forked from erosita/uds
Many changes
This commit is contained in:
parent
4e5f88e166
commit
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7
.gitignore
vendored
7
.gitignore
vendored
@ -16,6 +16,7 @@ lib64/
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parts/
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sdist/
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var/
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products/
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wheels/
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share/python-wheels/
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*.egg-info/
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@ -43,9 +44,15 @@ venv.bak/
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*#
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.#*
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# Astronomy
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*.eps
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*.cds
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*.fits
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*.fits.gz
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*.fits.fz
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*.awk
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*.tex
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*.evt
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*.evt.gz
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*.lock
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52767
data/4XMM-DR12/4XMM_DR12cat_v1.0_UDS.fits.catalog
Normal file
52767
data/4XMM-DR12/4XMM_DR12cat_v1.0_UDS.fits.catalog
Normal file
File diff suppressed because one or more lines are too long
@ -6,5 +6,10 @@
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```
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ftselect '4XMM_DR12cat_slim_v1.0.fits[1]' 4XMM_DR12cat_slim_v1.0_UDS.fits 'SC_RA > 32.75 && SC_RA < 36.31 && SC_DEC > -6.55 && SC_DEC < -3.0' clobber=yes
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ftselect '4XMM_DR12cat_v1.0.fits[1]' 4XMM_DR12cat_v1.0_UDS.fits 'SC_RA > 32.75 && SC_RA < 36.31 && SC_DEC > -6.55 && SC_DEC < -3.0' clobber=yes
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Demo with DR13:
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ftselect '4XMM_slim_DR13cat_v1.0.fits[1]' 4XMM_slim_DR13cat_v1.0_DEMO.fits 'SC_RA > 25.75 && SC_RA < 50.31 && SC_DEC > -16.55 && SC_DEC < 13.0' clobber=yes
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```
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BIN
data/4XMM-DR12/Rplots.pdf
Normal file
BIN
data/4XMM-DR12/Rplots.pdf
Normal file
Binary file not shown.
20
data/4XMM-DR12/barplot.r
Normal file
20
data/4XMM-DR12/barplot.r
Normal file
@ -0,0 +1,20 @@
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library(ggplot2)
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# see https://r-graph-gallery.com/4-barplot-with-error-bar.html
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png(file = "barplot.png")
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# create dummy data
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data <- data.frame(
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name=c('','yy','zz','ff','DR12'),
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flux=c(1,2,3,4,5),
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err=c(1,0.2,3,2,4)
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)
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# Most basic error bar
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ggplot(data) +
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geom_bar(aes(x=name, y=flux), stat="identity", fill="skyblue", alpha=0.7) +
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geom_errorbar( aes(x=name, ymin=flux-err, ymax=flux+err), width=0.4, colour="black", alpha=0.9, linewidth=2)
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dev.off()
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40
data/4XMM-DR12/plot_corr.r
Normal file
40
data/4XMM-DR12/plot_corr.r
Normal file
@ -0,0 +1,40 @@
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options(digits = 7) # knitr sometimes decreases number of digits shown
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require(stats)
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xgrid <- c(1e-17,1e-16,1e-15,1e-14,1e-13,1e-12);
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postscript(paste("../../products/eUDS_4XMM-DR12.flux.eps",sep=""), horizontal = FALSE, onefile = FALSE, paper = "special",width = 9.0, height = 6.0)
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par(oma=c(1,1,1,1))
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#layout(matrix(c(1,2), 2, 1, byrow = TRUE), heights = c(1.5,1), TRUE)
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par(mar=c(4.3, 4.3, 1, 1))
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par(cex.lab=1.2)
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par(cex.axis=1.2)
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a <- read.table("../../products/eUDS_4XMM-DR12.flux.cvs", col.names=c("eflux","eerr","xflux","xerr"))
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xlim <- c(1e-15,1e-12)
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ylim <- c(1e-16,1e-12)
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plot(NULL, pch=21, bg="gold",ylim=ylim, xlim=xlim, main="", ylab="eUDS, erg/s/cm2",type="p",xaxt="n",xlab="4XMM-DR12, erg/s/cm2", log="xy")
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axis(side=1, at=xgrid, labels=xgrid)
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segments(a$xflux,a$eflux-a$eerr,a$xflux,a$eflux+a$eerr)
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segments(a$xflux-a$xerr,a$eflux,a$xflux+a$xerr,a$eflux)
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#segments(a$xlo,d,a$xhi,d)
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points(a$xflux,a$eflux,pch=21, bg="gold")
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lines(c(1e-17,1e-12),c(1e-17,1e-12))
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lines(c(1e-17,1e-12),10*c(1e-17,1e-12),lt=2)
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lines(c(1e-17,1e-12),0.1*c(1e-17,1e-12),lt=2)
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grid()
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abline(h=0, col = "black",lty=2)
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abline(v=xgrid, col="lightgray", lty="dotted")
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dev.off()
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@ -1,15 +1,19 @@
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from astropy.io import fits
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import sys
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filename='4XMM_DR12cat_slim_v1.0_UDS.fits.catalog'
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#filename='4XMM_DR12cat_slim_v1.0_UDS.fits.catalog'
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filename='4XMM_slim_DR13cat_v1.0_DEMO.fits'
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fout=filename.replace(".fits.catalog", ".names.reg")
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hdul = fits.open(filename)
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#hdul.info()
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tbdata = hdul[1].data
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hdul.close()
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with open("../../products/{}".format(fout), 'w') as writer:
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#with open("./{}".format(fout), 'w') as writer:
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for rec in tbdata:
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#writer.write("fk5;point({}, {})\n".format(rec['sc_ra'],rec['sc_dec']))
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writer.write("fk5;circle({}, {}, {}) # text={{{}}}\n".format(rec['sc_ra'],rec['sc_dec'],rec['sc_poserr']/3600,rec['IAUNAME']))
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print("fk5;circle({}, {}, 0.008)".format(rec['sc_ra'],rec['sc_dec']))
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#writer.write("fk5;circle({}, {}, {}) # text={{{}}}\n".format(rec['sc_ra'],rec['sc_dec'],rec['sc_poserr']/3600,rec['IAUNAME']))
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BIN
data/ECF/ecf_tbabspow_g2nh0.02.pkl
Normal file
BIN
data/ECF/ecf_tbabspow_g2nh0.02.pkl
Normal file
Binary file not shown.
BIN
data/ECF/ecf_tbabspow_g2nh003.pkl
Normal file
BIN
data/ECF/ecf_tbabspow_g2nh003.pkl
Normal file
Binary file not shown.
27
data/NuSTAR/nustar.fits.catalog
Normal file
27
data/NuSTAR/nustar.fits.catalog
Normal file
File diff suppressed because one or more lines are too long
13
data/NuSTAR/print_ds9reg.py
Executable file
13
data/NuSTAR/print_ds9reg.py
Executable file
@ -0,0 +1,13 @@
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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from astropy.io import fits
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hdul = fits.open('nustar.fits.catalog')
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tbdata = hdul[1].data
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hdul.close()
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with open("../../products/nustar_UDS.reg", 'w') as writer:
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for rec in tbdata:
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writer.write("fk5;circle({}, {}, 0.0025) # color=magenta text={{{}}}\n".format(rec['RAJ2000'], rec['DEJ2000'], rec['NuSTAR']))
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@ -1,11 +0,0 @@
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method leven 10 0.01
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abund wilm
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xsect vern
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cosmo 70 0 0.73
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xset delta 0.01
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systematic 0
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model TBabs*powerlaw
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0.02 -1 0 0 100000 1e+06
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2 -1 -3 -2 9 10
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4.83094e-05 0.01 0 0 1e+20 1e+24
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bayes off
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@ -1,13 +0,0 @@
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pro rate
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ar=[[1.8847140728347272e-13, 0.37631887197494507],$
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[1.521645609807299e-13, 0.40992528200149536],$
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[4.915687878270888e-13, 1.0217742919921875],$
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[1.7903951117830771e-13, 0.282895565032959],$
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[6.886249544234846e-14, 0.21058528125286102],$
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[9.49530897031588e-14, 0.2018834501504898]]
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for i=0L,5 do begin
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print, i, (ar[1,i])/(ar[0,i])
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endfor
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end
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@ -35,14 +35,14 @@ outfile_dir=root_path+'/products'
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create_folder(outfile_dir)
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index=5 # select energy band
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index=3 # select energy band
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do_init = False
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do_init = True
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do_merge = True
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do_rate = False
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do_adapt = False # requires CIAO
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do_adapt = True # requires CIAO
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vign=True
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vign=False
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vignetting = 'vign' if (vign==True) else 'novign'
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events=[]
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@ -61,8 +61,8 @@ for tmkey in keylist_tm.keys():
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do_init=do_init,
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do_obsmode=False,
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do_center=False,
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do_evtool=False,
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do_expmap=True,
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do_evtool=True,
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do_expmap=False,
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vign=vign,
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ra_cen=ra_cen, de_cen=de_cen,
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emin_kev=emin_kev[index],
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@ -43,6 +43,8 @@ import sys, os, os.path, time, subprocess
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from pathlib import Path
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import numpy as np
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import glob
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from multiprocessing import Pool
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from os.path import dirname
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import inspect
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import uds
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@ -59,24 +61,29 @@ infile_dir=root_path+'/data/processed'
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outfile_dir=root_path+'/products'
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create_folder(outfile_dir)
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do_init = True
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do_ermask = True
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run_Pool=False
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do_erbox1 = True # local mode
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do_erbackmap1 = True #
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do_erbox2 = True # map mode, with background map
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do_erbackmap2 = True #
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do_erbox3 = True # map mode, with background map
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do_erbackmap3 = True #
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do_init = False
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do_ermask = False
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do_ermldet = True
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do_catprep = True
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do_erbox1 = False # local mode
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do_erbackmap1 = False #
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do_erbox2 = False # map mode, with background map
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do_erbackmap2 = False #
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do_erbox3 = False # map mode, with background map
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do_erbackmap3 = False #
