def inverse_flag_images(image):
"""
It creates a RMS-like image using its Weight-map
where it is defined as RMS = 1 / sqrt(WeightMap)
----
import alhambra_invflagimas as AIV
image = '/Volumes/amb22/imagenes/f04/f04p01_F814W_1.swp.weight.flag.fits'
AIV.inverse_flag_images(image)
"""
print 'Processing image: ', image
wim = image
data = P.open(wim)[0].data
nc = len(data[0, :])
nf = len(data[:, 0])
matrix = U.zeros((nf, nc), float)
for ii in range(nc):
for jj in range(nf):
if data[jj, ii] < 1:
matrix[jj, ii] = 1
else:
matrix[jj, ii] = 0
nameout = A.decapfile(wim) + '.inv.fits'
print 'Saving new image as...', nameout
P.writeto(nameout, matrix)
try:
A.addheader2another(image, nameout)
except:
print 'Impossible to update its header!!!'
def alhambramosaico(listofimages, xx, yy, size, ID_number):
"""
import clash_tools
from clash_tools import *
lista = '/Volumes/CLASH/psfmodels/May2012/final/listilla.txt'
size=25
coox = 13
cooy = 13
ids=777
clashmosaico(lista,coox,cooy,size,ids)
"""
# It creates the list of images to be used (from "listing.py").
image_list = U.get_str(listofimages, 0)
path = A.getpath(image_list[0])
# Paths & outputs
imageout = A.decapfile(
listofimages) + '.mosaic.X%iY%iID%i.fits' % (xx, yy, ID_number)
print 'Imgaeout: ', imageout
# STARTING WITH THE PROCESS...
# Creating "albumdata" where the whole information will be saved (MOSAIC!).
# ===================================================================================
n = 27 # Number of images to be used.
nx = 6 # Number of objects along the x-axis.
ny = 5 # Number of objects along the Y-axis.
mad = size # Size of every sub-squared-stamp. 100 is a good choice!
mad2 = mad + 1
albumdata = N.zeros((ny * mad2 + 1, nx * mad2 + 1), float)
print ' --------------------------------------------------------------------------- '
print ' A stamp size = %d x %d has been chosen ' % (mad, mad)
print ' One galaxy will be display in a %d x %d album-like image' % (nx,
ny)
print ' --------------------------------------------------------------------------- '
for i in range(len(image_list)):
# print 'i', i
ix = i % nx
iy = ny - (i / nx) - 1
image_in = image_list[i]
# It picks the ith-submatrix from the ith image.
# So, It creates every single sub-mosaic!
stamp = sta.stamping(image_in, xx, yy, mad)
ax = ix * mad2 + 1
ay = iy * mad2 + 1
# Saving the ith-submosaic in albumdata.
albumdata[ay:ay + mad, ax:ax + mad] = stamp.astype(float)
print ' Copying submosaic %i from image %i: ' % (i, i)
# Creating the new mosaic as a fits file.
fits.writeto(imageout, albumdata)
def flagging_dobledetections(cat1,cat2):
"""
This serves to append an extra column (each to both inputted catalogs)
indicating either a detection was repeated and with the lowest S/N
of the two.
Sources flagged as 1 are those detections to be excluded when combining
both catalogs into a single one.
--------
import alhambra_overlap as alhov
cat1 = '/Volumes/amb22/catalogos/reduction_v4e/f02/f02p02_colorproext_1_ISO.cat'
cat2 = '/Volumes/amb22/catalogos/reduction_v4e/f02/f02p01_colorproext_1_ISO.cat'
alhov.flagging_dobledetections(cat1,cat2)
"""
id1,ra1,dec1,x1,y1,s2n1 = U.get_data(cat1,(0,1,2,3,4,14))
id2,ra2,dec2,x2,y2,s2n2 = U.get_data(cat2,(0,1,2,3,4,14))
ne1 = len(id1)
ne2 = len(id2)
g1 = U.greater_equal(ra1,min(ra2))
g2 = U.less_equal(ra2,max(ra1))
id1r,ra1r,dec1r,x1r,y1r,s2n1r = U.multicompress(g1,(id1,ra1,dec1,x1,y1,s2n1))
id2r,ra2r,dec2r,x2r,y2r,s2n2r = U.multicompress(g2,(id2,ra2,dec2,x2,y2,s2n2))
flag1 = U.zeros(ne1)
flag2 = U.zeros(ne2)
dim1 = len(id1r)
dim2 = len(id2r)
print 'dim1,dim2',dim1,dim2
if dim1>0 and dim2>0:
print 'Matching samples....'
