generated from erosita/uds
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76
.gitignore
vendored
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76
.gitignore
vendored
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||||
# Byte-compiled / optimized / DLL files
|
||||
__pycache__/
|
||||
*.py[cod]
|
||||
*$py.class
|
||||
|
||||
# Distribution / packaging
|
||||
.Python
|
||||
build/
|
||||
develop-eggs/
|
||||
dist/
|
||||
downloads/
|
||||
eggs/
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||||
.eggs/
|
||||
lib/
|
||||
lib64/
|
||||
parts/
|
||||
sdist/
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||||
var/
|
||||
products/
|
||||
wheels/
|
||||
share/python-wheels/
|
||||
*.egg-info/
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||||
.installed.cfg
|
||||
*.egg
|
||||
MANIFEST
|
||||
|
||||
# PyBuilder
|
||||
.pybuilder/
|
||||
target/
|
||||
|
||||
# Jupyter Notebook
|
||||
.ipynb_checkpoints
|
||||
|
||||
# Environments
|
||||
.env
|
||||
.venv
|
||||
env/
|
||||
venv/
|
||||
ENV/
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||||
env.bak/
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||||
venv.bak/
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||||
|
||||
*~
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||||
*#
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||||
.#*
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||||
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||||
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# Astronomy
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||||
*.eps
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||||
*.cds
|
||||
*.fits
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||||
*.fits.gz
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||||
*.fits.fz
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||||
*.awk
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||||
*.tex
|
||||
*.evt
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||||
*.evt.gz
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||||
*.lock
|
||||
*.reg
|
||||
*.cross
|
||||
*.ref
|
||||
*.src
|
||||
*.dat
|
||||
*.xfm
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||||
*.log
|
||||
*.tmp
|
||||
*.attcorr
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||||
*.aspsol
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||||
*.txt
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||||
*.png
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||||
*.grp
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||||
*.csv
|
||||
.*
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||||
*.qdp
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||||
*.pickle
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||||
!.gitignore
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9
LICENSE
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9
LICENSE
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@ -0,0 +1,9 @@
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MIT License
|
||||
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||||
Copyright (c) <year> <copyright holders>
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||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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37
README.md
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37
README.md
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# uds
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Содержит код для обработки данных поля UDS.
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# Установка
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## Шаг 1. (опционально) Устанавливаем локальное виртуальное окружение Python
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||||
```
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||||
mkdir ~/work; cd ~/work
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||||
python -m venv venv
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source ./venv/bin/activate.csh
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||||
```
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||||
или запускаем другое виртуальное окружение, например:
|
||||
|
||||
``` conda activate ciao-4.15 ```
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## Шаг 2. Клонируем проект из репозитория
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```
|
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mkdir ~/work; cd ~/work
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git clone git@danko.iki.rssi.ru:erosita/uds.git
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```
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## Шаг 3. Устанавливаем проект в ваше виртуальное окружение
|
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```
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cd uds
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pip install --editable uds/
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```
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||||
Обратите внимание на параметр **--editable**, он позволяет вам редактировать исходный код данного пакета и сразу его выполнять. Если вы не планируете модифицировать локальную копию кода, можете убрать этот параметр.
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||||
После работы можете удалить проект:
|
||||
``` pip uninstall uds ```
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|
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## Работа с данными
|
||||
|
||||
Непосредственная работа с данными происходит в директории scripts, где нужно последовательно запускать скрипты обработки. В данной директории находится подробное описание всех действий.
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|
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4281
data/4XMM-DR12/4XMM_DR12cat_slim_v1.0_UDS.fits.catalog
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4281
data/4XMM-DR12/4XMM_DR12cat_slim_v1.0_UDS.fits.catalog
Normal file
File diff suppressed because one or more lines are too long
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
15
data/4XMM-DR12/README.md
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15
data/4XMM-DR12/README.md
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В данной директории находится каталог 4XMM-DR12
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Источник: http://xmmssc.irap.omp.eu/Catalogue/4XMM-DR12/4XMM_DR12.html
|
||||
|
||||
Для вырезки источников для работы с полем UDS была использована эта команда:
|
||||
|
||||
```
|
||||
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:
|
||||
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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||||
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||||
BIN
data/4XMM-DR12/Rplots.pdf
Normal file
BIN
data/4XMM-DR12/Rplots.pdf
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Binary file not shown.
20
data/4XMM-DR12/barplot.r
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20
data/4XMM-DR12/barplot.r
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library(ggplot2)
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||||
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||||
# see https://r-graph-gallery.com/4-barplot-with-error-bar.html
|
||||
|
||||
png(file = "barplot.png")
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||||
|
||||
# create dummy data
|
||||
data <- data.frame(
|
||||
name=c('','yy','zz','ff','DR12'),
|
||||
flux=c(1,2,3,4,5),
|
||||
err=c(1,0.2,3,2,4)
|
||||
)
|
||||
|
||||
# Most basic error bar
|
||||
ggplot(data) +
|
||||
geom_bar(aes(x=name, y=flux), stat="identity", fill="skyblue", alpha=0.7) +
|
||||
geom_errorbar( aes(x=name, ymin=flux-err, ymax=flux+err), width=0.4, colour="black", alpha=0.9, linewidth=2)
|
||||
|
||||
|
||||
dev.off()
|
||||
40
data/4XMM-DR12/plot_corr.r
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40
data/4XMM-DR12/plot_corr.r
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@ -0,0 +1,40 @@
|
||||
options(digits = 7) # knitr sometimes decreases number of digits shown
|
||||
require(stats)
|
||||
xgrid <- c(1e-17,1e-16,1e-15,1e-14,1e-13,1e-12);
|
||||
|
||||
|
||||
postscript(paste("../../products/eUDS_4XMM-DR12.flux.eps",sep=""), horizontal = FALSE, onefile = FALSE, paper = "special",width = 9.0, height = 6.0)
|
||||
par(oma=c(1,1,1,1))
|
||||
|
||||
#layout(matrix(c(1,2), 2, 1, byrow = TRUE), heights = c(1.5,1), TRUE)
|
||||
|
||||
par(mar=c(4.3, 4.3, 1, 1))
|
||||
par(cex.lab=1.2)
|
||||
par(cex.axis=1.2)
|
||||
|
||||
a <- read.table("../../products/eUDS_4XMM-DR12.flux.cvs", col.names=c("eflux","eerr","xflux","xerr"))
|
||||
|
||||
|
||||
xlim <- c(1e-15,1e-12)
|
||||
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)
|
||||
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$xhi,d)
|
||||
points(a$xflux,a$eflux,pch=21, bg="gold")
|
||||
|
||||
|
||||
lines(c(1e-17,1e-12),c(1e-17,1e-12))
|
||||
lines(c(1e-17,1e-12),10*c(1e-17,1e-12),lt=2)
|
||||
lines(c(1e-17,1e-12),0.1*c(1e-17,1e-12),lt=2)
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||||
|
||||
grid()
|
||||
|
||||
|
||||
|
||||
abline(h=0, col = "black",lty=2)
|
||||
abline(v=xgrid, col="lightgray", lty="dotted")
|
||||
|
||||
dev.off()
|
||||
19
data/4XMM-DR12/print_ds9reg.py
Executable file
19
data/4XMM-DR12/print_ds9reg.py
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@ -0,0 +1,19 @@
|
||||
from astropy.io import fits
|
||||
import sys
|
||||
|
||||
#filename='4XMM_DR12cat_slim_v1.0_UDS.fits.catalog'
|
||||
filename='4XMM_slim_DR13cat_v1.0_DEMO.fits'
|
||||
fout=filename.replace(".fits.catalog", ".names.reg")
|
||||
|
||||
hdul = fits.open(filename)
|
||||
#hdul.info()
|
||||
|
||||
tbdata = hdul[1].data
|
||||
hdul.close()
|
||||
|
||||
|
||||
#with open("./{}".format(fout), 'w') as writer:
|
||||
for rec in tbdata:
|
||||
print("fk5;circle({}, {}, 0.008)".format(rec['sc_ra'],rec['sc_dec']))
|
||||
#writer.write("fk5;circle({}, {}, {}) # text={{{}}}\n".format(rec['sc_ra'],rec['sc_dec'],rec['sc_poserr']/3600,rec['IAUNAME']))
|
||||
|
||||
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.
800
data/Gaia_unWISE/Gaia_unWISE_UDS.fits.catalog
Normal file
800
data/Gaia_unWISE/Gaia_unWISE_UDS.fits.catalog
Normal file
File diff suppressed because one or more lines are too long
10
data/Gaia_unWISE/README.md
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10
data/Gaia_unWISE/README.md
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|
||||
В данной директории находится каталог Gaia-unWISE из статьи https://ui.adsabs.harvard.edu/abs/2019MNRAS.489.4741S/abstract
|
||||
|
||||
Каталог был получен с этого ресурса: https://zenodo.org/record/6837642#.ZAcufYBByRR
|
||||
|
||||
Для вырезки источников для работы с полем UDS была использована эта команда:
|
||||
|
||||
```
|
||||
ftselect 'Gaia_unWISE_AGNs.fits[1]' Gaia_unWISE_UDS.fits 'RA > 32.75 && RA < 36.31 && DEC > -6.55 && DEC < -3.0' clobber=yes
|
||||
```
|
||||
|
||||
196
data/MCXC/mcxc.fits.catalog
Normal file
196
data/MCXC/mcxc.fits.catalog
Normal file
File diff suppressed because one or more lines are too long
15
data/MCXC/print_ds9reg.py
Executable file
15
data/MCXC/print_ds9reg.py
Executable file
@ -0,0 +1,15 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
from astropy.io import fits
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||||
|
||||
hdul = fits.open('mcxc.fits.catalog')
|
||||
tbdata = hdul[1].data
|
||||
hdul.close()
|
||||
|
||||
with open("../../products/mcxc.reg", 'w') as writer:
|
||||
for rec in tbdata:
|
||||
writer.write("fk5;point({}, {}) # color=magenta text={{{}}}\n".format(rec['RAJ2000'],
|
||||
rec['DEJ2000'],
|
||||
rec['OName'],))
|
||||
|
||||
|
||||
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 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
from astropy.io import fits
|
||||
|
||||
hdul = fits.open('nustar.fits.catalog')
|
||||
tbdata = hdul[1].data
|
||||
hdul.close()
|
||||
|
||||
with open("../../products/nustar_UDS.reg", 'w') as writer:
|
||||
for rec in tbdata:
|
||||
writer.write("fk5;circle({}, {}, 0.0025) # color=magenta text={{{}}}\n".format(rec['RAJ2000'], rec['DEJ2000'], rec['NuSTAR']))
|
||||
|
||||
|
||||
3
data/README.md
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3
data/README.md
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|
||||
Эта директория содержит данные (списки событий) телескопа еРОЗИТА.