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do_ermldet = False
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do_catprep = False
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do_cross_match = False
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do_wcs_match = True # Chandra task
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do_wcs_update = True # Chandra task
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do_astro_corr = False # search optimal shift
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do_astro_update = True
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eband_selected=[0,1,2,3,4]
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do_wcs_match = False # Chandra task -- DEPRECATED
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do_wcs_update = False # Chandra task -- DEPRECATED
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eband_selected=[5]
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vign=True
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vignetting = 'vign' if (vign==True) else 'novign'
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@ -96,6 +103,11 @@ def runme(datakey):
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bkgimage=[]
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srcmaps=[]
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print(datakey)
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print('module name:', __name__)
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print('parent process:', os.getppid())
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print('process id:', os.getpid())
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for ii in range(len(eband_selected)):
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index=eband_selected[ii]
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print("\t>>> Energy band en{} -- {}-{} keV".format(eband[index],emin_kev[index],emax_kev[index]))
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@ -114,10 +126,10 @@ def runme(datakey):
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expmaps.append(outfile_expmap)
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events.append(outfile_evtool)
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"""
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After astrometry-corrected files (*.attcorr.fits) are obtained, one can take them as original, in order to check the full chain:
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events.append(outfile_evtool.replace(".fits", ".attcorr.fits"))
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"""
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# After astrometry-corrected files (*.attcorr.fits) are obtained, one can take them as original, in order to check the full chain:
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#events.append(outfile_evtool.replace(".fits", ".attcorr.fits"))
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""" Detmask """
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@ -339,12 +351,13 @@ def runme(datakey):
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]
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if(do_ermldet==True):
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test_exe('ermldet')
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remove_file(mllist)
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remove_file(srcmap)
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os.system((" ").join(cmd))
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print((" ").join(cmd))
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#save_ermldet_ds9reg(mllist,scale=60*60)
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save_ermldet_ds9reg(mllist,scale=60*60)
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catprep="{}_SourceCatalog_en{}{}".format(os.path.join(outfile_dir,datakey), eband[index], outfile_post)
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catprep_en0="{}_SourceCatalog_en{}{}".format(os.path.join(outfile_dir,datakey), eband[0], outfile_post)
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@ -359,11 +372,23 @@ def runme(datakey):
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if(do_cross_match==True):
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crossmatch_shu2019(catprep,dlmin=10,refimage=events[ii],crval=wcslist[datakey],
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catalog=root_path+"/data/Gaia_unWISE/Gaia_unWISE_UDS.fits.catalog")
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catalog=root_path+"/data/Gaia_unWISE/Gaia_unWISE_UDS.fits.catalog",errlim=5.0)
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if(do_wcs_match==True and eband[index]==0):
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if(do_astro_corr==True and eband[index]=='0'):
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""" run astro_corr for 0.3-2.3 keV only """
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wcs_astro_corr(catprep)
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#wcs_match_ciao(catprep, method='rst',radius=12,residlim=0,residtype=0,residfac=1)
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if(do_astro_update==True):
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""" run astro_corr for 0.3-2.3 keV only """
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attcorr=wcs_update_shift(events[ii],flog=catprep_en0.replace(".fits", ".shift.log"))
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do_evtool_esass(evfile=attcorr,outfile=attcorr,rmlock=False, do_center=True, ra_cen=ra_cen, de_cen=de_cen)
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if(do_wcs_match==True and eband[index]=='0'):
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""" run wcs_match for 0.3-2.3 keV only """
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wcs_match_ciao(catprep, method='rst',radius=12,residlim=5)
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wcs_match_ciao(catprep, method='trans',radius=12,residlim=5)
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#wcs_match_ciao(catprep, method='rst',radius=12,residlim=0,residtype=0,residfac=1)
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if(do_wcs_update==True):
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""" use 0.3-2.3 keV transform matrix for all other bands """
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@ -372,13 +397,28 @@ def runme(datakey):
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"""
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testing
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# individual run, testing
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runme("tm7_obs_1")
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runme("tm5_obs_1")
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runme("tm6_scan_1")
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"""
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if(run_Pool==True):
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# parallel run
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items=[]
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for tmkey in keylist_tm.keys():
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for datakey in keylist_tm[tmkey]:
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items.append(datakey)
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with Pool() as pool:
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pool.map(runme, items)
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else:
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# conventional run
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for tmkey in keylist_tm.keys():
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print("TM{} in work... init events".format(tmkey))
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for datakey in keylist_tm[tmkey]:
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print("--> {}".format(datakey))
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runme(datakey)
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#sys.exit()
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@ -13,7 +13,7 @@
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ВЫЗОВ:
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esass
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./01_mosaics.py
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./04_mosaics.py
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УПРАВЛЕНИЕ:
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@ -74,37 +74,39 @@ local_run = False
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outkey="tm0"
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do_init = False
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do_merge = False
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do_detmask = False
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do_expmap = False
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do_erbox1 = False # local mode
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do_erbackmap1 = False #
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do_erbox2 = False # map mode, with background map
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do_erbackmap2 = False #
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do_erbox3 = False # map mode, with background map
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do_erbackmap3 = False #
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do_init = True
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do_merge = True
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do_detmask = True
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do_expmap = True
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do_erbox1 = True # local mode
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do_erbackmap1 = True #
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do_erbox2 = True # map mode, with background map
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do_erbackmap2 = True #
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do_erbox3 = True # map mode, with background map
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do_erbackmap3 = True #
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do_ersensmap = False
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do_ermldet = False
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do_ermldet = True
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do_fixcat = False # only for index=0
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do_fixxmm = True # only for index=0
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do_fixxmm = False # prepare forced photometry, only for index=0
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do_apetool = False
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do_catprep = False
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do_catprep = True
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do_filter_catalog = False
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do_cross_match = False
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index=0
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index=3
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forced=False
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""" If forced=True, take input catalog from energy range en0 """
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comm='-xmm' # for 4XMM-DR12 forced photometry use '-xmm'
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comm='' # for 4XMM-DR12 forced photometry use '-xmm'
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vign=True
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vignetting = 'vign' if (vign==True) else 'novign'
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attcorr=True
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events=[]
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expmaps=[]
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bkgmaps=[]
|
||||
@ -113,7 +115,7 @@ for tmkey in keylist_tm.keys():
|
||||
for datakey in keylist_tm[tmkey]:
|
||||
print("--> {}".format(datakey))
|
||||
""" Подготавливаем списки событий индивидуальных наблюдений """
|
||||
outfile_evtool,outfile_expmap=init_events(key=datakey,
|
||||
outfile_evtool,outfile_expmap=init_events(key=datakey,attcorr=attcorr,
|
||||
eband_index=eband[index],
|
||||
infile_dir=infile_dir,
|
||||
outfile_dir=outfile_dir,
|
||||
@ -121,7 +123,7 @@ for tmkey in keylist_tm.keys():
|
||||
do_obsmode=False,
|
||||
do_center=False,
|
||||
do_evtool=True,
|
||||
do_expmap=True,
|
||||
do_expmap=False,
|
||||
vign=vign,
|
||||
ra_cen=ra_cen, de_cen=de_cen,
|
||||
emin_kev=emin_kev[index],
|
||||
@ -256,8 +258,8 @@ if(forced==True):
|
||||
srcmap="{}_SourceMap_en{}.forced{}{}".format(os.path.join(outfile_dir,outkey), eband[index], comm, outfile_post)
|
||||
|
||||
""" for en1,2,3,6 give mllist from en0 as input """
|
||||
boxlist3="{}_MaxLikSourceList_en{}.forced{}{}".format(os.path.join(outfile_dir,outkey), eband[0], comm, outfile_post)
|
||||
if(index==0):
|
||||
#boxlist3="{}_MaxLikSourceList_en{}.forced{}{}".format(os.path.join(outfile_dir,outkey), eband[0], comm, outfile_post)
|
||||
#if(index==0):
|
||||
boxlist3="{}_MaxLikSourceList_en{}.fixed{}{}".format(os.path.join(outfile_dir,outkey), eband[0], comm, outfile_post)
|
||||
if not (os.path.exists(boxlist3)):
|
||||
print("{} not found. Run do_fixcat=True, index=0, forced=False".format(boxlist3))
|
||||
@ -267,8 +269,9 @@ if(forced==True):
|
||||
fitpos_flag="fitpos_flag=no"
|
||||
fitext_flag="fitext_flag=no"
|
||||
nmulsou = "nmulsou=1"
|
||||
nmaxfit="nmaxfit=1"
|
||||
""" don't allow ermpldet to split sources """
|
||||
nmaxfit="nmaxfit=10"
|
||||
multrad="multrad=15."
|
||||
cutrad="cutrad=15."
|
||||
if(index == 3 or index == 6):
|
||||
""" for hard band take unvignetted background """
|
||||
outfile_backmap3="{}_BackMap3_en{}.{}{}".format(os.path.join(outfile_dir,outkey), eband[index], "novign", outfile_post)
|
||||
@ -281,10 +284,12 @@ else:
|
||||
fitext_flag="fitext_flag=yes"
|
||||
nmulsou = "nmulsou=2"
|
||||
nmaxfit="nmaxfit=4"
|
||||
multrad="multrad=20."
|
||||
cutrad="cutrad=20."
|
||||
""" allow ermpldet to split sources (no more than two) """
|
||||
|
||||
cmd=["ermldet",
|
||||
"mllist=%s" %(mllist),
|
||||
"mllist={}".format(mllist),
|
||||
"boxlist=%s" %(boxlist3),
|
||||
"images=\'{}\'".format(outfile_evtool),
|
||||
"expimages=\'{}\'".format(outfile_expmap),
|
||||
@ -297,8 +302,8 @@ cmd=["ermldet",
|
||||
"likemin=0.",
|
||||
"extlikemin=5.",
|
||||
"compress_flag=N",
|
||||
"cutrad=15.",
|
||||
"multrad=20.",
|
||||
cutrad,
|
||||
multrad,
|
||||
"extmin=2.0",
|
||||
"extmax=35.0",
|
||||
#"bkgima_flag=Y", looks outdated
|
||||
@ -337,17 +342,22 @@ if(do_ersensmap==True):
|
||||
"""
|
||||
|
||||
if(do_ermldet==True):
|
||||
test_exe('ermldet')
|
||||
if(vign==False):
|
||||
print('Run ermldet with vignetted exposure!')
|
||||
sys.exit()
|
||||
remove_file(mllist)
|
||||
remove_file(srcmap)
|
||||
print(cmd)
|
||||
runme(cmd, local_run=local_run)
|
||||
print(cmd)
|
||||
save_ermldet_ds9reg(mllist,scale=60*60,label='det_like')
|
||||
save_ermldet_ds9reg(mllist,scale=60*60,label='id_src')
|
||||
|
||||
#correct_fluxerr_ermldet_forced(mllist)
|
||||
correct_fluxerr_ermldet_forced(mllist)
|
||||
if(forced==True):
|
||||
result = check_ermldet_forced(mllist)
|
||||
""" for a some reason, for an arbitrary energy band, ermldet break order of sources. Do this forced correction. """
|
||||
# for a some reason, for an arbitrary energy band, ermldet break order of sources. Do this forced correction.
|
||||
if(result == False):
|
||||
correct_srcid_ermldet_forced(mllist)
|
||||
|
||||
@ -359,32 +369,22 @@ if(do_fixcat==True):
|
||||
print("ERROR: You can fix only non-forced catalog for en0.")