pepe = matching_vects_ddet(id1r,ra1r,dec1r,id2r,ra2r,dec2r,0.000312) # We use now X,Y instead RA,Dec
# Purging null elements
matchidcol = pepe[:,0].astype(int)
good_det1 = U.greater(matchidcol,0) # Excluding 0's (non matched detections)
matchidcol = U.compress(good_det1,(matchidcol))
matchidsp = pepe[:,1].astype(int)
good_det2 = U.greater(matchidsp,0) # Excluding 0's (non matched detections)
matchidsp = U.compress(good_det2,(matchidsp))
if len(matchidcol) == len(matchidsp) and len(matchidcol) >0 :
newdim = len(matchidsp)
print 'Dimension of matching',newdim
idr1 = U.zeros(newdim)
idr2 = U.zeros(newdim)
s2nr1 = U.zeros(newdim)
s2nr2 = U.zeros(newdim)
for ii in range(newdim):
idr1index = ap.id2pos(id1r,matchidcol[ii])
idr2index = ap.id2pos(id2r,matchidsp[ii])
idr1[ii] = id1r[idr1index]
s2nr1[ii] = s2n1r[idr1index]
idr2[ii] = id2r[idr2index]
s2nr2[ii] = s2n2r[idr2index]
# Select/Purge detections according to its S/N
marcador1 = U.zeros(newdim)
marcador2 = U.zeros(newdim)
for ss in range(newdim):
cociente = s2nr1[ss]/s2nr2[ss]
if cociente >= 1.: marcador1[ss] = 1.
else: marcador2[ss] = 1.
cond1 = U.less(marcador1,1)
cond2 = U.less(marcador2,1)
idr1b = U.compress(cond1,idr1)
dim1rr = len(idr1b)
idr2b = U.compress(cond2,idr2)
dim2rr = len(idr2b)
# Two new IDs (finalid1 & finalid2) are generated with
# the final elements to be included in the output catalog.
for hh1 in range(ne1):
if id1[hh1] in idr1b:
flag1[hh1] = 1
for hh2 in range(ne2):
if id2[hh2] in idr2b:
flag2[hh2] = 1
# A new smaller catalog will be created containing specz info as an extra column.
outcat1 = ap.decapfile(cat1)+'.doubledetect.cat'
outcat2 = ap.decapfile(cat2)+'.doubledetect.cat'
print 'outcat1',outcat1
print 'outcat2',outcat2
ap.appendcol(cat1,flag1,'Flag2Detected',outcat1)
ap.appendcol(cat2,flag2,'Flag2Detected',outcat2)
# Renaming files
ap.renamefile(cat1,cat1+'.old.cat')
if not os.path.exists(cat1): ap.renamefile(outcat1,cat1)
ap.renamefile(cat2,cat2+'.old.cat')
if not os.path.exists(cat2): ap.renamefile(outcat2,cat2)
else:
print 'No common sources in betwen the catalogs'
# A new smaller catalog will be created containing specz info as an extra column.
outcat1 = ap.decapfile(cat1)+'.doubledetect.cat'
outcat2 = ap.decapfile(cat2)+'.doubledetect.cat'
print 'outcat1',outcat1
print 'outcat2',outcat2
ap.appendcol(cat1,flag1*0,'Flag2Detected',outcat1)
ap.appendcol(cat2,flag2*0,'Flag2Detected',outcat2)
# Renaming files
ap.renamefile(cat1,cat1+'.old.cat')
if not os.path.exists(cat1): ap.renamefile(outcat1,cat1)
ap.renamefile(cat2,cat2+'.old.cat')
if not os.path.exists(cat2): ap.renamefile(outcat2,cat2)
def purging_dobledetections(cat1,cat2):
"""
import alhambra_overlap
from alhambra_overlap import *
cat1 = '/Volumes/amb22/catalogos/reduction_v4e/f02/f02p02_colorproext_1_ISO.cat'
cat2 = '/Volumes/amb22/catalogos/reduction_v4e/f02/f02p01_colorproext_1_ISO.cat'
purging_dobledetections(cat1,cat2)
"""
id1,ra1,dec1,x1,y1,s2n1 = U.get_data(cat1,(0,1,2,3,4,14))
id2,ra2,dec2,x2,y2,s2n2 = U.get_data(cat2,(0,1,2,3,4,14))
ne1 = len(id1)
ne2 = len(id2)
g1 = U.greater_equal(ra1,min(ra2))
g2 = U.less_equal(ra2,max(ra1))
id1r,ra1r,dec1r,x1r,y1r,s2n1r = U.multicompress(g1,(id1,ra1,dec1,x1,y1,s2n1))
id2r,ra2r,dec2r,x2r,y2r,s2n2r = U.multicompress(g2,(id2,ra2,dec2,x2,y2,s2n2))
dim1 = len(id1r)
dim2 = len(id2r)
print 'dim1,dim2',dim1,dim2
if dim1>0 and dim2>0:
print 'Matching samples....'