|
||||
|
||||
raw -- оригинальные файлы с камер телескопа
|
||||
4
data/SXDS/README.md
Normal file
4
data/SXDS/README.md
Normal file
@ -0,0 +1,4 @@
|
||||
В данной директории находится каталог Subaru/XMM-Newton deep survey (SXDS) https://ui.adsabs.harvard.edu/abs/2008ApJS..179..124U/abstract
|
||||
|
||||
Каталог был получен с этого ресурса: https://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJS/179/124
|
||||
|
||||
477
data/SXDS/SXDS.fits.catalog
Normal file
477
data/SXDS/SXDS.fits.catalog
Normal file
File diff suppressed because one or more lines are too long
16
data/SXDS/print_ds9reg.py
Executable file
16
data/SXDS/print_ds9reg.py
Executable file
@ -0,0 +1,16 @@
|
||||
from astropy.io import fits
|
||||
import sys
|
||||
|
||||
filename='SXDS.fits.catalog'
|
||||
fout=filename.replace(".fits.catalog", ".reg")
|
||||
|
||||
hdul = fits.open(filename)
|
||||
#hdul.info()
|
||||
|
||||
tbdata = hdul[1].data
|
||||
|
||||
with open("../../products/{}".format(fout), 'w') as writer:
|
||||
for rec in tbdata:
|
||||
text="{}{}".format(rec['__UWS2008_'],rec['Note'])
|
||||
#writer.write("fk5;point({}, {})\n".format(rec['sc_ra'],rec['sc_dec']))
|
||||
writer.write("fk5;circle({}, {}, {}) # text={{{}}}\n".format(rec['RAJ2000'],rec['DEJ2000'],rec['e_pos']/3600,text))
|
||||
10
data/X-CLASS/README.md
Normal file
10
data/X-CLASS/README.md
Normal file
@ -0,0 +1,10 @@
|
||||
В данной директории находится каталог скоплений галактик X-CLASS из статьи https://ui.adsabs.harvard.edu/abs/2021A%26A...652A..12K/abstract
|
||||
|
||||
Каталог был получен с этого ресурса: https://vizier.cds.unistra.fr/viz-bin/VizieR-3?-source=J/A%2bA/652/A12/table3
|
||||
|
||||
Для вырезки источников для работы с полем UDS была использована эта команда:
|
||||
|
||||
```
|
||||
ftselect 'x-class.fits[1]' x-class_UDS.fits 'RAJ2000 > 32.75 && RAJ2000 < 36.31 && DEJ2000 > -6.55 && DEJ2000 < -3.0' clobber=yes
|
||||
```
|
||||
|
||||
18
data/X-CLASS/print_ds9reg.py
Executable file
18
data/X-CLASS/print_ds9reg.py
Executable file
@ -0,0 +1,18 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
from astropy.io import fits
|
||||
|
||||
hdul = fits.open('x-class_UDS.fits.catalog')
|
||||
tbdata = hdul[1].data
|
||||
hdul.close()
|
||||
|
||||
with open("../../products/x-class_UDS.fits.reg", 'w') as writer:
|
||||
for rec in tbdata:
|
||||
writer.write("fk5;circle({}, {}, {}) # color=magenta text={{{} {:.2f} {:.2f}}}\n".format(rec['RAJ2000'],
|
||||
rec['DEJ2000'],
|
||||
rec['extent']/3600,
|
||||
rec['XClass'],
|
||||
rec['MLdet'],
|
||||
rec['MLext'],))
|
||||
|
||||
|
||||
603
data/X-CLASS/x-class.fits.catalog
Normal file
603
data/X-CLASS/x-class.fits.catalog
Normal file
File diff suppressed because one or more lines are too long
10
data/X-CLASS/x-class_UDS.fits.catalog
Normal file
10
data/X-CLASS/x-class_UDS.fits.catalog
Normal file
File diff suppressed because one or more lines are too long
11
data/xspec/ML0001.xcm
Normal file
11
data/xspec/ML0001.xcm
Normal file
@ -0,0 +1,11 @@
|
||||
method leven 10 0.01
|
||||
abund wilm
|
||||
xsect vern
|
||||
cosmo 70 0 0.73
|
||||
xset delta 0.01
|
||||
systematic 0
|
||||
model TBabs*powerlaw
|
||||
0.0123819 1 0 0 100000 1e+06
|
||||
2 -1 -3 -2 9 10
|
||||
0.000106473 0.01 0 0 1e+20 1e+24
|
||||
bayes off
|
||||
11
data/xspec/ML0003.xcm
Normal file
11
data/xspec/ML0003.xcm
Normal file
@ -0,0 +1,11 @@
|
||||
method leven 10 0.01
|
||||
abund wilm
|
||||
xsect vern
|
||||
cosmo 70 0 0.73
|
||||
xset delta 0.01
|
||||
systematic 0
|
||||
model TBabs*powerlaw
|
||||
0.00327282 1 0 0 100000 1e+06
|
||||
2 -1 -3 -2 9 10
|
||||
0.000121635 0.01 0 0 1e+20 1e+24
|
||||
bayes off
|
||||
11
data/xspec/ML0004.xcm
Normal file
11
data/xspec/ML0004.xcm
Normal file
@ -0,0 +1,11 @@
|
||||
method leven 10 0.01
|
||||
abund wilm
|
||||
xsect vern
|
||||
cosmo 70 0 0.73
|
||||
xset delta 0.01
|
||||
systematic 0
|
||||
model TBabs*powerlaw
|
||||
0.00240283 1 0 0 100000 1e+06
|
||||
2 -1 -3 -2 9 10
|
||||
0.000297459 0.01 0 0 1e+20 1e+24
|
||||
bayes off
|
||||
11
data/xspec/ML0005.xcm
Normal file
11
data/xspec/ML0005.xcm
Normal file
@ -0,0 +1,11 @@
|
||||
method leven 10 0.01
|
||||
abund wilm
|
||||
xsect vern
|
||||
cosmo 70 0 0.73
|
||||
xset delta 0.01
|
||||
systematic 0
|
||||
model TBabs*powerlaw
|
||||
0.0320991 1 0 0 100000 1e+06
|
||||
2 -1 -3 -2 9 10
|
||||
0.000123814 0.01 0 0 1e+20 1e+24
|
||||
bayes off
|
||||
11
data/xspec/ecf.xcm
Normal file
11
data/xspec/ecf.xcm
Normal file
@ -0,0 +1,11 @@
|
||||
method leven 10 0.01
|
||||
abund wilm
|
||||
xsect vern
|
||||
cosmo 70 0 0.73
|
||||
xset delta 0.01
|
||||
systematic 0
|
||||
model TBabs*powerlaw
|
||||
0.02 -1 0 0 100000 1e+06
|
||||
2 -1 -3 -2 9 10
|
||||
4.83094e-05 0.01 0 0 1e+20 1e+24
|
||||
bayes off
|
||||
8
data/xspec/load.xcm
Normal file
8
data/xspec/load.xcm
Normal file
@ -0,0 +1,8 @@
|
||||
data tm0_SrcTool_020_SourceSpec_00005.fits.grp
|
||||
ign bad
|
||||
ign **-0.2
|
||||
ign 10.-**
|
||||
cpd /xs
|
||||
setpl en
|
||||
pl lda
|
||||
|
||||
61
scripts/00_check.py
Executable file
61
scripts/00_check.py
Executable file
@ -0,0 +1,61 @@
|
||||
#!/usr/bin/env python
|
||||
"""Печатает информацию о наблюдениях
|
||||
|
||||
"""
|
||||
|
||||
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
|
||||
|
||||
from uds.utils import *
|
||||
from uds.config import *
|
||||
|
||||
outkey="mosa_tm0"
|
||||
|
||||
""" find UDS root dir """
|
||||
root_path=dirname(dirname(dirname(inspect.getfile(uds))))
|
||||
print("UDS root path: {}".format(root_path))
|
||||
|
||||
infile_dir=root_path+'/data/processed'
|
||||
outfile_dir=root_path+'/products'
|
||||
create_folder(outfile_dir)
|
||||
|
||||
index=5
|
||||
|
||||
events=[]
|
||||
expmaps=[]
|
||||
totexp=0.0
|
||||
for tmkey in keylist_tm.keys():
|
||||
print("TM{} in work... init events".format(tmkey))
|
||||
for datakey in keylist_tm[tmkey]:
|
||||
#print("--> {}".format(datakey))
|
||||
""" Запускаем полностью в холостом режиме, нам нужно получить только названия файлов """
|
||||
outfile_evtool,outfile_expmap=init_events(key=datakey, eband_index=eband[index],
|
||||
infile_dir=infile_dir,
|
||||
outfile_dir=outfile_dir,
|
||||
do_init=False,
|
||||
do_obsmode=False,
|
||||
do_center=False,
|
||||
do_evtool=False,
|
||||
do_expmap=False,
|
||||
ra_cen=ra_cen, de_cen=de_cen,
|
||||
emin_kev=emin_kev[index],
|
||||
emax_kev=emax_kev[index])
|
||||
events.append(outfile_evtool)
|
||||
expmaps.append(outfile_expmap)
|
||||
tstart, tstop = read_tstart_tstop(infile=outfile_evtool)
|
||||
totexp=totexp+(tstop-tstart)
