#!/usr/bin/env python """ НАЗВАНИЕ: 05_srctool.py НАЗНАЧЕНИЕ: Запускает scrtool для самого широкого канала 0.2-10 кэВ, чтобы спектры имели самое полное покрытие по энергиям. Список источников берется из 0.3-2.3 кэВ. ВЫЗОВ: esass ./05_srctool.py УПРАВЛЕНИЕ: Требуется запуск предыдущего скрипта 04_mosaics.py ПАРАМЕТРЫ: index=4 : Выбранный энергетический диапазон ВЫВОД: Выходные файлы записываются в директорию outfile_dir/srctool_dir ИСТОРИЯ: Роман Кривонос, ИКИ РАН, krivonos@cosmos.ru Март 2023 """ from astropy.wcs import WCS from astropy.io import fits import sys, os, os.path, time, subprocess from pathlib import Path import numpy as np import glob from os.path import dirname import inspect import uds import matplotlib.pyplot as plt from uds.utils import * from uds.config import * from uds.sherpa import * """ find UDS root dir """ #root_path=dirname(dirname(dirname(inspect.getfile(uds)))) """ ftools does not like long file path names, for this reason, we use relative path here """ root_path='..' print("UDS root path: {}".format(root_path)) infile_dir=root_path+'/data/processed' outfile_dir=root_path+'/products' create_folder(outfile_dir) srctool_dir="{}/{}".format(outfile_dir,"srctool-products") create_folder(srctool_dir) outkey="tm0" outfile_srctool="{}_SrcTool_".format(outkey) do_flux_distr = False do_sens_curve = True index=0 catalog = "{}_SourceCatalog_en{}.main.selected.csv".format(os.path.join(outfile_dir,outkey), eband[0]) if not (os.path.isfile(catalog)==True): print("{} not found, run 05_srctool.py?".format(catalog)) sys.exit() if(do_flux_distr==True): data, logbins = get_log_distr(infile=catalog, field='ml_rate', minval=1e-3, maxval=2) fig, ax = plt.subplots() for axis in ['top','bottom','left','right']: ax.spines[axis].set_linewidth(1) ax.tick_params(axis="both", width=1, labelsize=14) plt.hist(data, bins=logbins, histtype='step', color='blue', linewidth=1, linestyle='solid') plt.xlabel('Count rate (counts s$^{-1}$)',fontsize=14, fontweight='normal') plt.ylabel('Number',fontsize=14, fontweight='normal') plt.grid(visible=True) plt.xscale('log') plt.yscale('log') plt.savefig(catalog.replace("main.selected.csv", "ml_rate.png"), bbox_inches='tight') plt.close(fig) data, logbins = get_log_distr(infile=catalog, field='ml_flux', minval=1e-15, maxval=2e-12) fig, ax = plt.subplots() for axis in ['top','bottom','left','right']: ax.spines[axis].set_linewidth(1) ax.tick_params(axis="both", width=1, labelsize=14) plt.hist(data, bins=logbins, histtype='step', color='blue', linewidth=1, linestyle='solid') plt.xlabel('Energy flux (erg s$^{-1}$ cm$^{-2}$)',fontsize=14, fontweight='normal') plt.ylabel('Number',fontsize=14, fontweight='normal') plt.grid(visible=True) plt.xscale('log') plt.yscale('log') plt.savefig(catalog.replace("main.selected.csv", "ml_flux.png"), bbox_inches='tight') plt.close(fig) if(do_sens_curve==True): coeff = 2.4336e-13 / 3.4012e-13 # see below areatab="{}_AreaTable_dl10_en{}{}".format(os.path.join(outfile_dir,outkey), eband[index], outfile_post) hdul = fits.open(areatab) tbdata = hdul[1].data """ convert limflux from 0.3-2.3 keV to 0.5-2 keV """ limflux_dl10 = tbdata['LIMFLUX']*coeff area_dl10 = tbdata['SKY_AREA'] hdul.close() areatab="{}_AreaTable_dl6_en{}{}".format(os.path.join(outfile_dir,outkey), eband[index], outfile_post) hdul = fits.open(areatab) tbdata = hdul[1].data """ convert limflux from 0.3-2.3 keV to 0.5-2 keV """ limflux_dl6 = tbdata['LIMFLUX']*coeff area_dl6 = tbdata['SKY_AREA'] hdul.close() fig, ax = plt.subplots() for axis in ['top','bottom','left','right']: ax.spines[axis].set_linewidth(1) ax.tick_params(axis="both", width=1, labelsize=14) ax.set_xlim([3e-16,1e-13]) ax.set_ylim([0.3,160]) df = pandas.read_csv("../data/surveys/eFEDS.dat",header=None,names=['limflux','area']) plt.plot(df['limflux'],df['area'], color="brown", linestyle='solid',label="eFEDS (DL6)") plt.plot(limflux_dl10,area_dl10, color="black", linestyle='solid',label="eUDS (DL10)") plt.plot(limflux_dl6,area_dl6, color="black", linestyle='dashed', label="eUDS (DL6)") df = pandas.read_csv("../data/surveys/cosmos-legacy.dat",header=None,names=['limflux','area']) plt.plot(df['limflux'],df['area'], color="blue", linestyle='solid',label="COSMOS Legacy") df = pandas.read_csv("../data/surveys/CDWFS.dat",header=None,names=['limflux','area']) plt.plot(df['limflux'],df['area'], color="green", linestyle='solid', label="CDWFS") df = pandas.read_csv("../data/surveys/XMM-RM.dat",header=None,names=['limflux','area']) plt.plot(df['limflux'],df['area'], color="magenta", linestyle='solid',label="XMM-RM") df = pandas.read_csv("../data/surveys/XMM-XXL-N.dat",header=None,names=['limflux','area']) plt.plot(df['limflux'],df['area'], color="red", linestyle='solid',label="XMM-XXL-N") ax.legend() #plt.hist(data, bins=logbins, histtype='step', color='blue', linewidth=1, linestyle='solid') plt.xlabel('Limiting flux (0.5-2 keV, erg s$^{-1}$ cm$^{-2}$)',fontsize=14, fontweight='normal') plt.ylabel('Area (deg$^{2}$)',fontsize=14, fontweight='normal') plt.grid(visible=True) plt.xscale('log') plt.yscale('log') png="{}_AreaTable_en{}.png".format(os.path.join(outfile_dir,outkey), eband[index]) plt.savefig(png, bbox_inches='tight') plt.close(fig) """ ======================================================================== Model TBabs<1>*powerlaw<2> Source No.: 1 Active/On Model Model Component Parameter Unit Value par comp 1 1 TBabs nH 10^22 2.00000E-02 frozen 2 2 powerlaw PhoIndex 2.00000 frozen 3 2 powerlaw norm 1.14851E-04 +/- 3.83988E-06 ________________________________________________________________________ Model Flux 0.00028334 photons (3.4012e-13 ergs/cm^2/s) range (0.30000 - 2.3000 keV) Model Flux 0.0001619 photons (2.4336e-13 ergs/cm^2/s) range (0.50000 - 2.0000 keV) """