def georun_sky(clustname, lims):
#run geomap and geoxytran. I have to run this within this module
#as geomap crashes when run from an external module.
#in this version
catpath = '.'
geomap_infile = catpath + '/geomap_coords_sky.' + clustname + '.in'
dbfile = catpath + '/' + clustname + '_geomap_sky.db'
iraf.geomap.xmin = lims['ramin']
iraf.geomap.xmax = lims['ramax']
iraf.geomap.ymin = lims['decmin']
iraf.geomap.ymax = lims['decmax']
iraf.geomap.maxiter = 3
iraf.geomap.reject = 3.0
iraf.geomap.fitgeometry = 'rxyscale'
iraf.geomap(geomap_infile, dbfile)
geotran_outfile = catpath + '/geomap_coords_sky.' + clustname + '.out'
#remove geotran output file if it already exists
if os.path.isfile(geotran_outfile) is True:
cmdstr = 'rm ' + geotran_outfile
os.system(cmdstr)
#transform the input coordinates in the geomap input file.
iraf.geoxytran(geomap_infile,
geotran_outfile,
dbfile,
geomap_infile,
direction="backward",
xcolumn=3,
ycolumn=4)
#read in the geomap input catalog that was transformed using geoxytran.
trans_ggdat = ascii.read(geotran_outfile)
ratrans = trans_ggdat['rain']
dectrans = trans_ggdat['decin']
raref = trans_ggdat['raref']
decref = trans_ggdat['decref']
#make a plot of the new residuals
posttrans_plotfile = catpath + '/posttrans.' + clustname + '_coordiff_sky.pdf'
cmts.match_diff_sky_plot(raref,
decref,
ratrans,
dectrans,
plotfile=posttrans_plotfile)
return dbfile, geomap_infile
def mosfire_geoxytrans(x_kfp,
y_kfp,
transform="final.pix2mm.4.972.120k",
database="ale/10March2011.4.972.db",
direction="forward"):
'''Conveninece wrapper around IRAF geoxytran'''
iraf.images()
path = os.path.join(os.environ["MOSPATH"], "platescale",
"10March2011.4.972.db")
database = path
pars = iraf.geoxytran.getParList()
iraf.geoxytran.unlearn()
ins = []
for i in range(len(x_kfp)):
ins.append("%f %f" % (x_kfp[i], y_kfp[i]))
results = iraf.geoxytran("STDIN",
"STDOUT",
Stdin=ins,
Stdout=1,
database=database,
transform=transform,
direction=direction)
iraf.geoxytran.setParList(pars)
poss = []
for result in results:
poss.append(np.array(result.split(), dtype=np.float64))
return np.array(poss)
def mosfire_geoxytran(x_kfp,
y_kfp,
transform="final.pix2mm.4.972.120k",
database="/platescale/10March2011.4.972.db",
direction="forward"):
'''Conveninece wrapper around IRAF geoxytran'''
iraf.images()
path = os.path.join(os.environ["MOSPATH"], "platescale",
"10March2011.4.972.db")
database = path
pars = iraf.geoxytran.getParList()
iraf.geoxytran.unlearn()
t = iraf.geoxytran("STDIN",
"STDOUT",
Stdin=["%f %f" % (x_kfp, y_kfp)],
Stdout=1,
database=database,
transform=transform,
direction=direction)
iraf.geoxytran.setParList(pars)
(x, y) = np.array(t[0].split(), dtype=np.float64)
return (x, y)
def mosfire_geoxytran(x_kfp, y_kfp, transform="final.pix2mm.4.972.120k",
database="/platescale/10March2011.4.972.db", direction="forward"):
'''Conveninece wrapper around IRAF geoxytran'''
iraf.images()
path = os.path.join(os.environ["MOSPATH"], "platescale",
"10March2011.4.972.db")
database = path
pars = iraf.geoxytran.getParList()
iraf.geoxytran.unlearn()
t = iraf.geoxytran("STDIN", "STDOUT", Stdin=["%f %f" % (x_kfp, y_kfp)], Stdout=1,
database=database,
transform=transform,
direction=direction)
iraf.geoxytran.setParList(pars)
(x,y) = np.array(t[0].split(), dtype=np.float64)
return (x,y)
def mosfire_geoxytrans(
x_kfp, y_kfp, transform="final.pix2mm.4.972.120k", database="ale/10March2011.4.972.db", direction="forward"
):
"""Conveninece wrapper around IRAF geoxytran"""
iraf.images()
path = os.path.join(os.environ["MOSPATH"], "platescale", "10March2011.4.972.db")
database = path
pars = iraf.geoxytran.getParList()
iraf.geoxytran.unlearn()
ins = []
for i in range(len(x_kfp)):
ins.append("%f %f" % (x_kfp[i], y_kfp[i]))
results = iraf.geoxytran(
"STDIN", "STDOUT", Stdin=ins, Stdout=1, database=database, transform=transform, direction=direction
)
iraf.geoxytran.setParList(pars)
poss = []
for result in results:
poss.append(np.array(result.split(), dtype=np.float64))
return np.array(poss)
def speczcat_trans_sky(incat, dbfile, geomap_infile, refcat, clustname, septol,
**kwargs):
'''This routine reads in a FITS catalog, writes a temporary output
ASCII catalog, then transforms this catalog using geoxytran. It
then writes a new catalog with old coordinates replaced by the new ones.
