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galfit.py
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galfit.py
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#!/usr/bin/env python
# encoding: utf-8
"""
galfit.py
Wrapper around GALFIT to fit the 3D-HST thumbnails.
$URL: https://subversion.assembla.com/svn/threedhst_internal/trunk/reduce.py $
$Author: gbrammer $
$Date: 2011-05-22 02:01:43 -0400 (Sun, 22 May 2011) $
"""
__version__ = " $Rev: 5 $"
import sys, os
import shutil
import glob
import numpy as np
import matplotlib.pyplot as plt
USE_PLOT_GUI=False
from matplotlib.figure import Figure
from matplotlib.backends.backend_agg import FigureCanvasAgg
#import pyfits
import astropy.io.fits as pyfits
import threedhst.catIO as catIO
import threedhst
import unicorn
def fit_cosmos():
import unicorn.galfit
import threedhst
sexCat = threedhst.sex.mySexCat('orient1_drz.cat')
mag = np.cast[float](sexCat.MAG_F1392W)
use = mag < 23.5
root='orient1'
#### matched catalog, do all objects that have NMBS matches to some K limit
match = catIO.Readfile('../../../../COSMOS/HTML_v1.0/SED/'+root+'_match.cat')
q = []
for id in match.id_f140w:
mat = np.where(sexCat.id == id)[0][0]
q.append(mat)
q = np.array(q)
use = q[(match.mag_ktot < 23) & (match.rmatch < 1) & (match.logm >= 10.9)]
for id in sexCat.id[use]:
try:
#
status = unicorn.galfit.go_fit(id=id, fix_n=False, fit_sky=False,
tar_root=root,
PSF_IMAGE='star_'+root+'_thumb.fits')
# status = unicorn.galfit.go_fit(id=id, fix_n=False,
# tar_root='orient2',
# PSF_IMAGE='star_orient2_01732_thumb.fits')
except:
pass
def fit_goodsn():
import unicorn.galfit
import threedhst
tar_path = '/research/HST/GRISM/3DHST/GOODS-N/HTML_TAR/'
catalogs = glob.glob('/research/HST/GRISM/3DHST/GOODS-N/HTML_v1.0/*drz.cat')
psfs = glob.glob('star_ib*fits')
matches = glob.glob('/research/HST/GRISM/3DHST/GOODS-N/HTML_v1.0/SED/*match.cat')
for i,catalog in enumerate(catalogs):
cat = threedhst.sex.mySexCat(catalog)
mag = np.cast[float](cat.MAG_F1392W)
match = catIO.Readfile(matches[i])
q = []
for id in match.id_f140w:
mat = np.where(cat.id == id)[0][0]
q.append(mat)
q = np.array(q)
use = q[(match.logm > 10.6) & (match.rmatch < 1)]
root=os.path.basename(catalog).split('_drz')[0]
for id in cat.id[use]:
status = unicorn.galfit.go_fit(id=id, fix_n=False, tar_root=root,
tar_path = tar_path,
PSF_IMAGE=psfs[i])
def fit_uds_marshall():
import unicorn.galfit
import threedhst
tar_path = '/research/HST/GRISM/3DHST/SN-MARSHALL/HTML/images/'
catalogs = glob.glob('/research/HST/GRISM/3DHST/SN-MARSHALL/HTML/*drz.cat')
PSF_IMAGE = 'star_UDS_direct1_00360.thumb.fits'
matches = glob.glob('/research/HST/GRISM/3DHST/SN-MARSHALL/HTML/SED/*match.cat')
for i,catalog in enumerate(catalogs):
cat = threedhst.sex.mySexCat(catalog)
mag = np.cast[float](cat.MAG_F1249W)
use = mag < 24.5
root=os.path.basename(catalog).split('_drz')[0]
match = catIO.Readfile(matches[i])
q = []
for id in match.id_f140w:
mat = np.where(cat.id == id)[0][0]
q.append(mat)
q = np.array(q)
use = q[(match.logm >= 10.9) & (match.rmatch < 1)]
for id in cat.id[use]:
if not os.path.exists('%s_%05d_galfit.png' %(root,id)):
status = unicorn.galfit.go_fit(id=id, fix_n=False,
tar_root=root, fit_sky=False,
tar_path = tar_path, PSF_IMAGE=PSF_IMAGE)
def make_cat(symbol_color='red', masslim=(11,13), CIRCULARIZE=True):
import unicorn.galfit
import threedhst
import numpy as np
sexCat = threedhst.sex.mySexCat('orient1_drz.cat')
sexCat.re = sexCat.id*0.-99
sexCat.n = sexCat.id*0.-99
sexCat.bovera = sexCat.id*0.-99
sexCat.chi2 = sexCat.id*0.+100
for i,id in enumerate(sexCat.id):