|
||||
sys.exit()
|
||||
|
||||
srcs_remove=[174,
|
||||
90,
|
||||
299,
|
||||
300,
|
||||
504,
|
||||
215,
|
||||
401,
|
||||
20,] # keep 671 as unclassified extended source
|
||||
srcs_add = {'4XMM J021925.4-042647':[34.8559099,-4.4465007, 1.366], # 147
|
||||
'4XMM J021922.8-042655':[34.8451832,-4.4487901, 1.958], # 147
|
||||
'4XMM J021929.4-043224':[34.8728586,-4.5400022, 0.660], # 90
|
||||
'4XMM J021931.2-043222':[34.8801169,-4.5395495, 2.561], # 90
|
||||
'4XMM J021911.2-050550':[34.7968110,-5.0972990, 0.732], # 504
|
||||
'4XMM J021919.3-050511':[34.8307176,-5.0864242,4.988], # 504
|
||||
'4XMM J021911.5-050501':[34.7981099,-5.0837146,6.834], # 504
|
||||
'4XMM J021658.9-044900':[34.2455964,-4.8168126,4.449], # 300
|
||||
'4XMM J021659.2-044945':[34.2468704,-4.8291892,1.548], # 300
|
||||
'4XMM J021812.2-045814':[34.5510753,-4.9705972,0.550], # 215
|
||||
'4XMM J021812.0-045813':[34.5502698,-4.9703004,0.497], # 215
|
||||
'4XMM J021912.6-052756':[34.8028459,-5.4656239,0.579], # 401
|
||||
'4XMM J021705.5-042254':[34.2730294,-4.3816810,0.288], # 20
|
||||
'4XMM J021705.3-042314':[34.2720952,-4.3873162,0.587], # 20
|
||||
'4XMM J021827.2-045456':[34.6134256,-4.9157208,0.252],
|
||||
'4XMM J021831.3-045504':[34.6306930,-4.9178676,0.242],
|
||||
'4XMM J021925.4-045201':[34.8558373,-4.8671200,0.529],
|
||||
|
||||
srcs_remove=[341,446,346,96]
|
||||
srcs_add = {'4XMM J021738.8-051257':[34.4117002, -5.2159135, 0.624],# 341
|
||||
'4XMM J021733.8-051311':[34.3910215,-5.2199877,2.247],# 341
|
||||
'4XMM J021929.4-051220':[34.8725460,-5.2056849,1.074],#446
|
||||
'4XMM J021930.7-051225':[34.8782267,-5.2072112,0.624],# 446
|
||||
'4XMM J021945.2-045331':[34.9383593,-4.8919843,1.538],#346
|
||||
'4XMM J021929.4-043224':[34.8728586,-4.5400022,0.659555],#96
|
||||
#'4XMM J021929.4-043224':[34.8728586,-4.5400022, 0.660],
|
||||
#'4XMM J021831.8-050059':[34.6328841,-5.0163909,1.529],
|
||||
#'4XMM J022131.1-050027':[35.3797879,-5.0075498,0.941],
|
||||
#'4XMM J022129.5-045914':[35.3732136,-4.9874025,0.332],
|
||||
#'4XMM J022026.3-050251':[35.1098619,-5.0476199,0.551],
|
||||
#'4XMM J021925.4-042647':[34.8559099,-4.4465007,1.366],
|
||||
#'4XMM J021910.9-045108':[34.7954311,-4.8522901,0.898],
|
||||
#'4XMM J021945.2-045331':[34.9383593,-4.8919843,1.538],
|
||||
#'4XMM J021733.8-051311':[34.3910215,-5.2199877,2.247],
|
||||
}
|
||||
fix_catalog(mllist=mllist,refimage=outfile_evtool, srcs_remove=srcs_remove, srcs_add=srcs_add)
|
||||
"""
|
||||
@ -451,7 +451,7 @@ if(do_filter_catalog==True):
|
||||
#filter_mllist(mllist,expcut=5000.0,dlcut=10.0,dlmin=10,dlmax=10000)
|
||||
""" works the same """
|
||||
filter_catprep(catprep,expcut=5000.0,dlmin=10,dlmax=10000,outkey='bright')
|
||||
filter_catprep(catprep,expcut=5000.0,dlmin=6,dlmax=10,outkey='faint')
|
||||
#filter_catprep(catprep,expcut=5000.0,dlmin=6,dlmax=10,outkey='faint')
|
||||
|
||||
if(do_cross_match==True):
|
||||
crossmatch_shu2019(catprep,dlmin=10,refimage=outfile_evtool,crval=[ra_cen, de_cen],
|
||||
|
||||
@ -79,14 +79,28 @@ do_srctool = False
|
||||
do_grppha = False
|
||||
do_ecf_calc = False # for all bands
|
||||
do_ecf_print = False # for all bands
|
||||
do_flux_calc = False # for all bands
|
||||
|
||||
do_catalog = False
|
||||
do_extended = False
|
||||
do_ds9reg = False
|
||||
do_euds_final = False
|
||||
do_euds_dr12 = False # crossmatch eUDS with DR12
|
||||
do_euds_stat = False
|
||||
do_euds_cds = False
|
||||
|
||||
do_xmm_catalog = False
|
||||
do_xmm_final = True
|
||||
do_xmm_final = False
|
||||
do_xmm_xmatch = False
|
||||
do_xmm_ds9reg = False
|
||||
do_xmm_cds = False
|
||||
do_euds_cosmatch = True
|
||||
|
||||
do_cross_check = False # Check whether all E3,E6 sources are detected in E0
|
||||
|
||||
|
||||
index=0
|
||||
""" работаем именно в этом диапазоне, чтобы спектры покрывали все энергии """
|
||||
""" чтобы спектры покрывали все энергии работаем в диапазоне 5 """
|
||||
|
||||
vign=True
|
||||
vignetting = 'vign' if (vign==True) else 'novign'
|
||||
@ -99,7 +113,7 @@ for tmkey in keylist_tm.keys():
|
||||
for datakey in keylist_tm[tmkey]:
|
||||
print("--> {}".format(datakey))
|
||||
""" Подготавливаем списки событий индивидуальных наблюдений """
|
||||
outfile_evtool,outfile_expmap=init_events(key=datakey,
|
||||
outfile_evtool,outfile_expmap=init_events(key=datakey,attcorr=True,
|
||||
eband_index=eband[index],
|
||||
infile_dir=infile_dir,
|
||||
outfile_dir=outfile_dir,
|
||||
@ -144,19 +158,21 @@ if(do_srctool==True):
|
||||
"eventfiles={}".format(outfile_evtool),
|
||||
"prefix=\'{}\'".format(os.path.join(srctool_dir,outfile_srctool)),
|
||||
"suffix=\'{}\'".format(suffix_srctool),
|
||||
"srccoord={}".format(catprep),
|
||||
"srccoord={}".format("../products/eUDS_for_srctool.fits"),
|
||||
# the same as original file eUDS.fits, but changed ML_CTS --> ML_CTS_0, ML_BKG --> ML_BKG_0, ML_EXP --> ML_EXP_0
|
||||
#"srcreg=\'fk5;circle * * 60s\'",
|
||||
#"backreg=\'fk5;annulus * * 90s 120s\'",
|
||||
"srcreg=AUTO",
|
||||
"backreg=AUTO",
|
||||
"clobber=yes",]
|
||||
os.system((" ").join(cmd))
|
||||
print((" ").join(cmd))
|
||||
#os.system((" ").join(cmd))
|
||||
#print((" ").join(cmd))
|
||||
|
||||
if(do_grppha==True):
|
||||
group_spectra("{}/*_SourceSpec_*.fits".format(srctool_dir))
|
||||
group_spectra("{}/*020_SourceSpec_*.fits".format(srctool_dir))
|
||||
|
||||
ecfout="{}_SampleFlux.pickle".format(os.path.join(outfile_dir,outkey))
|
||||
ecfout="{}_SampleFlux_v1.pickle".format(os.path.join(outfile_dir,outkey))
|
||||
|
||||
if(do_ecf_calc==True):
|
||||
calc_ecf("{}/tm0_SrcTool_020_ARF_?????.fits".format(srctool_dir),
|
||||
@ -165,16 +181,27 @@ if(do_ecf_calc==True):
|
||||
if(do_ecf_print==True):
|
||||
print_ecf(infile=ecfout, emin=emin_kev, emax=emax_kev, eband=eband, skipfrac=10.0)
|
||||
|
||||
index=0
|
||||
fluxout="{}_SherpaFlux.pickle".format(os.path.join(outfile_dir,outkey))
|
||||
if(do_flux_calc==True):
|
||||
calc_flux("{}/tm0_SrcTool_020_ARF_?????.fits".format(srctool_dir),
|
||||
catprep=catprep, emin=emin_kev, emax=emax_kev, eband=eband, outfile=ecfout, simnum=100)
|
||||
|
||||
|
||||
|
||||
#index=0
|
||||
|
||||
catprep="{}_SourceCatalog_en{}{}".format(os.path.join(outfile_dir,outkey), eband[index], outfile_post)
|
||||
rawcat="{}_SourceCatalog_en{}.pickle".format(os.path.join(outfile_dir,outkey), eband[index])
|
||||
if(do_catalog==True):
|
||||
forced_xmm_sources="{}_MaxLikSourceList_en{}.xmm.pickle".format(os.path.join(outfile_dir,outkey), eband[index])
|
||||
with open(forced_xmm_sources, 'rb') as f:
|
||||
print("Reading forced XMM sources from {}".format(forced_xmm_sources))
|
||||
srcs_forced = pickle.load(f)
|
||||
print()
|
||||
print(srcs_forced)
|
||||
print()
|
||||
|
||||
make_catalog(infile='../products/tm0_SourceCatalog_en0.forced.fits', rawcat=rawcat, dlmin=10.0, dlmax=100000, ext_like=1000,
|
||||
make_euds_catalog(infile='../products/tm0_SourceCatalog_en0.forced.fits', rawcat=rawcat, dlmin=10.0, dlmax=100000, ext_like=1000,
|
||||
emin=emin_kev[index], emax=emax_kev[index], eband=eband[index],
|
||||
infile_en00cat=catprep,
|
||||
infile_en01cat='../products/tm0_SourceCatalog_en1.forced.fits',
|
||||
@ -194,7 +221,27 @@ if(do_extended==True):
|
||||
make_extended(infile=rawcat,outreg="{}_ExtendedCat_en{}.reg".format(os.path.join(outfile_dir,outkey), eband[index]))
|
||||
|
||||
if(do_ds9reg==True):
|
||||
make_final_ds9reg(infile=rawcat,outreg="{}_FinalCat_dl10.reg".format(os.path.join(outfile_dir,outkey)))
|
||||
#make_final_ds9reg(infile=rawcat,outreg="{}_FinalCat_dl10.reg".format(os.path.join(outfile_dir,outkey)))
|
||||
make_final_ds9reg(infile=rawcat,scale=(60*60)/10,outreg="{}_FinalCat_dl10_talk.reg".format(os.path.join(outfile_dir,outkey)))
|
||||
|
||||
if(do_euds_final==True):
|
||||
""" make final eUDS catalog """
|
||||
final_euds_catalog(infile=rawcat, outfile_fits='../products/eUDS.fits')
|
||||
|
||||
if(do_euds_dr12==True):
|
||||
crossmatch_dr12('../products/eUDS.fits', catalog=root_path+"/data/4XMM-DR12/4XMM_DR12cat_slim_v1.0_UDS.fits.catalog", devmax=15)
|
||||
|
||||
|
||||
|
||||
if(do_euds_stat==True):
|
||||
make_euds_stat(infile="../products/eUDS.fits",fluxlim=5e-14)
|
||||
|
||||
if(do_euds_cds==True):
|
||||
make_euds_cds(infile="../products/eUDS.fits",outfile='../products/eUDS.cds')
|
||||
|
||||
if(do_cross_check==True):
|
||||
""" cross check final eUDS catalog """
|
||||
cross_check_euds(infile=catprep, euds='../products/eUDS.fits', outkey="../products/en{}_FinalCat_dl10".format(index))
|
||||
|
||||
