from config_bonn import appendix, cluster, tag, arc, filters, filter_root, appendix_root
cluster = sys.argv[1] #'MACS0717+37'
path='/nfs/slac/g/ki/ki05/anja/SUBARU/%s/' % cluster
plot_res('./OUTPUT/photz.zout','./OUTPUT/')
type='all'
filecommand = open('record.analysis','w')
BASE="coadd"
image = BASE + '.fits'
images = []
filters.reverse()
ims = {}
ims_seg = {}
for filter in filters[0:3]:
params = {'path':path,
'filter_root': filter_root,
'cluster':cluster,
'filter':filter,
'appendix':appendix, }
print params
# now run sextractor to determine the seeing:
image = '%(path)s/%(filter)s/SCIENCE/coadd_%(cluster)s%(appendix)s/coadd.fits' %params
images.append(image)
print 'reading in ' + image
seg_image = '/%(path)s/%(filter)s/PHOTOMETRY/coadd.apertures.fits' % params
ims[filter] = pyfits.open(image)[0].data
def run(cluster):
import pyfits
import os
import os, sys, bashreader, commands
from utilities import *
from config_bonn import appendix, tag, arc, filters, filter_root, appendix_root
print cluster
path='/nfs/slac/g/ki/ki05/anja/SUBARU/%s/' % cluster
type='all'
filecommand = open('record.analysis','w')
BASE="coadd"
image = BASE + '.fits'
from glob import glob
images = []
filters.reverse()
print filters
ims = {}
ims_seg = {}
params = {'path':path,
'filter_root': filter_root,
'cluster':cluster,
'appendix':appendix, }
catalog = '%(path)s/PHOTOMETRY/%(cluster)s.slr.cat' %params
starcatalog = '%(path)s/PHOTOMETRY/%(cluster)s.stars.calibrated.cat' %params
import do_multiple_photoz
filterlist = do_multiple_photoz.get_filters(catalog,'OBJECTS')
print filterlist
mkcolorcolor(filterlist,catalog,starcatalog,cluster)
ffile = os.environ['sne'] + '/photoz/' + cluster + '/all.tif'
if not glob(ffile):
for filter in filters[0:3]:
params = {'path':path,
'filter_root': filter_root,
'cluster':cluster,
'filter':filter,
'appendix':appendix, }
print params
# now run sextractor to determine the seeing:
image = '%(path)s/%(filter)s/SCIENCE/coadd_%(cluster)s%(appendix)s/coadd.fits' %params
images.append(image)
print 'reading in ' + image
seg_image = '/%(path)s/%(filter)s/PHOTOMETRY/coadd.apertures.fits' % params
ims[filter] = pyfits.open(image)[0].data
print 'read in ' + image
#ims_seg[filter] = pyfits.open(seg_image)[0].data
os.system('mkdir ' + os.environ['sne'] + '/photoz/' + cluster + '/')
os.system('chmod o+rx ' + os.environ['sne'] + '/photoz/' + cluster + '/')
from glob import glob
os.system('stiff ' + reduce(lambda x,y:x + ' ' + y,images) + ' -OUTFILE_NAME ' + ffile + ' -BINNING 1 -GAMMA_FAC 1.6')
os.system('convert ' + os.environ['sne'] + '/photoz/' + cluster + '/all.tif ' + os.environ['sne'] + '/photoz/' + cluster + '/fix.tif')
print ffile
import Image
im = Image.open(os.environ['sne'] + '/photoz/' + cluster + '/fix.tif')
print catalog
p_cat = pyfits.open(catalog)[1].data
outputcat = '%(path)s/PHOTOMETRY/%(cluster)s.1.spec.bpz.tab' % params
#outputcat = '%(path)s/PHOTOMETRY/all_bpz1_' % params
if glob(outputcat.replace('.tab','')):
plot_res(outputcat.replace('.tab',''),os.environ['sne'] + '/photoz/' + cluster + '/')
print outputcat
spec = True
if not spec:
outputcat = '%(path)s/PHOTOMETRY/%(cluster)s.1.all.bpz.tab' % params
print outputcat
bpz_cat = pyfits.open(outputcat)[1].data
print outputcat
gals = []
for i in range(len(bpz_cat)): #[75227,45311,53658, 52685, 64726]:
print i
line = bpz_cat[i]
print line
text = ''
#for x,y,side,index in [[4800,4900,200,1],[5500,5500,100,2],[4500,5500,300,2]]:
text += '<tr>\n'
SeqNr = int(line['SeqNr'])
fileNumber = str(int(line['BPZ_NUMBER']))
params['fileNumber'] = str(fileNumber)
if spec:
base = '%(path)s/PHOTOMETRY/%(cluster)s.1.spec' % params
