def main():
get_photometry(sys.argv[1], sys.argv[2])
with open('NGC4621_i.cat', 'r') as catalog:
tmp = filter(lambda line: phot_utils.no_head(line), catalog)
tmp2 = map(lambda line: Sources.SCAMSource(line), tmp)
ra = map(lambda line: line.ra, tmp2)
dec = map(lambda line: line.dec, tmp2)
i_sources = Quadtree.ScamEquatorialQuadtree(min(ra), min(dec),
max(ra), max(dec))
with open('NGC4621_i.cat', 'r') as catalog:
tmp = filter(lambda line: phot_utils.no_head(line), catalog)
map(lambda line: i_sources.insert(Sources.SCAMSource(line)), tmp)
makeRegionFile.makeRegionFile('NGC4621_i.cat', 'NGC4621_i.reg', 10, 'blue')
with open('NGC4621_g.cat', 'r') as catalog:
tmp = filter(lambda line: phot_utils.no_head(line), catalog)
tmp2 = map(lambda line: Sources.SCAMSource(line), tmp)
ra = map(lambda line: line.ra, tmp2)
dec = map(lambda line: line.dec, tmp2)
g_sources = Quadtree.ScamEquatorialQuadtree(min(ra), min(dec),
max(ra), max(dec))
with open('NGC4621_g.cat', 'r') as catalog:
tmp = filter(lambda line: phot_utils.no_head(line), catalog)
map(lambda line: g_sources.insert(Sources.SCAMSource(line)), tmp)
makeRegionFile.makeRegionFile('NGC4621_g.cat', 'NGC4621_g.reg', 10, 'blue')
# Aaron gave me the coordinates
m59_ucd3_i = i_sources.match(190.54601, 11.64478)
m59_ucd3_g = g_sources.match(190.54601, 11.64478)
print '\n'
print "M58-UCD3's Location in catalog: ", m59_ucd3_i.name
print "I Mag and G Mag: ", m59_ucd3_i.mag_auto, m59_ucd3_g.mag_auto
print 'M59-UCD3 g-i: ', m59_ucd3_g.mag_auto - m59_ucd3_i.mag_auto
print 'M59-UCD3 FWHM: ', m59_ucd3_g.fwhm*0.2
print "Coordinates from i-band catalog - "
print phot_utils.convertRA(m59_ucd3_i.ra), phot_utils.convertDEC(m59_ucd3_i.dec)
print "Coordinates from g-band catalog - "
print phot_utils.convertRA(m59_ucd3_g.ra), phot_utils.convertDEC(m59_ucd3_g.dec)
print '\n'
print '\n'
m59cO_i = i_sources.match(190.48056, 11.66771)
m59cO_g = g_sources.match(190.48056, 11.66771)
print "M59cO's Location in catalog: ", m59cO_i.name
print "I Mag and G Mag: ", m59cO_i.mag_auto, m59cO_g.mag_auto
print 'M59cO g-i: ', m59cO_g.mag_auto - m59cO_i.mag_auto
print "Coordinates from i-band catalog - "
print phot_utils.convertRA(m59cO_i.ra), phot_utils.convertDEC(m59cO_i.dec)
print "Coordinates from g-band catalog - "
print phot_utils.convertRA(m59cO_g.ra), phot_utils.convertDEC(m59cO_g.dec)
print '\n'
def correct_mags(galaxy, catalog, band):
print "band: ", band
zp = calcZeropoint.calcZP(galaxy, catalog, band)
if verbose:
print "Zeropoint for " + band + "-band", zp
with open(catalog, 'r') as f:
tmp = filter(lambda line: phot_utils.no_head(line), f)
sources = map(lambda line: Sources.SCAMSource(line), tmp)
for source in sources:
source.mag_aper = round(source.mag_aper + zp, 3)
source.mag_auto = round(source.mag_auto + zp, 3)
source.mag_best = round(source.mag_best + zp, 3)
new_catalog = 'zpcorrected_' + catalog
with open(new_catalog, 'w') as output:
output.write(''.join(
map(
lambda source: '%5s' % source.name + '%15s' % source.flux_iso +
'%15s' % source.fluxerr_iso + '%15s' % source.flux_aper +
'%15s' % source.fluxerr_aper + '%15s' % source.ximg + '%15s' %
source.yimg + '%15s' % source.ra + '%15s' % source.dec + '%15s'
% source.mag_auto + '%15s' % source.mag_auto_err + '%15s' %
source.mag_best + '%15s' % source.mag_best_err + '%15s' %
source.mag_aper + '%15s' % source.mag_aper_err + '%15s' %
source.a_world + '%15s' % source.a_world_err + '%15s' % source.