#print id
try:
root='orient1_%05d_galfit' %(id)
params = unicorn.galfit.read_log(root+'.log')
x0, y0, mag, re, n, bovera, chi2 = params
sexCat.re[i] = np.float(re)
sexCat.n[i] = np.float(n)
sexCat.bovera[i] = np.float(bovera)
sexCat.chi2[i] = np.float(chi2)
#print re
except:
pass
#
try:
root='orient2_%05d_galfit' %(id)
params = unicorn.galfit.read_log(root+'.log')
x0, y0, mag, re, n, bovera, chi2 = params
sexCat.re[i] = np.float(re)
sexCat.n[i] = np.float(n)
sexCat.bovera[i] = np.float(bovera)
sexCat.chi2[i] = np.float(chi2)
#print re
except:
pass
##### Make plot of sizes vs. z
match = catIO.Readfile('../../../../COSMOS/HTML_v1.0/SED/orient1_match.cat')
match1 = catIO.Readfile('../../../../COSMOS/HTML_v1.0/SED/orient1_match.cat')
q = []
for id in match1.id_f140w:
mat = np.where(sexCat.id == id)[0][0]
q.append(mat)
#
match2 = catIO.Readfile('../../../../COSMOS/HTML_v1.0/SED/orient2_match.cat')
for id in match2.id_f140w:
mat = np.where(sexCat.id == id)[0][0]
q.append(mat)
for col in match.columns:
match[col] = np.append(match1[col],match2[col])
q = np.array(q)
fp = open('orient1_galfit.cat','w')
fp.write('# id_f140w re n bovera chi2 id_nmbs46 z_peak logm star_flag r_match \n')
for i,qi in enumerate(q):
fp.write('%-5d %7.2f %7.2f %7.2f %9.1e %-5d %8.3f %6.2f %1d %5.2f\n' %(sexCat.id[qi], sexCat.re[qi], sexCat.n[qi], sexCat.bovera[qi], sexCat.chi2[qi], match.id_phot[i], match.z_peak[i], match.logm[i], match.star_flag[i], match.rmatch[i]))
fp.close()
zgrid = np.array([0.2, 0.3, 0.4, 0.45, 0.5, 0.55, 0.6, 0.65, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.1, 2.2, 2.3, 2.4, 2.5])
scale = np.array([3.268, 4.421, 5.343, 5.733, 6.082, 6.394, 6.673, 6.922, 7.144, 7.518, 7.812, 8.041, 8.216, 8.346, 8.439, 8.502, 8.539, 8.556, 8.555, 8.540, 8.512, 8.475, 8.430, 8.377, 8.320, 8.257, 8.192])
use = (match.star_flag == 0) & (match.rmatch < 1)
use = (match.logm > masslim[0]) & (match.logm < masslim[1])
use = use & (sexCat.chi2[q] < 2)
sint = np.interp(match.z_peak[use], zgrid, scale)
xvd = np.array([0, 0.6, 1.1, 1.6, 2.0])
yvd = np.array([12.4, 8.0, 5.3, 4.1, 3.0])
if CIRCULARIZE:
sexCat.re *= np.sqrt(1./np.abs(sexCat.bovera))
plt.semilogy(match.z_peak[use], sexCat.re[q][use]*sint*0.06, marker='o', linestyle='None', color=symbol_color, markersize=12, alpha=0.7)
print symbol_color
plt.plot(xvd, yvd, marker='None', linewidth=10, alpha=0.3, color='black')
#### Add GOODS-N
# catalogs = glob.glob('/research/HST/GRISM/3DHST/GOODS-N/HTML_v1.0/*drz.cat')
# tar_path = '/research/HST/GRISM/3DHST/GOODS-N/HTML_TAR/'
# for catalog in catalogs:
# print catalog
# cat = threedhst.sex.mySexCat(catalog)
# mag = np.cast[float](cat.MAG_F1392W)
# use = mag < 23.5
# root=os.path.basename(catalog).split('_drz')[0]
# cat.re = cat.id*0.-99
# cat.n = cat.id*0.-99
# cat.bovera = cat.id*0.-99
# cat.chi2 = cat.id*0.+100
# for i,id in enumerate(cat.id):
# #print id
# try:
# rooti=root+'_%05d_galfit' %(id)
# params = unicorn.galfit.read_log(rooti+'.log')
# x0, y0, mag, re, n, bovera, chi2 = params
# cat.re[i] = np.float(re)
# cat.n[i] = np.float(n)
# cat.bovera[i] = np.float(bovera)
# cat.chi2[i] = np.float(chi2)
# #print re
# except:
# pass
# #
# match = catIO.Readfile('/research/HST/GRISM/3DHST/GOODS-N/HTML_v1.0/SED/'+root+'_match.cat')
# q = []
# for id in match.id_f140w:
# mat = np.where(cat.id == id)[0][0]
# q.append(mat)
# #
# q = np.array(q)
# #
# use = (match.rmatch < 1)
# use = (match.logm >= masslim[0]) & (match.logm <= masslim[1])
# use = use & (cat.chi2[q] < 2)
# sint = np.interp(match.z_peak[use], zgrid, scale)
# #
# if CIRCULARIZE:
# cat.re *= np.sqrt(1./np.abs(cat.bovera))
#
# print match.z_peak[use], cat.re[q][use]*sint*0.06
#
# plt.semilogy(match.z_peak[use], cat.re[q][use]*sint*0.06, marker='o', linestyle='None', color='green', markersize=10, alpha=0.6)
# #### Add UDS
catalogs = glob.glob('/research/HST/GRISM/3DHST/SN-MARSHALL/HTML/*drz.cat')