INPUT
incat: the input fits catalog
dbfile: the geomap database file
geomap_infile: used as the database record
refcat: the original astrometric reference catalog
clustname: the name of the cluster
septol: the maximum separation allowed for a match in arcseconds
OPTIONAL KEYWORDS
ramin, ramax, decmin, decmax. These are the limits over which the
transform was originally computed. If these are given then it
uses those limits to color the points in the ra and decdiff plots.
If one is given, all must be given.
'''
#read in the spectroscopic redshift catalog
cat_hdul = fits.open(incat)
cat_dat = cat_hdul["MDF"].data
#read in original astrometric catalog
ref_dat = ascii.read(refcat)
raref = np.array(ref_dat['ALPHA_SKY'])
decref = np.array(ref_dat['DELTA_SKY'])
#tmp coordinate files for geoxytran
tmpin = 'tmp_geoxytran_sky_in'
tmpout = 'tmp_geoxytran_sky_out'
#remove the existing transformed file
newcat = incat.replace('.fits', '.trans.fits')
if os.path.isfile(tmpout) is True:
cmdstr = 'rm ' + tmpout
os.system(cmdstr)
cmdstr = 'rm ' + newcat
os.system(cmdstr)
#output temporary ASCII file with coordinates
fo = open(tmpin, "w")
fo.write("# ra dec\n")
for i, val in enumerate(cat_dat['RA']):
#convert speczcat RA to degrees when writing out
fo.write('{} {}\n'.format(cat_dat['RA'][i] * 15.0, cat_dat['DEC'][i]))
fo.close()
iraf.geoxytran(tmpin, tmpout, dbfile, geomap_infile, direction="backward",\
xcolumn=1, ycolumn = 2)
#read in ascii output file
trans_dat = ascii.read(tmpout)
ratrans = np.array(trans_dat['ra'])
dectrans = np.array(trans_dat['dec'])
#replace the old RAs and DECs with new RAs and DECs in place
tcat_hdul = cat_hdul
#convert RA back to hours for output
tcat_hdul["MDF"].data['RA'] = ratrans / 15.0
tcat_hdul["MDF"].data['DEC'] = dectrans
#write the new fits file
tcat_hdul.writeto(newcat)
#match new catalog against original catalog
mfile = "speczcat_sky_match.txt"
(rarefm,decrefm,ratransm,dectransm, translims) = cmts.cat_sky_match(raref, decref, \
ratrans, dectrans, septol, \
matchfile = mfile)
#make a plot of the residuals
allcattrans_plotfile = 'speczcat_trans.' + clustname + '_coordiff_sky.pdf'
#passes ra and dec limits if they are defined to find source
#outside of ra and dec lims. Assumes that if one keyword is given
#that all are given
if 'ramin' in kwargs.keys():
cmts.match_diff_sky_plot(rarefm,decrefm,ratransm,dectransm, plotfile = allcattrans_plotfile, \
ramin = kwargs['ramin'], ramax = kwargs['ramax'], \
decmin = kwargs['decmin'], decmax = kwargs['decmax'])
else:
cmts.match_diff_sky_plot(rarefm,
decrefm,
ratransm,
dectransm,
plotfile=allcattrans_plotfile)
def cat_trans_im(incat, dbfile, geomap_infile, refcat, clustname, septol, **kwargs):
'''This routine reads in a FITS catalog, writes a temporary output
ASCII catalog, then transforms this catalog using geoxytran. It
then appends these new coordinates as new columns to the original catalog.