b_world + '%15s' % source.b_world_err + '%15s' % source.
theta_err + '%15s' % source.theta + '%15s' % source.isoarea +
'%15s' % source.mu + '%15s' % source.flux_radius + '%15s' %
source.flags + '%15s' % source.fwhm + '%15s' % source.elogation
+ '%15s' % source.vignet + '\n', sources)))
return new_catalog
def fromFile(filename, outname, pixsize, color):
with open(filename, "r") as catalog:
sources = [Sources.SCAMSource(line) for line in catalog if phot_utils.no_head(line)]
with open(outname, "w") as out:
for source in sources:
out.write("physical;circle(" + str(source.ximg) + "," +
str(source.yimg) + "," + str(pixsize) + ") #color=" + str(color) + "\n")
def correct_mags(galaxy, catalog, band):
print "band: ", band
zp = calcZeropoint.calcZP(galaxy, catalog, band)
if verbose:
print "Zeropoint for " + band + "-band", zp
with open(catalog, 'r') as f:
tmp = filter(lambda line: phot_utils.no_head(line), f)
sources = map(lambda line: Sources.SCAMSource(line), tmp)
for source in sources:
source.mag_aper = round(source.mag_aper + zp, 3)
source.mag_auto = round(source.mag_auto + zp, 3)
source.mag_best = round(source.mag_best + zp, 3)
new_catalog = 'zpcorrected_' + catalog
with open(new_catalog, 'w') as output:
output.write(''.join(map(lambda source: '%5s' % source.name + '%15s' % source.flux_iso +
'%15s' % source.fluxerr_iso + '%15s' % source.flux_aper +
'%15s' % source.fluxerr_aper + '%15s' % source.ximg + '%15s' % source.yimg +
'%15s' % source.ra + '%15s' % source.dec + '%15s' % source.mag_auto +
'%15s' % source.mag_auto_err + '%15s' % source.mag_best +
'%15s' % source.mag_best_err + '%15s' % source.mag_aper +
'%15s' % source.mag_aper_err + '%15s' % source.a_world +
'%15s' % source.a_world_err + '%15s' % source.b_world +
'%15s' % source.b_world_err + '%15s' % source.theta_err +
'%15s' % source.theta + '%15s' % source.isoarea + '%15s' % source.mu +
'%15s' % source.flux_radius + '%15s' % source.flags + '%15s' % source.fwhm +
'%15s' % source.elogation + '%15s' % source.vignet + '\n', sources)))
return new_catalog
def calcZP(galaxy, scam, band):
"""
To calculate the zeropoint of the Subaru image match the Subaru catalog
and the table returned from Vizier.