|
||||
print("{}, {} -- {}, {} -- {}, {:.2f} ks".format(outfile_evtool,tstart,tstop,
|
||||
mission2date_utc(tstart),
|
||||
mission2date_utc(tstop),
|
||||
(tstop-tstart)/1000))
|
||||
|
||||
print("\n***\n*** Total exposure: {:.1f} ks\n***".format(totexp))
|
||||
|
||||
|
||||
58
scripts/01_init_events.py
Executable file
58
scripts/01_init_events.py
Executable file
@ -0,0 +1,58 @@
|
||||
#!/usr/bin/env python
|
||||
"""Создает начальные списки событий и помещает их в uds/data/processed
|
||||
|
||||
Оригинальные файлы со списками событий задаются в файлах uds/data/evtlists/*.txt
|
||||
"""
|
||||
|
||||
import os
|
||||
import inspect
|
||||
|
||||
from os.path import dirname
|
||||
|
||||
import uds
|
||||
from uds.config import *
|
||||
from uds.utils import *
|
||||
|
||||
|
||||
""" find UDS root dir """
|
||||
root_path=dirname(dirname(dirname(inspect.getfile(uds))))
|
||||
print("UDS root path: {}".format(root_path))
|
||||
|
||||
el=root_path+'/data/evtlists/'
|
||||
pr=root_path+'/data/processed/'
|
||||
|
||||
|
||||
region="box({},{},4d,4d,0)".format(ra_cen,de_cen)
|
||||
""" Selection region """
|
||||
|
||||
|
||||
"""
|
||||
# TM1
|
||||
do_evtool_esass(evlist=el+'tm1.txt', outfile=pr+'tm1_obs_1.fits', gti='621296896. 621304128.', rmlock=True)
|
||||
|
||||
# TM5
|
||||
do_evtool_esass(evlist=el+'tm5.txt', outfile=pr+'tm5_obs_1.fits', gti='620606016. 620614848.', rmlock=True)
|
||||
do_evtool_esass(evlist=el+'tm5.txt', outfile=pr+'tm5_obs_2.fits', gti='620676992. 620689792.', rmlock=True)
|
||||
|
||||
# TM6
|
||||
do_evtool_esass(evlist=el+'tm6.txt', outfile=pr+'tm6_park_1.fits', gti='620174080. 620178002.620032', rmlock=True)
|
||||
do_evtool_esass(evlist=el+'tm6.txt', outfile=pr+'tm6_scan_1.fits', gti='620178002.620032 620192246.62720', rmlock=True)
|
||||
do_evtool_esass(evlist=el+'tm6.txt', outfile=pr+'tm6_park_2.fits', gti='620192448. 620194624.', rmlock=True)
|
||||
do_evtool_esass(evlist=el+'tm6.txt', outfile=pr+'tm6_scan_2.fits', gti='620194666.606144 620208904.673408', rmlock=True)
|
||||
do_evtool_esass(evlist=el+'tm6.txt', outfile=pr+'tm6_park_3.fits', gti='620209162.670976 620211316.650304', rmlock=True)
|
||||
do_evtool_esass(evlist=el+'tm6.txt', outfile=pr+'tm6_scan_3.fits', gti='620211328. 620225600.', rmlock=True)
|
||||
do_evtool_esass(evlist=el+'tm6.txt', outfile=pr+'tm6_park_4.fits', gti='620225853.609024 620227974.68832', rmlock=True)
|
||||
do_evtool_esass(evlist=el+'tm6.txt', outfile=pr+'tm6_scan_4.fits', gti='620227904. 620242176.', rmlock=True)
|
||||
do_evtool_esass(evlist=el+'tm6.txt', outfile=pr+'tm6_obs_1.fits', gti='620242432. 620258368.', rmlock=True)
|
||||
|
||||
do_evtool_esass(evlist=el+'tm6.txt', outfile=pr+'tm6_obs_2.fits', gti='620607424. 620614656.', rmlock=True)
|
||||
do_badpix_tm6(filename=pr+'tm6_obs_2.fits')
|
||||
|
||||
do_evtool_esass(evlist=el+'tm6.txt', outfile=pr+'tm6_obs_3.fits', gti='620676992. 620690368.', rmlock=True)
|
||||
do_badpix_tm6(filename=pr+'tm6_obs_3.fits')
|
||||
"""
|
||||
# TM7
|
||||
do_evtool_esass(evlist=el+'tm7.txt', outfile=pr+'tm7_obs_1.fits', gti='621043136. 621052416.', emin=0.2, emax=10.0, region=region, rmlock=True)
|
||||
#do_evtool_esass(evlist=el+'tm7.txt', outfile=pr+'tm7_obs_2.fits', gti='621110272. 621117952.', region=region, rmlock=True)
|
||||
|
||||
|
||||
95
scripts/02_merge_events.py
Executable file
95
scripts/02_merge_events.py
Executable file
@ -0,0 +1,95 @@
|
||||
#!/usr/bin/env python
|
||||
"""Создает объедененный список событий и помещает его в uds/products
|
||||
|
||||
Этот список событий нужен, в основном для извлечения спектров с помощью srctool
|
||||
"""
|
||||
|
||||
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
|
||||
|
||||
from uds.utils import *
|
||||
from uds.config import *
|
||||
|
||||
outkey="mosa_tm0"
|
||||
|
||||
""" 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)
|
||||
|
||||
index=3 # select energy band
|
||||
|
||||
do_init = True
|
||||
do_merge = True
|
||||
do_rate = False
|
||||
do_adapt = True # requires CIAO
|
||||
|
||||
vign=False
|
||||
vignetting = 'vign' if (vign==True) else 'novign'
|
||||
|
||||
events=[]
|
||||
expmaps=[]
|
||||
bkgmaps=[]
|
||||
for tmkey in keylist_tm.keys():
|
||||
print("TM{} in work... init events".format(tmkey))
|
||||
for datakey in keylist_tm[tmkey]:
|
||||
#if not ("scan" in datakey):
|
||||
# continue
|
||||
print("--> {}".format(datakey))
|
||||
""" Подготавливаем списки событий индивидуальных наблюдений """
|
||||
outfile_evtool,outfile_expmap=init_events(key=datakey, eband_index=eband[index],
|
||||
infile_dir=infile_dir,
|
||||
outfile_dir=outfile_dir,
|
||||
do_init=do_init,
|
||||
do_obsmode=False,
|
||||
do_center=False,
|
||||
do_evtool=True,
|
||||
do_expmap=False,
|
||||
vign=vign,
|
||||
ra_cen=ra_cen, de_cen=de_cen,
|
||||
emin_kev=emin_kev[index],
|
||||
emax_kev=emax_kev[index])
|
||||
events.append(outfile_evtool)
|
||||
expmaps.append(outfile_expmap)
|
||||
bkgmaps.append("{}_BackMap3_en{}.fits".format(os.path.join(outfile_dir,datakey), eband[0]))
|
||||
|
||||
""" Собираем общий список событий """
|
||||
outfile_evtool="{}_EventList_en{}.fits".format(os.path.join(outfile_dir,outkey), eband[index])
|
||||
|
||||
outfile_expmap="{}_ExposureMap_en{}.{}.fits".format(os.path.join(outfile_dir,outkey), eband[index], vignetting)
|
||||
outfile_bkgmap="{}_BackMap_en{}.{}.fits".format(os.path.join(outfile_dir,outkey), eband[index], vignetting)
|
||||
|
||||
if(do_merge==True):
|
||||
do_evtool_esass(events=events, outfile=outfile_evtool)
|
||||
do_fimgmerge_ftools(maps=expmaps, outfile=outfile_expmap)
|
||||
do_fimgmerge_ftools(maps=bkgmaps, outfile=outfile_bkgmap)
|
||||
|
||||
outfile_rate="{}_RateMap_en{}.{}.fits".format(os.path.join(outfile_dir,outkey), eband[index], vignetting)
|
||||
if(do_rate==True):
|
||||
make_rate_map(cntmap=outfile_evtool, expmap=outfile_expmap, outfile=outfile_rate)
|
||||
|
||||
|
||||
function='gaussian'
|
||||
outfile_adapt="{}_ImageAdapt_en{}.{}.{}.fits".format(os.path.join(outfile_dir,outkey), eband[index], function, vignetting)
|
||||
if(do_adapt==True):
|
||||
do_adapt_ciao(infile=outfile_evtool, outfile=outfile_adapt, expmap=outfile_expmap, function=function, expcut=100)
|
||||
|
||||
|
||||
424
scripts/03_init_obs.py
Executable file
424
scripts/03_init_obs.py
Executable file
@ -0,0 +1,424 @@
|
||||
#!/usr/bin/env python
|
||||
"""
|
||||
НАЗВАНИЕ:
|
||||
|
||||
01_init_obs.py
|
||||
|
||||
|
||||
НАЗНАЧЕНИЕ:
|
||||
|
||||
Подготавливает списки событий в разных энергетических диапазонах.