pepe = matching_vects_ddet(id1r,ra1r,dec1r,id2r,ra2r,dec2r,0.000312) # We use now X,Y instead RA,Dec
# Purging null elements
matchidcol = pepe[:,0].astype(int)
good_det1 = U.greater(matchidcol,0) # Excluding 0's (non matched detections)
matchidcol = U.compress(good_det1,(matchidcol))
matchidsp = pepe[:,1].astype(int)
good_det2 = U.greater(matchidsp,0) # Excluding 0's (non matched detections)
matchidsp = U.compress(good_det2,(matchidsp))
if len(matchidcol) == len(matchidsp) and len(matchidcol) >0 :
newdim = len(matchidsp)
print 'Dimension of matching',newdim
idr1 = U.zeros(newdim)
idr2 = U.zeros(newdim)
s2nr1 = U.zeros(newdim)
s2nr2 = U.zeros(newdim)
for ii in range(newdim):
idr1index = ap.id2pos(id1r,matchidcol[ii])
idr2index = ap.id2pos(id2r,matchidsp[ii])
idr1[ii] = id1r[idr1index]
s2nr1[ii] = s2n1r[idr1index]
idr2[ii] = id2r[idr2index]
s2nr2[ii] = s2n2r[idr2index]
# Select/Purge detections according to its S/N
marcador1 = U.zeros(newdim)
marcador2 = U.zeros(newdim)
for ss in range(newdim):
cociente = s2nr1[ss]/s2nr2[ss]
if cociente >= 1.: marcador1[ss] = 1.
else: marcador2[ss] = 1.
cond1 = U.less(marcador1,1)
cond2 = U.less(marcador2,1)
idr1b = U.compress(cond1,idr1)
dim1rr = len(idr1b)
idr2b = U.compress(cond2,idr2)
dim2rr = len(idr2b)
print ''
print 'Number of detections to be removed from cat1: ', dim1rr
print 'Number of detections to be removed from cat2: ', dim2rr
print ''
# Two new IDs (finalid1 & finalid2) are generated with
# the final elements to be included in the output catalog.
finalid1 = U.zeros((ne1-dim1rr))
finalid2 = U.zeros((ne2-dim2rr))
kk1 = 0
for hh1 in range(ne1):
if id1[hh1] not in idr1b:
finalid1[kk1] = id1[hh1]
kk1 += 1
print 'kk1',kk1
kk2 = 0
for hh2 in range(ne2):
if id2[hh2] not in idr2b:
if kk2 <= (ne2-dim2rr-1):
finalid2[kk2] = id2[hh2]
kk2+=1
print 'kk2',kk2
# A new smaller catalog will be created containing specz info as an extra column.
outcat1 = ap.decapfile(cat1)+'.wo2detect.cat'
outcat2 = ap.decapfile(cat2)+'.wo2detect.cat'
print 'outcat1',outcat1
print 'outcat2',outcat2
ap.select_rows_bylist(cat1,finalid1,outcat1)
ap.select_rows_bylist(cat2,finalid2,outcat2)
else:
print 'No common sources in betwen the catalogs'
def alhambra_multiple_mosaic(listaids):
"""
----------
import os,sys
import useful as U
import alhambra_photools as alh
import alhambra_mosaics as alhmos
idlist = '/Users/albertomolino/doctorado/photo/programas/mosaico.list'
alhmos.alhambra_multiple_mosaic(idlist)
"""
size = 20 # 100 # cell's size for mosaic image
resol = 1
single = 1
wavel = 0
ids0 = U.get_str(listaids, 0)
ids = ids0[::resol]
print 'Starting with the sample selection...'