"""
sdss = getSDSS(galaxy)
column = str(band + 'mag')
print "Column: ", column
# Get only the brightest sources of both SDSS and Subaru.
mag = map(lambda source: source[column], sdss)
max_mag = np.mean(mag) + 0.25*np.mean(np.std(mag))
sdss = filter(lambda s: phot_utils.mag_cut(s[column], 18, max_mag), sdss)
with open(scam, 'r') as f:
catalog = [S.SCAMSource(line) for line in f if phot_utils.no_head(line)]
mag = map(lambda s: s.mag_best, catalog)
max_mag = np.mean(mag) + 0.25*np.mean(np.std(mag))
sources = filter(lambda s: phot_utils.mag_cut(s.mag_best, 18, max_mag), catalog)
ra = [source.ra for source in catalog]
dec = [source.dec for source in catalog]
scam_sources = Q.ScamEquatorialQuadtree(min(ra), min(dec),
max(ra), max(dec))
map(lambda sources: scam_sources.insert(sources), sources)
matches = associate(sdss, scam_sources)
m_scam_sources = map(lambda source: source.mag_aper, matches)
m_sdss_sources = map(lambda source: source.match2[column], matches)
# Clip outliers of (m_sdss - m_scam)
difference = []
for m_sdss, m_scam in zip(m_sdss_sources, m_scam_sources):
difference.append(m_sdss - m_scam)
std = np.std(difference)
# Make a region file to check the matching
makeRegionFile.fromList(matches, band + "_scam_match_source.reg", 0.1, "red")
makeRegionFile.fromList(matches, band + "_sdss_match_source.reg", 0.1, "green")
clipped = []
for entry in matches:
if entry.match2[column] - entry.mag_aper < std*3:
clipped.append(entry)
difference = []
for entry in clipped:
difference.append(entry.match2[column] - entry.mag_aper)
m_scam = map(lambda source: source.mag_aper, clipped)
# Look at offsets
plt.plot(difference, m_scam, linestyle='none', marker='o')
plt.xlabel(r'$m_{SDSS}$ - $m_{SCAM}$', fontsize=20)
plt.ylabel(r'$m_{SCAM}$', fontsize=20, labelpad=30)
path = os.getcwd()
phot_utils.save(path, band + '_zp.png')
# Take median of offset
return np.median(difference)
def makeRegionFile(filename, outname, pixsize, color):
catalog = open(filename, "r")
tmp = filter(lambda line: pu.no_head(line), catalog)
sources = map(lambda line: S.SCAMSource(line), tmp)
out = open(outname, "w")
for source in sources:
out.write("physical;circle(" + str(source.ximg) + "," +
str(source.yimg) + "," + str(pixsize) + ") #color=" + str(color) + "\n")
def makeRegionFile(filename, outname, pixsize, color):
catalog = open(filename, "r")
tmp = filter(lambda line: pu.no_head(line), catalog)
sources = map(lambda line: S.SCAMSource(line), tmp)
out = open(outname, "w")
for source in sources:
out.write("physical;circle(" + str(source.ximg) + "," +
str(source.yimg) + "," + str(pixsize) + ") #color=" +
str(color) + "\n")
def make_trees(catalog):
with open(catalog, 'r') as f:
tmp = filter(lambda line: phot_utils.no_head(line), f)
tmp2 = map(lambda line: Sources.SCAMSource(line), tmp)
ra = map(lambda line: line.ra, tmp2)
dec = map(lambda line: line.dec, tmp2)
sources = Quadtree.ScamEquatorialQuadtree(min(ra), min(dec), max(ra),
max(dec))
map(lambda line: sources.insert(line), tmp2)
#if verbose:
# makeRegionFile.makeRegionFile('NGC4621_i.cat', 'NGC4621_i.reg', 10, 'blue')
return sources
def make_trees(catalog):
with open(catalog, 'r') as f:
tmp = filter(lambda line: phot_utils.no_head(line), f)
tmp2 = map(lambda line: Sources.SCAMSource(line), tmp)
ra = map(lambda line: line.ra, tmp2)
dec = map(lambda line: line.dec, tmp2)
sources = Quadtree.ScamEquatorialQuadtree(min(ra), min(dec),
max(ra), max(dec))
map(lambda line: sources.insert(line), tmp2)
if verbose:
makeRegionFile.makeRegionFile('NGC4621_i.cat', 'NGC4621_i.reg', 10, 'blue')
return sources
def main():
#get_photometry(sys.argv[1], sys.argv[2])
catalogs = (glob.glob('NGC4621*.cat'))
for catalog in catalogs:
if verbose:
print "Working on catalog: ", catalog
corrected_catalog = correct_mags(sys.argv[1], catalog, catalog[-5])
sys.exit()
with open('NGC4621_g.cat', 'r') as catalog:
tmp = filter(lambda line: phot_utils.no_head(line), catalog)
g_sources = map(lambda source: Sources.SCAMSource(source), tmp)
r_sources = make_trees('NGC4621_r.cat')
i_sources = make_trees('NGC4621_i.cat')
matches = associate(g_sources, r_sources, i_sources)
with open('matched_gri.cat', 'w') as out:
out.write()
def calcZP(galaxy, scam, band):
"""
To calculate the zeropoint of the Subaru image match the Subaru catalog
and the table returned from Vizier.