probs = '%(path)s/PHOTOMETRY/all.spec.cat.bpz1.probs' % params
#base = '%(path)s/PHOTOMETRY/specsave.cat' % params
#probs = '%(path)s/PHOTOMETRY/all.spec.cat.bpz1.probs' % params
else:
base = '%(path)s/PHOTOMETRY/all_bpz1_%(fileNumber)s' % params
probs = '%(path)s/PHOTOMETRY/all_bpz1_%(fileNumber)s.probs' % params
print probs
probs_f = open(probs,'r').readlines()
resid = line['BPZ_Z_B'] - line['BPZ_Z_S']
ODDS = line['BPZ_ODDS']
if True: #0.38 < line['BPZ_Z_B'] < 0.42: #abs(resid) > 0.15: # and ODDS > 0.95:
mask = p_cat.field('SeqNr') == SeqNr
temp = p_cat[mask]
x = int(temp.field('Xpos')[0])
y = 10000 - int(temp.field('Ypos')[0])
x_fits = int(temp.field('Xpos')[0])
y_fits = int(temp.field('Ypos')[0])
import pyraf
from pyraf import iraf
if line['BPZ_Z_S'] != 0:
resid = line['BPZ_Z_B'] - line['BPZ_Z_S']
if resid > 0:
color='green'
resid_str = ' <font color=' + color + '>+' + str(resid) + '</font> '
else:
color='red'
resid_str = ' <font color=' + color + '>' + str(resid) + '</font> '
else:
resid = 'no spec z'
color = 'black'
resid_str = ' <font color=' + color + '>' + str(resid) + '</font> '
t = ['BPZ_Z_B','BPZ_ODDS','BPZ_CHI-SQUARED']
text += '<td colspan=10>' + str(SeqNr) + ' z=' + str(line['BPZ_Z_B']) + resid_str + ' ODDS=' + str(line['BPZ_ODDS']) + ' TYPE=' + str(line['BPZ_T_B']) + ' CHISQ=' + str(line['BPZ_CHI-SQUARED']) + ' x=' + str(x) + ' y=' + str(y) + '</td></tr><tr>\n'
print x,y
index = SeqNr
outfile = os.environ['sne'] + '/photoz/' + cluster + '/' + str(index) + '.png'
plot_bpz_probs(index, probs_f, outfile)
#file = 'Id%09.f.spec' % index
#outfile = os.environ['sne'] + '/photoz/' + str(index) + '.png'
#print outfile
#plot(file,outfile)
text += '<td align=left><img height=400px src=' + str(index) + '.png></img>\n'
text += '<img height=400px src=' + str(index) + 'spec.png></img>\n'
images = []
file = '/nfs/slac/g/ki/ki04/pkelly/photoz/' + cluster + '/' + str(SeqNr) + 'spec.png' #print 'SAVING', outdir + outimg
command = 'python ' + os.environ['BPZPATH'] + '/plots/sedplot.py ' + base + ' ' + str(SeqNr) + ' ' + file
print command
import sedplot
sys.argv = ['',base,str(SeqNr),file]
filt_info = sedplot.run()
print filt_info
#print command
#os.system(command)
try:
p = im.crop([x-side,y-side,x+side,y+side])
image = os.environ['sne'] + '/photoz/' + cluster + '/' + str(index) + '.jpg'
os.system('rm ' + image)
p.save(image,'JPEG')
except: print 'fail'
text += '<img src=' + str(index) + '.jpg></img></td><td colspan=20></td>\n'
text += '</tr>\n'
keys = ['name','wavelength','observed','flux','fluxerror','expectedflux','chioffset']
text += '<tr><td colspan=10><table><tr>' + reduce(lambda x,y: x + y,['<td>'+n+'</td>' for n in keys]) + "</tr>"
for f in filt_info:
text += '<tr>' + reduce(lambda x,y: x + y,['<td>'+str(f[n])+'</td>' for n in keys]) + "</tr>"
text += "</table></td></tr>"
side = 100 #x = temp.field('Xpos')[0]
bounds = '[' + str(int(x_fits-side)) + ':' + str(int(x_fits+side)) + ',' + str(int(y_fits-side)) + ':' + str(int(y_fits+side)) + ']'
text += '<td colspan=20><table>\n'
textim = ''
textlabel = ''
import string
filters_b = []
name_t = None
for f in filt_info:
print f['name']
if string.find(f['name'],'MEGAPRIME') != -1:
n = f['name'][-1]
if string.find(f['name'],'SUBARU') != -1:
import re
res = re.split('-W',f['name'])
print res, f['name']
n = 'W' + res[1]
if n != name_t:
filters_b.append(n)
name_t = n
for filter in filters_b[1:]:
fitsfile = '/nfs/slac/g/ki/ki04/pkelly/photoz/' + cluster + '/' + str(SeqNr) + 'cutout' + filter + '.fits' #print 'SAVING', outdir + outimg
jpg = '/nfs/slac/g/ki/ki04/pkelly/photoz/' + cluster + '/' + str(SeqNr) + 'cutout' + filter + '.jpg' #print 'SAVING', outdir + outimg