if(do_xmm_catalog==True):
|
||||
""" complile raw forced XMM catalog """
|
||||
@ -211,3 +258,27 @@ if(do_xmm_final==True):
|
||||
""" make final XMM-forced catalog """
|
||||
final_xmm_catalog(infile='../products/tm0_4XMM-DR12.pickle', outfile_fits='../products/eUDS_4XMM-DR12.fits')
|
||||
|
||||
if(do_xmm_xmatch==True):
|
||||
""" cross-match XMM-forced catalog
|
||||
outfile_cvs contains 0.3-2.3 keV eUDS flux (col1=flux,col2=err) vs. 4XMM-DR12 flux (col3=flux, col4=err)
|
||||
XMM flux was converted from 0.2-2.0 keV to 0.3-2.3 keV using wabs*powerlow with wabs=0.02 gamma=2.0
|
||||
"""
|
||||
final_xmm_xmatch(infile='../products/eUDS_4XMM-DR12.fits',
|
||||
xmmslim='../data/4XMM-DR12/4XMM_DR12cat_slim_v1.0_UDS.fits.catalog',
|
||||
xmmfull='../data/4XMM-DR12/4XMM_DR12cat_v1.0_UDS.fits.catalog',
|
||||
xmmlim=2e-14,
|
||||
outfile_flux="../products/eUDS_4XMM-DR12.flux.csv")
|
||||
|
||||
if(do_xmm_ds9reg==True):
|
||||
""" show XMM-forced catalog """
|
||||
make_xmm_ds9reg_confused(infile='../products/eUDS_4XMM-DR12.fits', outfile='../products/eUDS_4XMM-DR12.confused.reg')
|
||||
|
||||
""" obsolete """
|
||||
if(do_xmm_cds==True):
|
||||
make_xmm_cds(infile="../products/eUDS_4XMM-DR12.fits", outfile='../products/eUDS_4XMM-DR12.cds')
|
||||
|
||||
|
||||
|
||||
if(do_euds_cosmatch==True):
|
||||
""" prepare eUDS catalog for CosMatch (Mescheryakov) """
|
||||
make_euds_cosmatch(infile='../products/eUDS.fits', outfile='../products/eUDS-CosMatch.fits')
|
||||
|
||||
@ -45,10 +45,10 @@ import glob
|
||||
from os.path import dirname
|
||||
import inspect
|
||||
import uds
|
||||
|
||||
from scipy.stats import norm
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
|
||||
import pandas as pd
|
||||
|
||||
from uds.utils import *
|
||||
from uds.config import *
|
||||
@ -76,7 +76,13 @@ outkey="tm0"
|
||||
outfile_srctool="{}_SrcTool_".format(outkey)
|
||||
|
||||
do_flux_distr = False
|
||||
do_sens_curve = True
|
||||
do_sens_curve = False
|
||||
do_4xmm_ratio = False
|
||||
do_euds_radec_err = False
|
||||
do_euds_dr12_diff = False
|
||||
do_euds_dr12_stat = True
|
||||
|
||||
do_print_ecf = False
|
||||
|
||||
index=0
|
||||
|
||||
@ -88,7 +94,8 @@ if not (os.path.isfile(catalog)==True):
|
||||
|
||||
if(do_flux_distr==True):
|
||||
|
||||
data, logbins = get_log_distr(infile=catalog, field='ml_rate', minval=1e-3, maxval=2)
|
||||
|
||||
data, logbins, mean, median = 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)
|
||||
@ -103,7 +110,7 @@ if(do_flux_distr==True):
|
||||
plt.close(fig)
|
||||
|
||||
|
||||
data, logbins = get_log_distr(infile=catalog, field='ml_flux', minval=1e-15, maxval=2e-12)
|
||||
data, logbins, mean, median = 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)
|
||||
@ -143,11 +150,12 @@ if(do_sens_curve==True):
|
||||
ax.set_xlim([3e-16,1e-13])
|
||||
ax.set_ylim([0.3,160])
|
||||
|
||||
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/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")
|
||||
@ -187,3 +195,251 @@ if(do_sens_curve==True):
|
||||
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)
|
||||
"""
|
||||
if(do_4xmm_ratio==True):
|
||||
filename="../products/eUDS_4XMM-DR12.flux.csv"
|
||||
|
||||
data, logbins, mean, median = get_log_distr(infile=filename, field='ratio', minval=8e-2, maxval=60, nbin=60)
|
||||
print("Median {}".format(median))
|
||||
print(" Mean {}".format(mean))
|
||||
print("Ntotal {}".format(len(data)))
|
||||
fig, ax = plt.subplots()
|
||||
#plt.figure(figsize=(5,5))
|
||||
#plt.figure().set_figheight(3.6)
|
||||
#plt.rcParams['figure.figsize'] = [4, 4]
|
||||
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.axvline(x = median, color = 'black', label = 'Median value', linestyle='dashed')
|
||||
plt.xlabel('Energy flux ratio',fontsize=14, fontweight='normal')
|
||||
plt.ylabel('Number',fontsize=14, fontweight='normal')
|
||||
plt.grid(visible=True)
|
||||
plt.xscale('log')
|
||||
plt.yscale('log')
|
||||
plt.savefig(filename.replace(".csv", ".distr.png"), bbox_inches='tight')
|
||||
plt.close(fig)
|
||||
|
||||
df = pandas.read_csv(filename)
|
||||
fig, ax = plt.subplots()
|
||||
#plt.rcParams['figure.figsize'] = [4, 4]
|
||||
#plt.figure(figsize=(5,5))
|
||||
#plt.figure().set_figheight(4)
|
||||
for axis in ['top','bottom','left','right']:
|
||||
ax.spines[axis].set_linewidth(1)
|
||||
ax.tick_params(axis="both", width=1, labelsize=14)
|
||||
plt.plot(np.array([1e-17,1e-11]), np.array([1e-17,1e-11]), linestyle = 'solid', color='black')
|
||||
plt.plot(np.array([1e-17,1e-11]), 10*np.array([1e-17,1e-11]), linestyle = 'dashed', color='black')
|
||||
plt.plot(np.array([1e-17,1e-11]), 0.1*np.array([1e-17,1e-11]), linestyle = 'dotted', color='black')
|
||||
#plt.plot(np.array([1e-17,1e-11]), median*np.array([1e-17,1e-11]), linestyle = 'dashed', color='blue')
|
||||
plt.errorbar(df['dr12_flux'],df['euds_flux'], yerr=df['euds_flux_err'], xerr=df['dr12_flux_err'], linestyle='None', color='black', label='Errors')
|
||||
plt.plot(df['dr12_flux'],df['euds_flux'], marker="o", linewidth=1, linestyle='None', markerfacecolor='Gold',markeredgecolor="black",)
|
||||
#plt.axvline(x = median, color = 'black', label = 'Median value', linestyle='dashed')
|
||||
plt.xlabel('4XMM-DR12 Energy flux (erg s$^{-1}$ cm$^{-2}$)',fontsize=14, fontweight='normal')
|
||||
plt.ylabel('eUDS Energy flux (erg s$^{-1}$ cm$^{-2}$)',fontsize=14, fontweight='normal')
|
||||
plt.grid(visible=True)
|
||||
plt.xlim(2e-16,1e-12)
|
||||
plt.ylim(1e-15,2e-12)
|
||||
plt.xscale('log')
|
||||
plt.yscale('log')
|
||||
plt.savefig(filename.replace(".csv", ".png"), bbox_inches='tight')
|
||||
plt.close(fig)
|
||||
|
||||
if(do_euds_radec_err==True):
|
||||
filename="../products/eUDS.fits"
|
||||
|
||||
ecat={}
|
||||
hdul = fits.open(filename)
|
||||
etab = hdul[1].data
|
||||
hdul.close()
|
||||
|
||||
x=[]
|
||||
y=[]
|
||||
for s in etab:
|
||||
if ("XMM" in s['DR12_IAU_NAME']):
|
||||
print("Skip ",s['DR12_IAU_NAME'])
|
||||
continue
|
||||
if (s['EXT_LIKE']>0.0):
|
||||
print("Skip extended ",s['ID_SRC'])
|
||||
continue
|
||||
x.append(s['DET_LIKE'])
|
||||
y.append(s['RADEC_ERR'])
|
||||
|
||||
|
||||
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([10,10000])
|
||||
ax.set_ylim([0.1,40])
|
||||
|
||||
plt.plot(x,y,".", color="gold", markersize=12, markeredgewidth=1.5, markeredgecolor="black")
|
||||
|
||||
plt.xlabel('DET_LIKE',fontsize=14, fontweight='normal')
|
||||
plt.ylabel('RADEC_ERR (arcsec)',fontsize=14, fontweight='normal')
|
||||
plt.grid(visible=True)
|
||||
plt.xscale('log')
|
||||
plt.yscale('log')
|
||||
png="../products/en0_radec_err.png"
|
||||
plt.savefig(png, bbox_inches='tight')
|
||||
plt.close(fig)
|
||||
|
||||
stat={}
|
||||
hdul = fits.open("../products/eUDS.dr12.cross.fits")
|
||||
tab = hdul[1].data
|
||||
hdul.close()
|
||||
|
||||
print(len(np.unique(tab['ID'])))
|
||||
for rec in tab:
|
||||
sid=rec['ID']
|
||||
if sid in stat.keys():
|
||||
stat[sid]=stat[sid]+1
|
||||
else:
|
||||
stat[sid]=1
|
||||
|
||||
unique=0
|
||||
double=0
|
||||
triple=0
|
||||
for key in stat.keys():
|
||||
if(stat[key]==1):
|
||||
unique=unique+1
|
||||
if(stat[key]==2):
|
||||
double=double+1
|
||||
if(stat[key]==3):
|
||||
triple=triple+1
|
||||
print("unique: {}, double: {}. triple: {}".format(unique, double, triple))
|
||||
|
||||
|
||||
if(do_euds_dr12_diff==True):
|
||||
# read forced first
|
||||
# fieldnames = ['euds_det_like', 'euds_flux', 'euds_flux_err', 'dr12_flux', 'dr12_flux_err', 'ratio']
|
||||
filename="../products/eUDS_4XMM-DR12.flux.csv"
|
||||
df = pandas.read_csv(filename)
|
||||
# calculate difference similar to Bruner
|
||||
|
||||
threshold=5e-14
|
||||
|
||||
# forced catalog contains CONF flag, take it to remove from histogram
|
||||
hdul = fits.open("../products/eUDS_4XMM-DR12.fits")
|
||||
forced = hdul[1].data
|
||||
fcat={}
|
||||
for rec in forced:
|
||||
key=rec['DR12_SRCID']
|
||||
fcat[key]={'conf':rec['CONF'],}
|
||||
|
||||
# read cross-match results (not forced)
|
||||
hdul = fits.open('../products/eUDS.dr12.cross.fits')
|
||||
tb = hdul[1].data
|
||||
cross_diff=[]
|
||||
cross_ratio=[]
|
||||
mean=0.0
|
||||
count=0
|
||||
for ind,s in enumerate(tb):
|
||||
key=rec['DR12_SRCID']
|
||||
#if not (tb[ind]['dr12_flux']>threshold and tb[ind]['src_flux']>threshold):
|
||||
if not (tb[ind]['dr12_flux']>threshold):
|
||||
continue
|
||||
ape_flux=(tb[ind]['ape_cts']-tb[ind]['ape_bkg'])/tb[ind]['ape_exp']/ecf[index]
|
||||
|
||||
cross_dr12_flux=(tb[ind]['dr12_flux'])
|
||||