"""
sdss = getSDSS(galaxy)
column = str(band + 'mag')
with open(scam, 'r') as catalog:
tmp = filter(lambda line: phot_utils.no_head(line), catalog)
# Do magnitude cute on data here
tmp2 = map(lambda line: S.SCAMSource(line), tmp)
mag = map(lambda s: s.mag_best, tmp2)
max_mag = phot_utils.calc_average(mag) + 0.25 * phot_utils.calc_average(
phot_utils.variance(mag))
sources = filter(lambda s: phot_utils.mag_cut(s.mag_best, 0, max_mag),
tmp2)
ra = map(lambda line: line.ra, tmp2)
dec = map(lambda line: line.dec, tmp2)
scam_sources = Q.ScamEquatorialQuadtree(min(ra), min(dec), max(ra),
max(dec))
map(lambda sources: scam_sources.insert(sources), sources)
matches = associate(sdss, scam_sources)
m_scam = map(lambda source: source.mag_aper, matches)
m_sdss = map(lambda source: source.match2[column], matches)
# Clip outliers of (m_sdss - m_scam)
difference = []
for i, entry in enumerate(m_scam):
difference.append(m_sdss[i] - m_scam[i])
std = np.std(difference)
# Make a region file to check the matching
with open("scam_match_source.reg", "w") as out:
for source in matches:
out.write("j2000; circle " + str(phot_utils.convertRA(source.ra)) +
"," + str(phot_utils.convertDEC(source.dec)) +
" .1' #color=red \n")
with open("sdss_match_source.reg", "w") as out:
for source in matches:
out.write("j2000; circle " +
str(phot_utils.convertRA(source.match2['RAJ2000'])) +
"," +
str(phot_utils.convertDEC(source.match2['DEJ2000'])) +
" .15' #color=green \n")
clipped = []
for entry in matches:
if entry.match2[column] - entry.mag_aper < std * 3:
clipped.append(entry)
difference = []
for entry in clipped:
difference.append(entry.match2[column] - entry.mag_aper)
m_scam = map(lambda source: source.mag_aper, clipped)
# Look at offsets
plt.plot(difference, m_scam, linestyle='none', marker='o')
plt.xlabel(r'$m_{SDSS}$ - $m_{SCAM}$', fontsize=20)
plt.ylabel(r'$m_{SCAM}$', fontsize=20, labelpad=30)
plt.show()
# Take median of offset
return phot_utils.calc_median(difference)
def findBestAperture(path, image, satur, seeing):
if os.path.isdir('BestApertureFiles') == False:
os.mkdir('BestApertureFiles')
sname = "sign"
nname = "noise"
filter_file = "default.conv"
assoc_file = "measurefluxat.txt"
output = open(assoc_file, "w")
for i in xrange(0, 100000):
output.write('%.3f' % r.uniform(1, 11000) +
'%10.3f' % r.uniform(1, 9000) + '\n')
sp.createSexParam(sname, False)
sp.createSexParam(nname, True)
sparam_file = sname + ".param"
nparam_file = nname + ".param"
signal = []
noise = []
aperture = np.linspace(0.5, 12, num=10)
for ap in aperture:
sc.createSexConfig(sname, filter_file, sparam_file, satur, seeing,
"nill", ap, False)
call(['sex', '-c', sname + '.config', image])
sc.createSexConfig(nname, filter_file, nparam_file, satur, seeing,
assoc_file, ap, True)
call(['sex', '-c', nname + '.config', image])
scat = open(sname + ".cat")
stmp = filter(lambda line: pu.no_head(line), scat)
ncat = open(nname + ".cat")
ntmp = filter(lambda line: pu.no_head(line), ncat)