os.system('rm ' + fitsfile)
os.system('rm ' + jpg)
bigfile = '/a/wain023/g.ki.ki05/anja/SUBARU/' + cluster + '/' + filter + '/SCIENCE/coadd_' + cluster + '_all/coadd.fits'
iraf.imcopy(bigfile + bounds,fitsfile)
import commands
seeing = commands.getoutput('gethead ' + bigfile + ' SEEING')
print 'seeing', seeing
import os
#os.system("ds9 " + fitsfile + " -view info no -view panner no -view magnifier no -view buttons no -view colorbar yes -view horzgraph no -view wcs no -view detector no -view amplifier no -view physical no -zoom to fit -minmax -histequ -invert -zoom to fit -saveas jpeg " + jpg ) # -quit >& /dev/null &")
#os.system("xpaset -p ds9 " + fitsfile + " -zoom to fit -view colorbar no -minmax -histequ -invert -zoom to fit -saveas jpeg " + jpg + " ") # -quit >& /dev/null &")
com = ['file ' + fitsfile, 'zoom to fit', 'view colorbar no', 'minmax', 'scale histequ' , 'cmap invert', 'saveimage jpeg ' + jpg] # -quit >& /dev/null &")
for c in com:
z = 'xpaset -p ds9 ' + c
print z
os.system(z)
print jpg
text += '<td><img height=200px src=' + str(SeqNr) + 'cutout' + filter + '.jpg></img></td>\n'
textlabel += '<td>' + filter + ' seeing ' + seeing + '</td>\n'
text += '<tr>' + textim + '</tr><tr>' + textlabel + '</tr></table></td></tr><tr>'
#os.system('stiff ' + image_seg + ' -OUTFILE_NAME ' + image_seg.replace('fits','tif'))
gals.append([line['BPZ_T_B'],text])
page = open(os.environ['sne'] + '/photoz/' + cluster + '/index.html','w')
t = '<head><link href="http://www.slac.stanford.edu/~pkelly/photoz/table.css" rel="stylesheet" type="text/css"></head>'
t += '<table align=left><tr><td colspan=5 class="dark"><h1>' + cluster + '</h1></td></tr><tr><td colspan=5><a href=stars.html>Stellar Color-Color Plots</a><td></tr>\n'
t += '<tr><td colspan=10 align=left><img height=400px src=RedshiftErrors.png></img>\n'
t += '<img height=400px src=RedshiftScatter04.png></img>\n'
t += '<img height=400px src=RedshiftScatter01.png></img></td></tr>\n'
page.write(t)
gals.sort()
for gal in gals:
page.write(gal[1])
page.write('<table>\n')
page.close()
if len(gals) > 100:
break
''' make SED plots '''
def run(cluster):
ratio = []
import pyfits, cutout_bpz
import os
import os, sys, bashreader, commands
from utilities import *
from config_bonn import appendix, tag, arc, filters, filter_root, appendix_root
type='all'
magtype = 'APER'
if len(sys.argv) > 2:
for s in sys.argv:
if s == 'spec':
type = 'spec'
elif s == 'rand':
type = 'rand'
elif s == 'all':
type = 'all'
elif s == 'picks':
type = 'picks'
elif s == 'ISO':
magtype = 'ISO'
elif s == 'APER':
magtype = 'APER'
print cluster
path='/nfs/slac/g/ki/ki05/anja/SUBARU/%s/' % cluster
filecommand = open('record.analysis','w')
BASE="coadd"
image = BASE + '.fits'
from glob import glob
images = []
filters.reverse()
print filters
ims = {}
ims_seg = {}
params = {'path':path,
'filter_root': filter_root,
'cluster':cluster,
'appendix':appendix, }
catalog = '%(path)s/PHOTOMETRY/%(cluster)s.slr.cat' %params
starcatalog = '%(path)s/PHOTOMETRY/%(cluster)s.stars.calibrated.cat' %params
save_file = '%(path)s/PHOTOMETRY/pat_slr.calib' %params
import do_multiple_photoz, os
reload(do_multiple_photoz)
filterlist = do_multiple_photoz.get_filters(catalog,'OBJECTS')
print filterlist
filters = cutout_bpz.conv_filt(filterlist)
y = {}
for f in filters:
y[f] = 'yes'
filters = y.keys()
filters.sort(cutout_bpz.sort_filters)
print filters
os.system('mkdir -p ' + os.environ['sne'] + '/photoz/' + cluster)
mkcolorcolor(filterlist,catalog,starcatalog,cluster,magtype,save_file)
def run(cluster):
ratio = []
import pyfits
import os