It is usually run by hand after the geomap solution has been derived.
INPUT
incat: the input SExtractor catalog
dbfile: the geomap database file
geomap_infile: used as the database record
refcat: the original astrometric reference catalog
clustname: the name of the cluster
septol: the maximum separation allowed for a match in pixels
OPTIONAL KEYWORDS
xmin, xmax, ymin, ymax. These are the limits over which the
transform was originally computed. If these are given then it
uses those limits to color the points in the ra and decdiff plots.
If one is given, all must be given.
'''
#read in GMOS sextractor photometry catalog with (x,y) coordinates
cat_dat = ascii.read(incat)
#read in original astrometric catalog
ref_dat = ascii.read(refcat)
xref = np.array(ref_dat['X_IMAGE'])
yref = np.array(ref_dat['Y_IMAGE'])
#tmp coordinate files for geoxytran
tmpin = 'tmp_geoxytran_im_in'
tmpout = 'tmp_geoxytran_im_out'
#make a new name for the transformed file
newcat = incat.replace('.sexcat','.trans.cat')
if os.path.isfile(tmpout) is True:
cmdstr = 'rm ' + tmpout
os.system(cmdstr)
cmdstr = 'rm ' + newcat
os.system(cmdstr)
#output temporary ASCII file with coordinates
fo = open(tmpin, "w")
fo.write("# x y\n")
for i,val in enumerate(cat_dat['X_IMAGE']):
fo.write('{} {}\n'.format(cat_dat['X_IMAGE'][i],cat_dat['Y_IMAGE'][i]))
fo.close()
iraf.geoxytran(tmpin, tmpout, dbfile, geomap_infile, direction="backward",\
xcolumn=1, ycolumn = 2)
#read in ascii output file
trans_dat = ascii.read(tmpout)
xtrans = np.array(trans_dat['x'])
ytrans = np.array(trans_dat['y'])
#replace the old RAs and DECs with new RAs and DECs in place
tcat_dat = cat_dat
tcat_dat['X_IMAGE'] = xtrans
tcat_dat['Y_IMAGE'] = ytrans
#write the new catalog file with the transformed coordinates
ascii.write(tcat_dat, newcat, format='commented_header')
#match new catalog against original catalog
mfile = "allcat_im_match.txt"
(xrefm,yrefm,xtransm,ytransm, translims) = cmti.cat_im_match(xref, yref, \
xtrans, ytrans, septol, \
matchfile = mfile)
#make a plot of the residuals
allcattrans_plotfile = 'allcat_trans.' + clustname + '_coordiff_im.pdf'
#passes ra and dec limits if they are defined to find source
#outside of ra and dec lims. Assumes that if one keyword is givenSPT0205_GMOS_z.v0.sexcat'
#that all are given
if 'xmin' in kwargs.keys():
cmti.match_diff_im_plot(xrefm,yrefm,xtransm,ytransm, plotfile = allcattrans_plotfile, \
xmin = kwargs['xmin'], xmax = kwargs['xmax'], \
ymin = kwargs['ymin'], ymax = kwargs['ymax'])
else:
cmti.match_diff_im_plot(xrefm,yrefm,xtransm,ytransm, plotfile = allcattrans_plotfile)
def speczcat_trans_sky(incat, dbfile, geomap_infile, refcat, clustname, septol,
**kwargs):
'''This routine reads in a FITS catalog, writes a temporary output
ASCII catalog, then transforms this catalog using geoxytran. It
then writes a new catalog with old coordinates replaced by the new ones.
INPUT
incat: the input fits catalog
dbfile: the geomap database file
geomap_infile: used as the database record
refcat: the original astrometric reference catalog
clustname: the name of the cluster
septol: the maximum separation allowed for a match in arcseconds
OPTIONAL KEYWORDS
ramin, ramax, decmin, decmax. These are the limits over which the
transform was originally computed. If these are given then it
uses those limits to color the points in the ra and decdiff plots.
If one is given, all must be given.