# Background measuresments can't overlap with source detections
ssources = q.ScamPixelQuadtree(0, 0, 12000, 10000)
map(lambda line: ssources.insert(S.SCAMSource(line)), stmp)
nsources = map(lambda line: S.SCAMSource(line), ntmp)
start = time.time()
bkgddetections = disassociate(nsources, ssources, ap)
end = time.time()
print("ELAPSED TIME: " + str(end - start))
srcdetections = map(lambda line: S.SCAMSource(line), stmp)
flux = map(lambda f: f.flux_aper, bkgddetections)
noise.append(pu.calc_MAD(flux))
flux = map(lambda f: f.flux_aper, srcdetections)
signal.append(pu.calc_MAD(flux))
with open(image[-6] + "_ap_" + str(round(ap, 2)) + "noise.txt",
"w") as output:
for source in bkgddetections:
output.write(source.line)
call([
'mv', image[-6] + "_ap_" + str(round(ap, 2)) + "noise.txt",
'BestApertureFiles'
])
with open(image[-6] + "_ap_" + str(round(ap, 2)) + "signal.txt",
"w") as output:
for source in srcdetections:
output.write(source.line)
call([
'mv', image[-6] + "_ap_" + str(round(ap, 2)) + "signal.txt",
'BestApertureFiles'
])
'''
The files generated here aren't important and need to be
removed for the next steps to work properly.
'''
try:
os.remove('measurefluxat.txt')
except OSError:
pass
noise_files = (glob.glob('noise*'))
try:
for f in noise_files:
os.remove(f)
except OSError:
pass
sign_files = (glob.glob('sign*'))
try:
for f in sign_files:
os.remove(f)
except OSError:
pass
snr = []
for i in range(len(noise)):
snr.append(signal[i] / noise[i])
plt.plot(aperture, snr, linestyle='none', marker='o')
plt.xlabel('Aperture (pix)')
plt.ylabel('SNR')
pu.save(path, image[-6] + '_snr')
maxsnr = snr.index(max(snr))
return aperture[maxsnr]
def findBestAperture(path, image, satur, seeing):
if os.path.isdir('BestApertureFiles') == False:
os.mkdir('BestApertureFiles')
sname = "sign"
nname = "noise"
filter_file = "default.conv"
assoc_file = "measurefluxat.txt"
output = open(assoc_file, "w")
for i in xrange(0,100000):
output.write('%.3f' % r.uniform(1,11000) + '%10.3f' % r.uniform(1,9000) + '\n')
sp.createSexParam(sname, False)
sp.createSexParam(nname, True)
sparam_file = sname + ".param"
nparam_file = nname + ".param"
signal = []
noise = []
aperture = np.linspace(0.5, 12, num=10)
for ap in aperture:
sc.createSexConfig(sname, filter_file, sparam_file, satur, seeing, "nill", ap, False)
call(['sex', '-c', sname + '.config', image])
sc.createSexConfig(nname, filter_file, nparam_file, satur, seeing, assoc_file, ap, True)
call(['sex', '-c', nname + '.config', image])
scat = open(sname + ".cat")
stmp = filter(lambda line: pu.no_head(line), scat)
ncat = open(nname + ".cat")
ntmp = filter(lambda line: pu.no_head(line), ncat)
# Background measuresments can't overlap with source detections
ssources = q.ScamPixelQuadtree(0, 0, 12000, 10000)
map(lambda line: ssources.insert(S.SCAMSource(line)), stmp)
nsources = map(lambda line: S.SCAMSource(line), ntmp)
start = time.time()
bkgddetections = disassociate(nsources, ssources, ap)
end = time.time()
print("ELAPSED TIME: " + str(end-start))
srcdetections = map(lambda line: S.SCAMSource(line), stmp)