dim = len(ids)
print 'dimension: ', dim
file1name = alh.decapfile(listaids) + 'Bcolor.list'
file2name = alh.decapfile(listaids) + 'Rcolor.list'
file3name = alh.decapfile(listaids) + 'zcolor.list'
if not os.path.exists(file1name) and not os.path.exists(
file2name) and not os.path.exists(file3name):
file1 = open(file1name, 'w')
file2 = open(file2name, 'w')
file3 = open(file3name, 'w')
ff = 0
pp = 0
cc = 0
for ii in range(dim):
idi = ids[ii]
field = int(idi[3:4])
pointing = int(idi[4:5])
ccd = int(idi[5:6])
yo = int(idi[6:]) * 1
# print 'Looking for ID: %s'%ids[ii]
image1 = root_images + 'f0%i/f0%ip0%i_B_Subaru_%i.swp.fits' % (
field, field, pointing, ccd)
image2 = root_images + 'f0%i/f0%ip0%i_R_Subaru_%i.swp.fits' % (
field, field, pointing, ccd)
image3 = root_images + 'f0%i/f0%ip0%i_F814W_%i.swp.fits' % (
field, field, pointing, ccd)
# print field,ff
# print pointing,pp
# print ccd,cc
if field != ff and pointing != pp and ccd != cc:
# print 'reading new catalog'
# catalog = '/Users/albertomolino/doctorado/photo/catalogos/reduction_v4f/alhambra.F0%iP0%iC0%i.ColorProBPZ.cat'%(field,field,pointing,ccd)
catalog = root_catalogs + 'f0%i/alhambra.F0%iP0%iC0%i.ColorProBPZ.cat' % (
field, field, pointing, ccd)
# print catalog
idd = U.get_str(catalog, 0)
ne = len(idd)
x, y, mo = U.get_data(catalog, (6, 7, 65))
# Sorting detections by magnitude.
idd, x, y = U.multisort(mo, (idd, x, y))
pos = N.where(idd == idi)[0][0]
# for ss in range(ne):
# # print idd[ss]
# # if idd[ss]==idi:
# if idi[0] in idd:
# pos = ss
if pos != -1:
xx = int(round(x[pos]))
yy = int(round(y[pos]))
line1 = '%s %i %i %i %i %i\n' % (image1, xx, yy, field,
pointing, ccd)
# print line1
file1.write(line1)
line2 = '%s %i %i %i %i %i\n' % (image2, xx, yy, field,
pointing, ccd)
# print line2
file2.write(line2)
line3 = '%s %i %i %i %i %i\n' % (image3, xx, yy, field,
pointing, ccd)
# print line3
file3.write(line3)
else:
print 'ID not found...'
ff == field
pp == pointing
cc == ccd
file1.close()
file2.close()
file3.close()
print 'Sample reading completed'
print 'Starting with mosaic...'
nt = dim
valor = U.sqrt(dim)
nx = int(round(valor))
ny = int(U.ceil(valor))
imageout1 = alh.decapfile(file1name) + '.mosaic.fits'
if not os.path.exists(imageout1):
file1name = alh.decapfile(listaids) + 'Bcolor.list'
ims1 = U.get_str(file1name, 0)
x1, y1, field1, pointing1, ccd1 = U.get_data(file1name,
(1, 2, 3, 4, 5))
if single:
alhmos.singlemosaico(ims1, x1, y1, size, nt, nx, ny, imageout1)
if wavel:
alhmos.singlemosaico_pro(ims1, x1, y1, field1, pointing1, ccd1,
size, nt, 24, nt, imageout1)
imageout2 = alh.decapfile(file2name) + '.mosaic.fits'
if not os.path.exists(imageout2):
file2name = alh.decapfile(listaids) + 'Rcolor.list'
ims2 = U.get_str(file2name, 0)
x2, y2, field2, pointing2, ccd2 = U.get_data(file2name,
(1, 2, 3, 4, 5))
if single:
alhmos.singlemosaico(ims2, x2, y2, size, nt, nx, ny, imageout2)
if wavel:
alhmos.singlemosaico_pro(ims2, x2, y2, field2, pointing2, ccd2,
size, nt, 24, nt, imageout2)
imageout3 = alh.decapfile(file3name) + '.mosaic.fits'
if not os.path.exists(imageout3):
file3name = alh.decapfile(listaids) + 'zcolor.list'
ims3 = U.get_str(file3name, 0)
x3, y3, field3, pointing3, ccd3 = U.get_data(file3name,
(1, 2, 3, 4, 5))
if single:
alhmos.singlemosaico(ims3, x3, y3, size, nt, nx, ny, imageout3)
if wavel:
alhmos.singlemosaico_pro(ims3, x3, y3, field3, pointing3, ccd3,
size, nt, 24, nt, imageout3)
if os.path.exists(imageout1) and os.path.exists(
imageout2) and os.path.exists(imageout3):
alhmos.trilogy_alhambra_multiple_mosaic(imageout1, imageout2,
imageout3)