tar_path = '/research/HST/GRISM/3DHST/SN-MARSHALL/HTML/images/'
for catalog in catalogs[0:1]:
cat = threedhst.sex.mySexCat(catalog)
mag = np.cast[float](cat.MAG_F1249W)
use = mag < 23.5
root=os.path.basename(catalog).split('_drz')[0]
cat.re = cat.id*0.-99
cat.n = cat.id*0.-99
cat.bovera = cat.id*0.-99
cat.chi2 = cat.id*0.+100
for i,id in enumerate(cat.id):
#print id
try:
rooti=root+'_%05d_galfit' %(id)
params = unicorn.galfit.read_log(rooti+'.log')
x0, y0, mag, re, n, bovera, chi2 = params
cat.re[i] = np.float(re)
cat.n[i] = np.float(n)
cat.bovera[i] = np.float(bovera)
cat.chi2[i] = np.float(chi2)
#print re
except:
pass
#
match = catIO.Readfile('/research/HST/GRISM/3DHST/SN-MARSHALL/HTML/SED/'+root+'_match.cat')
q = []
for id in match.id_f140w:
mat = np.where(cat.id == id)[0][0]
q.append(mat)
#
q = np.array(q)
#
use = (match.star_flag == 0) & (match.rmatch < 1)
use = (match.logm >= masslim[0]) & (match.logm <= masslim[1])
use = use & (cat.chi2[q] < 2)
sint = np.interp(match.z_peak[use], zgrid, scale)
print match.z_peak[use]
if CIRCULARIZE:
cat.re *= np.sqrt(1./np.abs(cat.bovera))
#
plt.plot(match.z_peak[use], cat.re[q][use]*sint*0.06, marker='o', linestyle='None', color='orange', markersize=10, alpha=0.6)
plt.ylim(0.5,30)
#plt.ylim(-5,25)
plt.xlim(0,3.5)
plt.xlabel(r'$z_\mathrm{phot}$')
plt.ylabel(r'$r_e$ [kpc]')
plt.text(2.0, 13, r'F140W, $%4.1f\ <\ \log\ M/M_\odot\ <\ %4.1f$' %(masslim[0], masslim[1]))
plt.savefig('3dhst_cosmos_sizes.png')
def z2_galaxies(zrange=(1.6,2.4)):
os.chdir('/research/HST/GRISM/3DHST/ANALYSIS/GALFIT/TEST/COSMOS/Z2_COSMOS')
root_path = '/research/HST/GRISM/3DHST/COSMOS/HTML_v1.0/'
root = 'orient1'
co = catIO.Readfile('../orient1_galfit.cat')
co.re *= np.sqrt(1./co.bovera)
#### Select z~2
use = (co.z_peak >= zrange[0]) & (co.z_peak <= zrange[1]) & (co.logm > 10.9) & (co.r_match < 1) & (co.re > 0)
idx = np.arange(len(use))
use = idx[use]
use = use[np.argsort(co.re[use])]
#### Angular scale
zgrid = np.array([0.2, 0.3, 0.4, 0.45, 0.5, 0.55, 0.6, 0.65, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.1, 2.2, 2.3, 2.4, 2.5])
scale = np.array([3.268, 4.421, 5.343, 5.733, 6.082, 6.394, 6.673, 6.922, 7.144, 7.518, 7.812, 8.041, 8.216, 8.346, 8.439, 8.502, 8.539, 8.556, 8.555, 8.540, 8.512, 8.475, 8.430, 8.377, 8.320, 8.257, 8.192])
sint = np.interp(co.z_peak, zgrid, scale)
co.re_kpc = co.re*0.06*sint
fp = open('z2.html','w')
fp.write("""
<html>
<head>
<link rel="stylesheet" href="http://localhost/~gbrammer/COSMOS/scripts/style.css" type="text/css" id="" media="print, projection, screen" />
<script type="text/javascript" src="http://localhost/~gbrammer/COSMOS/scripts/jquery-1.4.2.min.js"></script>
<script type="text/javascript" src="http://localhost/~gbrammer/COSMOS/scripts/jquery.tablesorter.min.js"></script>
<script type="text/javascript" id="js">
// Add ability to sort the table
$(document).ready(function() {
$.tablesorter.defaults.sortList = [[4,4]];
$("table").tablesorter({
// pass the headers argument and assing a object
headers: {
// assign the secound column (we start counting zero)
4: {
sorter: false
},
5: {
sorter: false
},
}
});
});
</script>
</head>
<body>
<table id="myTable" cellspacing="1" class="tablesorter">
<thead>
<th> Grism id </th>
<th> z </th>
<th> logM </th>