flux = map(lambda f: f.flux_aper, bkgddetections)
noise.append(pu.calc_MAD(flux))
flux = map(lambda f: f.flux_aper, srcdetections)
signal.append(pu.calc_MAD(flux))
with open(image[-6] + "_ap_" + str(round(ap, 2)) + "noise.txt", "w") as output:
for source in bkgddetections:
output.write(source.line)
call(['mv', image[-6] + "_ap_" + str(round(ap, 2)) + "noise.txt", 'BestApertureFiles'])
with open(image[-6] + "_ap_" + str(round(ap, 2)) + "signal.txt", "w") as output:
for source in srcdetections:
output.write(source.line)
call(['mv', image[-6] + "_ap_" + str(round(ap, 2)) + "signal.txt", 'BestApertureFiles'])
'''
The files generated here aren't important and need to be
removed for the next steps to work properly.
'''
try:
os.remove('measurefluxat.txt')
except OSError:
pass
noise_files = (glob.glob('noise*'))
try:
for f in noise_files:
os.remove(f)
except OSError:
pass
sign_files = (glob.glob('sign*'))
try:
for f in sign_files:
os.remove(f)
except OSError:
pass
snr = []
for i in range(len(noise)):
snr.append(signal[i]/noise[i])
plt.plot(aperture, snr, linestyle='none', marker='o')
plt.xlabel('Aperture (pix)')
plt.ylabel('SNR')
pu.save(path, image[-6]+'_snr')
maxsnr = snr.index(max(snr))
return aperture[maxsnr]
import random as r
import Quadtree
import Sources as S
import phot_utils
sources = Quadtree.ScamPixelQuadtree(0, 0, 15000, 15000)
with open("/Users/alexawork/Documents/GlobularClusters/Photometry/NGC4649/NGC4649_g.cat") as f:
tmp = filter(lambda line: phot_utils.no_head(line), f)
map(lambda line: sources.insert(S.SCAMSource(line)), tmp)
sources.match(10, 15)
sources.debug()
def calcZP(galaxy, scam, band):
"""
To calculate the zeropoint of the Subaru image match the Subaru catalog
and the table returned from Vizier.
"""
sdss = getSDSS(galaxy)
column = str(band + 'mag')
with open(scam, 'r') as catalog:
tmp = filter(lambda line: phot_utils.no_head(line), catalog)
# Do magnitude cute on data here
tmp2 = map(lambda line: S.SCAMSource(line), tmp)
mag = map(lambda s: s.mag_best, tmp2)
max_mag = phot_utils.calc_average(mag) + 0.25*phot_utils.calc_average(phot_utils.variance(mag))
sources = filter(lambda s: phot_utils.mag_cut(s.mag_best, 0, max_mag), tmp2)
ra = map(lambda line: line.ra, tmp2)
dec = map(lambda line: line.dec, tmp2)
scam_sources = Q.ScamEquatorialQuadtree(min(ra), min(dec),
max(ra), max(dec))
map(lambda sources: scam_sources.insert(sources), sources)
matches = associate(sdss, scam_sources)
m_scam = map(lambda source: source.mag_aper, matches)
m_sdss = map(lambda source: source.match2[column], matches)
# Clip outliers of (m_sdss - m_scam)
difference = []
for i, entry in enumerate(m_scam):
difference.append(m_sdss[i] - m_scam[i])
std = np.std(difference)
# Make a region file to check the matching
with open("scam_match_source.reg", "w") as out:
for source in matches:
out.write("j2000; circle " + str(phot_utils.convertRA(source.ra)) + "," +
str(phot_utils.convertDEC(source.dec)) + " .1' #color=red \n")
with open("sdss_match_source.reg", "w") as out:
for source in matches:
out.write("j2000; circle " + str(phot_utils.convertRA(source.match2['RAJ2000']))
+ "," + str(phot_utils.convertDEC(source.match2['DEJ2000'])) + " .15' #color=green \n")
clipped = []
for entry in matches:
if entry.match2[column] - entry.mag_aper < std*3:
clipped.append(entry)
difference = []
for entry in clipped:
difference.append(entry.match2[column] - entry.mag_aper)
m_scam = map(lambda source: source.mag_aper, clipped)
# Look at offsets
plt.plot(difference, m_scam, linestyle='none', marker='o')
plt.xlabel(r'$m_{SDSS}$ - $m_{SCAM}$', fontsize=20)
plt.ylabel(r'$m_{SCAM}$', fontsize=20, labelpad=30)
plt.show()
# Take median of offset
return phot_utils.calc_median(difference)
import random as r
import Quadtree
import Sources as S
import phot_utils
sources = Quadtree.ScamPixelQuadtree(0, 0, 15000, 15000)
with open(
"/Users/alexawork/Documents/GlobularClusters/Photometry/NGC4649/NGC4649_g.cat"
) as f:
tmp = filter(lambda line: phot_utils.no_head(line), f)
map(lambda line: sources.insert(S.SCAMSource(line)), tmp)
sources.match(10, 15)
sources.debug()
import Quadtree
import phot_utils
import _angular_dist
import _norm
def associate(list1, tree2):
dist = 5
with open("test.reg", "w") as out:
for entry in list1:
match2 = tree2.match(entry.ximg, entry.yimg)
if match2 != None and _norm.norm(entry.ximg, entry.yimg, match2.ximg, match2.yimg) <= dist:
out.write("physical;circle(" + str(entry.ximg) + "," + str(entry.yimg) +
" 10) #color=red \n")
with open('NGC4621_i.cat', 'r') as f:
i_catalog = [Sources.SCAMSource(line) for line in f if phot_utils.no_head(line)]
with open('NGC4621_g.cat', 'r') as f:
g_catalog = [Sources.SCAMSource(line) for line in f if phot_utils.no_head(line)]
ximg = [source.ximg for source in i_catalog]
yimg = [source.yimg for source in i_catalog]
sources = Quadtree.ScamPixelQuadtree(min(ximg), min(yimg), max(ximg), max(yimg))
#ra = [source.ra for source in i_catalog]
#dec = [source.dec for source in i_catalog]
#sources = Quadtree.ScamEquatorialQuadtree(min(ra), min(dec), max(ra), max(dec))
[sources.insert(source) for source in i_catalog]
#match = sources.match(190.7027198, 11.3355764)
def associate(list1, tree2):
dist = 5
with open("test.reg", "w") as out:
for entry in list1:
match2 = tree2.match(entry.ximg, entry.yimg)
if match2 != None and _norm.norm(entry.ximg, entry.yimg,
match2.ximg, match2.yimg) <= dist:
out.write("physical;circle(" + str(entry.ximg) + "," +
str(entry.yimg) + " 10) #color=red \n")
with open('NGC4621_i.cat', 'r') as f:
i_catalog = [
Sources.SCAMSource(line) for line in f if phot_utils.no_head(line)
]
with open('NGC4621_g.cat', 'r') as f:
g_catalog = [
Sources.SCAMSource(line) for line in f if phot_utils.no_head(line)
]
ximg = [source.ximg for source in i_catalog]
yimg = [source.yimg for source in i_catalog]
sources = Quadtree.ScamPixelQuadtree(min(ximg), min(yimg), max(ximg),
max(yimg))
#ra = [source.ra for source in i_catalog]
#dec = [source.dec for source in i_catalog]
#sources = Quadtree.ScamEquatorialQuadtree(min(ra), min(dec), max(ra), max(dec))