cross_dr12_flux_error=(tb[ind]['dr12_flux_error'])
|
||||
cross_euds_flux=(tb[ind]['src_flux'])
|
||||
#cross_euds_flux=ape_flux
|
||||
cross_euds_flux_error=(tb[ind]['src_flux_error'])
|
||||
|
||||
print(cross_euds_flux,cross_euds_flux_error,tb[ind]['ape_cts'],tb[ind]['det_like'])
|
||||
|
||||
d=(cross_dr12_flux - cross_euds_flux) / np.sqrt(cross_dr12_flux_error**2 + cross_euds_flux_error**2)
|
||||
#if(d < -15):
|
||||
# continue
|
||||
r=cross_euds_flux/cross_dr12_flux
|
||||
cross_diff.append(d)
|
||||
cross_ratio.append(r)
|
||||
|
||||
#if(d < -15.0):
|
||||
#print("GGG",d,r,cross_euds_flux,cross_dr12_flux)
|
||||
#print(tb[ind]['DR12_NAME'],tb[ind]['DR12_RA'],tb[ind]['DR12_DEC'])
|
||||
mean=mean + (cross_euds_flux/cross_dr12_flux)
|
||||
count=count+1
|
||||
|
||||
|
||||
|
||||
print("min={:.2f}, max={:.2f}, mean={:.2f}, median={:.2f}, std={:.2f} N={}".format(min(cross_diff),
|
||||
max(cross_diff),
|
||||
np.mean(cross_diff),
|
||||
np.median(cross_diff),
|
||||
np.std(cross_diff),
|
||||
len(cross_diff)))
|
||||
print("ratio mean",mean/count)
|
||||
print("ratio median",np.median(cross_ratio))
|
||||
|
||||
|
||||
|
||||
nbin=50
|
||||
bins=np.linspace(-30,30, nbin)
|
||||
|
||||
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(cross_diff, bins=bins,histtype='step', color='green', linewidth=1, linestyle='solid', density=True)
|
||||
|
||||
#x = np.arange(-10, 10, 0.001)
|
||||
#plot normal distribution with mean 0 and standard deviation 1
|
||||
#plt.plot(x, norm.pdf(x, 0, 1), color='red', linewidth=2)
|
||||
|
||||
plt.ylabel('Relative fraction',fontsize=14, fontweight='normal')
|
||||
plt.xlabel('(F$_{XMM}$-F$_{eUDS}$)/$\sqrt{\Delta F_{XMM}^{2}+\Delta F_{eUDS}^{2}}$',fontsize=14, fontweight='normal')
|
||||
plt.grid(visible=True)
|
||||
plt.xscale('linear')
|
||||
plt.yscale('linear')
|
||||
ax.set_xlim([-31, 31])
|
||||
ax.set_ylim([0, 0.2])
|
||||
plt.savefig("../products/cross-match_diff.png", bbox_inches='tight')
|
||||
plt.close(fig)
|
||||
|
||||
|
||||
nbin=200
|
||||
bins=np.linspace(-1,1.0, nbin)
|
||||
|
||||
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(cross_ratio, bins=bins, histtype='step', color='green', linewidth=1, linestyle='solid', density=False)
|
||||
|
||||
#x = np.arange(-10, 10, 0.001)
|
||||
#plot normal distribution with mean 0 and standard deviation 1
|
||||
#plt.plot(x, norm.pdf(x, 0, 1), color='red', linewidth=2)
|
||||
|
||||
plt.xlabel('eUDS and 4XMM-DR12 flux ratio',fontsize=14, fontweight='normal')
|
||||
plt.ylabel('Relative fraction',fontsize=14, fontweight='normal')
|
||||
plt.grid(visible=True)
|
||||
plt.xscale('linear')
|
||||
plt.yscale('linear')
|
||||
plt.savefig("../products/cross-match_ratio.png", bbox_inches='tight')
|
||||
plt.close(fig)
|
||||
|
||||
|
||||
if(do_print_ecf==True):
|
||||
filename='../data/ECF/ecf_tbabspow_g2nh0.02.pkl'
|
||||
with open(filename, 'rb') as f:
|
||||
ecf_table = pickle.load(f)
|
||||
"""
|
||||
for key in table.keys():
|
||||
print("{} --> {}".format(key,table[key]))
|
||||
"""
|
||||
|
||||
print(ecf_table[(0.3,2.3)])
|
||||
print(ecf_table[(0.3,0.6)])
|
||||
print(ecf_table[(0.6,2.3)])
|
||||
print(ecf_table[(2.3,5.0)])
|
||||
print(ecf_table[(5.0,8.0)])
|
||||
print()
|
||||
print(ecf_table[(0.5,1.0)]) # 4XMM-DR12 EP2 band
|
||||
print(ecf_table[(1.0,2.0)]) # 4XMM-DR12 EP3 band
|
||||
|
||||
if(do_euds_dr12_stat==True):
|
||||
dr12_stat(infile='../products/eUDS_4XMM-DR12.fits',
|
||||
xmmslim='../data/4XMM-DR12/4XMM_DR12cat_slim_v1.0_UDS.fits.catalog',
|
||||
xmmlim=None,
|
||||
outfile_reg='../products/dr12_fluxlim.reg')
|
||||
|
||||
55
scripts/print_radec_err.py
Normal file
55
scripts/print_radec_err.py
Normal file
@ -0,0 +1,55 @@
|
||||
import glob, sys
|
||||
from astropy.io import fits
|
||||
import statistics
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
import csv
|
||||
colnames=['Match', 'Ref', 'Dup', 'RA', 'Dec', 'Incl']
|
||||
|
||||
flist=glob.glob('../products/tm[1,5,6,7]*en0*src.fits')
|
||||
total1=0
|
||||
total2=0
|
||||
|
||||
for f in flist:
|
||||
|
||||
hdul = fits.open(f)
|
||||
try:
|
||||
table=hdul[1].data['RADEC_ERR']
|
||||
except:
|
||||
continue
|
||||
hdul.close()
|
||||
|
||||
dref=f.replace("src.fits","ref.fits")
|
||||
hdul = fits.open(dref)
|
||||
try:
|
||||
rtable=hdul[1].data['RA']
|
||||
except:
|
||||
continue
|
||||
hdul.close()
|
||||
|
||||
err=[]
|
||||
err10=[]
|
||||
dfile=f.replace("shu2019.src.fits","xfm.log.dat.awk")
|
||||
with open(dfile) as csvfile:
|
||||
spamreader = csv.reader(csvfile, delimiter=' ')
|
||||
total=0
|
||||
for row in spamreader:
|
||||
if(row[5] == 'N'):
|
||||
continue
|
||||
for ii,values in np.ndenumerate(rtable):
|
||||
if(int(row[2]) == int(ii[0])):
|
||||
total=total+1
|
||||
#print(">>",row[5],rtable[ii],table[ii],ii[0])
|
||||
if(table[ii]>0.0):
|
||||
err.append(table[ii])
|
||||
if(table[ii]>10.0):
|
||||
err10.append(table[ii])
|
||||
|
||||
total1=total1+total
|
||||
total2=total2+len(err)
|
||||
#print("{} MIN {:.2f} MAX {:.2f} ({}/{})".format(f[12:15],min(err),max(err),len(err10),len(err)))
|
||||
print("{} MIN {:.2f} MAX {:.2f} ({}/{})".format(f,min(err),max(err),len(err10),len(err)))
|
||||
#sys.exit()
|
||||
|
||||
|
||||
#print(total1,total2)
|
||||
67
scripts/print_transform.py
Normal file
67
scripts/print_transform.py
Normal file
@ -0,0 +1,67 @@
|
||||
import glob, sys
|
||||
from astropy.io import fits
|
||||
import statistics
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
import csv
|
||||
from uds.config import *
|
||||
|
||||
colnames=['Match', 'Ref', 'Dup', 'RA', 'Dec', 'Incl']
|
||||
|
||||
flist=glob.glob('../products/tm[1,5,6,7]*en0*.xfm')
|
||||
total1=0
|
||||
total2=0
|
||||
|
||||
for f in flist:
|
||||
|
||||
pos = f.find("_SourceCatalog")
|
||||
key=f[12:pos]
|
||||
|
||||
hdul = fits.open(f)
|
||||
try:
|
||||
tab=hdul[1].data
|
||||
except:
|
||||
continue
|
||||
hdul.close()
|
||||
|
||||
dsrc=f.replace(".xfm",".shu2019.src.fits")
|
||||
hdul = fits.open(dsrc)
|
||||
try:
|
||||
hdr=hdul[0].header
|
||||
cdelt=hdr['CDELT2']*3600
|
||||
except:
|
||||
continue
|
||||
hdul.close()
|
||||
|
||||
a11=tab[0]['a11']
|
||||
a12=tab[0]['a12']
|
||||
a22=tab[0]['a22']
|
||||
a21=tab[0]['a21']
|
||||
x_scale=tab[0]['x_scale']
|
||||
y_scale=tab[0]['y_scale']
|
||||
|
||||
t1=tab[0]['t1']*cdelt
|
||||
t2=tab[0]['t2']*cdelt
|
||||
|
||||
sx1=np.sign(a11)*np.sqrt(a11**2 + a12**2)
|
||||
sy1=np.sign(a22)*np.sqrt(a21**2 + a22**2)
|
||||
|
||||
sx2=np.sign(a11)*np.sqrt(a11**2 + a21**2)
|
||||
sy2=np.sign(a22)*np.sqrt(a12**2 + a22**2)
|
||||
|
||||
a1 = np.arctan2(a12/sx1,a11/sy2) * 180 / np.pi * 60
|
||||
a2 = np.arctan2(a12/sx1,a22/sy2) * 180 / np.pi * 60
|
||||
|
||||
b1 = np.arctan2(a21,a11) * 180 / np.pi * 60
|
||||
b2 = np.arctan2(a21,a22) * 180 / np.pi * 60
|
||||
|
||||
det=a11*a22-a12*a21
|
||||
|
||||
alpha=355*np.pi/180
|
||||
a3 = np.arctan2(np.sin(alpha),np.cos(alpha)) * 180 / np.pi
|
||||
|
||||
print("{:+.8} {:+.8}".format(a11,a12))
|
||||
print("{:+.8} {:+.8}".format(a21,a22))
|
||||
|
||||
#print("{} d {:.10f} s {:.8f} {:.8f} {:.8f} {:.8f} | {:+.8f} {:+.8f} {:+.8f} {:+.8f} t {:+.2f} {:+.2f}".format(obslist[key],np.sqrt(det)*cdelt,sx1*cdelt,sx2*cdelt,sy1*cdelt,sy2*cdelt,a1,a2,b1,b2,t1,t2))
|
||||
#print("{} d {:.10f} s {:.8f} {:.8f} {:.8f} {:.8f} | {:+.8f} {:+.8f} {:+.8f} {:+.8f} t {:+.2f} {:+.2f}".format(obslist[key],np.sqrt(det)*cdelt,sx1*cdelt,sx2*cdelt,sy1*cdelt,sy2*cdelt,a1,a2,b1,b2,t1,t2))
|
||||
468
uds/uds/astrometry.py
Normal file
468
uds/uds/astrometry.py
Normal file
@ -0,0 +1,468 @@
|
||||
import glob
|
||||
import os
|
||||
import sys
|
||||
import numpy as np
|
||||
from astropy.io import fits
|
||||
import pickle
|
||||
from scipy.stats import sem
|
||||
from astropy.wcs import WCS
|
||||
|
||||
from astropy.coordinates import SkyCoord # High-level coordinates
|
||||
from astropy.coordinates import ICRS, Galactic, FK4, FK5 # Low-level frames
|
||||
from astropy.coordinates import Angle, Latitude, Longitude # Angles
|
||||
import matplotlib.pyplot as plt
|
||||
from astropy.table import QTable, Table, Column
|
||||
|
||||
from mpdaf.obj import WCS as mWCS
|
||||
|
||||
|
||||
from sherpa.astro.ui import *
|
||||
|
||||
from uds.config import *
|
||||
|
||||
from scipy.optimize import minimize
|
||||
from random import uniform
|
||||
|
||||
def sky2pix(wcs,dsrc):
|
||||
# converts ra,dec --> x,y
|
||||
|
||||
# checks
|
||||
#sk = wcs.pix2sky([0.0,0.0])
|
||||
#print(sk)
|
||||
#px = wcs.sky2pix([-6.86525105,36.54071803],nearest=False)
|