import os, sys, bashreader, commands
from config_bonn import appendix, tag, arc, filters, filter_root, appendix_root
type = 'all'
AP_TYPE = ''
magtype = 'APER1'
DETECT_FILTER = ''
SPECTRA = 'CWWSB_capak.list'
LIST = None
if len(sys.argv) > 2:
for s in sys.argv:
if s == 'spec':
type = 'spec'
elif s == 'rand':
type = 'rand'
elif s == 'all':
type = 'all'
elif s == 'picks':
type = 'picks'
elif s == 'ISO':
magtype = 'ISO'
elif s == 'APER1':
magtype = 'APER1'
import string
if string.find(s, 'detect') != -1:
import re
rs = re.split('=', s)
DETECT_FILTER = '_' + rs[1]
if string.find(s, 'aptype') != -1:
import re
rs = re.split('=', s)
AP_TYPE = '_' + rs[1]
if string.find(s, 'spectra') != -1:
import re
rs = re.split('=', s)
SPECTRA = rs[1]
if string.find(s, 'spectra') != -1:
import re
rs = re.split('=', s)
SPECTRA = rs[1]
if string.find(s, 'list') != -1:
import re
rs = re.split('=', s)
LIST = rs[1]
print DETECT_FILTER
print cluster
path = '/nfs/slac/g/ki/ki05/anja/SUBARU/%s/' % cluster
filecommand = open('record.analysis', 'w')
BASE = "coadd"
image = BASE + '.fits'
from glob import glob
images = []
filters.reverse()
print filters
ims = {}
ims_seg = {}
params = {
'path': path,
'filter_root': filter_root,
'cluster': cluster,
'appendix': appendix,
'DETECT_FILTER': DETECT_FILTER,
'AP_TYPE': AP_TYPE
}
params['SPECTRA'] = SPECTRA
params['type'] = type
params['magtype'] = magtype
outputcat = '%(path)s/PHOTOMETRY%(DETECT_FILTER)s%(AP_TYPE)s/%(cluster)s.%(magtype)s.1.%(SPECTRA)s.%(type)s.bpz.tab' % params
catalog = '%(path)s/PHOTOMETRY%(DETECT_FILTER)s%(AP_TYPE)s/%(cluster)s.slr.cat' % params
starcatalog = '%(path)s/PHOTOMETRY%(DETECT_FILTER)s%(AP_TYPE)s/%(cluster)s.stars.calibrated.cat' % params
import do_multiple_photoz, os
filterlist = do_multiple_photoz.get_filters(catalog, 'OBJECTS')
print filterlist
filters = conv_filt(filterlist)
y = {}
for f in filters:
y[f] = 'yes'
filters = y.keys()
filters.sort(sort_filters)
print filters
stars_dict = star_num(filterlist,
catalog,
starcatalog,
cluster,
'APER1',
name_suffix='')
os.system('mkdir -p ' + os.environ['sne'] + '/photoz/' + cluster + '/' +
SPECTRA + '/')
if False:
pagemain = open(
os.environ['sne'] + '/photoz/' + cluster + '/' + SPECTRA +
'/index.html', 'w')
pagemain.write(
'<table align=left><tr><td colspan=5 class="dark"><h1>' + cluster +
'</h1></td></tr><tr><td colspan=5><a href=http://www.slac.stanford.edu/~pkelly/photoz/'
+ cluster +
'/stars.html>Stellar Color-Color Plots</a><td></tr><tr><td colspan=5><a href=redsequence.html>Red Sequence Redshifts</a><td></tr><tr><td><a href=objects.html>Photoz Plots</a><td></tr><tr><td><a href=thecorrections.html>Correction Plots</a><td></tr><tr><td><a href=zdistribution.html>Z Distribution</a><td></tr></table>\n'
)
pagemain.close()
import pyfits, pylab, scipy
p = pyfits.open(outputcat)['STDTAB'].data
pylab.clf()
pylab.hist(p.field('BPZ_ODDS'), bins=scipy.arange(0, 1, 0.02))
pylab.xlabel('ODDS')
pylab.ylabel('Number of Galaxies')
pylab.savefig(os.environ['sne'] + '/photoz/' + cluster + '/' +
SPECTRA + '/odds.png')
cut = 0.5
p = p[p.field('BPZ_ODDS') > cut]
pylab.clf()
pylab.hist(p.field('BPZ_Z_B'), bins=scipy.arange(0, 4, 0.02))
pylab.xlabel('Photometric Redshift')
pylab.ylabel('Number of Galaxies (ODDS > ' + str(cut) + ')')
pylab.savefig(os.environ['sne'] + '/photoz/' + cluster + '/' +
SPECTRA + '/zdist.png')
pagemain = open(
os.environ['sne'] + '/photoz/' + cluster + '/' + SPECTRA +
'/zdistribution.html', 'w')
pagemain.write('<img src=zdist.png></a>')
pagemain.write('<img src=odds.png></a>')
pagemain.close()
pylab.clf()
import flux_comp
corrections, plot_dict, title_dict = reload(flux_comp).calc_comp(