'''
#read in the spectroscopic redshift catalog
cat_hdul = fits.open(incat)
cat_dat = cat_hdul["MDF"].data
#read in original astrometric catalog
#assume that this is a GAIA VOTable
votable = parse(refcat)
table = votable.get_first_table()
ref_dat = table.array
#convert masked arrays to normal arrays
raref = np.array(ref_dat['RA_ICRS'])
decref = np.array(ref_dat['DE_ICRS'])
#ref_dat = ascii.read(refcat)
#raref = np.array(ref_dat['ALPHA_SKY'])
#decref = np.array(ref_dat['DELTA_SKY'])
#tmp coordinate files for geoxytran
tmpin = 'tmp_geoxytran_sky_in'
tmpout = 'tmp_geoxytran_sky_out'
#remove the existing transformed file
newcat = incat.replace('.fits', '.trans.fits')
if os.path.isfile(tmpout) is True:
cmdstr = 'rm ' + tmpout
os.system(cmdstr)
cmdstr = 'rm ' + newcat
os.system(cmdstr)
#output temporary ASCII file with coordinates
fo = open(tmpin, "w")
fo.write("# ra dec\n")
for i, val in enumerate(cat_dat['RA']):
#convert speczcat RA to degrees when writing out
fo.write('{} {}\n'.format(cat_dat['RA'][i] * 15.0, cat_dat['DEC'][i]))
fo.close()
iraf.geoxytran(tmpin, tmpout, dbfile, geomap_infile, direction="backward",\
xcolumn=1, ycolumn = 2)
#read in ascii output file
trans_dat = ascii.read(tmpout)
ratrans = np.array(trans_dat['ra'])
dectrans = np.array(trans_dat['dec'])
#replace the old RAs and DECs with new RAs and DECs in place
tcat_hdul = cat_hdul
#convert RA back to hours for output
tcat_hdul["MDF"].data['RA'] = ratrans / 15.0
tcat_hdul["MDF"].data['DEC'] = dectrans
#write the new fits file
tcat_hdul.writeto(newcat)
def transformcoords(im1, im2):
checkxy = 1
infile = '/Users/rfinn/clusters/spitzer/Mastertables/' + prefix + 'mastertable24.dat'
input = open(infile, 'r')
i = 0
k = 0
era = [] #ediscs ra
edec = [] #ediscs dec
excorr = [] #ediscs x pixel position
eycorr = [] #ediscs y pixel position
for line in input:
if line.find('#') > -1: #skip lines with '#' in them
continue
if line.find('\\') > -1: #skip lines with '#' in them
continue
if line.find('|') > -1: #skip lines with '#' in them
continue
t = line.split() #break up columns & save ra and dec
era.append(float(t[1]))
edec.append(float(t[2]))
excorr.append(float(t[3]))
eycorr.append(float(t[4]))
input.close()
era = N.array(era, 'd')
edec = N.array(edec, 'd')
excorr = N.array(excorr, 'd')
eycorr = N.array(eycorr, 'd')
output = prefix + 'radec.dat'
out1 = open(output, 'w')
for i in range(len(era)):
s = "%14.10f %14.10f \n" % (era[i], edec[i])
out1.write(s)
out1.close()
output = prefix + '-ediscsxy.dat' #now contains xcorr, ycorr
out1 = open(output, 'w')
for i in range(len(era)):
s = "%14.10f %14.10f \n" % (excorr[i], eycorr[i])
out1.write(s)
out1.close()
#transform ra and dec to x and y coords on ediscs image using ediscs i band image
#write era and edec to a file
outfile = output
#outfile=prefix+'-ediscsxy.dat'#file containing x and y pixels values on ediscs iband image
#iraf.wcsctran(output,outfile,image=im2,inwcs='world',outwcs='physical',columns='1 2', verbose='no')
if checkxy > 0:
iraf.display(im2, 1, fill='yes')
iraf.tvmark(1, outfile, color=204, radii=15)
#iraf.tvmark(1,output,color=204,radii=15)#plot xcorr and ycorr instead of transformed coordinates
flag = raw_input("Enter 0 to terminate now or 1 to continue \n")
if flag < 0.1:
return
dbase = prefix + '-match-geomap'
outfile2 = prefix + '-GMOSxy.dat' #file containing x and y pixels values on gmos image
iraf.geoxytran(outfile,
output=outfile2,
database=dbase,
transform='gmos',
direction='backward')
if checkxy > 0:
iraf.display(im1, 2, fill='yes')
iraf.tvmark(2, outfile2, color=204, radii=15)
im3 = 'g' + im2
iraf.display(im3, 3, fill='yes')
iraf.tvmark(3, outfile2, color=204, radii=15)
flag = raw_input("Enter anything to continue \n")