||||
#print(px)
|
||||
#sk = wcs.pix2sky([px[0][1],px[0][0]])
|
||||
#print(sk)
|
||||
|
||||
for idx, s in enumerate(dsrc):
|
||||
ra0=s['ra']
|
||||
dec0=s['dec']
|
||||
|
||||
px = wcs.sky2pix([dec0,ra0],nearest=False)
|
||||
s['x']=px[0][1]
|
||||
s['y']=px[0][0]
|
||||
|
||||
#sk = wcs.pix2sky([y0,x0])
|
||||
#ra=sk[0][1]
|
||||
#dec=sk[0][0]
|
||||
|
||||
#px = wcs.sky2pix([dec,ra],nearest=False)
|
||||
#x=px[0][1]
|
||||
#y=px[0][0]
|
||||
#print("{:.4f} {:.4f} --> {} {} --> {:.4f} {:.4f} --> {} {}".format(ra0,dec0,x0,y0,ra,dec,x,y))
|
||||
|
||||
|
||||
def pix2sky(wcs,dsrc):
|
||||
# converts x,y --> ra1,dec1
|
||||
for idx, s in enumerate(dsrc):
|
||||
sk = wcs.pix2sky([s['y'],s['x']])
|
||||
s['ra1']=sk[0][1]
|
||||
s['dec1']=sk[0][0]
|
||||
|
||||
def plot_resid(dsrc,dref,crval1,crval2):
|
||||
# calculates RMS of original ra,dec
|
||||
center_crd = SkyCoord(crval1, crval2, frame=FK5(), unit="deg")
|
||||
offset=[]
|
||||
resid=[]
|
||||
error=[]
|
||||
for idx, s in enumerate(dsrc):
|
||||
src_crd = SkyCoord(dsrc[idx]['ra'], dsrc[idx]['dec'], frame=FK5(), unit="deg")
|
||||
ref_crd = SkyCoord(dref[idx]['ra'], dref[idx]['dec'], frame=FK5(), unit="deg")
|
||||
offset.append(src_crd.separation(center_crd).arcmin)
|
||||
resid.append(src_crd.separation(ref_crd).arcsec)
|
||||
error.append(s['radec_err'])
|
||||
|
||||
indices = sorted(
|
||||
range(len(offset)),
|
||||
key=lambda index: offset[index]
|
||||
)
|
||||
|
||||
return ([offset[index] for index in indices],
|
||||
[resid[index] for index in indices],
|
||||
[error[index] for index in indices])
|
||||
|
||||
def plot_resid1(dsrc,dref,crval1,crval2):
|
||||
# calculates RMS of original ra,dec
|
||||
center_crd = SkyCoord(crval1, crval2, frame=FK5(), unit="deg")
|
||||
offset=[]
|
||||
resid=[]
|
||||
error=[]
|
||||
for idx, s in enumerate(dsrc):
|
||||
src_crd = SkyCoord(dsrc[idx]['ra1'], dsrc[idx]['dec1'], frame=FK5(), unit="deg")
|
||||
ref_crd = SkyCoord(dref[idx]['ra'], dref[idx]['dec'], frame=FK5(), unit="deg")
|
||||
offset.append(src_crd.separation(center_crd).arcmin)
|
||||
resid.append(src_crd.separation(ref_crd).arcsec)
|
||||
error.append(s['radec_err'])
|
||||
|
||||
indices = sorted(
|
||||
range(len(offset)),
|
||||
key=lambda index: offset[index]
|
||||
)
|
||||
|
||||
return ([offset[index] for index in indices],
|
||||
[resid[index] for index in indices],
|
||||
[error[index] for index in indices])
|
||||
|
||||
|
||||
def get_rms(dsrc,dref):
|
||||
# calculates RMS of original ra,dec
|
||||
resid=0.0
|
||||
n=0
|
||||
for idx, s in enumerate(dsrc):
|
||||
radec_err=s['radec_err']
|
||||
src_crd = SkyCoord(dsrc[idx]['ra'], dsrc[idx]['dec'], frame=FK5(), unit="deg")
|
||||
ref_crd = SkyCoord(dref[idx]['ra'], dref[idx]['dec'], frame=FK5(), unit="deg")
|
||||
sep=src_crd.separation(ref_crd).arcsec
|
||||
resid = resid+sep**2
|
||||
n=n+1
|
||||
return np.sqrt(resid/n)
|
||||
|
||||
def get_rms_w(dsrc,dref):
|
||||
# calculates RMS of original ra,dec
|
||||
resid=0.0
|
||||
n=0
|
||||
A=0.0
|
||||
B=0.0
|
||||
for idx, s in enumerate(dsrc):
|
||||
radec_err=s['radec_err']
|
||||
src_crd = SkyCoord(dsrc[idx]['ra'], dsrc[idx]['dec'], frame=FK5(), unit="deg")
|
||||
ref_crd = SkyCoord(dref[idx]['ra'], dref[idx]['dec'], frame=FK5(), unit="deg")
|
||||
sep=src_crd.separation(ref_crd).arcsec
|
||||
A=A+sep/radec_err**2
|
||||
B=B+1.0/radec_err**2
|
||||
n=n+1
|
||||
return A/B
|
||||
|
||||
# A=Total(table_lc_sav.rate/(table_lc_sav.err)^2)
|
||||
# B=Total(1.0/(table_lc_sav.err)^2)
|
||||
def get_rms1_w(dsrc,dref):
|
||||
# calculates RMS of original ra,dec
|
||||
resid=0.0
|
||||
n=0
|
||||
A=0.0
|
||||
B=0.0
|
||||
for idx, s in enumerate(dsrc):
|
||||
radec_err=s['radec_err']
|
||||
src_crd = SkyCoord(dsrc[idx]['ra1'], dsrc[idx]['dec1'], frame=FK5(), unit="deg")
|
||||
ref_crd = SkyCoord(dref[idx]['ra'], dref[idx]['dec'], frame=FK5(), unit="deg")
|
||||
sep=src_crd.separation(ref_crd).arcsec
|
||||
A=A+sep/radec_err**2
|
||||
B=B+1.0/radec_err**2
|
||||
n=n+1
|
||||
return A/B
|
||||
|
||||
|
||||
def get_chi2_radec(dsrc,dref):
|
||||
# calculates RMS of original ra,dec
|
||||
resid=0.0
|
||||
n=0
|
||||
for idx, s in enumerate(dsrc):
|
||||
radec_err=s['radec_err']
|
||||
src_crd = SkyCoord(dsrc[idx]['ra'], dsrc[idx]['dec'], frame=FK5(), unit="deg")
|
||||
ref_crd = SkyCoord(dref[idx]['ra'], dref[idx]['dec'], frame=FK5(), unit="deg")
|
||||
sep=src_crd.separation(ref_crd).arcsec
|
||||
resid = resid+sep**2/radec_err**2
|
||||
n=n+1
|
||||
return resid
|
||||
|
||||
def get_rms1(dsrc,dref):
|
||||
# calculates RMS of modified ra1,dec1
|
||||
resid=0.0
|
||||
n=0
|
||||
for idx, s in enumerate(dsrc):
|
||||
radec_err=s['radec_err']
|
||||
src_crd = SkyCoord(dsrc[idx]['ra1'], dsrc[idx]['dec1'], frame=FK5(), unit="deg")
|
||||
ref_crd = SkyCoord(dref[idx]['ra'], dref[idx]['dec'], frame=FK5(), unit="deg")
|
||||
sep=src_crd.separation(ref_crd).arcsec
|
||||
resid = resid+sep*sep
|
||||
n=n+1
|
||||
return np.sqrt(resid/n)
|
||||
|
||||
def get_chi2_radec1(dsrc,dref):
|
||||
# calculates RMS of modified ra1,dec1
|
||||
resid=0.0
|
||||
n=0
|
||||
for idx, s in enumerate(dsrc):
|
||||
radec_err=s['radec_err']
|
||||
src_crd = SkyCoord(dsrc[idx]['ra1'], dsrc[idx]['dec1'], frame=FK5(), unit="deg")
|
||||
ref_crd = SkyCoord(dref[idx]['ra'], dref[idx]['dec'], frame=FK5(), unit="deg")
|
||||
sep=src_crd.separation(ref_crd).arcsec
|
||||
resid = resid+sep**2/radec_err**2
|
||||
n=n+1
|
||||
return resid
|
||||
|
||||
|
||||
|
||||
def do_transform_resid(params, wcs, dsrc, dref, crval1, crval2):
|
||||
|
||||
angle_in, crval1_in, crval2_in = params
|
||||
|
||||
# fills x,y
|
||||
sky2pix(wcs,dsrc)
|
||||
|
||||
wcs1=wcs.copy()
|
||||
|
||||
# do transform here
|
||||
#wcs1.rotate(angle_in/60)
|
||||
|
||||
wcs1.set_crval1(crval1_in)
|
||||
wcs1.set_crval2(crval2_in)
|
||||
|
||||
# fills ra1,dec1
|
||||
pix2sky(wcs1,dsrc)
|
||||
|
||||
# caclulate new statistics
|
||||
resid1 = get_chi2_radec1(dsrc,dref)
|
||||
#print("--> {:+.4f} {:+.4f} {:.4f}".format((crval1-wcs.get_crval1())*3600,(crval2-wcs.get_crval2())*3600,resid1))
|
||||
return resid1
|
||||
|
||||
|
||||
def do_astro_corr(src=None, ref=None, catalog=None):
|
||||
""" calculates astronomy correction """
|
||||
|
||||
log=catalog.replace(".fits", ".shift.log")
|
||||
log0=catalog.replace(".fits", ".orig.qdp")
|
||||
log1=catalog.replace(".fits", ".shift.qdp")
|
||||
fout=catalog.replace(".fits", ".shift-map.fits")
|
||||
|
||||
title=os.path.split(catalog)[1]
|
||||
key=title.replace("_SourceCatalog_en0.fits","")
|
||||
|
||||
#png=catalog.replace(".fits", ".opti.png")
|
||||
#png=png.replace(key,"{}_{}".format(obslist[key],key))
|
||||
t = Table(names=('rota', 'shift_ra','shift_dec','chi2',), dtype=('f8','f8','f8','f8'))
|
||||
|
||||
print(src)
|
||||
hdul = fits.open(src)
|
||||
src_map_data = hdul[0].data
|
||||
src_map_hdr = hdul[0].header
|
||||
src_tab_data = hdul[1].data
|
||||
src_tab_hdr = hdul[1].header
|
||||
hdul.close()
|
||||
|
||||
dsrc=[]
|
||||
for rec in src_tab_data:
|
||||
d = dict(ra = rec['RA'], dec = rec['DEC'], ra_err = rec['RA_ERR'], dec_err = rec['DEC_ERR'], radec_err = rec['RADEC_ERR'])
|
||||
dsrc.append(d)
|
||||
|
||||
print(ref)
|
||||
hdul = fits.open(ref)
|
||||
ref_map_data = hdul[0].data
|
||||
ref_map_hdr = hdul[0].header
|
||||
ref_tab_data = hdul[1].data
|
||||
ref_tab_hdr = hdul[1].header
|
||||
hdul.close()
|
||||
|
||||
dref=[]
|
||||
for rec in ref_tab_data:
|
||||
d = dict(ra = rec['RA'], dec = rec['DEC'], ra_err = rec['RA_ERR'], dec_err = rec['DEC_ERR'])
|
||||
dref.append(d)
|
||||
|
||||
rms = get_rms(dsrc,dref)
|
||||
chi2_radec = get_chi2_radec(dsrc,dref)
|
||||
wcs_src=mWCS(src_map_hdr)
|
||||
wcs_src.info()
|
||||
crval1=wcs_src.get_crval1()
|
||||
crval2=wcs_src.get_crval2()
|
||||
#print(crval1,crval2)
|
||||
|
||||
offset0, sep0, err0 = plot_resid(dsrc,dref,crval1,crval2)
|
||||
with open(log0, 'w') as writer:
|
||||
|
||||
writer.write("label Y Separation, arcsec\nlabel X Offset, arcmin\nr y -1 15\n")
|
||||
writer.write("ma 9 on\n")
|
||||
writer.write("read serr 2\n")
|
||||
for idx, s in enumerate(offset0):
|
||||
writer.write("{:.2f} {:.2f} {:.2f}\n".format(offset0[idx],sep0[idx],err0[idx]))
|
||||
|
||||
|
||||
|
||||
wcs_ref=mWCS(ref_map_hdr)
|
||||
wcs_ref.info()
|
||||
|
||||
chi2_radec1_opt=1000
|
||||
rota_opt=0.0
|
||||
crval1_opt=crval1
|
||||
crval2_opt=crval2
|
||||
|
||||
rota_min=-30
|
||||
rota_max=30
|
||||
Rsim=10.0
|
||||
Nsim=20000
|
||||
crd = SkyCoord(crval1, crval2, frame=FK5(), unit="deg")