cluster,
DETECT_FILTER.replace('_', ''),
AP_TYPE,
SPECTRA,
type='all',
plot=True)
print corrections
pagemain = open(
os.environ['sne'] + '/photoz/' + cluster + '/' + SPECTRA +
'/thecorrections.html', 'w')
def s(a, b):
if corrections[a] < corrections[b]:
return 1
else:
return -1
keys2 = corrections.keys()
keys2.sort(s)
import scipy
from scipy import stats
kernel = scipy.array(
[scipy.stats.norm.pdf(i, 1.) for i in [4, 3, 2, 1, 0, 1, 2, 3, 4]])
kernel = kernel / kernel.sum()
pagemain.write('<br>CORRECTIONS<br><ul>')
ims = ''
nums = '<br><br>NUMBER OF GOOD STARS<br><ul>\n'
for key in keys2:
if key != 'ID' and key != 'Z_S':
file = os.environ[
'sne'] + '/photoz/' + cluster + '/' + SPECTRA + '/' + key + '.png'
pylab.clf()
o = pylab.hist(plot_dict[key], bins=100, range=[0.5, 1.5])
y_smooth = scipy.convolve(o[0], kernel, 'same') #[5:-5]
print o[1], y_smooth, len(o[1]), len(y_smooth)
#pylab.linewidth = 4
xs = o[1][:-1] + scipy.ones(len(
o[1][:-1])) * (o[1][1] - o[1][0]) * 0.5
ys = y_smooth
pylab.plot(xs, ys, 'r', linewidth=2)
pylab.suptitle(title_dict[key])
print o
pylab.savefig(file)
ims += '<img src=' + key + '.png></a>\n'
a = zip(y_smooth, xs)
a.sort()
max = a[-1][1]
pagemain.write(key + ' median=' + str(corrections[key]) +
' smoothed peak=' + str(max) + '<br>')
nums += key + ' ' + str(stars_dict[key]) + '<br>\n'
pagemain.write('</ul>' + nums + '</ul>' + ims)
pagemain.close()
os.system('mkdir -p ' + os.environ['sne'] + '/photoz/' + cluster)
#mkcolorcolor(filterlist,catalog,starcatalog,cluster,'APER1',name_suffix='aperapercalib')
#mkcolorcolor(filterlist,catalog,starcatalog,cluster,',name_suffix='')
if False:
mkcolorcolor(filterlist,
catalog,
starcatalog,
cluster,
'APER1',
name_suffix='')
#import sys
#sys.exit(0)
print catalog
#catalog = '/u/ki/dapple/subaru/MACS2243-09/PHOTOMETRY_W-J-V_iso/MACS2243-09.aper.slr.cat'
#file = mkcolorcolor(filterlist,catalog,starcatalog,cluster,'ISO',name_suffix='isomags_apercalib')
#catalog = '/u/ki/dapple/subaru/MACS2243-09/PHOTOMETRY_W-J-V_iso/MACS2243-09.slr.cat'
#file = mkcolorcolor(filterlist,catalog,starcatalog,cluster,'ISO',name_suffix='isomags_isocalib')
#catalog = '/u/ki/dapple/subaru/MACS2243-09/PHOTOMETRY_W-J-V_aper/MACS2243-09.slr.cat'
#file = mkcolorcolor(filterlist,catalog,starcatalog,cluster,'APER1',name_suffix='apermags_apercalib')
#print file
ffile = os.environ['sne'] + '/photoz/' + cluster + '/all.tif'
print filters
if not glob(ffile):
print filters[1:4]
for filt in filters[1:4]:
#filter = filter.replace('MEGAPRIME-0-1-','').replace('SUBARU-10_2-1-','').replace('SUBARU-10_2-2-','').replace('SUBARU-10_1-1-','').replace('SUBARU-10_1-2-','')#.replace('SUBARU-8-1-','')
params = {
'path': path,
'filter_root': filter_root,
'cluster': cluster,
'filter': filt,
'DETECT_FILTER': DETECT_FILTER,
'AP_TYPE': AP_TYPE,
'appendix': appendix,
}
print params
# now run sextractor to determine the seeing:
image = '%(path)s/%(filter)s/SCIENCE/coadd_%(cluster)s%(appendix)s/coadd.fits' % params
images.append(image)
print 'reading in ' + image
seg_image = '/%(path)s/%(filter)s/PHOTOMETRY/coadd.apertures.fits' % params
ims[filt] = pyfits.open(image)[0].data
print 'read in ' + image
#ims_seg[filter] = pyfits.open(seg_image)[0].data
print images
os.system('mkdir ' + os.environ['sne'] + '/photoz/' + cluster + '/')
os.system('chmod o+rx ' + os.environ['sne'] + '/photoz/' + cluster +
'/')
from glob import glob
os.system('stiff ' + reduce(lambda x, y: x + ' ' + y, images) +
' -OUTFILE_NAME ' + ffile + ' -BINNING 1 -GAMMA_FAC 1.6')
os.system('convert ' + os.environ['sne'] + '/photoz/' + cluster +