<th> r_e </th>
<th> Thumb </th>
<th> SED </th>
</thead>
<tbody>
""")
old = 0
for i in use:
if co.id_f140w[i] == old:
root='orient2'
else:
root='orient1'
old=co.id_f140w[i]
file="%s_%05d" %(root, co.id_f140w[i])
if not os.path.exists('%s/SED/%s_SED.png' %(root_path, file)):
root='orient2'
file="%s_%05d" %(root, co.id_f140w[i])
fp.write("""
<tr>
<td> %s </td>
<td> %5.2f </td>
<td> %5.2f </td>
<td> %5.2f </td>
<td> <img src=../%s_galfit.png height=180px> </td>
<td> <img src=%s/SED/%s_SED.png height=180px> </td>
</tr>
""" %(file, co.z_peak[i], co.logm[i], co.re_kpc[i],
file,
root_path, file))
fp.write("</tbody></table></body></html>")
fp.close()
def get_thumb(id=None, root='orient1',
path='/research/HST/GRISM/3DHST/COSMOS/HTML_TAR/v1.0/', tarfile=True):
thumb_file = root+'_%05d_thumb.fits' %(id)
try:
os.remove(thumb_file)
except:
pass
if tarfile:
status = os.system('tar xzvf '+path+'/'+root+'_thumbs.tar.gz %s.gz' %(thumb_file))
if status != 0:
return False
else:
shutil.copy(path+'/'+thumb_file+'.gz','.')
return thumb_file
#os.system('gunzip %s.gz' %(thumb_file))
def sync():
import os
print 'Syncing GALFIT files...'
os.system('rsync -az /3DHST/Spectra/Work/ANALYSIS/GALFIT/ /Users/gbrammer/Sites_GLOBAL/P/GRISM_v1.6/GALFIT/')
print unicorn.noNewLine+'Syncing GALFIT files...Done.'
def make_full_catalog(output='full_galfit.cat'):
"""
Find all of the log files in the GALFIT directory and make a single
catalog with the galfit parameters.
"""
import glob
import unicorn.galfit
import time
os.chdir('/3DHST/Spectra/Work/ANALYSIS/GALFIT')
files=glob.glob('*G141*log')
if files == []:
### For some reason, glob doesn't appear to work when too many files present
os.system('ls |grep G141 |grep log > files.list')
files = np.loadtxt('files.list', dtype=np.str)
lines = ['# id PSF_FIT mag mag_err r_e r_e_err n n_err ba ba_err chi2\n# '+time.ctime()+'\n']
for file in files:
object = file.split('_galfit')[0]
print unicorn.noNewLine+object
try:
log = unicorn.galfit.GalfitLogfile(file)
chi2 = log.chi2
#
if 'psf' in log.components:
is_psf = 1
mag = log.list[0]['mag']
re = (-1,-1)
n = (-1,-1)
ba = (-1, -1)
else:
is_psf = 0
mag = log.list[0]['mag']
re = log.list[0]['re']
n = log.list[0]['n']
ba = log.list[0]['ba']
except:
is_psf = -1
mag = (-1,-1)
re = (-1,-1)
n = (-1,-1)
ba = (-1, -1)
chi2 = -1
#
lines.append("%s %d %7.2f %7.2f %7.2f %7.2f %5.1f %5.1f %5.2f %5.2f %6.2e\n" %(object, is_psf, mag[0], mag[1], re[0], re[1], n[0], n[1], ba[0], ba[1], chi2))
fp = open(output,'w')
fp.writelines(lines)
fp.close()
status = os.system('cp '+output+' /Library/WebServer/Documents/P/GRISM_v1.6/ANALYSIS')
status = os.system('gzip /Library/WebServer/Documents/P/GRISM_v1.6/ANALYSIS/'+output)
def get_galfit_psf_image(object='COSMOS-15-G141_00388'):
"""
Find the right PSF for each pointing/field
"""
pointing = object.split('-G141')[0]
if os.path.exists('/3DHST/Spectra/Work/ANALYSIS/GALFIT/'+pointing+'_PSF.fits'):
return pointing+'_PSF.fits'
else:
return 'star_PSF.fits'
def fit_all_fields():
unicorn.galfit.fits_for_samples(field='AEGIS')
unicorn.galfit.fits_for_samples(field='COSMOS')
unicorn.galfit.fits_for_samples(field='GOODS-S')
unicorn.galfit.fits_for_samples(field='GOODS-N')
unicorn.galfit.fits_for_samples(field='AEGIS')
unicorn.galfit.fits_for_samples(field='PRIMO')
unicorn.galfit.fits_for_samples(field='GEORGE')
unicorn.galfit.fits_for_samples(field='MARSHALL')
def fits_for_samples(field=''):
"""
Run galfit on every object in that has the EAZY redshift fit completed. The
outputs of the redshift fits are in /Users/gbrammer/Sites_GLOBAL/P/GRISM/EAZY/.