|
||||
i=0
|
||||
while i < Nsim:
|
||||
#rota_rand = uniform(rota_min, rota_max)
|
||||
rota_rand=0.0
|
||||
crval1_rand = uniform(crval1-Rsim/3600, crval1+Rsim/3600)
|
||||
crval2_rand = uniform(crval2-Rsim/3600, crval2+Rsim/3600)
|
||||
#crval1_rand = crval1
|
||||
#crval2_rand = crval2
|
||||
|
||||
sim_crd = SkyCoord(crval1_rand, crval2_rand, frame=FK5(), unit="deg")
|
||||
if(sim_crd.separation(crd).arcsec > Rsim):
|
||||
continue
|
||||
chi2_radec1 = do_transform_resid([rota_rand, crval1_rand, crval2_rand], wcs_src, dsrc, dref, crval1, crval2)
|
||||
t.add_row((rota_rand,(crval1-crval1_rand)*3600,(crval2-crval2_rand)*3600,chi2_radec1))
|
||||
if(chi2_radec1 < chi2_radec1_opt):
|
||||
chi2_radec1_opt = chi2_radec1
|
||||
rota_opt = rota_rand
|
||||
crval1_opt = crval1_rand
|
||||
crval2_opt = crval2_rand
|
||||
i += 1
|
||||
|
||||
# set optimal parameters
|
||||
r = do_transform_resid([rota_opt, crval1_opt, crval2_opt], wcs_src, dsrc, dref, crval1, crval2)
|
||||
print(chi2_radec1_opt,'==',r)
|
||||
|
||||
shift_ra=(crval1-crval1_opt)*3600
|
||||
shift_dec=(crval2-crval2_opt)*3600
|
||||
|
||||
t.write(fout, format='fits', overwrite=True)
|
||||
|
||||
rms1 = get_rms1(dsrc,dref)
|
||||
|
||||
offset1, sep1, err1 = plot_resid1(dsrc,dref,crval1,crval2)
|
||||
with open(log1, 'w') as writer:
|
||||
writer.write("label Y Separation, arcsec\nlabel X Offset, arcmin\nr y -1 15\n")
|
||||
writer.write("ma 9 on\n")
|
||||
writer.write("read serr 2\n")
|
||||
for idx, s in enumerate(offset1):
|
||||
writer.write("{:.2f} {:.2f} {:.2f}\n".format(offset1[idx],sep1[idx],err1[idx]))
|
||||
|
||||
with open(log, 'w') as writer:
|
||||
writer.write("{} {:+.2f} {:+.2f} {:+.2f} ({:.2f} - {:.2f}) = {:.2f} {:.2f} ({:.2f}) {:.2f} ({:.2f}) N={} -- {}\n".format(obslist[key],
|
||||
rota_opt,
|
||||
shift_ra,
|
||||
shift_dec,
|
||||
get_chi2_radec(dsrc,dref),
|
||||
get_chi2_radec1(dsrc,dref),
|
||||
chi2_radec-chi2_radec1_opt,
|
||||
rms,get_rms_w(dsrc,dref),
|
||||
rms1,get_rms1_w(dsrc,dref),
|
||||
len(dsrc),key))
|
||||
|
||||
|
||||
|
||||
"""
|
||||
Nsim=20000 Shift only
|
||||
N01 +0.00 +4.76 +0.07 (171.22 - 28.06) = 143.15 6.35 (5.11) 3.92 (1.40) N=22 -- tm1_obs_1
|
||||
N02 +0.00 +2.77 -2.74 (354.15 - 225.27) = 128.88 10.10 (5.34) 9.38 (2.61) N=31 -- tm5_obs_1
|
||||
N03 +0.00 +3.88 -3.65 (542.25 - 303.25) = 239.00 8.74 (6.87) 6.73 (3.07) N=36 -- tm5_obs_2
|
||||
N04 +0.00 +0.28 +0.03 (43.16 - 43.04) = 0.12 6.04 (3.39) 6.07 (3.36) N=17 -- tm6_park_1
|
||||
N05 +0.00 +0.65 -0.78 (175.10 - 169.55) = 5.56 6.77 (4.47) 6.54 (4.51) N=38 -- tm6_scan_1
|
||||
N06 +0.00 -0.38 +0.27 (26.60 - 26.37) = 0.23 6.54 (4.27) 6.52 (4.23) N=11 -- tm6_park_2
|
||||
N07 +0.00 +0.04 -0.35 (128.82 - 127.98) = 0.84 5.76 (4.21) 5.75 (4.18) N=35 -- tm6_scan_2
|
||||
N08 +0.00 +0.58 -0.22 (10.07 - 9.79) = 0.29 3.94 (2.83) 3.89 (2.82) N= 9 -- tm6_park_3
|
||||
N09 +0.00 +1.35 -0.56 (95.06 - 87.04) = 8.02 5.73 (4.45) 5.60 (4.28) N=38 -- tm6_scan_3
|
||||
N10 +0.00 +0.56 +0.36 (15.71 - 15.41) = 0.30 4.22 (3.49) 4.22 (3.43) N=10 -- tm6_park_4
|
||||
N11 +0.00 +1.08 -0.62 (116.34 - 108.60) = 7.73 5.38 (4.41) 5.11 (4.26) N=37 -- tm6_scan_4
|
||||
N12 +0.00 -0.56 -1.56 (84.93 - 59.86) = 25.07 4.20 (2.45) 4.09 (1.88) N=30 -- tm6_obs_1
|
||||
N13 +0.00 +0.19 -1.03 (17.58 - 13.28) = 4.30 3.38 (1.90) 3.23 (1.31) N=13 -- tm6_obs_2_badpix
|
||||
N14 +0.00 +1.03 -1.99 (63.23 - 35.27) = 27.97 4.36 (2.73) 3.27 (2.05) N=23 -- tm6_obs_3_badpix
|
||||
N15 +0.00 +0.88 -1.66 (187.51 - 164.26) = 23.25 6.93 (3.29) 6.62 (2.68) N=33 -- tm7_obs_1
|
||||
N16 +0.00 +2.74 -0.52 (113.70 - 75.09) = 38.61 5.34 (4.23) 4.73 (3.42) N=26 -- tm7_obs_2
|
||||
|
||||
Nsim=20000 Shift+Rotation
|
||||
N01 -1.50 +4.93 +0.00 (171.22 - 27.67) = 143.55 6.35 (5.11) 3.83 (1.38) N=22 -- tm1_obs_1
|
||||
N02 -2.15 +2.47 -3.05 (354.15 - 223.27) = 130.88 10.10 (5.34) 9.29 (2.71) N=31 -- tm5_obs_1
|
||||
N03 -5.08 +3.87 -4.04 (542.25 - 296.00) = 246.25 8.74 (6.87) 6.93 (2.82) N=36 -- tm5_obs_2
|
||||
N04 +5.90 -0.19 +0.50 (43.16 - 39.56) = 3.60 6.04 (3.39) 5.57 (3.57) N=17 -- tm6_park_1
|
||||
N05 -5.84 +1.37 -0.85 (175.10 - 111.02) = 64.08 6.77 (4.47) 5.53 (3.58) N=38 -- tm6_scan_1
|
||||
N06 -0.30 -0.27 +0.31 (26.60 - 26.36) = 0.24 6.54 (4.27) 6.50 (4.27) N=11 -- tm6_park_2
|
||||
N07 -5.49 +0.73 -0.98 (128.82 - 86.16) = 42.66 5.76 (4.21) 4.94 (3.62) N=35 -- tm6_scan_2
|
||||
N08 -0.28 +0.51 -0.29 (10.07 - 9.78) = 0.29 3.94 (2.83) 3.90 (2.82) N= 9 -- tm6_park_3
|
||||
N09 -4.56 +0.91 -0.40 (95.06 - 64.56) = 30.49 5.73 (4.45) 4.93 (3.56) N=38 -- tm6_scan_3
|
||||
N10 +2.01 +0.54 +0.63 (15.71 - 15.17) = 0.54 4.22 (3.49) 4.03 (3.39) N=10 -- tm6_park_4
|
||||
N11 -3.83 +1.01 -1.29 (116.34 - 82.25) = 34.08 5.38 (4.41) 4.75 (3.72) N=37 -- tm6_scan_4
|
||||
N12 -1.35 -0.23 -1.27 (84.93 - 60.30) = 24.63 4.20 (2.45) 4.20 (1.82) N=30 -- tm6_obs_1
|
||||
N13 -1.52 +0.17 -1.38 (17.58 - 13.30) = 4.29 3.38 (1.90) 3.21 (1.28) N=13 -- tm6_obs_2_badpix
|
||||
N14 -1.24 +0.63 -2.18 (63.23 - 34.42) = 28.81 4.36 (2.73) 3.28 (1.92) N=23 -- tm6_obs_3_badpix
|
||||
N15 -5.23 +0.82 -1.47 (187.51 - 161.20) = 26.31 6.93 (3.29) 6.31 (2.66) N=33 -- tm7_obs_1
|
||||
N16 -5.41 +2.47 -0.97 (113.70 - 60.40) = 53.30 5.34 (4.23) 4.59 (2.89) N=26 -- tm7_obs_2
|
||||
"""
|
||||
def do_astro_corr_rota(src=None, ref=None, catalog=None):
|
||||
""" calculates astronomy correction """
|
||||
|
||||
title=os.path.split(catalog)[1]
|
||||
png=catalog.replace(".fits", ".rota.png")
|
||||
log=catalog.replace(".fits", ".rota.log")
|
||||
key=title.replace("_SourceCatalog_en0.fits","")
|
||||
png=png.replace(key,"{}_{}".format(obslist[key],key))
|
||||
|
||||
print(src)
|
||||
hdul = fits.open(src)
|
||||
src_map_data = hdul[0].data
|
||||
src_map_hdr = hdul[0].header
|
||||
src_tab_data = hdul[1].data
|
||||
src_tab_hdr = hdul[1].header
|
||||
hdul.close()
|
||||
|
||||
dsrc=[]
|
||||
for rec in src_tab_data:
|
||||
d = dict(ra = rec['RA'], dec = rec['DEC'], ra_err = rec['RA_ERR'], dec_err = rec['DEC_ERR'], radec_err = rec['RADEC_ERR'])
|
||||
dsrc.append(d)
|
||||
|
||||
|
||||
|
||||
print(ref)
|
||||
hdul = fits.open(ref)
|
||||
ref_map_data = hdul[0].data
|
||||
ref_map_hdr = hdul[0].header
|
||||
ref_tab_data = hdul[1].data
|
||||
ref_tab_hdr = hdul[1].header
|
||||
hdul.close()
|
||||
|
||||
dref=[]
|
||||
for rec in ref_tab_data:
|
||||
d = dict(ra = rec['RA'], dec = rec['DEC'], ra_err = rec['RA_ERR'], dec_err = rec['DEC_ERR'])
|
||||
dref.append(d)
|
||||
|
||||
|
||||
resid = get_rms(dsrc,dref)
|
||||
print(resid)
|
||||
|
||||
wcs_src=mWCS(src_map_hdr)
|
||||
wcs_src.info()
|
||||
|
||||
wcs_ref=mWCS(ref_map_hdr)
|
||||
wcs_ref.info()
|
||||
|
||||
x=[]
|
||||
y=[]
|
||||
rms_min=1000.0
|
||||
rota_min=1000.0
|
||||
for angle in np.arange(-0.5, 0.5, 0.01):
|
||||
resid1=do_transform(angle,wcs_src,dsrc,dref)
|
||||
x.append(angle*60)
|
||||
y.append(resid1/resid)
|
||||
if(resid1<rms_min):
|
||||
rms_min=resid1
|
||||
rota_min=angle*60
|
||||
|
||||
with open(log, 'w') as writer:
|
||||
writer.write("{} {} {:.2f} {:.2f} {:.2f} {:.2f}%\n".format(obslist[key],title,rota_min, rms_min, resid, (1.0-rms_min/resid)*100.0))
|
||||
|
||||
|
||||
fig, ax = plt.subplots( nrows=1, ncols=1 ) # create figure & 1 axis
|
||||
ax.plot(x,y)
|
||||
plt.ylabel('RMS/RMS0, RMS0={:.2f} arcsec'.format(resid))
|
||||
plt.xlabel('Rotation, arcmin')
|
||||
plt.title("{} {} {} pairs, {:.1f}%".format(obslist[key], title,len(dsrc),(1.0-rms_min/resid)*100.0))
|
||||
plt.grid(True)
|
||||
plt.axvline(x = 0.0, color = 'b', label = 'zero')
|
||||
fig.savefig(png)
|
||||
plt.close(fig) # close the figure window
|
||||
|
||||
def do_transform(angle,wcs,dsrc,dref):
|
||||
# fills x,y
|
||||
sky2pix(wcs,dsrc)
|
||||
|
||||
# do transform here
|
||||
wcs.rotate(angle)
|
||||
|
||||
# fills ra1,dec1
|
||||
pix2sky(wcs,dsrc)
|
||||
|
||||
resid1 = get_rms1(dsrc,dref)
|
||||
return resid1
|
||||
@ -43,18 +43,36 @@ wcslist={'tm1_obs_1':[34.7279760,-5.0680267],
|
||||
'tm6_scan_3':[34.5405596,-4.8088748],
|
||||
'tm6_scan_4':[34.5405596,-4.8088748]}
|
||||
|
||||
""" Это просто индекс диапазона для выходных файлов. """
|
||||
eband=[ "0", "1", "2", "3", "4", "5", "6"]
|
||||
""" Диапазоны энергий. """
|
||||
emin_ev=[ 300, 300, 600, 2300, 200, 300, 5000]
|
||||
emax_ev=[2300, 600, 2300, 5000, 10000,8000, 8000]
|
||||
""" like in the paper (Table 1) """
|
||||
obslist={'tm1_obs_1':'N01',
|
||||
'tm5_obs_1':'N02',
|
||||
'tm5_obs_2':'N03',
|
||||
'tm7_obs_1':'N15',
|
||||
'tm7_obs_2':'N16',
|
||||