'/all.tif ' + os.environ['sne'] + '/photoz/' + cluster +
'/fix.tif')
print ffile
import Image
im = Image.open(os.environ['sne'] + '/photoz/' + cluster + '/fix.tif')
print catalog
p_cat = pyfits.open(catalog)[1].data
#outputcat = '%(path)s/PHOTOMETRY/all_bpz1_' % params
#spec = True
picks = False
#SPECTRA = 'CWWSB4_txitxo.list'
#SPECTRA = 'CWWSB_capak.list' # use Peter Capak's SEDs
print SPECTRA
outbase = os.environ['sne'] + '/photoz/' + cluster + '/'
os.system('mkdir -p ' + outbase + '/' + SPECTRA + '/')
SeqNr_file = open('SeqNr_file', 'w')
if type == 'spec':
probsout = '%(path)s/PHOTOMETRY%(DETECT_FILTER)s%(AP_TYPE)s/%(cluster)s.%(magtype)s.1.%(SPECTRA)s.%(type)s.probs' % params
#outputcat = '%(path)s/PHOTOMETRY/%(cluster)s.1.all.bpz.tab' % params
print probsout, outputcat.replace('.tab', '')
f = open(probsout, 'r').readlines()
fz_temp = open(outputcat.replace('.tab', ''), 'r').readlines()
fz = []
for l in fz_temp:
if l[0] != '#': fz.append(l)
import re
res = re.split('\s+', f[0])
print res[4]
res2 = re.split('\,', res[4].replace('z=arange(', '').replace(')', ''))
print res2
import scipy
increment = float(res2[2])
#matrix = scipy.array(zs*
print zip(f[1:], fz[:])[1] #zs
end = int(1. / increment)
zs = (scipy.arange(float(res2[0]), 1. + increment, increment))
prob_matrix = scipy.zeros((end, end))
for l, zf in zip(f[1:], fz[:]):
#print l, zf
import re
resz = re.split('\s+', zf[:-1])
if resz[0] == '': resz = resz[1:]
#print resz
z_spec = float(resz[9])
odds = float(resz[5])
res = re.split('\s+', l[:-1])
if res[-1] == '': res = res[:-1]
#print res
pdz = scipy.array([float(x) for x in res[1:]])
from copy import copy
zs_copy = copy(zs)
#zs_copy = zs_copy[pdz != 0]
#pdz = pdz[pdz != 0]
#print zs_copy, pdz, resz[9]
for i in range(len(zs_copy))[:end]: #z,p in zip(zs_copy, pdz):
if odds > 0.95 and z_spec < 1.:
prob_matrix[i, int(z_spec / increment)] += pdz[i]
#print prob_matrix
#pdz.append(
print 'done calculating'
X, Y = pylab.meshgrid(zs_copy, zs_copy)
print prob_matrix.shape, X.shape, Y.shape
pylab.clf()
print prob_matrix.max()
prob_matrix[prob_matrix > 1] = 1.
pylab.pcolor(X,
Y,
-1. * prob_matrix,
cmap='gray',
alpha=0.9,
shading='flat',
edgecolors='None')
pylab.plot([0, 1], [0, 1], color='red')
pylab.xlabel('SpecZ')
pylab.ylabel('PhotZ')
pylab.savefig(outbase + '/' + SPECTRA + '/RedshiftPDZ01.png')
#pylab.pcolor(X, Y,prob_matrix,cmap='gray',alpha=0.9,shading='flat',edgecolors='None')
#pylab.colorbar()
#doFormating(**formating)
#histogram2d(zs_copy,zs_copy,prob_matrix)
#for l in f[1:]:
# res = re.split('\s+',l)
# print res
if True: #glob(outputcat.replace('.tab','')):
plot_res(outputcat.replace('.tab', ''), outbase, SPECTRA)
print 'plot_res'
print outputcat
bpz_cat = pyfits.open(outputcat)[1].data
print outputcat
gals = []
set = range(len(bpz_cat))
if type == 'rand':
set = range(100)
f_nums = [e[:-1] for e in open('SeqNr_save', 'r').readlines()]
for i in set: #[0:25]: #[75227,45311,53658, 52685, 64726]:
print i
line = bpz_cat[i]
print line, outputcat
text = ''
#for x,y,side,index in [[4800,4900,200,1],[5500,5500,100,2],[4500,5500,300,2]]:
text += '<tr>\n'
SeqNr = int(line['SeqNr'])
fileNumber = str(int(line['BPZ_NUMBER']))
params['fileNumber'] = str(fileNumber)
base = '%(path)s/PHOTOMETRY%(DETECT_FILTER)s%(AP_TYPE)s/%(cluster)s.%(magtype)s.1.%(SPECTRA)s.%(type)s' % params
probs = '%(path)s/PHOTOMETRY%(DETECT_FILTER)s%(AP_TYPE)s/%(cluster)s.%(magtype)s.1.%(SPECTRA)s.%(type)s.probs' % params
print probs
print base, probs
resid = line['BPZ_Z_B'] - line['BPZ_Z_S']
z = line['BPZ_Z_B']
ODDS = line['BPZ_ODDS']
