylabel('Sample fraction',fontsize=14,labelpad=9)
axPlot_r2.set_ylabel('Sample fraction',fontsize=14,labelpad=9)
axPlot_i2.set_ylabel('Sample fraction',fontsize=14,labelpad=9)
axPlot_z2.set_ylabel('Sample fraction',fontsize=14,labelpad=9)
plt.savefig(plot_filepath,format='pdf',transparent=True)
plt.clf()
plt.cla()
plt.close()
mcd.output_log_entry(path_logfile,'Histograms of uncertainties for MACADAMIA and SDSS data plotted successfully.')
keep_going = True
except Exception as e:
mcd.output_error_log_entry(path_logfile,path_errorfile,'Function failed: create_err_histograms_griz()')
mcd.output_error_log_entry_nonstring(path_logfile,path_errorfile,e)
keep_going = False
else:
mcd.output_log_entry(path_logfile,'Function skipped: create_err_histograms_griz()')
return keep_going
def create_diff_histograms_griz(mag_diffs_g,mag_diffs_r,mag_diffs_i,mag_diffs_z,plot_filepath,keep_going,path_logfile,path_errorfile):
if keep_going:
try:
rect_plot_1 = [0.12,0.43,0.35,0.25]
rect_plot_2 = [0.12,0.12,0.35,0.25]
rect_plot_3 = [0.55,0.43,0.35,0.25]
rect_plot_4 = [0.55,0.12,0.35,0.25]
plt.figure(1,figsize=(12,12))
axPlot_g = plt.axes(rect_plot_1)
axPlot_r = plt.axes(rect_plot_2)
axPlot_i = plt.axes(rect_plot_3)
axPlot_z = plt.axes(rect_plot_4)
n_mag_diff_bins = 81
#mag_diff_min = np.amin(mag_diffs)
#mag_diff_max = np.amax(mag_diffs)
#n_mag_diff_bins = 401
mag_diff_min = -1.0125
mag_diff_max = 1.0125
mag_diff_bins = np.arange(mag_diff_min,mag_diff_max,(mag_diff_max-mag_diff_min)/n_mag_diff_bins)
mu_g,sigma_g = norm.fit(mag_diffs_g)
mu_r,sigma_r = norm.fit(mag_diffs_r)
mu_i,sigma_i = norm.fit(mag_diffs_i)
mu_z,sigma_z = norm.fit(mag_diffs_z)
x_g,bins_g,p_g = axPlot_g.hist(mag_diffs_g,bins=mag_diff_bins,histtype='bar',density=True,edgecolor='black',color='#2077b4',zorder=2)
x_r,bins_r,p_r = axPlot_r.hist(mag_diffs_r,bins=mag_diff_bins,histtype='bar',density=True,edgecolor='black',color='#2077b4',zorder=2)
x_i,bins_i,p_i = axPlot_i.hist(mag_diffs_i,bins=mag_diff_bins,histtype='bar',density=True,edgecolor='black',color='#2077b4',zorder=2)
x_z,bins_z,p_z = axPlot_z.hist(mag_diffs_z,bins=mag_diff_bins,histtype='bar',density=True,edgecolor='black',color='#2077b4',zorder=2)
major_xticks = np.arange(-2,2,0.2)
minor_xticks = np.arange(-2,2,0.1)
#major_xticks = np.arange(-12,12,2)
#minor_xticks = np.arange(-12,12,0.5)
major_yticks = np.arange(-2,2,0.1)
minor_yticks = np.arange(-2,2,0.05)
axPlot_g.tick_params(axis='both',which='major',labelsize=13)
axPlot_g.tick_params(axis='both',which='minor',labelsize=0)
axPlot_r.tick_params(axis='both',which='major',labelsize=13)
axPlot_r.tick_params(axis='both',which='minor',labelsize=0)
axPlot_i.tick_params(axis='both',which='major',labelsize=13)
axPlot_i.tick_params(axis='both',which='minor',labelsize=0)
axPlot_z.tick_params(axis='both',which='major',labelsize=13)
axPlot_z.tick_params(axis='both',which='minor',labelsize=0)
axPlot_g.set_xticks(major_xticks)
axPlot_g.set_xticks(minor_xticks,minor=True)
axPlot_r.set_xticks(major_xticks)
axPlot_r.set_xticks(minor_xticks,minor=True)
axPlot_i.set_xticks(major_xticks)
axPlot_i.set_xticks(minor_xticks,minor=True)
axPlot_z.set_xticks(major_xticks)
axPlot_z.set_xticks(minor_xticks,minor=True)
axPlot_g.set_yticks(major_yticks)
axPlot_g.set_yticks(minor_yticks,minor=True)
axPlot_r.set_yticks(major_yticks)
axPlot_r.set_yticks(minor_yticks,minor=True)
axPlot_i.set_yticks(major_yticks)
axPlot_i.set_yticks(minor_yticks,minor=True)
axPlot_z.set_yticks(major_yticks)
axPlot_z.set_yticks(minor_yticks,minor=True)
axPlot_g.tick_params(which='both',direction='in')
axPlot_r.tick_params(which='both',direction='in')
axPlot_i.tick_params(which='both',direction='in')
axPlot_z.tick_params(which='both',direction='in')
axPlot_g.set_xlim([-0.5,0.5])
axPlot_r.set_xlim([-0.5,0.5])
axPlot_i.set_xlim([-0.5,0.5])
axPlot_z.set_xlim([-0.5,0.5])
#axPlot_g.set_xlim([-1,1])
#axPlot_r.set_xlim([-1,1])
#axPlot_i.set_xlim([-1,1])
#axPlot_z.set_xlim([-1,1])
axPlot_g.set_ylim([0,0.45])
axPlot_r.set_ylim([0,0.45])
axPlot_i.set_ylim([0,0.45])
axPlot_z.set_ylim([0,0.45])