"""
import glob
import unicorn.galfit
os.chdir('/3DHST/Spectra/Work/ANALYSIS/GALFIT')
files = glob.glob('/Users/gbrammer/Sites_GLOBAL/P/GRISM_v1.6/EAZY/'+field+'*eazy.png')
for file in files:
object = os.path.basename(file.split('_eazy')[0])
if not os.path.exists(object+'_galfit.png'):
PSF = unicorn.galfit.get_galfit_psf_image(object=object)
try:
unicorn.galfit.fit_3dhst_object(object=object, fit_sky=True, open=False, PSF_IMAGE=PSF)
except:
pass
unicorn.galfit.sync()
def fit_3dhst_object(object='COSMOS-15-G141_00388', fit_sky=True, open=False, PSF_IMAGE='star_PSF.fits'):
import unicorn.analysis
import unicorn.galfit
import os
PATH = unicorn.analysis.get_grism_path(root=object.split('G141')[0])
thumb_path = PATH+'/HTML/images/%s_thumb.fits.gz' %(object)
print thumb_path
if os.path.exists(thumb_path):
#### First try, fit sersic + sky
result = unicorn.galfit.go_fit(thumb_file=thumb_path, fix_n=False, fit_sky=fit_sky, PSF_IMAGE = PSF_IMAGE)
if result:
log = unicorn.galfit.GalfitLogfile(object+'_galfit.log')
chi_s = log.chi2
r_e_fit = log.list[0].re.value
n_fit = log.list[0].n.value
else:
chi_s = 1.e5
r_e_fit = 0.
n_fit = 100
# #### Fit is high-n, high-re, try adding a disk
# if (r_e_fit*0.06 > 4) & (n_fit > 5):
# result = unicorn.galfit.go_fit(thumb_file=thumb_path, fix_n=False, add_disk=True)
# if result:
# log = unicorn.galfit.GalfitLogfile(object+'_galfit.log')
# chi_s = log.chi2
# else:
# chi_s = 1.e5
#### If died or high chi2, fit PSF + sky
if (result is False) | (chi_s > 50): # | (r_e_fit == 0.01):
result = unicorn.galfit.go_fit(thumb_file=thumb_path, psf_only=True, fit_sky=fit_sky, PSF_IMAGE=PSF_IMAGE)
#### If died again, try turning off sky fit
if not result:
result = unicorn.galfit.go_fit(thumb_file=thumb_path, psf_only=True, fit_sky=False, PSF_IMAGE=PSF_IMAGE)
if result:
log = unicorn.galfit.GalfitLogfile(object+'_galfit.log')
chi_p = log.chi2
else:
chi_p = chi_s*10
if chi_p > chi_s:
### Revert to sersic fit
result = unicorn.galfit.go_fit(thumb_file=thumb_path, fix_n=False, fit_sky=fit_sky)
def go_fit(thumb_file=None, mask=True, add_disk=False, fix_n=4,
PSF_IMAGE='star_PSF.fits',
fit_sky=True,
psf_only=False,
extension='_galfit'):
import unicorn.galfit
try:
os.remove('galfit.01')
except:
pass
root = os.path.basename(thumb_file).split('_thumb')[0]
imgal = pyfits.open(thumb_file)
#### Direct image exposure time (not right in full orient1 image)
TEXP = 808
#### Convert to ADU
imgal[0].header.update('EXPTIME',TEXP)