if True: #line['BPZ_ODDS'] > 0.5 and 0.6 < line['BPZ_Z_B'] < 0.8 and 0.2 < line['BPZ_Z_S'] < 0.4: #abs(resid) > 0.2: #abs(resid) > 0.04 and 0.4 < line['BPZ_Z_S'] < 0.6: #True: #SeqNr==24778: # SeqNr == 4441 or SeqNr==1285: #abs(resid) > 0.1:
# print f_nums
# if True: #len(filter(lambda x: int(line['SeqNr']) == int(x),f_nums)):
probs_f = open(probs, 'r').readlines()
print line['SeqNr']
file = '/nfs/slac/g/ki/ki04/pkelly/photoz/' + cluster + '/' + SPECTRA + '/' + str(
SeqNr) + 'spec.png' #print 'SAVING', outdir + outimg
sys.argv = ['', base, str(SeqNr), file]
import sedplot
print base, 'base'
filt_info = sedplot.run()
print filt_info
import math
if 1: #filt_info[0]['flux'] > 0:
ratio.append(filt_info[0]['expectedflux'] /
filt_info[0]['flux'])
#import pylab
#from scipy import arange
#print ratio
#import scipy
#print 'ratio', scipy.median(scipy.array(ratio))
#a, b, varp = pylab.hist(ratio,bins=arange(0,5,0.1))
#pylab.show()
#if line['BPZ_ODDS'] > 0.95 and abs(resid) > 0.2: #abs(resid) > 0.04 and 0.4 < line['BPZ_Z_S'] < 0.6: #True: #SeqNr==24778: # SeqNr == 4441 or SeqNr==1285: #abs(resid) > 0.1:
#if 1:
print line['BPZ_Z_B']
SeqNr_file.write(str(SeqNr) + '\n')
mask = p_cat.field('SeqNr') == SeqNr
temp = p_cat[mask]
x = int(temp.field('Xpos')[0])
y = 10000 - int(temp.field('Ypos')[0])
x_fits = int(temp.field('Xpos')[0])
y_fits = int(temp.field('Ypos')[0])
import pyraf
from pyraf import iraf
if line['BPZ_Z_S'] != 0:
resid = line['BPZ_Z_B'] - line['BPZ_Z_S']
if resid > 0:
color = 'green'
resid_str = ' <font color=' + color + '>+' + str(
resid) + '</font> '
else:
color = 'red'
resid_str = ' <font color=' + color + '>' + str(
resid) + '</font> '
else:
resid = 'no spec z'
color = 'black'
resid_str = ' <font color=' + color + '>' + str(
resid) + '</font> '
t = [
'BPZ_Z_B', 'BPZ_ODDS', 'BPZ_CHI-SQUARED', 'BPZ_Z_B_MIN',
'BPZ_Z_B_MAX'
]
text += '<td colspan=10>' + str(SeqNr) + ' z=' + str(
line['BPZ_Z_B']
) + ' MIN=' + str(line['BPZ_Z_B_MIN']) + ' MAX=' + str(
line['BPZ_Z_B_MAX']) + resid_str + ' ODDS=' + str(
line['BPZ_ODDS']) + ' TYPE=' + str(
line['BPZ_T_B']) + ' CHISQ=' + str(
line['BPZ_CHI-SQUARED']) + ' x=' + str(
x) + ' y=' + str(y) + '</td></tr><tr>\n'
print x, y
index = SeqNr
outfile = os.environ[
'sne'] + '/photoz/' + cluster + '/' + SPECTRA + '/' + str(
index) + '.png'
plot_bpz_probs(index, probs_f, outfile)
#file = 'Id%09.f.spec' % index
#outfile = os.environ['sne'] + '/photoz/' + str(index) + '.png'
#print outfile
#plot(file,outfile)
text += '<td align=left><img height=400px src=' + str(
index) + '.png></img>\n'
text += '<img height=400px src=' + str(index) + 'spec.png></img>\n'
images = []
file = '/nfs/slac/g/ki/ki04/pkelly/photoz/' + cluster + '/' + str(
SeqNr) + 'spec.png' #print 'SAVING', outdir + outimg
command = 'python ' + os.environ[
'BPZPATH'] + '/plots/sedplot.py ' + base + ' ' + str(
SeqNr) + ' ' + file
print command
import sedplot
#sys.argv = ['',base,str(SeqNr),file]
#filt_info = sedplot.run()
#print filt_info
#print command
#os.system(command)
side = 100 #x = temp.field('Xpos')[0]
if 1: #try:
p = im.crop([x - side, y - side, x + side, y + side])
image = os.environ[
'sne'] + '/photoz/' + cluster + '/' + SPECTRA + '/' + str(
index) + '.jpg'
os.system('rm ' + image)
p.save(image, 'JPEG')
#except: print 'fail'
text += '<img src=' + str(
index) + '.jpg></img></td><td colspan=20></td>\n'
text += '</tr>\n'
keys = [
'name', 'wavelength', 'observed', 'flux', 'fluxerror',
'expectedflux', 'chioffset'
]
text += '<tr><td colspan=10><table><tr>' + reduce(
lambda x, y: x + y, ['<td>' + n + '</td>'
for n in keys]) + "</tr>"
for f in filt_info:
text += '<tr>' + reduce(
lambda x, y: x + y,
['<td>' + str(f[n]) + '</td>' for n in keys]) + "</tr>"