|
||||
Производит списки источников в наждом наблюдении и делает астрокоррекцию с помощью wcs_match/wcs_update
|
||||
|
||||
ВЫЗОВ:
|
||||
|
||||
conda activate ciao-4.15
|
||||
esass
|
||||
./01_init_obs.py
|
||||
|
||||
|
||||
УПРАВЛЕНИЕ:
|
||||
|
||||
Запуск отдельных команд управляется переменными, например: do_init = True
|
||||
Выбранные энергетические диапазоны управляется массивом eband_selected
|
||||
|
||||
ПАРАМЕТРЫ:
|
||||
eband_selected : Выбранные энергетические диапазоны
|
||||
|
||||
|
||||
ВЫВОД:
|
||||
|
||||
Выходные файлы записываются в директорию outfile_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 multiprocessing import Pool
|
||||
|
||||
from os.path import dirname
|
||||
import inspect
|
||||
import uds
|
||||
|
||||
from uds.utils import *
|
||||
from uds.config import *
|
||||
|
||||
|
||||
""" find UDS root dir """
|
||||
root_path=dirname(dirname(dirname(inspect.getfile(uds))))
|
||||
print("UDS root path: {}".format(root_path))
|
||||
|
||||
infile_dir=root_path+'/data/processed'
|
||||
outfile_dir=root_path+'/products'
|
||||
create_folder(outfile_dir)
|
||||
|
||||
run_Pool=False
|
||||
|
||||
do_init = False
|
||||
do_ermask = False
|
||||
|
||||
do_erbox1 = False # local mode
|
||||
do_erbackmap1 = False #
|
||||
do_erbox2 = False # map mode, with background map
|
||||
do_erbackmap2 = False #
|
||||
do_erbox3 = False # map mode, with background map
|
||||
do_erbackmap3 = False #
|
||||
|
||||
do_ermldet = False
|
||||
do_catprep = False
|
||||
do_cross_match = False
|
||||
|
||||
do_astro_corr = False # search optimal shift
|
||||
do_astro_update = True
|
||||
|
||||
do_wcs_match = False # Chandra task -- DEPRECATED
|
||||
do_wcs_update = False # Chandra task -- DEPRECATED
|
||||
|
||||
eband_selected=[5]
|
||||
|
||||
vign=True
|
||||
vignetting = 'vign' if (vign==True) else 'novign'
|
||||
|
||||
|
||||
def runme(datakey):
|
||||
""" runs datakey over energy bands """
|
||||
events=[]
|
||||
expmaps=[]
|
||||
outfile_boxlist1=[]
|
||||
outfile_boxlist2=[]
|
||||
outfile_boxlist3=[]
|
||||
outfile_backmap1=[]
|
||||
outfile_backmap2=[]
|
||||
outfile_backmap3=[]
|
||||
cheesemask=[]
|
||||
bkgimage=[]
|
||||
srcmaps=[]
|
||||
|
||||
print(datakey)
|
||||
print('module name:', __name__)
|
||||
print('parent process:', os.getppid())
|
||||
print('process id:', os.getpid())
|
||||
|
||||
for ii in range(len(eband_selected)):
|
||||
index=eband_selected[ii]
|
||||
print("\t>>> Energy band en{} -- {}-{} keV".format(eband[index],emin_kev[index],emax_kev[index]))
|
||||
outfile_evtool, outfile_expmap = init_events(key=datakey, eband_index=eband[index],
|
||||
infile_dir=infile_dir,
|
||||
outfile_dir=outfile_dir,
|
||||
do_init=do_init,
|
||||
do_obsmode=True,
|
||||
do_center=True,
|
||||
do_evtool=True,
|
||||
do_expmap=True,
|
||||
vign=vign,
|
||||
ra_cen=ra_cen, de_cen=de_cen,
|
||||
emin_kev=emin_kev[index],
|
||||
emax_kev=emax_kev[index])
|
||||
expmaps.append(outfile_expmap)
|
||||
events.append(outfile_evtool)
|
||||
|
||||
|
||||
# After astrometry-corrected files (*.attcorr.fits) are obtained, one can take them as original, in order to check the full chain:
|
||||
#events.append(outfile_evtool.replace(".fits", ".attcorr.fits"))
|
||||
|
||||
|
||||
""" Detmask """
|
||||
|
||||
detmask="{}_DetectionMask{}".format(os.path.join(outfile_dir,datakey), outfile_post)
|
||||
if(do_ermask==True):
|
||||
cmd=["ermask",
|
||||
"expimage=%s" %(expmaps[0]), # use the first exposure maps calculated for that skyfield, independent of the energy band
|
||||
"detmask=%s" %(detmask),
|
||||
"threshold1=0.01",
|
||||
"threshold2=10.0",
|
||||
"regionfile_flag=no"
|
||||
]
|
||||
remove_file(detmask)
|
||||
print((" ").join(cmd))
|
||||
os.system((" ").join(cmd))
|
||||
|
||||
for ii in range(len(eband_selected)):
|
||||
index=eband_selected[ii]
|
||||
print("\t>>> Energy band en{} -- {}-{} keV".format(eband[index],emin_kev[index],emax_kev[index]))
|
||||
|
||||
""" erbox in local mode """
|
||||
outfile_boxlist1.append("{}_BoxList1_en{}{}".format(os.path.join(outfile_dir,datakey), eband[index], outfile_post))
|
||||
if(do_erbox1==True):
|
||||
""" erbox in local mode """
|
||||
cmd=["erbox",
|
||||
"images=%s" %(events[ii]),
|
||||
"boxlist=%s" %(outfile_boxlist1[ii]),
|
||||
"expimages=%s" %(expmaps[ii]),
|
||||
"detmasks=%s" %(detmask),
|
||||
"emin=%s" %(emin_ev[index]),
|
||||
"emax=%s" %(emax_ev[index]),
|
||||
"ecf=1.0",
|
||||
"nruns=2",
|
||||
"likemin=6.0",
|
||||
"boxsize=4",
|
||||
"compress_flag=N",
|
||||
"bkgima_flag=N",
|
||||
"expima_flag=Y",
|
||||
"detmask_flag=Y"
|
||||
]
|
||||
|
||||
remove_file(outfile_boxlist1[ii])
|
||||
|
||||
print((" ").join(cmd))
|
||||
os.system((" ").join(cmd))
|
||||
save_ds9reg(outfile_boxlist1[ii])
|
||||
|
||||
|
||||
outfile_backmap1.append("{}_BackMap1_en{}{}".format(os.path.join(outfile_dir,datakey), eband[index], outfile_post))
|
||||
cheese_mask="{}_CheeseMask1_en{}{}".format(os.path.join(outfile_dir,datakey), eband[index], outfile_post)
|
||||
if(do_erbackmap1==True):
|
||||
""" back map 1 """
|
||||
cmd=["erbackmap",
|
||||
"image=%s" %(events[ii]),
|
||||
"expimage=%s" %(expmaps[ii]),
|
||||
"boxlist=%s" %(outfile_boxlist1[ii]),
|
||||
"detmask=%s" %(detmask),
|
||||
"emin=%s" %(emin_ev[index]),
|
||||
"emax=%s" %(emax_ev[index]),
|
||||
"bkgimage=%s" %(outfile_backmap1[ii]),
|
||||
"cheesemask=%s" %(cheese_mask),
|
||||
"idband=1",
|
||||
"scut=0.001",
|
||||
"mlmin=6",
|
||||
"maxcut=0.5",
|
||||
"fitmethod=smooth smoothval=15",
|
||||
"snr=40.",
|
||||
]
|
||||
|
||||
remove_file(cheese_mask)
|
||||
remove_file(outfile_backmap1[ii])
|
||||
|
||||
os.system((" ").join(cmd))
|
||||
print((" ").join(cmd))
|
||||
|
||||
outfile_boxlist2.append("{}_BoxList2_en{}{}".format(os.path.join(outfile_dir,datakey), eband[index], outfile_post))
|
||||
if(do_erbox2==True):
|
||||
""" erbox in background mode """
|
||||
cmd=["erbox",
|
||||
"images=%s" %(events[ii]),
|
||||
"boxlist=%s" %(outfile_boxlist2[ii]),
|
||||
"expimages=%s" %(expmaps[ii]),
|
||||
"detmasks=%s" %(detmask),
|
||||
"emin=%s" %(emin_ev[index]),
|
||||
"emax=%s" %(emax_ev[index]),
|
||||
"ecf=1.0",
|
||||
"nruns=2",
|
||||
"likemin=4.0",
|
||||
"boxsize=4",
|
||||
"compress_flag=N",
|
||||
"bkgima_flag=Y",
|
||||
"bkgimages={}".format(outfile_backmap1[ii]),
|
||||
"expima_flag=Y",
|
||||
"detmask_flag=Y"
|
||||
]
|
||||
|
||||
remove_file(outfile_boxlist2[ii])
|
||||
|
||||
print((" ").join(cmd))
|
||||
os.system((" ").join(cmd))
|
||||
save_ds9reg(outfile_boxlist2[ii])
|
||||
|
||||
|
||||
outfile_backmap2.append("{}_BackMap2_en{}{}".format(os.path.join(outfile_dir,datakey), eband[index], outfile_post))
|
||||
cheese_mask="{}_CheeseMask2_en{}{}".format(os.path.join(outfile_dir,datakey), eband[index], outfile_post)
|
||||
if(do_erbackmap2==True):
|
||||
""" back map 2 """
|
||||
cmd=["erbackmap",
|
||||
"image=%s" %(events[ii]),
|
||||
"expimage=%s" %(expmaps[ii]),
|
||||
"boxlist=%s" %(outfile_boxlist2[ii]),
|
||||
"detmask=%s" %(detmask),
|
||||
"emin=%s" %(emin_ev[index]),
|
||||
"emax=%s" %(emax_ev[index]),
|
||||
"bkgimage=%s" %(outfile_backmap2[ii]),
|
||||
"cheesemask=%s" %(cheese_mask),
|
||||
"idband=1",
|
||||
"scut=0.001",
|
||||
"mlmin=6",
|
||||
"maxcut=0.5",
|
||||
"fitmethod=smooth smoothval=15",
|
||||
"snr=40.",
|
||||
]
|
||||
|
||||
remove_file(cheese_mask)
|
||||
remove_file(outfile_backmap2[ii])
|
||||
|
||||
os.system((" ").join(cmd))
|
||||
print((" ").join(cmd))
|
||||
|
||||
outfile_boxlist3.append("{}_BoxList3_en{}{}".format(os.path.join(outfile_dir,datakey), eband[index], outfile_post))
|
||||
if(do_erbox3==True):
|
||||
""" erbox in map mode FINAL """
|
||||
cmd=["erbox",
|
||||
"images=%s" %(events[ii]),
|
||||
"boxlist=%s" %(outfile_boxlist3[ii]),
|
||||
"expimages=%s" %(expmaps[ii]),
|
||||
"detmasks=%s" %(detmask),
|
||||
"emin=%s" %(emin_ev[index]),
|
||||
"emax=%s" %(emax_ev[index]),
|
||||
"ecf=1.0",
|
||||
"nruns=2",
|
||||
"likemin=4.0",
|
||||
"boxsize=4",
|
||||
"compress_flag=N",
|
||||
"bkgima_flag=Y",
|
||||
"bkgimages={}".format(outfile_backmap2[ii]),
|
||||
"expima_flag=Y",
|
||||
"detmask_flag=Y"
|
||||
]
|
||||
|
||||
remove_file(outfile_boxlist3[ii])
|
||||
|
||||
print((" ").join(cmd))
|
||||