imgal[0].header.update('GAIN',1.0)
imgal[0].data *= TEXP
imgal.writeto('gal.fits', clobber=True)
if mask:
unicorn.galfit.make_segmap_mask(root)
#### Star PSF
star = pyfits.open(PSF_IMAGE)
star[0].header.update('EXPTIME',TEXP)
star[0].data *= TEXP
star.writeto('psf.fits', clobber=True)
unicorn.galfit.make_galfit_param(imgal, mask=mask, add_disk=add_disk, fix_n=fix_n, psf_only=psf_only, fit_sky=fit_sky)
os.system('galfit galfit.feedme')
try:
shutil.move('fit.log',root+extension+'.log')
shutil.move('imgblock.fits', root+extension+'.fits')
except:
return False
os.system('ls galfit.[0-9]*')
#logs = glob.glob('galfit.[0-9]*')
#print logs
#print logs[-1]
shutil.move('galfit.01', root+extension+'.param')
#os.system('mv galfit.01 '+root+'.param')
unicorn.galfit.make_plot(root+extension)
#os.system('ls galfit.[0-9]*')
# if open:
# os.system('open '+root+extension+'.png')
return True
def make_segmap_mask(root, extension='_galfit'):
import threedhst
se = threedhst.sex.SExtractor()
## Set the output parameters required for aXe
## (stored in [threedhst source]/data/aXe.param)
se.aXeParams()
## XXX add test for user-defined .conv file
se.copyConvFile()
se.overwrite = True
se.options['CATALOG_NAME'] = root+extension+'.cat'
se.options['CHECKIMAGE_NAME'] = root+extension+'_seg.fits'
se.options['CHECKIMAGE_TYPE'] = 'SEGMENTATION'
se.options['WEIGHT_TYPE'] = 'NONE'
se.options['FILTER'] = 'Y'
se.options['DETECT_THRESH'] = '1.5'
se.options['ANALYSIS_THRESH'] = '1.'
se.options['MAG_ZEROPOINT'] = '26.46'
status = se.sextractImage('gal.fits')
im = pyfits.open(root+extension+'_seg.fits')
NY, NX = im[0].data.shape
self_id = im[0].data[NY/2., NX/2]
other = (im[0].data > 0) & (im[0].data != self_id)
im[0].data *= 0
im[0].data[other] = 1
im.writeto('mask.fits', clobber=True)
th = pyfits.open('gal.fits')
seg = pyfits.open(root+extension+'_seg.fits')
mask = seg[0].data == 0
### Subtract background
th[0].data -= np.median(th[0].data[mask])
th.writeto('gal.fits', clobber=True)
### Make rms image
rms = np.std(th[0].data[mask])
#th[0].data = th[0].data*0.+rms #*np.random.randn(NY, NX)
GAIN = 2.5
th[0].data = np.sqrt(np.abs(th[0].data)*GAIN/np.sqrt(4.)+rms**2)
th.writeto('rms.fits', clobber=True)
def make_galfit_param(img, mask=False, fit_sky=True, add_disk=False, fix_n=4,
psf_only=False):
NY, NX = img[0].data.shape
if mask:
mask_file = 'mask.fits'
else:
mask_file = 'none'
if fit_sky:
fit_sky = 1
else:
fit_sky = 0
if fix_n is False:
nval = 4.