'tm6_obs_1':'N12',
|
||||
'tm6_obs_2_badpix':'N13',
|
||||
'tm6_obs_3_badpix':'N14',
|
||||
'tm6_park_1':'N04',
|
||||
'tm6_park_2':'N06',
|
||||
'tm6_park_3':'N08',
|
||||
'tm6_park_4':'N10',
|
||||
'tm6_scan_1':'N05',
|
||||
'tm6_scan_2':'N07',
|
||||
'tm6_scan_3':'N09',
|
||||
'tm6_scan_4':'N11'}
|
||||
|
||||
emin_kev=[0.3, 0.3, 0.6, 2.3, 0.2, 0.3, 5.0]
|
||||
emax_kev=[2.3, 0.6, 2.3, 5.0, 10.0, 8.0, 8.0]
|
||||
""" Это просто индекс диапазона для выходных файлов. """
|
||||
eband=[ "0", "1", "2", "3", "4", "5", "6", "7", "8"]
|
||||
""" Диапазоны энергий. """
|
||||
emin_ev=[ 300, 300, 600, 2300, 200, 300, 5000, 500, 1000]
|
||||
emax_ev=[2300, 600, 2300, 5000, 10000,8000, 8000, 1000, 2000]
|
||||
|
||||
emin_kev=[0.3, 0.3, 0.6, 2.3, 0.2, 0.3, 5.0, 0.5, 1.0]
|
||||
emax_kev=[2.3, 0.6, 2.3, 5.0, 10.0, 8.0, 8.0, 1.0, 2.0]
|
||||
|
||||
#ecf = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
|
||||
ecf = [9.7817E+11, 3.2982E+12, 1.3903E+12, 2.3322E+12, 5.2022E+11, 5.8453E+11, 3.8468E+12]
|
||||
|
||||
# something is wrong here
|
||||
#ecf = [9.7817E+11, 3.2982E+12, 1.3903E+12, 2.3322E+12, 5.2022E+11, 5.8453E+11, 3.8468E+12]
|
||||
"""
|
||||
*** en0 ecf 9.7817E+11 +/- 2.4606E+10 2.52% N=17
|
||||
*** en1 ecf 3.2982E+12 +/- 8.2963E+10 2.52% N=17
|
||||
@ -64,6 +82,22 @@ ecf = [9.7817E+11, 3.2982E+12, 1.3903E+12, 2.3322E+12, 5.2022E+11, 5.8453E+1
|
||||
*** en5 ecf 5.8453E+11 +/- 1.4743E+10 2.52% N=17
|
||||
"""
|
||||
|
||||
# finally use Pavel's file ../data/ECF/ecf_tbabspow_g2nh0.02.pkl
|
||||
"""
|
||||
for e in [(0.3, 2.3), (0.3, 0.6), (0.6, 2.3), (2.3, 5.0), (5.0, 8.0)]:
|
||||
print(f'{ecf[e]:g}')
|
||||
"""
|
||||
ecf = [1.0911e+12, # (0.3, 2.3)
|
||||
1.07252e+12, # (0.3, 0.6)
|
||||
1.08963e+12, # (0.6, 2.3)
|
||||
1.14674e+11, # (2.3, 5.0)
|
||||
1.0,
|
||||
1.0,
|
||||
2.77581e+10, # (5.0, 8.0)
|
||||
1354632916123.6191, # (0.5, 1.0) 4XMM-DR12 EP2 band
|
||||
1014764099304.4968] # (1.0, 2.0) 4XMM-DR12 EP3 band
|
||||
|
||||
|
||||
outfile_post='.fits'
|
||||
|
||||
"""
|
||||
|
||||
@ -35,8 +35,8 @@ def calc_ecf(path,catprep=None, emin=None, emax=None, eband=None, outfile=None,
|
||||
srcid=rec['detUID']
|
||||
|
||||
""" consider only non-extended sources """
|
||||
if(rec['EXT'] > 0.0):
|
||||
continue
|
||||
#if(rec['EXT'] > 0.0):
|
||||
# continue
|
||||
|
||||
if(srcid in mlrate.keys()):
|
||||
print("Duplicate SrcID! {}".format(srcid))
|
||||
@ -52,7 +52,7 @@ def calc_ecf(path,catprep=None, emin=None, emax=None, eband=None, outfile=None,
|
||||
|
||||
print("Reading {}".format(filename))
|
||||
|
||||
fout=filename.replace(".fits", ".uncorr.fits")
|
||||
#fout=filename.replace(".fits", ".uncorr.fits")
|
||||
|
||||
pha=filename.replace("ARF", "SourceSpec")
|
||||
pha=pha.replace(".fits", ".fits.grp")
|
||||
@ -69,10 +69,10 @@ def calc_ecf(path,catprep=None, emin=None, emax=None, eband=None, outfile=None,
|
||||
continue
|
||||
|
||||
|
||||
hdul = fits.open(filename,mode='readonly')
|
||||
specresp = np.divide(hdul[1].data['SPECRESP'], hdul[1].data['CORRCOMB'])
|
||||
hdul[1].data['SPECRESP'] = specresp
|
||||
hdul.writeto(fout, overwrite=True)
|
||||
#hdul = fits.open(filename,mode='readonly')
|
||||
#specresp = np.divide(hdul[1].data['SPECRESP'], hdul[1].data['CORRCOMB'])
|
||||
#hdul[1].data['SPECRESP'] = specresp
|
||||
#hdul.writeto(fout, overwrite=True)
|
||||
clean() # sherpa
|
||||
set_xsxsect("vern")
|
||||
set_xsabund('wilm')
|
||||
@ -166,6 +166,144 @@ def calc_ecf(path,catprep=None, emin=None, emax=None, eband=None, outfile=None,
|
||||
with open(outfile, 'wb') as f:
|
||||
pickle.dump(data, f)
|
||||
|
||||
def calc_flux(path,catprep=None, emin=None, emax=None, eband=None, outfile=None, fitmin=0.2, fitmax=5.0, simnum=100):
|
||||
""" """
|
||||
|
||||
data={}
|
||||
|
||||
if (catprep == None):
|
||||
print("catprep file is not provided, exit")
|
||||
sys.exit()
|
||||
else:
|
||||
print("Reading {}".format(catprep))
|
||||
|
||||
catprep_hdul = fits.open(catprep,mode='readonly')
|
||||
catprep_data = catprep_hdul[1].data
|
||||
#print(catprep_data['detUID'])
|
||||
mlrate = {}
|
||||
mlrate_err = {}
|
||||
dl = {}
|
||||
for rec in catprep_data:
|
||||
srcid=rec['detUID']
|
||||
|
||||
""" consider only non-extended sources """
|
||||
#if(rec['EXT'] > 0.0):
|
||||
# continue
|
||||
|
||||
if(srcid in mlrate.keys()):
|
||||
print("Duplicate SrcID! {}".format(srcid))
|
||||
sys.exit()
|
||||
else:
|
||||
mlrate[srcid]=rec['ML_RATE_0']
|
||||
mlrate_err[srcid]=rec['ML_RATE_ERR_0']
|
||||
dl[srcid]=rec['DET_LIKE_0']
|
||||
|
||||
|
||||
flist=glob.glob(path)
|
||||
for filename in flist:
|
||||
|
||||
print("Reading {}".format(filename))
|
||||
|
||||
pha=filename.replace("ARF", "SourceSpec")
|
||||
pha=pha.replace(".fits", ".fits.grp")
|
||||
pha_header = fits.getheader(pha,ext=1)
|
||||
object = pha_header['OBJECT']
|
||||
|
||||
|
||||
srcid="ML{}".format(object)
|
||||
if not (srcid in mlrate.keys()):
|
||||
print("Skip {}".format(srcid))
|
||||
continue
|
||||
|
||||
|
||||
clean() # sherpa
|
||||
set_xsxsect("vern")
|
||||
set_xsabund('wilm')
|
||||
load_pha(pha) # sherpa
|
||||
|
||||
# Define the source model
|
||||
#sh.set_source("powlaw1d.p1")
|
||||
set_source("xstbabs.abs1 * powlaw1d.p1") # sherpa
|
||||
abs1.nH = 0.02
|
||||
# Change reference energy of the model
|
||||
p1.ref = 1 # 1 keV
|
||||
p1.gamma = 2.0
|
||||
p1.ampl = 1e-4 # in cm**-2 s**-1 keV**-1
|
||||
freeze(abs1.nH, p1.gamma) # sherpa
|
||||
|
||||
### Define the statistic
|
||||
set_stat("wstat") # sherpa
|
||||
|
||||
photon_flx=[]
|
||||
energy_flx=[]
|
||||
skipme=False
|
||||
for ie in range(len(eband)):
|
||||
ignore_bad() # sherpa
|
||||
### Define the fit range
|
||||
print("Notice {}-{} keV:".format(emin[ie], emax[ie]))
|
||||
notice(emin[ie], emax[ie]) # sherpa
|
||||
|
||||
""" Check wether spectrum still has counts after filtering """
|
||||
dep = get_dep(filter=True)
|
||||
if not (len(dep)):
|
||||
print("*** Skip {} due to low counts".format(srcid))
|
||||
continue
|
||||
|
||||
### Do the fit
|
||||
fit()
|
||||
res_fit=get_fit_results()
|
||||
rstat=res_fit.rstat
|
||||
|
||||
set_analysis('energy')
|
||||
|
||||
ph_flx=calc_photon_flux(emin[ie], emax[ie])
|
||||
en_flx=calc_energy_flux(emin[ie], emax[ie])
|
||||
if not (ph_flx>0):
|
||||
skipme=True
|
||||
photon_flx.append(ph_flx)
|
||||
energy_flx.append(en_flx)
|
||||
print("en{} Photon flux: {:.4E} Energy flux: {:.4E}".format(eband[ie], ph_flx, en_flx))
|
||||
print("----> Success: {} pow norm: {:.4E} reduced stat: {:.2f}".format(res_fit.succeeded,res_fit.parvals[0], rstat))
|
||||
|
||||
if (skipme == True):
|
||||
print("*** Skip zero flux for {}".format(srcid))
|
||||
continue
|
||||
|
||||
|
||||
sample_flx=[]
|
||||
sample_flx_lo=[]
|
||||
sample_flx_hi=[]
|
||||
if (res_fit.rstat < 3.0):
|
||||
conf()
|
||||
res_conf=get_conf_results()
|
||||
#print(res_conf)
|
||||
component=abs1+p1
|
||||
#print(component)
|
||||
#covar()
|
||||
#errs = get_covar_results().parmaxes
|
||||
#ans = sample_flux(correlated=False, scales=errs, num=500)
|
||||
for ie in range(len(eband)):
|
||||
pars_flux = sample_flux(modelcomponent=component, lo=emin[ie], hi=emax[ie], num=simnum, correlated=True, numcores=10, confidence=68)
|
||||
sample_flx.append(pars_flux[0][0])
|
||||
sample_flx_lo.append(pars_flux[0][2])
|
||||
sample_flx_hi.append(pars_flux[0][1])
|
||||
|
||||
else:
|
||||
continue
|
||||
|
||||
print("### SAMPLE FLUX: {}".format(sample_flx))
|
||||
data[srcid]={'sample_flx':sample_flx,
|
||||
'sample_flx_lo':sample_flx_lo,
|
||||
'sample_flx_hi':sample_flx_hi,
|
||||
'photon_flx':photon_flx,
|
||||
'energy_flx':energy_flx,
|
||||
'ml_rate':mlrate[srcid],
|
||||
'ml_rate_err':mlrate_err[srcid],
|
||||
'det_like':dl[srcid]}
|
||||
|
||||
with open(outfile, 'wb') as f:
|
||||
pickle.dump(data, f)
|
||||
|
||||
|
||||
def print_ecf(infile=None, emin=None, emax=None, eband=None, skipfrac=5.0):
|
||||
|
||||
@ -211,9 +349,11 @@ def print_ecf(infile=None, emin=None, emax=None, eband=None, skipfrac=5.0):
|
||||
ecf.append(ecf0)
|
||||
|
||||
|
||||
|
||||
ecf_mean = np.mean(ecf)
|
||||
ecf_err = np.std(ecf, ddof=1)/np.sqrt(np.size(ecf))
|
||||
print("\n*** en{} ecf {:.4E} +/- {:.4E} {:.2f}% N={}".format(eband[ie],
|
||||
ecf_mean,
|
||||
ecf_err,100*ecf_err/ecf_mean,
|
||||
np.size(ecf)))
|
||||
sys.exit()
|
||||
|
||||
1636
uds/uds/utils.py
1636
uds/uds/utils.py
File diff suppressed because it is too large
Load Diff
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x
Reference in New Issue
Block a user