os.system((" ").join(cmd))
|
||||
save_ds9reg(outfile_boxlist3[ii])
|
||||
|
||||
outfile_backmap3.append("{}_BackMap3_en{}{}".format(os.path.join(outfile_dir,datakey), eband[index], outfile_post))
|
||||
cheese_mask="{}_CheeseMask3_en{}{}".format(os.path.join(outfile_dir,datakey), eband[index], outfile_post)
|
||||
if(do_erbackmap3==True):
|
||||
""" back map 3 FINAL """
|
||||
cmd=["erbackmap",
|
||||
"image=%s" %(events[ii]),
|
||||
"expimage=%s" %(expmaps[ii]),
|
||||
"boxlist=%s" %(outfile_boxlist3[ii]),
|
||||
"detmask=%s" %(detmask),
|
||||
"emin=%s" %(emin_ev[index]),
|
||||
"emax=%s" %(emax_ev[index]),
|
||||
"bkgimage=%s" %(outfile_backmap3[ii]),
|
||||
"cheesemask=%s" %(cheese_mask),
|
||||
"idband=1",
|
||||
"scut=0.001",
|
||||
"mlmin=6",
|
||||
"maxcut=0.5",
|
||||
"fitmethod=smooth smoothval=15",
|
||||
"snr=40.",
|
||||
]
|
||||
|
||||
remove_file(cheese_mask)
|
||||
remove_file(outfile_backmap3[ii])
|
||||
|
||||
os.system((" ").join(cmd))
|
||||
print((" ").join(cmd))
|
||||
|
||||
mllist="{}_MaxLikSourceList_en{}{}".format(os.path.join(outfile_dir,datakey), eband[index], outfile_post)
|
||||
srcmap="{}_SourceMap_en{}{}".format(os.path.join(outfile_dir,datakey), eband[index], outfile_post)
|
||||
|
||||
cmd=["ermldet",
|
||||
"mllist=%s" %(mllist),
|
||||
"boxlist=%s" %(outfile_boxlist3[ii]),
|
||||
"images=%s" %(events[ii]),
|
||||
"expimages=%s" %(expmaps[ii]),
|
||||
"detmasks=%s" %(detmask),
|
||||
"bkgimages=%s" %(outfile_backmap3[ii]),
|
||||
"emin=%s" %(emin_ev[index]),
|
||||
"emax=%s" %(emax_ev[index]),
|
||||
"hrdef=",
|
||||
"ecf={}".format(ecf[index]),
|
||||
"likemin=5.",
|
||||
"extlikemin=6.",
|
||||
"compress_flag=N",
|
||||
"cutrad=15.",
|
||||
"multrad=20.",
|
||||
"extmin=2.0",
|
||||
"extmax=15.0",
|
||||
#"bkgima_flag=Y", looks outdated
|
||||
"expima_flag=Y",
|
||||
"detmask_flag=Y",
|
||||
"extentmodel=beta",
|
||||
"thres_flag=N",
|
||||
"thres_col=like",
|
||||
"thres_val=30.",
|
||||
"nmaxfit=4",
|
||||
"nmulsou=2",
|
||||
"fitext_flag=yes",
|
||||
"srcima_flag=yes",
|
||||
"srcimages=%s" %(srcmap)
|
||||
|
||||
]
|
||||
|
||||
if(do_ermldet==True):
|
||||
test_exe('ermldet')
|
||||
remove_file(mllist)
|
||||
remove_file(srcmap)
|
||||
|
||||
os.system((" ").join(cmd))
|
||||
print((" ").join(cmd))
|
||||
save_ermldet_ds9reg(mllist,scale=60*60)
|
||||
|
||||
catprep="{}_SourceCatalog_en{}{}".format(os.path.join(outfile_dir,datakey), eband[index], outfile_post)
|
||||
catprep_en0="{}_SourceCatalog_en{}{}".format(os.path.join(outfile_dir,datakey), eband[0], outfile_post)
|
||||
if(do_catprep==True):
|
||||
cmd=["catprep",
|
||||
"infile={}".format(mllist),
|
||||
"outfile={}".format(catprep),]
|
||||
remove_file(catprep)
|
||||
os.system((" ").join(cmd))
|
||||
print((" ").join(cmd))
|
||||
save_catprep_ds9reg(catprep,scale=60*60)
|
||||
|
||||
if(do_cross_match==True):
|
||||
crossmatch_shu2019(catprep,dlmin=10,refimage=events[ii],crval=wcslist[datakey],
|
||||
catalog=root_path+"/data/Gaia_unWISE/Gaia_unWISE_UDS.fits.catalog",errlim=5.0)
|
||||
|
||||
if(do_astro_corr==True and eband[index]=='0'):
|
||||
""" run astro_corr for 0.3-2.3 keV only """
|
||||
wcs_astro_corr(catprep)
|
||||
#wcs_match_ciao(catprep, method='rst',radius=12,residlim=0,residtype=0,residfac=1)
|
||||
|
||||
if(do_astro_update==True):
|
||||
""" run astro_corr for 0.3-2.3 keV only """
|
||||
attcorr=wcs_update_shift(events[ii],flog=catprep_en0.replace(".fits", ".shift.log"))
|
||||
do_evtool_esass(evfile=attcorr,outfile=attcorr,rmlock=False, do_center=True, ra_cen=ra_cen, de_cen=de_cen)
|
||||
|
||||
|
||||
if(do_wcs_match==True and eband[index]=='0'):
|
||||
""" run wcs_match for 0.3-2.3 keV only """
|
||||
wcs_match_ciao(catprep, method='trans',radius=12,residlim=5)
|
||||
#wcs_match_ciao(catprep, method='rst',radius=12,residlim=0,residtype=0,residfac=1)
|
||||
|
||||
if(do_wcs_update==True):
|
||||
""" use 0.3-2.3 keV transform matrix for all other bands """
|
||||
attcorr=wcs_update_ciao(events[ii],crval=wcslist[datakey],transformfile=catprep_en0.replace(".fits", ".xfm"),clean=False)
|
||||
do_evtool_esass(evfile=attcorr,outfile=attcorr,rmlock=False, do_center=True, ra_cen=ra_cen, de_cen=de_cen)
|
||||
|
||||
|
||||
"""
|
||||
# individual run, testing
|
||||
runme("tm7_obs_1")
|
||||
runme("tm5_obs_1")
|
||||
runme("tm6_scan_1")
|
||||
"""
|
||||
|
||||
|
||||
|
||||
if(run_Pool==True):
|
||||
# parallel run
|
||||
items=[]
|
||||
for tmkey in keylist_tm.keys():
|
||||
for datakey in keylist_tm[tmkey]:
|
||||
items.append(datakey)
|
||||
|
||||
with Pool() as pool:
|
||||
pool.map(runme, items)
|
||||
|
||||
else:
|
||||
# conventional run
|
||||
for tmkey in keylist_tm.keys():
|
||||
for datakey in keylist_tm[tmkey]:
|
||||
print("--> {}".format(datakey))
|
||||
runme(datakey)
|
||||
#sys.exit()
|
||||
458
scripts/04_mosaics.py
Executable file
458
scripts/04_mosaics.py
Executable file
@ -0,0 +1,458 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
НАЗВАНИЕ:
|
||||
|
||||
04_mosaics.py
|
||||
|
||||
|
||||
НАЗНАЧЕНИЕ:
|
||||
|
||||
Собирает мозайки в разных энергетических диапазонах.
|
||||
|
||||
ВЫЗОВ:
|
||||
|
||||
esass
|
||||
./04_mosaics.py
|
||||
|
||||
|
||||
УПРАВЛЕНИЕ:
|
||||
|
||||
Запуск отдельных команд управляется переменными, например: do_init = True
|
||||
Выбранный энергетический диапазон управляется переменной index
|
||||
forced=True делает принудительную фотометрию
|
||||
|
||||
ПАРАМЕТРЫ:
|
||||
|
||||
index : Выбранный энергетический диапазон
|
||||
|
||||
|
||||
ВЫВОД:
|
||||
|
||||
Выходные файлы записываются в директорию outfile_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 pickle
|
||||
|
||||
|
||||
|
||||
import uds
|
||||
|
||||
from uds.utils import *
|
||||
from uds.config 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)
|
||||
|
||||
local_run = False
|
||||
|
||||
outkey="tm0"
|
||||
|
||||
do_init = True
|
||||
do_merge = True
|
||||
do_detmask = True
|
||||
do_expmap = True
|
||||
do_erbox1 = True # local mode
|
||||
do_erbackmap1 = True #
|
||||
do_erbox2 = True # map mode, with background map
|
||||
do_erbackmap2 = True #
|
||||
do_erbox3 = True # map mode, with background map
|
||||
do_erbackmap3 = True #
|
||||
do_ersensmap = False
|
||||
do_ermldet = True
|
||||
do_fixcat = False # only for index=0
|
||||
do_fixxmm = False # prepare forced photometry, only for index=0
|
||||
do_apetool = False
|
||||
do_catprep = True
|
||||
do_filter_catalog = False
|
||||
|
||||
do_cross_match = False
|
||||
|
||||
index=3
|
||||
|
||||
forced=False
|
||||
""" If forced=True, take input catalog from energy range en0 """
|
||||
|
||||
comm='' # for 4XMM-DR12 forced photometry use '-xmm'
|
||||
|
||||
|
||||
vign=True
|
||||
vignetting = 'vign' if (vign==True) else 'novign'
|
||||
|
||||
attcorr=True
|
||||
|
||||
events=[]
|
||||
expmaps=[]
|
||||
bkgmaps=[]
|
||||
for tmkey in keylist_tm.keys():
|
||||
print("TM{} in work... init events".format(tmkey))
|
||||
for datakey in keylist_tm[tmkey]:
|
||||
print("--> {}".format(datakey))
|
||||
""" Подготавливаем списки событий индивидуальных наблюдений """
|
||||
outfile_evtool,outfile_expmap=init_events(key=datakey,attcorr=attcorr,
|
||||
eband_index=eband[index],
|
||||
infile_dir=infile_dir,
|
||||
outfile_dir=outfile_dir,
|
||||
do_init=do_init,
|
||||
do_obsmode=False,
|
||||
do_center=False,
|
||||
do_evtool=True,
|
||||
do_expmap=False,
|
||||
vign=vign,
|
||||
ra_cen=ra_cen, de_cen=de_cen,
|
||||
emin_kev=emin_kev[index],
|
||||
emax_kev=emax_kev[index])
|
||||
events.append(outfile_evtool)
|
||||
expmaps.append(outfile_expmap)
|
||||
|
||||
|
||||
""" Собираем общий список событий """
|
||||
outfile_evtool="{}_EventList_en{}.fits".format(os.path.join(outfile_dir,outkey),
|
||||
eband[index])
|
||||
|
||||
if(do_merge==True):
|
||||
do_evtool_esass(events=events, outfile=outfile_evtool)
|
||||
|
||||
|
||||
""" makes detmask from TM exposures """
|
||||
detmask="{}/{}_DetectorMask_en{}{}".format(outfile_dir,
|
||||
outkey,
|
||||
eband[index],
|
||||
outfile_post)
|
||||
if(do_detmask==True):
|
||||
create_detmask_merged(expmaps,detmask,minval=100)
|
||||
|
||||
"""
|
||||
Собираем общую карту экспозиции, обратите внимание на коэффициент 7.
|
||||
Экспозиция рассчитывается на 7 телескопов.
|
||||
outfile_expmap="{}_ExposureMap_en{}.{}.fits".format(os.path.join(outfile_dir,outkey), eband[index], vignetting)
|
||||
outfile_bkgmap="{}_BackMap_en{}.{}.fits".format(os.path.join(outfile_dir,outkey), eband[index], vignetting)
|
||||
"""
|
||||
outfile_expmap="{}_ExposureMap_en{}.{}{}".format(os.path.join(outfile_dir,outkey),
|
||||
eband[index],vignetting,
|
||||
outfile_post)
|
||||
if(do_expmap==True):
|
||||
create_expmap_merged(expmaps,outfile_expmap,scale=7.0)
|
||||
|
||||
outfile_boxlist1="{}/{}_BoxList1_en{}{}".format(outfile_dir,outkey, eband[index], outfile_post)
|
||||
if(do_erbox1==True):
|
||||
cmd=["erbox",
|
||||
"images=\'{}\'".format(outfile_evtool),
|
||||
"boxlist=%s" %(outfile_boxlist1),
|
||||
"expimages=\'{}\'".format(outfile_expmap),
|
||||
"detmasks=\'{}\'".format(detmask),
|
||||
"emin=\'{}\'".format(emin_ev[index]),
|
||||
"emax=\'{}\'".format(emax_ev[index]),
|
||||
"ecf=\'{}\'".format(ecf[index]),
|
||||
"nruns=2",
|
||||
"likemin=6.0",
|
||||
"boxsize=4",
|
||||
"compress_flag=N",
|
||||
"bkgima_flag=N",
|
||||
"expima_flag=Y",
|
||||
"detmask_flag=Y"
|
||||
]
|
||||
remove_file(outfile_boxlist1)
|
||||
print((" ").join(cmd))
|
||||
os.system((" ").join(cmd))
|
||||
save_ds9reg(outfile_boxlist1)
|
||||
|
||||
""" Background map 1 """
|
||||
outfile_backmap1="{}_BackMap1_en{}{}".format(os.path.join(outfile_dir,outkey), eband[index], outfile_post)
|
||||
cheese_mask="{}_CheeseMask1_en{}{}".format(os.path.join(outfile_dir,outkey), eband[index], outfile_post)
|
||||
if(do_erbackmap1==True):
|
||||
do_erbackmap_esass(outfile_evtool,outfile_expmap,outfile_boxlist1,detmask,emin_ev[index],emax_ev[index],
|
||||
outfile_backmap1,cheese_mask)
|
||||
|
||||
outfile_boxlist2="{}/{}_BoxList2_en{}{}".format(outfile_dir,outkey, eband[index], outfile_post)
|
||||
if(do_erbox2==True):
|
||||
cmd=["erbox",
|
||||
"images=\'{}\'".format(outfile_evtool),
|
||||
"boxlist=%s" %(outfile_boxlist2),
|
||||
"expimages=\'{}\'".format(outfile_expmap),
|
||||
"detmasks=\'{}\'".format(detmask),
|
||||
"emin=\'{}\'".format(emin_ev[index]),
|
||||
"emax=\'{}\'".format(emax_ev[index]),
|
||||
"ecf=\'{}\'".format(ecf[index]),
|
||||
"nruns=2",
|
||||
"likemin=6.0",
|
||||
"boxsize=4",
|
||||
"compress_flag=N",
|
||||
"bkgima_flag=Y",
|
||||
"bkgimages={}".format(outfile_backmap1),
|
||||
"expima_flag=Y",
|
||||
"detmask_flag=Y"
|
||||
]
|
||||
remove_file(outfile_boxlist2)
|
||||
print((" ").join(cmd))
|
||||
os.system((" ").join(cmd))
|
||||
save_ds9reg(outfile_boxlist2)
|
||||
|
||||
""" Background map 2 """
|
||||
outfile_backmap2="{}_BackMap2_en{}{}".format(os.path.join(outfile_dir,outkey), eband[index], outfile_post)
|
||||
cheese_mask="{}_CheeseMask2_en{}{}".format(os.path.join(outfile_dir,outkey), eband[index], outfile_post)
|
||||
if(do_erbackmap2==True):
|
||||
do_erbackmap_esass(outfile_evtool,outfile_expmap,outfile_boxlist2,detmask,emin_ev[index],emax_ev[index],
|
||||
outfile_backmap2,cheese_mask)
|
||||
|
||||
outfile_boxlist3="{}/{}_BoxList3_en{}{}".format(outfile_dir,outkey, eband[index], outfile_post)
|
||||
if(do_erbox3==True):
|
||||
cmd=["erbox",
|
||||
"images=\'{}\'".format(outfile_evtool),
|
||||
"boxlist=%s" %(outfile_boxlist3),
|
||||
"expimages=\'{}\'".format(outfile_expmap),
|
||||
"detmasks=\'{}\'".format(detmask),
|
||||
"emin=\'{}\'".format(emin_ev[index]),
|
||||
"emax=\'{}\'".format(emax_ev[index]),
|
||||
"ecf=\'{}\'".format(ecf[index]),
|
||||
"nruns=2",
|
||||
"likemin=6.0",
|
||||
"boxsize=4",
|
||||
"compress_flag=N",
|
||||
"bkgima_flag=Y",
|
||||
"bkgimages={}".format(outfile_backmap2),
|
||||
"expima_flag=Y",
|
||||
"detmask_flag=Y"
|
||||
]
|
||||
remove_file(outfile_boxlist3)
|
||||
print((" ").join(cmd))
|
||||
os.system((" ").join(cmd))
|
||||
save_ds9reg(outfile_boxlist3)
|
||||
|
||||
""" Background map 3 """
|
||||
outfile_backmap3="{}_BackMap3_en{}.{}{}".format(os.path.join(outfile_dir,outkey), eband[index], vignetting, outfile_post)
|
||||
cheese_mask="{}_CheeseMask3_en{}.{}{}".format(os.path.join(outfile_dir,outkey), eband[index], vignetting, outfile_post)
|
||||
if(do_erbackmap3==True):
|
||||
boxlist3 = outfile_boxlist3 if(forced == False) else "{}/{}_BoxList3_en{}{}".format(outfile_dir,outkey, eband[0], outfile_post)
|
||||
do_erbackmap_esass(outfile_evtool,outfile_expmap,boxlist3,detmask,emin_ev[index],emax_ev[index],
|
||||
outfile_backmap3,cheese_mask)
|
||||
|
||||
if(forced==True):
|
||||
mllist="{}_MaxLikSourceList_en{}.forced{}{}".format(os.path.join(outfile_dir,outkey), eband[index], comm, outfile_post)
|
||||
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{}.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))
|
||||
sys.exit()
|
||||
|
||||
add_specific_columns(boxlist3)
|
||||
fitpos_flag="fitpos_flag=no"
|
||||
fitext_flag="fitext_flag=no"
|
||||
nmulsou = "nmulsou=1"
|
||||
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)
|
||||
|
||||
else:
|
||||
mllist="{}_MaxLikSourceList_en{}{}".format(os.path.join(outfile_dir,outkey), eband[index], outfile_post)
|
||||
srcmap="{}_SourceMap_en{}{}".format(os.path.join(outfile_dir,outkey), eband[index], outfile_post)
|
||||
boxlist3 = outfile_boxlist3
|
||||
fitpos_flag="fitpos_flag=yes"
|
||||
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={}".format(mllist),
|
||||
"boxlist=%s" %(boxlist3),
|
||||
"images=\'{}\'".format(outfile_evtool),
|
||||
"expimages=\'{}\'".format(outfile_expmap),
|
||||
"detmasks=\'{}\'".format(detmask),
|
||||
"bkgimages=\'{}\'".format(outfile_backmap3),
|
||||
"emin=\'{}\'".format(emin_ev[index]),
|
||||
"emax=\'{}\'".format(emax_ev[index]),
|
||||
"ecf=\'{}\'".format(ecf[index]),
|
||||
"hrdef=",
|
||||
"likemin=0.",
|
||||
"extlikemin=5.",
|
||||
"compress_flag=N",
|
||||
cutrad,
|
||||
multrad,
|
||||
"extmin=2.0",
|
||||
"extmax=35.0",
|
||||
#"bkgima_flag=Y", looks outdated
|
||||
"expima_flag=Y",
|
||||
"detmask_flag=Y",
|
||||
"shapelet_flag=yes",
|
||||
"photon_flag=yes",
|
||||
"extentmodel=beta",
|
||||
"thres_flag=N",
|
||||
"thres_col=like",
|
||||
"thres_val=30.",
|
||||
nmaxfit,
|
||||
nmulsou,
|
||||
fitpos_flag,
|
||||
fitext_flag,
|
||||
"srcima_flag=yes",
|
||||
"srcimages=\'{}\'".format(srcmap)
|
||||
]
|
||||
|
||||
if(do_ersensmap==True):
|
||||
detlike=10
|
||||
create_sensmap(sensmap="{}_SensitivityMap_dl{}_en{}{}".format(os.path.join(outfile_dir,outkey), detlike,
|
||||
eband[index], outfile_post),
|
||||
areatab="{}_AreaTable_dl{}_en{}{}".format(os.path.join(outfile_dir,outkey),
|
||||
detlike, eband[index], outfile_post),
|
||||
expmap=outfile_expmap, backmap=outfile_backmap3,detlike=detlike,
|
||||
detmask=detmask, emin=emin_ev[index], emax=emax_ev[index],ecf=ecf[index])
|
||||
"""
|
||||
detlike=6
|
||||
create_sensmap(sensmap="{}_SensitivityMap_dl{}_en{}{}".format(os.path.join(outfile_dir,outkey), detlike,
|
||||
eband[index], outfile_post),
|
||||
areatab="{}_AreaTable_dl{}_en{}{}".format(os.path.join(outfile_dir,outkey),
|
||||
detlike, eband[index], outfile_post),
|
||||
expmap=outfile_expmap, backmap=outfile_backmap3,detlike=detlike,
|
||||
detmask=detmask, emin=emin_ev[index], emax=emax_ev[index],ecf=ecf[index])
|
||||
"""
|
||||
|
||||
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)
|
||||
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.
|
||||
if(result == False):
|
||||
correct_srcid_ermldet_forced(mllist)
|
||||
|
||||
if(do_fixcat==True):
|
||||
if not index == 0:
|
||||
print("ERROR: You can fix only reference catalog for en0.")
|
||||
sys.exit()
|
||||
if forced == True:
|
||||
print("ERROR: You can fix only non-forced catalog for en0.")
|
||||
sys.exit()
|
||||
|
||||
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)
|
||||
"""
|
||||
Note that fix_catalog added ID_SRC to each XMM source.
|
||||
Next, we save forced XMM sources (with new ID_SRC!) for later catalog compilation
|
||||
"""
|
||||
with open(mllist.replace(".fits", ".xmm.pickle"), 'wb') as f:
|
||||
pickle.dump(srcs_add, f)
|
||||
|
||||
if(do_fixxmm==True):
|
||||
if not index == 0:
|
||||
print("ERROR: You can fix only reference catalog for en0.")
|
||||
sys.exit()
|
||||
if forced == True:
|
||||
print("ERROR: You can fix only non-forced catalog for en0.")