text += "</table></td></tr>"
side = 100 #x = temp.field('Xpos')[0]
#if x_fits - 100 < 0: x_fits = 101
#if y_fits - 100 < 0: y_fits = 101
#if x_fits + 100 > 9999: x_fits = 9899
#if y_fits + 100 > 9999: y_fits = 9899
xlow = int(x_fits - side)
xhigh = int(x_fits + side)
ylow = int(y_fits - side)
yhigh = int(y_fits + side)
if xlow < 0: xlow = ''
if ylow < 0: ylow = ''
if xhigh > 9999: xhigh = ''
if yhigh > 9999: yhigh = ''
bounds = '[' + str(xlow) + ':' + str(xhigh) + ',' + str(
ylow) + ':' + str(yhigh) + ']'
text += '<td colspan=20><table>\n'
textim = ''
textlabel = ''
import string
filters_b = conv_filt(filt_info)
for filt in []: #filters_b: #[1:]:
fitsfile = '/nfs/slac/g/ki/ki04/pkelly/photoz/' + cluster + '/' + SPECTRA + '/' + str(
SeqNr
) + 'cutout' + filt + '.fits' #print 'SAVING', outdir + outimg
jpg = '/nfs/slac/g/ki/ki04/pkelly/photoz/' + cluster + '/' + SPECTRA + '/' + str(
SeqNr
) + 'cutout' + filt + '.jpg' #print 'SAVING', outdir + outimg
os.system('rm ' + fitsfile)
os.system('rm ' + jpg)
bigfile = '/a/wain023/g.ki.ki05/anja/SUBARU/' + cluster + '/' + filt + '/SCIENCE/coadd_' + cluster + '_all/coadd.fits'
iraf.imcopy(bigfile + bounds, fitsfile)
import commands
seeing = commands.getoutput('gethead ' + bigfile + ' SEEING')
print 'seeing', seeing
import os
#os.system("ds9 " + fitsfile + " -view info no -view panner no -view magnifier no -view buttons no -view colorbar yes -view horzgraph no -view wcs no -view detector no -view amplifier no -view physical no -zoom to fit -minmax -histequ -invert -zoom to fit -saveas jpeg " + jpg ) # -quit >& /dev/null &")
#os.system("xpaset -p ds9 " + fitsfile + " -zoom to fit -view colorbar no -minmax -histequ -invert -zoom to fit -saveas jpeg " + jpg + " ") # -quit >& /dev/null &")
print 'bounds', bigfile + bounds
com = [
'file ' + fitsfile, 'zoom to fit', 'view colorbar no',
'minmax', 'scale histequ', 'saveimage jpeg ' + jpg
] # -quit >& /dev/null &")
for c in com:
z = 'xpaset -p ds9 ' + c
print z
os.system(z)
print jpg
text += '<td><img height=200px src=' + str(
SeqNr) + 'cutout' + filt + '.jpg></img></td>\n'
textlabel += '<td>' + filt + ' seeing ' + seeing + '</td>\n'
text += '<tr>' + textim + '</tr><tr>' + textlabel + '</tr></table></td></tr><tr>'
#os.system('stiff ' + image_seg + ' -OUTFILE_NAME ' + image_seg.replace('fits','tif'))
gals.append([line['BPZ_T_B'], text])
from datetime import datetime
t2 = datetime.now()
file = os.environ[
'sne'] + '/photoz/' + cluster + '/' + SPECTRA + '/objects.html'
print file
page = open(file, 'w')
t = '<head><link href="http://www.slac.stanford.edu/~pkelly/photoz/table.css" rel="stylesheet" type="text/css"></head>'
t += '<table align=left><tr><td colspan=5 class="dark"><h1>' + cluster + '</h1></td></tr><tr><td colspan=5><h4>created ' + t2.strftime(
"%Y-%m-%d %H:%M:%S"
) + '</h4></td></tr><tr><td colspan=5><a href=stars.html>Stellar Color-Color Plots</a><td></tr>\n'
if type == 'spec':
t += '<tr><td colspan=5 class="dark"><h2>Spectroscopic Sample</h2></td></tr>\n'
t += '<tr><td colspan=10 align=left><img height=400px src=RedshiftErrors.png></img>\n'
t += '<img height=400px src=RedshiftScatter04.png></img>\n'
t += '<img height=400px src=RedshiftScatter01.png></img>\n'
t += '<img height=400px src=RedshiftPDZ01.png></img></td></tr>\n'
if type == 'rand':
t += '<tr><td colspan=5 class="dark"><h2>Random Sample of 100 Galaxies</h2></td></tr>\n'
if type == 'picks':
t += '<tr><td colspan=5 class="dark"><h2>Pick</h2></td></tr>\n'
page.write(t)
gals.sort()
for gal in gals:
page.write(gal[1])
page.write('<table>\n')
page.close()
print 'CLOSED!!'
if len(gals) > 100:
break
''' make SED plots '''