fix_n = 1
else:
nval = fix_n
fix_n = 0
header = """ ================================================================
# IMAGE and GALFIT CONTROL PARAMETERS
A) gal.fits # Input data image (FITS file)
B) imgblock.fits # Output data image block
C) none # Sigma image name (made from data if blank or "none")
D) psf.fits # # Input PSF image and (optional) diffusion kernel
E) 1 # PSF fine sampling factor relative to data
F) %s # Bad pixel mask (FITS image or ASCII coord list)
G) none # File with parameter constraints (ASCII file)
H) 1 %d 1 %d # Image region to fit (xmin xmax ymin ymax)
I) %d %d # Size of the convolution box (x y)
J) 26.46 # Magnitude photometric zeropoint
K) 0.06 0.06 # Plate scale (dx dy) [arcsec per pixel]
O) regular # Display type (regular, curses, both)
P) 0 # Choose: 0=optimize, 1=model, 2=imgblock, 3=subcomps
""" %(mask_file, NX, NY, int(NX*3./4), int(NY*3/4))
#### Sky
sky_model = """
# Sky
0) sky # object type
1) 0.0 %d # sky background at center of fitting region [ADUs]
2) 0.0000 0 # dsky/dx (sky gradient in x)
3) 0.0000 0 # dsky/dy (sky gradient in y)
Z) 0 # output option (0 = resid., 1 = Don't subtract)
""" %(fit_sky)
#### Sersic, fix or free n
sersic_model = """
# Object number: 1 (bulge)
0) sersic # object type
1) %f %f 1 1 # position x, y
3) 21.31 1 # Integrated magnitude
4) 4.0 1 # R_e (half-light radius) [pix]
5) %f %d # Sersic index n (de Vaucouleurs n=4)
6) 0.0000 0 # -----
7) 0.0000 0 # -----
8) 0.0000 0 # -----
9) 1.0 1 # axis ratio (b/a)
10) 45.3690 1 # position angle (PA) [deg: Up=0, Left=90]
Z) 0 # output option (0 = resid., 1 = Don't subtract)
""" %(NX/2.+0.5, NY/2.+0.5, nval, fix_n)
#### Disk component, n=1 fixed
disk_model = """
0) sersic # object type
1) %f %f 1 1 # position x, y
3) 23.31 1 # Integrated magnitude
4) 4.0 1 # R_e (half-light radius) [pix]
5) 1.0 0 # Sersic index n (de Vaucouleurs n=4)
6) 0.0000 0 # -----
7) 0.0000 0 # -----
8) 0.0000 0 # -----
9) 0.2570 1 # axis ratio (b/a)
10) 45.3690 1 # position angle (PA) [deg: Up=0, Left=90]
Z) 0 # output option (0 = resid., 1 = Don't subtract)
""" %(NX/2.+0.5, NY/2.+0.5)
#### PSF component
psf_model = """
0) psf # object type
1) %f %f 1 1 # position x, y
3) 23.31 1 # Integrated magnitude
4) 4.0 1 # R_e (half-light radius) [pix]
5) 1.0 0 # Sersic index n (de Vaucouleurs n=4)
6) 0.0000 0 # -----
7) 0.0000 0 # -----
8) 0.0000 0 # -----
9) 0.2570 0 # axis ratio (b/a)
10) 45.3690 0 # position angle (PA) [deg: Up=0, Left=90]
Z) 0 # output option (0 = resid., 1 = Don't subtract)
""" %(NX/2.+0.5, NY/2.+0.5)
#### Make the parameter file
fp = open('galfit.feedme','w')
fp.write(header)
if psf_only:
fp.write(psf_model)
else:
fp.write(sersic_model)
if add_disk:
fp.write(disk_model)
fp.write(sky_model)
fp.close()
def axis_ticks(im, ax):
## Axis ticks in units of arcsec
ax.set_xticklabels([])
ax.set_yticklabels([])
size = im[0].header.get('NAXIS1')
pixel_scale = 0.06
asec_pix = 1./pixel_scale
nasec = int(size/asec_pix/2)
ax.set_yticklabels([])
xtick = ax.set_xticks(np.arange(-1*nasec,nasec+1,1)*asec_pix+size/2)
ax.set_xticklabels([])
ytick = ax.set_yticks(np.arange(-1*nasec,nasec+1,1)*asec_pix+size/2)
def make_plot(root):
import matplotlib.pyplot as plt
import unicorn.galfit
plt.rcParams['image.cmap'] = 'gray'
im = pyfits.open(root+'.fits')
seg = pyfits.open(root+'_seg.fits')
if USE_PLOT_GUI:
fig = plt.figure(figsize=[6,2.3],dpi=100)
else:
fig = Figure(figsize=[6,2.3], dpi=100)
fig.subplots_adjust(wspace=0.0,hspace=0.0,left=0.02,
bottom=0.02,right=0.98,top=0.87)
#
im_max = im[1].data.max()
im[1].data = 0-im[1].data
im[2].data = 0-im[2].data
im[3].data = 0-im[3].data
#im_max *= -1
scl = 0.8
ax = fig.add_subplot(131)
ax.imshow(im[1].data, vmin=-1*im_max*scl, vmax=0.1*im_max*scl, interpolation='nearest')
axis_ticks(im, ax)
ax = fig.add_subplot(132)
ax.imshow(im[2].data, vmin=-1*im_max*scl, vmax=0.1*im_max*scl, interpolation='nearest')
axis_ticks(im, ax)
scl = scl*0.2
ax = fig.add_subplot(133)
ax.imshow(im[3].data, vmin=-1*im_max*scl, vmax=0.1*im_max*scl, interpolation='nearest')
axis_ticks(im, ax)