|
||||
sys.exit()
|
||||
|
||||
fix_xmm_sources(mllist=mllist,refimage=outfile_evtool, xmm_catalog='../data/4XMM-DR12/4XMM_DR12cat_slim_v1.0_UDS.fits.catalog')
|
||||
|
||||
|
||||
if(do_apetool==True):
|
||||
psfmap="{}_PsfMap{}".format(os.path.join(outfile_dir,outkey), outfile_post)
|
||||
#remove_file(psfmap)
|
||||
#cmd=["apetool",
|
||||
# "images=\'{}\'".format(outfile_evtool),
|
||||
# "psfmaps=\'{}\'".format(psfmap),
|
||||
# "psfmapflag=yes",]
|
||||
#runme(cmd, local_run=local_run)
|
||||
|
||||
cmd=["apetool",
|
||||
"mllist={}".format(mllist),
|
||||
"apelistout={}".format(mllist), # give the same file
|
||||
"images=\'{}\'".format(outfile_evtool),
|
||||
"expimages=\'{}\'".format(outfile_expmap),
|
||||
"detmasks=\'{}\'".format(detmask),
|
||||
"bkgimages=\'{}\'".format(outfile_backmap3),
|
||||
"emin=\'{}\'".format(emin_ev[index]),
|
||||
"emax=\'{}\'".format(emax_ev[index]),
|
||||
"srcimages=\'{}\'".format(srcmap),
|
||||
"psfmaps={}".format(psfmap),
|
||||
"psfmapflag=no",
|
||||
"stackflag=no",
|
||||
"apexflag=yes",
|
||||
"apesenseflag=no",
|
||||
"eefextract=0.65",
|
||||
"cutrad=15",
|
||||
"eindex=1",]
|
||||
runme(cmd, local_run=local_run)
|
||||
|
||||
if(forced==True):
|
||||
catprep="{}_SourceCatalog_en{}.forced{}{}".format(os.path.join(outfile_dir,outkey), eband[index], comm, outfile_post)
|
||||
else:
|
||||
catprep="{}_SourceCatalog_en{}{}".format(os.path.join(outfile_dir,outkey), eband[index], outfile_post)
|
||||
|
||||
if(do_catprep==True):
|
||||
cmd=["catprep",
|
||||
"infile={}".format(mllist),
|
||||
"outfile={}".format(catprep),]
|
||||
remove_file(catprep)
|
||||
runme(cmd, local_run=local_run)
|
||||
|
||||
|
||||
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')
|
||||
|
||||
if(do_cross_match==True):
|
||||
crossmatch_shu2019(catprep,dlmin=10,refimage=outfile_evtool,crval=[ra_cen, de_cen],
|
||||
catalog=root_path+"/data/Gaia_unWISE/Gaia_unWISE_UDS.fits.catalog")
|
||||
284
scripts/05_srctool.py
Executable file
284
scripts/05_srctool.py
Executable file
@ -0,0 +1,284 @@
|
||||
#!/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 pickle
|
||||
|
||||
import uds
|
||||
|
||||
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_init = False
|
||||
do_merge = False
|
||||
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 = 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
|
||||
""" чтобы спектры покрывали все энергии работаем в диапазоне 5 """
|
||||
|
||||
vign=True
|
||||
vignetting = 'vign' if (vign==True) else 'novign'
|
||||
|
||||
events=[]
|
||||
expmaps=[]
|
||||
bkgmaps=[]
|
||||
for tmkey in keylist_tm.keys():
|
||||
print("TM{} in work... init events".format(tmkey))
|
||||
for datakey in keylist_tm[tmkey]:
|
||||
print("--> {}".format(datakey))
|
||||
""" Подготавливаем списки событий индивидуальных наблюдений """
|
||||
outfile_evtool,outfile_expmap=init_events(key=datakey,attcorr=True,
|
||||
eband_index=eband[index],
|
||||
infile_dir=infile_dir,
|
||||
outfile_dir=outfile_dir,
|
||||
do_init=do_init,
|
||||
do_obsmode=False,
|
||||
do_center=False,
|
||||
do_evtool=False,
|
||||
do_expmap=False,
|
||||
vign=vign,
|
||||
ra_cen=ra_cen, de_cen=de_cen,
|
||||
emin_kev=emin_kev[index],
|
||||
emax_kev=emax_kev[index])
|
||||
events.append(outfile_evtool)
|
||||
expmaps.append(outfile_expmap)
|
||||
|
||||
|
||||
""" Собираем общий список событий """
|
||||
outfile_evtool="{}_EventList_en{}.fits".format(os.path.join(outfile_dir,outkey),
|
||||
eband[index])
|
||||
|
||||
if(do_merge==True):
|
||||
do_evtool_esass(events=events, outfile=outfile_evtool)
|
||||
|
||||
|
||||
suffix_srctool=".fits"
|
||||
""" Output filename suffix - all output filenames appended with this string.
|
||||
If suffix contains no filename extension (does not contain a "."), then ".fits"
|
||||
is also appended to the filename. """
|
||||
|
||||
catprep="{}_SourceCatalog_en{}{}".format(os.path.join(outfile_dir,outkey), eband[0], outfile_post)
|
||||
""" take source catalog from 0.3-2.3 keV band """
|
||||
|
||||
if not (os.path.isfile(catprep)==True):
|
||||
print("{} not found, run 04_mosaics.py?".format(catprep))
|
||||
sys.exit()
|
||||
|
||||
|
||||
if(do_srctool==True):
|
||||
test_exe('srctool')
|
||||
cmd=['srctool',
|
||||
"insts=\'1 5 6 7\'",
|
||||
"eventfiles={}".format(outfile_evtool),
|
||||
"prefix=\'{}\'".format(os.path.join(srctool_dir,outfile_srctool)),
|
||||
"suffix=\'{}\'".format(suffix_srctool),
|
||||
"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",]
|
||||
print((" ").join(cmd))
|
||||
#os.system((" ").join(cmd))
|
||||
#print((" ").join(cmd))
|
||||
|
||||
if(do_grppha==True):
|
||||
group_spectra("{}/*020_SourceSpec_*.fits".format(srctool_dir))
|
||||
|
||||
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),
|
||||
catprep=catprep, emin=emin_kev, emax=emax_kev, eband=eband, outfile=ecfout, simnum=10000)
|
||||
|
||||
if(do_ecf_print==True):
|
||||
print_ecf(infile=ecfout, emin=emin_kev, emax=emax_kev, eband=eband, skipfrac=10.0)
|
||||
|
||||
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_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',
|
||||
infile_en02cat='../products/tm0_SourceCatalog_en2.forced.fits',
|
||||
infile_en03cat='../products/tm0_SourceCatalog_en3.forced.fits',
|
||||
infile_en06cat='../products/tm0_SourceCatalog_en6.forced.fits',
|
||||
infile_en00sens='../products/tm0_SensitivityMap_dl10_en0.fits',
|
||||
infile_en01sens='../products/tm0_SensitivityMap_dl10_en1.fits',
|
||||
infile_en02sens='../products/tm0_SensitivityMap_dl10_en2.fits',
|
||||
infile_en03sens='../products/tm0_SensitivityMap_dl10_en3.fits',
|
||||
infile_en06sens='../products/tm0_SensitivityMap_dl10_en6.fits',
|
||||
srcs_forced=srcs_forced,
|
||||
)
|
||||
|
||||
|
||||
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,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 """
|
||||
make_xmm_catalog(infile_en00cat='../products/tm0_SourceCatalog_en0.forced-xmm.fits',
|
||||
infile_en01cat='../products/tm0_SourceCatalog_en1.forced-xmm.fits',
|
||||
infile_en02cat='../products/tm0_SourceCatalog_en2.forced-xmm.fits',
|
||||
infile_en03cat='../products/tm0_SourceCatalog_en3.forced-xmm.fits',
|
||||
infile_en06cat='../products/tm0_SourceCatalog_en6.forced-xmm.fits',
|
||||
forced_xmm_sources='../products/tm0_MaxLikSourceList_en0.fixed-xmm.pickle',
|
||||
outfile='../products/tm0_4XMM-DR12.pickle')
|
||||
|
||||
|
||||
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')
|
||||
445
scripts/06_plot.py
Executable file
445
scripts/06_plot.py
Executable file
@ -0,0 +1,445 @@
|
||||
#!/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
|
||||
from scipy.stats import norm
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
import pandas as pd
|
||||
|
||||
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 = 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
|
||||
|
||||
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, 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)
|
||||
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}$)',fontsize=14, fontweight='normal')
|
||||
plt.ylabel('Number',fontsize=14, fontweight='normal')
|
||||
plt.grid(visible=True)
|
||||
plt.xscale('log')
|
||||
plt.yscale('log')
|
||||
plt.savefig(catalog.replace("main.selected.csv", "ml_rate.png"), bbox_inches='tight')
|
||||
plt.close(fig)
|
||||
|
||||
|
||||
data, logbins, mean, median = get_log_distr(infile=catalog, field='ml_flux', minval=1e-15, maxval=2e-12)
|
||||
fig, ax = plt.subplots()
|
||||
for axis in ['top','bottom','left','right']:
|
||||
ax.spines[axis].set_linewidth(1)
|
||||
ax.tick_params(axis="both", width=1, labelsize=14)
|
||||
plt.hist(data, bins=logbins, histtype='step', color='blue', linewidth=1, linestyle='solid')
|
||||
plt.xlabel('Energy flux (erg s$^{-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])
|
||||
|
||||
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)")
|
||||
|
||||
|
||||
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)
|
||||
"""
|
||||
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')
|
||||
44
scripts/README.md
Normal file
44
scripts/README.md
Normal file
@ -0,0 +1,44 @@
|
||||
Подготовка рабочего окружения:
|
||||
```
|
||||
source <MY PATH>/venv/bin/activate.csh
|
||||
source <MY PATH>/eSASS4EDR/bin/esass-init.csh
|
||||
```
|
||||
|
||||
|
||||
### 01_init_events.py
|
||||
|
||||
Создает начальные списки событий и помещает их в ```uds/data/processed```
|
||||
Оригинальные файлы со списками событий задаются в файлах ```uds/data/evtlists/*.txt```
|
||||
|
||||
### 02_merge_events.py
|
||||
|
||||
Создает объедененный список событий и помещает его в ```uds/products```. Этот список событий нужен, в основном для извлечения спектров с помощью ```srctool```.
|
||||
|
||||
Попутно этот скрипт унифицирует оригинальные списки событий для последующей обработки. А именно, корректируются слова OBS_MODE=POINING/SURVEY в зависимости от типа наблюдения и производится центрирование на одни и те же координаты с помощью команды ```radec2xy```.
|
||||
|
||||
Для запуска адаптивного сглаживания ```do_adapt = True``` требуется запустить окружение ```ciao```, так как нужна команда ```dmimgadapt```
|
||||
|
||||
```
|
||||
conda activate ciao-4.15
|
||||
source <MY PATH>/eSASS4EDR/bin/esass-init.csh
|
||||
```
|
||||
|
||||
### 03_init_obs.py
|
||||
|
||||
1) Подготавливает списки событий в разных энергетических диапазонах.
|
||||
2) Запускает ```erbox``` в три этапа, чтобы получить рабочий список источников для ```ermldet```.
|
||||
3) Запускает ```ermldet```
|
||||
4) Делает кросс-корреляцию с каталогом Gaia-unWISE ```do_cross_match=True```, которая создает три файла: ```.cross``` -- все пересечения, и ```.ref``` / ```.src``` -- входные каталоги для последующей команды ```wcs_match```
|
||||
5) Делает матрицу преобразования координат и корректирует списки событий. Для запуска команд```wcs_match/wcs_update``` требуется запустить окружение ```ciao``` (см. выше)
|
||||
|
||||
### 04_mosaics.py
|
||||
|
||||
Создает сборные изображения (мозайки) в разных энергетических диапазонах.
|
||||
|
||||
### 05_scrtool.py
|
||||
|
||||
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.
|
||||
|
||||
Вычисляет ECF для всех диапазонов.
|
||||
|
||||
Делает принудительную фотометрию в выбранных каналах (параметр```forced=True```). Внимание! ermldet из eSASS4EDR не делает ассимитричные ошибки на потоки. Мы запускаем более последнюю версию ermldet (v1.56/2.18 esass_200412 Jul 2 12:04:46 2022). Для этого используется параметр ```local_run=True```, который высвечивает какую команду надо запустить на другой машине и ждет ввода.
|
||||
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))
|
||||
9
uds/setup.py
Normal file
9
uds/setup.py
Normal file
@ -0,0 +1,9 @@
|
||||
from setuptools import setup, find_packages
|
||||
|
||||
setup(name="uds",
|
||||
version="0.1",
|
||||
description='eROSITA UDS field analysis',
|
||||
author='Roman Krivonos',
|
||||
author_email='krivonos@cosmos.ru',
|
||||
url='https://www.srg.cosmos.ru',
|
||||
packages=find_packages())
|
||||
0
uds/uds/__init__.py
Normal file
0
uds/uds/__init__.py
Normal file
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
|
||||
109
uds/uds/config.py
Normal file
109
uds/uds/config.py
Normal file
@ -0,0 +1,109 @@
|
||||
from pathlib import Path
|
||||
|
||||
work_dir = Path('/path/to/some/logical/parent/dir')
|
||||
|
||||
"""
|
||||
Координаты сентрального кадра, к которому будут
|
||||
приводиться изображения всех списков событий
|
||||
"""
|
||||
ra_cen=34.5342131
|
||||
de_cen=-4.7956710
|
||||
|
||||
|
||||
"""
|
||||
Словарь камер со списком наблюдений каждой камеры.
|
||||
Номера камер должны быть отсортированы
|
||||
"""
|
||||
keylist_tm={'1':['tm1_obs_1',],
|
||||
'5':['tm5_obs_1','tm5_obs_2',],
|
||||
'6':['tm6_obs_1','tm6_obs_2_badpix','tm6_obs_3_badpix',
|
||||
'tm6_park_1','tm6_park_2','tm6_park_3','tm6_park_4',
|
||||
'tm6_scan_1','tm6_scan_2','tm6_scan_3','tm6_scan_4'],
|
||||
'7':['tm7_obs_1','tm7_obs_2',]}
|
||||
|
||||
"""
|
||||
Примерные центры изображений каждого наблюдения.
|
||||
Требуется для астрокоррекции. Будет расчитываться матрица сдвигов и поворотов,
|
||||
так вот, повороты будут проводиться вокруг данных координат.
|
||||
"""
|
||||
wcslist={'tm1_obs_1':[34.7279760,-5.0680267],
|
||||
'tm5_obs_1':[34.7351248,-4.4407314],
|
||||
'tm5_obs_2':[34.8748997,-4.4871658],
|
||||
'tm7_obs_1':[35.0015120,-4.7602124],
|
||||
'tm7_obs_2':[34.9810029,-4.5915912],
|
||||
'tm6_obs_1':[34.4227062,-4.7207170],
|
||||
'tm6_obs_2_badpix':[34.7272339,-4.4294153],
|
||||
'tm6_obs_3_badpix':[34.8750291,-4.4708468],
|
||||
'tm6_park_1':[35.0544951,-4.0613619],
|
||||
'tm6_park_2':[35.0558675,-4.0683084],
|
||||
'tm6_park_3':[35.0565263,-4.0583538],
|
||||
'tm6_park_4':[35.0602986,-4.0622220],
|
||||
'tm6_scan_1':[34.5405596,-4.8088748],
|
||||
'tm6_scan_2':[34.5405596,-4.8088748],
|
||||
'tm6_scan_3':[34.5405596,-4.8088748],
|
||||
'tm6_scan_4':[34.5405596,-4.8088748]}
|
||||
|
||||
""" 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'}
|
||||
|
||||
""" 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]
|
||||
# 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
|
||||
*** en2 ecf 1.3903E+12 +/- 3.5036E+10 2.52% N=17
|
||||
*** en3 ecf 2.3322E+12 +/- 5.8717E+10 2.52% N=17
|
||||
*** en4 ecf 5.2022E+11 +/- 1.3110E+10 2.52% N=17
|
||||
*** 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'
|
||||
|
||||
"""
|
||||
Pavel Medvedev:
|
||||
0.3-2.3: 9.135819435325375e-13
|
||||
0.3-0.6: 9.160477830652834e-13
|
||||
0.6-2.3: 9.201664167869427e-13
|
||||
2.3-5.0: 8.721504826794627e-12
|
||||
"""
|
||||
359
uds/uds/sherpa.py
Normal file
359
uds/uds/sherpa.py
Normal file
@ -0,0 +1,359 @@
|
||||
import glob
|
||||
import os
|
||||
import sys
|
||||
import numpy as np
|
||||
from astropy.io import fits
|
||||
import pickle
|
||||
from scipy.stats import sem
|
||||
|
||||
#import matplotlib.pyplot as plt
|
||||
#plt.style.use('ggplot')
|
||||
|
||||
from sherpa.astro.ui import *
|
||||
|
||||
def calc_ecf(path,catprep=None, emin=None, emax=None, eband=None, outfile=None, fitmin=0.2, fitmax=5.0, simnum=100):
|
||||
"""
|
||||
Do uncorrection of SPECRESP for CORRCOMP=CORRPSF*CORRVIGN, like this:
|
||||
SPECRESP=SPECRESP/CORRCOMB, because because ermldet does not correct for PSF and vignetting.
|
||||
"""
|
||||
|
||||
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))
|
||||
|
||||
#fout=filename.replace(".fits", ".uncorr.fits")
|
||||
|
||||
pha=filename.replace("ARF", "SourceSpec")
|
||||
pha=pha.replace(".fits", ".fits.grp")
|
||||
pha_header = fits.getheader(pha,ext=1)
|
||||
object = pha_header['OBJECT']
|
||||
|
||||
""" check a given source (testing...) """
|
||||
#if (int(object) > 10):
|
||||
# continue
|
||||
|
||||
srcid="ML{}".format(object)
|
||||
if not (srcid in mlrate.keys()):
|
||||
print("Skip {}".format(srcid))
|
||||
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)
|
||||
clean() # sherpa
|
||||
set_xsxsect("vern")
|
||||
set_xsabund('wilm')
|
||||
load_pha(pha) # sherpa
|
||||
|
||||
""" load uncorrected ARF """
|
||||
# load_arf(fout) # 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
|
||||
|
||||
ignore_bad() # sherpa
|
||||
### Define the fit range
|
||||
print("Notice 0.3-5.0 keV:")
|
||||
notice(fitmin, fitmax) # 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')
|
||||
|
||||
photon_flx=[]
|
||||
energy_flx=[]
|
||||
skipme=False
|
||||
for ie in range(len(eband)):
|
||||
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))
|
||||
|
||||
if (skipme == True):
|
||||
print("*** Skip zero flux for {}".format(srcid))
|
||||
continue
|
||||
|
||||
print("----> Success: {} pow norm: {:.4E} reduced stat: {:.2f}".format(res_fit.succeeded,res_fit.parvals[0], rstat))
|
||||
|
||||
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 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):
|
||||
|
||||
|
||||
|
||||
with open(infile, 'rb') as f:
|
||||
data = pickle.load(f)
|
||||
|
||||
for ie in range(len(eband)):
|
||||
print()
|
||||
ecf=[]
|
||||
|
||||
for key in data.keys():
|
||||
ar=data[key]
|
||||
ml = ar['ml_rate']
|
||||
dml = ar['ml_rate_err']
|
||||
|
||||
flx = ar['sample_flx'][ie]
|
||||
dflx1 = ar['sample_flx'][ie] - ar['sample_flx_lo'][ie]
|
||||
dflx2 = ar['sample_flx_hi'][ie] - ar['sample_flx'][ie]
|
||||
|
||||
# take maximum error as conservative approach
|
||||
dflx = np.maximum(dflx1,dflx2)
|
||||
|
||||
ecf0 = ml/flx
|
||||
decf0 = abs(flx*dml - ml*dflx) / np.power(flx,2)
|
||||
frac0 = 100 * abs(flx*dml - ml*dflx) / (flx*ml)
|
||||
|
||||
skipme=False
|
||||
if((100*dflx/flx) < skipfrac):
|
||||
skipme=False
|
||||
else:
|
||||
skipme=True
|
||||
|
||||
#if not (len(ar['sample_flx'])>0):
|
||||
# continue
|
||||
print("en{} {} DL={:.2f} FLUX: {:4E} (-{:.4E} +{:.4E} {:.2f}%) ML_RATE: {:.4f} +/- {:.4f} ({:.2f}%) --> {:.4E} +/- {:.4E} {:.2f}% skip={}".format(eband[ie],key,ar['det_like'],
|
||||
flx,dflx1,dflx2,100*dflx/flx,
|
||||
ml,dml,100*dml/ml,
|
||||
ecf0,decf0,frac0,skipme))
|
||||
if(skipme==True):
|
||||
continue
|
||||
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()
|
||||
3506
uds/uds/utils.py
Normal file
3506
uds/uds/utils.py
Normal file
File diff suppressed because it is too large
Load Diff
Loading…
x
Reference in New Issue
Block a user