#### Segmentation mask
# ax = fig.add_subplot(133)
# #obj = seg[0].data > 0
# #seg[0].data[obj] = -1
# mask = 0-seg[0].data*1./seg[0].data.max()
# plt.imshow(mask, vmin=-1, vmax=0, interpolation='nearest')
id = root.split('_')[1]
id = root.replace('-G141','').replace('_galfit','')
x0, y0, mag, re, n, bovera, chi2 = unicorn.galfit.read_log(root+'.log')
re = '%5.2f' %(np.float(re.replace('*',''))*0.06)
label = '#'+id+r' $r_e$='+re+r'$^{\prime\prime}$ $n$='+n+r' $b/a$='+bovera+r' $\chi^2_\nu$='+chi2
#### Smarter label
log = unicorn.galfit.GalfitLogfile(root+'.log')
label = id +r' $\log\ \chi^2_\nu $=%.2f' %(np.log10(log.chi2))
NCOMP = 0
ax.text(-2,1.08, label, horizontalalignment='left',
verticalalignment='center',transform = ax.transAxes)
y0 = 1.08
for comp in log.list:
label = ''
if comp.type == 'sersic':
label = r'$r_e=%5.2f^{\prime\prime}$ $n$=%4.2f $b/a$=%4.2f' %(comp.re.value*0.06, comp.n.value, comp.ba.value)
NCOMP += 1
if comp.type == 'psf':
label = 'PSF '
NCOMP += 1
if NCOMP > 1:
y0-=0.1
if label:
ax.text(1,y0, label, horizontalalignment='right',
verticalalignment='center',transform = ax.transAxes)
if USE_PLOT_GUI:
fig.savefig(root+'.png',dpi=100,transparent=False)
plt.close()
else:
canvas = FigureCanvasAgg(fig)
canvas.print_figure(root+'.png', dpi=100, transparent=False)
def process_parameters(parline, errline):
for char in ',:()':
parline = parline.replace(char,'')
errline = errline.replace(char,'')
parline = parline.split()
errline = errline.split()
return parline, errline
class GalfitParameter():
def __init__(self, value, error):
self.fixed=False
self.warning=False
if isinstance(value,'string'.__class__):
if value.find('*') >= 0:
self.warning=True
value = value.replace('*','')
error = error.replace('*','')
#print value
try:
self.value = float(value)
self.error = float(error)
#print self.value, self.error
except:
self.value = np.nan
self.error = np.nan
class GalfitComponent():
def __getitem__(self, param):
if param not in self.params:
print 'Parameter, %s, not found for component "%s"\n"' %(param, self.type)
return np.nan
stri = 'val = self.'+param+'.value'
exec(stri)
stri = 'err = self.'+param+'.error'
exec(stri)
return val, err
def __init__(self, parline, errline):
for char in ',:()[]':
parline = parline.replace(char,'')
errline = errline.replace(char,'')
parline = parline.split()
errline = errline.split()
self.type = parline[0]
if self.type == 'sersic':
self.x0 = GalfitParameter(parline[1], errline[0])
self.y0 = GalfitParameter(parline[2], errline[1])
self.mag = GalfitParameter(parline[3], errline[2])
self.re = GalfitParameter(parline[4], errline[3])
self.n = GalfitParameter(parline[5], errline[4])
self.ba = GalfitParameter(parline[6], errline[5])
self.PA = GalfitParameter(parline[7], errline[6])
self.params = ['x0','y0','mag','re','n','ba','PA']
if self.type == 'psf':
self.x0 = GalfitParameter(parline[1], errline[0])
self.y0 = GalfitParameter(parline[2], errline[1])
self.mag = GalfitParameter(parline[3], errline[2])
self.params = ['x0','y0','mag']
if self.type == 'sky':
self.sky = GalfitParameter(parline[3], errline[0])
self.dx = GalfitParameter(parline[4], errline[1])
self.dy = GalfitParameter(parline[5], errline[2])
self.params = ['sky','dx','dy']
#### Info string
info = 'Type: %s\n' %self.type
for param in self.params:
info+='%6s' %param + '=%g (%g)\n' %(self.__getitem__(param))
self.info = info
class GalfitLogfile():
def __init__(self, logfile):
fp = open(logfile)
loglines = fp.readlines()
fp.close()
components = []
for i,line in enumerate(loglines):
if line.strip().startswith('sersic'):
components.append(GalfitComponent(loglines[i], loglines[i+1]))
if line.strip().startswith('psf'):
components.append(GalfitComponent(loglines[i], loglines[i+1]))
if line.strip().startswith('sky'):
components.append(GalfitComponent(loglines[i], loglines[i+1]))
if line.strip().startswith('Chi^2/nu'):
chi2 = np.float(line.split()[2])
self.chi2 = chi2
self.list = components
self.NCOMP = len(components)
self.components = []
for comp in components:
self.components.append(comp.type)
def __getitem__(self, idx):
if isinstance(idx,'string'.__class__):
for i,comp in enumerate(self.components):
if idx == comp: