def addwenss(aipsname,
indisk,
ra,
dec,
maxoff,
pmin,
pmax,
w_max=1000.,
incl='IMAP'):
if have_astLib:
wenss = np.load('wenss2000.npy')
wenss = wenss[wenss[:, 2] < 2] # only single or centre of multiple
wenss = wenss[wenss[:, 3] > w_max] # only sources >w_max mJy
a = correlate(np.array([[ra, dec]]), 0, 1, wenss, 0, 1, maxoff)
fo = open('starsfile', 'w')
for i in a:
idx = int(i[1])
sra = astCoords.decimal2hms(wenss[idx, 0], ' ')
sdec = astCoords.decimal2dms(wenss[idx, 1], ' ')
fo.write('%s %s\n' % (sra, sdec))
fo.close()
stars(aipsname,
incl,
indisk,
intext='./starsfile',
logfiledir=logfiledir)
greys(aipsname, incl, indisk, pmin, pmax, 5, 1, logfiledir=logfiledir)
lwpla(aipsname,
incl,
indisk,
'./' + aipsname + '_plot.ps',
logfiledir=logfiledir)
AIPSImage(aipsname, incl, indisk, 1).zap()
os.system('rm starsfile')
def read_secat(catfile, fitsfile, logfile=False, wcs=False):
patchtable = [[] for dummy in xrange(3)] #ra, dec, NHI
#Must catch empty catalog file:
try: #Call will fail if the catalog file is empty or does not have the expected format
catalog = se_catalog(catfile, readfile=True, preserve_case=False)
except:
print "Warning: no clumps found. Creating empty entry."
patchtable[0].append(0), patchtable[1].append(0)
patchtable[2].append(0)
return patchtable
records = len(catalog.alphapeak_j2000)
header, image = open_image(fitsfile)
for n in range(records):
a, d = catalog.alphapeak_j2000[n], catalog.deltapeak_j2000[n]
x, y = header.wcs2pix(a, d)
x = int(np.round(x))
y = int(np.round(y))
maxHI = image[y, x]
print "a,d: ", a, d, "x,y: ", x, y, "value: ", maxHI #no offset? Verify!!
patchtable[0].append(astCoords.decimal2hms(a, " "))
patchtable[1].append(astCoords.decimal2dms(d, " "))
patchtable[2].append(maxHI)
#patchtable[3].append(0.1) #error now calculated after calling this routine
#print "Warning: hardcoding sNHI at 0.1"
logdump(logfile, "{} {} {}\n".format(a, d, maxHI))
return patchtable #calling function administrates PDRID
def _outputMinima(self):
"""
Outputs the results to a file and also to the screen if debugging was turned on.
"""
if 'chi' in self.fitting['method']:
str = '{0:.2f}\t{1:.0f}\t{2:.0f}\t{3:.0f}\t{4:.0f}\t{5:.2f}\t\t{6:.2f}\n'.format(self.result['rotation'],
self.result['xcenter'],
self.result['ycenter'],
self.result['x'],
self.result['y'],
self.result[
'minimaPosition'][3],
self.result[
'minimaPosition'][4])
elif 'corr' in self.fitting['method']:
str = '{0:.2f}\t{1:.0f}\t{2:.0f}\t{3:.0f}\t{4:.0f}\t{5:.5f}\n'.format(self.result['rotation'],
self.result['xcenter'],
self.result['ycenter'],
self.result['x'],
self.result['y'],
self.result['minimaPosition'][6])
else:
raise NotImplementedError, 'This minimization method has not yet been implemented...'
fh1 = open('min.txt', 'a')
fh1.write(str)
fh1.close()
if self.debug:
if 'chi' in self.fitting['method']:
print '\n\nr \t x \t y \txoff \tyoff \tchi**2 reduced chi**2'
elif 'corr' in self.fitting['method']:
print '\n\nr \t x \t y \txoff \tyoff \tcorrelation coefficient'
else:
raise NotImplementedError, 'This minimization method has not yet been implemented...'
print str
print '\nInitial RA and DEC (of the centre of the centre slit)'
print astCoords.decimal2hms(self.result['RAinit'], ':'), astCoords.decimal2dms(self.result['DECinit'], ':')
print '\nFinal RA and DEC (of the centre of the centre slit)'
print astCoords.decimal2hms(self.result['RA'], ':'), astCoords.decimal2dms(self.result['DEC'], ':')
print '\nDistance on the sky (in arcseconds)'
print astCoords.calcAngSepDeg(self.result['RAinit'],
self.result['DECinit'],
self.result['RA'],
self.result['DEC']) * 3600
def work(outpath, ra, dec, name):
ra_sex = decimal2hms(ra, ':')
dec_sex = decimal2dms(dec, ':')
cmd = 'panstamps --width=40 --filters grizy '
cmd += f'--downloadFolder={outpath}/{name} stack {ra_sex} {dec_sex}'
print(cmd)
p = subprocess.Popen(shlex.split(cmd))
p.wait()
def info(self,showHeader=False):
"""
@brief pretty print informstion sbout the litMap
"""
arcmin = 180*60./np.pi
print "Dimensions (Ny,Nx) = (%d,%d)"%(self.Ny,self.Nx)
print "Pixel Scales: (%f,%f) arcmins. "%(self.pixScaleY*arcmin,self.pixScaleX*arcmin)
print "Map Bounds: [(x0,y0), (x1,y1)]: [(%f,%f),(%f,%f)] (degrees)"%(self.x0,self.y0,self.x1,self.y1)
print "Map Bounds: [(x0,y0), (x1,y1)]: [(%s,%s),(%s,%s)]"%\
(astCoords.decimal2hms(self.x0,':'),\
astCoords.decimal2dms(self.y0,':'),\
astCoords.decimal2hms(self.x1,':'),\
astCoords.decimal2dms(self.y1,':'))
print "Map area = %f sq. degrees."%(self.area)
print "Map mean = %f"%(self.data.mean())
print "Map std = %f"%(self.data.std())
if showHeader:
print "Map header \n %s"%(self.header)
def info(self,showHeader=False):
"""
@brief pretty print informstion sbout the litMap
"""
arcmin = 180*60./np.pi
print "Dimensions (Ny,Nx) = (%d,%d)"%(self.Ny,self.Nx)
print "Pixel Scales: (%f,%f) arcmins. "%(self.pixScaleY*arcmin,self.pixScaleX*arcmin)
print "Map Bounds: [(x0,y0), (x1,y1)]: [(%f,%f),(%f,%f)] (degrees)"%(self.x0,self.y0,self.x1,self.y1)
print "Map Bounds: [(x0,y0), (x1,y1)]: [(%s,%s),(%s,%s)]"%\
(astCoords.decimal2hms(self.x0,':'),\
astCoords.decimal2dms(self.y0,':'),\
astCoords.decimal2hms(self.x1,':'),\
astCoords.decimal2dms(self.y1,':'))
print "Map area = %f sq. degrees."%(self.area)
print "Map mean = %f"%(self.data.mean())
print "Map std = %f"%(self.data.std())
if showHeader:
print "Map header \n %s"%(self.header)
def writeDS9(nodes,regionfile):
f = open(regionfile,'w')
f.write('# Region file format: DS9 version 4.1\n')
f.write('global color=green dashlist=8 3 width=1 font="helvetica 10 normal roman" select=1 highlite=1 dash=0 fixed=0 edit=1 move=1 delete=1 include=1 source=1\n')
f.write('fk5\n')
for i in range(0,len(nodes)):
ra = nodes[i][0]
dec = nodes[i][1]
ra_hms = ac.decimal2hms(ra,delimiter=':')
dec_dms = ac.decimal2dms(dec,delimiter=':')
f.write('circle('+ra_hms+','+dec_dms+',1.0)\n')
f.close()
def create_lobos_ms (infile='',ra='',dec='',nP=3,radius=2.5):
infile='L401323_SB349_uv.dppp.MS'
ra,dec,radius,nP='13:40:00','55:00:00',2.5,3
try: # ra, dec input can either be decimal or hh:mm:ss, dd:mm:ss
ra, dec = 1.0*ra, 1.0*dec
hexra = astCoords.decimal2hms(ra,':')
hexdec = astCoords.decimal2dms(dec,':')
except:
hexra, hexdec = ra, dec
ra = astCoords.hms2decimal(ra,':')
dec = astCoords.dms2decimal(dec,':')
if not os.path.isfile ('lobos_stats.sum'):
os.system ('wget http://www.jb.man.ac.uk/~njj/lobos_stats.sum')
lobos = np.loadtxt('lobos_stats.sum',dtype='S')
for l in lobos:
new = np.array([astCoords.hms2decimal(l[1],':'),\
astCoords.dms2decimal(l[2],':')])
try:
lobos_coord = np.vstack((lobos_coord,new))
except:
lobos_coord = np.copy(new)
a = correlate(np.array([[ra,dec]]),0,1,lobos_coord,0,1,radius)
nlobos = 0
os.system('rm lshift_*')
for i in np.asarray(a[:,1],dtype='int'):
if lobos[i][5].count('P')>=nP:
oroot = infile.replace('uv.dppp.MS','')
namera = lobos[i,1].replace(':','').split('.')[0]
namedec = lobos[i,2].replace(':','').split('.')[0]
dpppra = lobos[i,1].replace(':','h',1).replace(':','m',1)+'s'
dpppdec = lobos[i,2].replace(':','d',1).replace(':','m',1)+'s'
hemisphere = '-' if '-' in hexdec else '+'
f = open('lshift_%03d'%nlobos, 'w')
f.write('msin = '+infile+'\n')
f.write('msout = '+oroot+namera+hemisphere+namedec+'.ms\n')
f.write('msin.datacolumn = DATA\n')
f.write('steps = [shift,adder,filter,avg]\n')
f.write('shift.type = \'phaseshift\'\n')
f.write('shift.phasecenter = [\''+dpppra+'\',\''+dpppdec+'\']\n')
f.write('adder.type = \'stationadder\'\n')
f.write('adder.stations = {TS001:\'CS*\'}\n')
f.write('filter.type = \'filter\'\n')
f.write('filter.baseline = \'!CS*&*\'\n')
f.write('avg.type = average\n')
f.write('avg.freqstep = 16\n')
f.write('avg.timestep = 20\n')
f.close()
nlobos+=1
lshift_thread.parallel = parallel_function(lshift_thread)
k = range(nlobos)
parallel_result = lshift_thread.parallel(k)
def addwenss (aipsname,indisk,ra,dec,maxoff,pmin,pmax,w_max=1000.,incl='IMAP'):
if have_astLib:
wenss = np.load('wenss2000.npy')
wenss = wenss[wenss[:,2]<2] # only single or centre of multiple
wenss = wenss[wenss[:,3]>w_max] # only sources >w_max mJy
a = correlate (np.array([[ra,dec]]),0,1,wenss,0,1,maxoff)
fo = open('starsfile','w')
for i in a:
idx = int(i[1])
sra = astCoords.decimal2hms(wenss[idx,0],' ')
sdec = astCoords.decimal2dms(wenss[idx,1],' ')
fo.write('%s %s\n' % (sra,sdec))
fo.close()
stars (aipsname,incl,indisk,intext='./starsfile',logfiledir=logfiledir)
greys (aipsname,incl,indisk,pmin,pmax,5,1,logfiledir=logfiledir)
lwpla (aipsname,incl,indisk,'./'+aipsname+'_plot.ps',logfiledir=logfiledir)
AIPSImage(aipsname,incl,indisk,1).zap()
os.system('rm starsfile')
def first_download (ra,dec,outfile='',gif=0,fits=1,imsize=2.0,\
imserver='third.ucllnl.org'):
format = 'hms'
try:
if np.isreal(ra):
format = 'decimal'
except:
pass
if format=='decimal':
ra=astCoords.decimal2hms(ra,' ')
dec=astCoords.decimal2dms(dec,' ')
if outfile=='':
outfile=ra.replace(' ','')+dec.replace(' ','')
outfile=outfile + ('.fits' if fits==1 else '.gif')
ra=ra.split()
dec=dec.split()
command = ('wget -O %s "http://%s/cgi-bin/firstimage?RA=%s%%20%s%%20%s%%20%s%%20%s%%20%s&Dec=&Equinox=J2000&ImageSize=%.1f&MaxInt=10&GIF=%d&FITS=%d&Download=1"'%(outfile,imserver,ra[0],ra[1],ra[2],dec[0],dec[1],dec[2],imsize,gif,fits))
print (command)
os.system(command)
def wcslabels(wcs, xlim, ylim, xsep='00:00:01', ysep='00:00:15',
ax=None, label_color='k', rotate_x=0, rotate_y=90):
"""
Get WCS ticklabels
Parameters
----------
wcs : astWCS.WCS instance
the wcs of the image to be shown
xlim : sequence of length 2
the minimum and maximum values of the x axis
ylim : sequence of length 2
the minimum and maximum values of the y axis
xsep : string
separation of right ascension ticks in the x axis,
in colon-separated hms format
xsep : string
separation of declination ticks in the y axis, in
colon-separated dms format
ax : matplotlib.Axes instance (optional)
if provided, the ticks will be displayed on it
label_color : string or matplotlib color
color with which the tick labels will be displayed,
if ax is provided
rotate_x : float
by how much to rotate the x tick labels if ax is
provided
rotate_y : float
by how much to rotate the y tick labels if ax is
provided
Returns
-------
[xticks, xticklabels] : lists containing the positions and
labels for right ascension hms labels
[yticks, yticklabels] : lists containing the positions and
labels for declination dms labels
"""
def format_wcs(x):
"""
replace the 60's for 0's and change other values consistently,
and add 0's at the beginning of single-digit values
"""
x = x.split(':')
x[2] = round(float(x[2]), 0)
x[2] = '{0:.0f}'.format(x[2]) if x[2] >= 10 \
else '0{0:.0f}'.format(x[2])
for i in (1, 0):
if x[i+1] == '60':
if x[0][0] == '-':
if i == 0:
x[i] = '-{0}'.format(str(int(x[i]) - 1))
else:
x[i] = str(int(x[i]) - 1)
else:
x[i] = str(int(x[i]) + 1)
x[i+1] = '00'
for i in xrange(len(x)):
if 0 <= int(x[i]) < 10:
x[i] = '0{:.0f}'.format(int(x[i]))
elif -10 < int(x[i]) < 0:
x[i] = '-0{:.0f}'.format(-int(x[i]))
return ':'.join(x)
left, right = xlim
bottom, top = ylim
wcslim = [wcs.pix2wcs(left, bottom), wcs.pix2wcs(right, top)]
ralim, declim = numpy.transpose(wcslim)
rasep = astCoords.hms2decimal(xsep, ':')
decsep = astCoords.dms2decimal(ysep, ':')
raticks = numpy.arange(0, max(ralim), rasep)
raticks = raticks[raticks > min(ralim)]
decticks = numpy.arange(-90, max(declim), decsep)
decticks = decticks[decticks > min(declim)]
# this assumes that the rotation angle of the image is 0/90/180/270
# degrees
xticks = [wcs.wcs2pix(x, declim[0])[0] for x in raticks]
yticks = [wcs.wcs2pix(ralim[0], y)[0] for y in decticks]
xticklabels = [astCoords.decimal2hms(t, ':') for t in raticks]
yticklabels = [astCoords.decimal2dms(t, ':').replace('+', '')
for t in decticks]
# format properly (remove 60's and add 0's)
xticklabels = [format_wcs(xt) for xt in xticklabels]
yticklabels = [format_wcs(yt) for yt in yticklabels]
# get tick positions for rounded labels
raticks = [astCoords.hms2decimal(xt, ':') for xt in xticklabels]
decticks = [astCoords.dms2decimal(yt, ':') for yt in yticklabels]
xticks = [wcs.wcs2pix(x, declim[0])[0] for x in raticks]
yticks = [wcs.wcs2pix(ralim[0], y)[1] for y in decticks]
# display?
if ax:
ax.set_xticks(xticks)
ax.set_yticks(yticks)
ax.set_xticklabels(xticklabels, color=label_color, rotation=rotate_x)
ax.set_yticklabels(yticklabels, color=label_color, rotation=rotate_y)
return [xticks, xticklabels], [yticks, yticklabels]
def main():
__version_info__ = (0,0,1)
__version__ = ".".join( map(str,__version_info__) )
for i, arg in enumerate(sys.argv):
if (arg[0] == '-') and arg[1].isdigit(): sys.argv[i] = ' ' + arg
parser = ArgumentParser(description='Image based stacking tool S Makhathini <*****@*****.**>')
add = parser.add_argument
add("-v","--version", action='version',version='{:s} version {:s}'.format(parser.prog, __version__))
add("-i", "--image",
help="FITS image name")
add("-c", "--catalog", metavar="CATALOG_NAME:DELIMITER",
help="Catalog name. Default delimiter is a comma. Format: 'ra,dec,freq' ")
add("-p", "--prefix", default="gota_stackem_all",
help="Prefix for output products.")
add("-w", "--width", type=float, default=0,
help="For line stacking: Band width [MHz] to sample across frequency (for line stacking). Default is 1."
"For continuum stacking: Width (in beams) of subregion to stack. Default is 10 beams")
add("-vbl", "--vebosity-level", dest="vbl", choices=["0", "1", "2", "3"], default="0",
help="Verbosity level. 0-> INFO, 1-> DEBUG, 2-> ERROR, 3-> CRITICAL. Default is 0")
add("-b", "--beam", metavar="BMIN[:BMIN:BPA]",
help="PSF (a.k.a dirty beam) FWHM in degrees. No default")
add("-b2p", "--beam2pix", action="store_true",
help="Do Jy/beam to Jy/pixel conversion")
add("-L", "--line", action="store_true",
help="Do line stacking")
add("-C", "--cont", action="store_true",
help="Do continuum stacking")
add("-mc", "--monte-carlo", metavar="SAMPLES:START:FINISH:N", default=False,
help="Do a monte carlo analysis of the noise. That is, "
"stack on START random positions NSAMPLES times. "
"Repeat this N times with (FINISH-START)/N increments."
"if set -mc/--mont-carlo=yes, default is '400:1000:8000:7'")
args = parser.parse_args()
if args.catalog:
catalog_string = args.catalog.split(":")
if len(catalog_string)>1:
catalgname, delimiter = catalog_string
else:
catalogname, delimiter = catalog_string[0], ","
if args.beam:
beam = args.beam.split(":")
if len(beam)==1:
beam = float(beam[0])
elif len(beam)==2:
beam = map(float, beam) + [0]
else:
beam = map(float, beam)
else:
beam = None
pylab.clf()
prefix = args.prefix or "stackem_default"
pylab.figure(figsize=(15,10))
if args.line:
from Stackem import LineStacker
stack = LineStacker.load(args.image, catalogname, delimiter=delimiter,
beam=beam, width=args.width, beam2pix=args.beam2pix,
verbosity=args.vbl)
stacked_line = stack.stack()*1e6 # convert to uJy
peak, nu, sigma = gfit_params = stack.fit_gaussian(stacked_line)
gfit = utils.gauss(range(stack.width), *gfit_params)
freqs = (numpy.linspace(-stack.width/2, stack.width/2, stack.width)*stack.dfreq - stack.freq0)*1e-9 # convert to GHz
# plot profile
pylab.plot(freqs, stacked_line, "r.", label="stacked profile")
pylab.plot(freqs, gfit, "k-", label="Gaussian fit")
pylab.grid()
pylab.xlim(freqs[0], freqs[-1])
pylab.xlabel("Frequency [GHz]")
pylab.ylabel("Flux density [mJy/{:s}]".format("beam" if args.beam2pix else "pixel"))
pylab.legend(loc=1)
pylab.savefig(prefix+"-line.png")
pylab.clf()
# save
numpy.savetxt(prefix+"-line.txt", stacked_line, delimiter=",")
with open(prefix+"-line_stats.txt", "w") as info:
tot = sigma*peak*math.sqrt(2*math.pi)
stack.log.info("Gaussian Fit parameters.")
info.write("Gaussian Fit parameters\n")
info.write("Peak Flux : {:.4g} uJy\n".format(peak))
stack.log.info("Peak Flux : {:.4g} uJy".format(peak))
info.write("Integrated Flux : {:.4g} uJy\n".format(tot))
stack.log.info("Integrated Flux : {:.4g} uJy".format(tot))
info.write("Profile width : {:.4g} MHz \n".format(sigma*stack.dfreq))
stack.log.info("Profile width : {:.4g} kHz".format(sigma*stack.dfreq*1e-3))
stack.log.info("Line stacking ran successfully. Find your outputs at {:s}-line*".format(prefix))
if args.cont:
pylab.figure(figsize=(20, 20))
from Stackem import ContStacker
stack = ContStacker.load(args.image, catalogname, delimiter=delimiter,
beam=beam, beam2pix=args.beam2pix, width=int(args.width),
verbosity=args.vbl)
stacked = stack.stack()
mask = utils.elliptical_mask(stacked, stack.bmajPix/2., stack.bminPix/2., stack.bpa)
flux = utils.gauss_weights(stacked, stack.bmajPix/2., stack.bmajPix/2., mask=mask)
flux = flux.sum()
rms = utils.negnoise(stacked)
with open(prefix+"-cont.txt", "w") as cont:
stack.log.info("Stacked flux: {:.3g} +/- {:.3g} uJy".format(flux*1e6, rms*1e6))
cont.write("Stacked flux: {:.3g} +/- {:.3g} uJy/beam".format(flux*1e6, rms*1e6))
# Plot stacked image, and cross-sections
rotated = numpy.rot90(stacked.T)
import matplotlib.gridspec as gridspec
gs = gridspec.GridSpec(2, 2,
width_ratios = [4,1],
height_ratios = [1,4])
gs.update(wspace=0.05, hspace=0.05)
ax1 = pylab.subplot(gs[2])
ax2 = pylab.subplot(gs[0], sharex=ax1)
ax3 = pylab.subplot(gs[3], sharey=ax1)
pylab.setp(ax3.get_yticklabels(), visible=False)
pylab.setp(ax3.get_xticklabels(), rotation=90)
pylab.setp(ax2.get_xticklabels(), visible=False)
ax1.imshow(stacked, interpolation="nearest")
ax1.set_aspect("auto")
ra0, dec0 = stack.wcs.getCentreWCSCoords()
ras = numpy.linspace(stack.width/2, -stack.width/2, stack.width)*stack.cell - ra0
decs = numpy.linspace(-stack.width/2, stack.width/2, stack.width)*stack.cell - dec0
ax1.set_xticklabels( map(lambda x: coords.decimal2hms(x, ":"), ras) )
ax1.set_yticklabels( map(lambda x: coords.decimal2dms(x, ":"), decs) )
ax1.set_xlabel("RA [hms]")
ax1.set_ylabel("DEC [dms]")
pylab.setp(ax1.get_xticklabels(), rotation=90)
ax2.plot(rotated[:, stack.width/2]*1e6)
ax3.plot(rotated[stack.width/2,:][::-1]*1e6, range(stack.width))
ax3.set_ylim(0, stack.width-1)
ax2.set_xlim(0, stack.width-1)
ax2.set_ylabel("Flux density [uJy/beam]")
ax3.set_xlabel("Flux density [uJy/beam]")
pylab.savefig(prefix+"-cont.png")
# save stacked image as fits
hdr = stack.hdr
hdr["crpix1"] = stack.width/2
hdr["crpix2"] = stack.width/2
pyfits.writeto(prefix+"-cont.fits", stacked, hdr, clobber=True)
stack.log.info("Continuum stacking ran successfully. Find your outputs at {:s}-line*".format(prefix))
if args.monte_carlo:
if args.monte_carlo in ["yes", "1", "True", "true"]:
runs, stacks = 400, xrange(1000, 8000, 1000)
else:
a, b, c, d = map(int, args.monte_carlo.split(":"))
runs, stacks = a, xrange(b, c, (c-b)/d)
from Stackem import ContStacker
noise = ContStacker.mc_noise_stack(args.image, runs=runs, stacks=stacks,
beam=beam, beam2pix=args.beam2pix, width=args.width,
verbosity=args.vbl)
pylab.clf()
pylab.loglog(stacks, noise)
pylab.grid()
pylab.ylabel("Log (Noise [Jy/beam])")
pylab.xlabel("Log (Random Stacks). {:d} Samples".format(runs))
pylab.savefig(prefix+"-cont_mc.png")
pylab.clf()
def update_data_object(args):
import pickle as p
from astLib import astCoords
from glob import glob
### ALL QSOs observed and added to the web:
allQSOs = glob('/Users/krogager/Sites/redQSOs/images/*.png')
observedQSOs = []
for qso in allQSOs:
name = qso.split('/')[-1].split('.')[0]
observedQSOs.append(name)
SDSS = p.load(open('/Users/krogager/Projects/redQSOs/OptNIR/SDSS_phot.p'))
metaData = np.genfromtxt(
'/Users/krogager/Projects/redQSOs/QSO_sampleData.txt',
delimiter='\t',
dtype={
'names': [
'name', 'z', 'Ab', 'IR', 'BAL', 'nored', 'SMC', 'other',
'noabs', 'narrow', 'strong', 'weak', 'intervening'
],
'formats': ['S11', 'f8', 'f8'] + ['i8' for i in range(10)]
})
js_out = []
for id, objID, ra, dec, type, u, e_u, g, e_g, r, e_r, i, e_i, z, e_z, specObjID, redshift, primTarget in SDSS:
ra_hex = astCoords.decimal2hms(ra, ':')
dec_hex = astCoords.decimal2dms(dec, ':')
if id in observedQSOs:
obs = 1
else:
obs = 0
if id in metaData['name']:
ij = metaData['name'].tolist().index(id)
spec_z = metaData['z'][ij]
Ab = metaData['Ab'][ij]
BAL = int(metaData['BAL'][ij])
nored = int(metaData['nored'][ij])
SMC = int(metaData['SMC'][ij])
other = int(metaData['other'][ij])
noabs = int(metaData['noabs'][ij])
narrow = int(metaData['narrow'][ij])
strong = int(metaData['strong'][ij])
weak = int(metaData['weak'][ij])
DLA = int(metaData['intervening'][ij])
else:
spec_z = -1
Ab = -1
BAL = 0
nored = 0
SMC = 0
other = 0
noabs = 0
narrow = 0
strong = 0
weak = 0
DLA = 0
js_out.append("'%s': {id:%d, sid:%d, ra:%f, dec:%f, ra_hex:'%s', dec_hex:'%s', redshift:%s,\
u:%.2f, g:%.2f, r:%.2f, i:%.2f, z:%.2f, obs:%i, spec_z:%.2f, Ab:%.2f, BAL:%i,nored:%i,SMC:%i,other:%i,\
noabs:%i,narrow:%i,strong:%i,weak:%i,DLA:%i}" \
%(id,objID,specObjID,ra,dec,ra_hex,dec_hex,redshift,u,g,r,i,z,obs,spec_z,Ab,BAL,nored,SMC,other,\
noabs,narrow,strong,weak,DLA) )
js = open('/Users/krogager/Sites/redQSOs/redQSOs_data.js', 'w')
now = datetime.datetime.now()
js.write("//Last update:\n")
js.write("var last_update='" + now.strftime("%B %d %Y") + "';\n\n")
js.write("var observedQSOs=['")
js.write("','".join(observedQSOs))
js.write("'];\n")
js.write("\n")
js.write("var redQSOs={\n")
js.write(',\n'.join(js_out))
js.write("};\n")
js.close()
if not args.quiet:
print "\n [OK] Successfully updated redQSOs_data.js \n"
# our info
table['RA'] = nan
table['DEC'] = nan
table['Dist'] = nan
table['z'] = m['zBCG_boada']
table['Mag Lim'] = m['Cmag_i']
#table['N'] = nan
# extern info
table['RA EX'] = m['RA_y']
table['DEC EX'] = m['DEC_y']
table['Dist EX'] = nan
table['z EX'] = m['z_extern']
#table['N EX'] = m['R']
table['Flag'] = m['Flag']
table['Ref'] = m['REDSHIFT_SOURCE']
fixed1 = m.loc[pd.notnull(m['RAJ2000']),
'RAJ2000'].apply(lambda x: astCoords.decimal2hms(x, ':'))
fixed2 = m.loc[pd.notnull(m['DEJ2000']),
'DEJ2000'].apply(lambda x: astCoords.decimal2dms(x, ':'))
table.loc[fixed1.index, 'RA EX'] = fixed1
table.loc[fixed2.index, 'DEC EX'] = fixed2
for i, row in table.iterrows():
table.loc[i, 'Dist EX'] = astCoords.calcAngSepDeg(
row['RA PSZ'], row['DEC PSZ'], row['RA EX'], row['DEC EX']) * 60
print('done')
def testdecimal2dms(self):
for dec, result in self.decimal2dms:
answer = astCoords.decimal2dms(dec, ':')
self.assertEqual(result, answer)
def dms(self):
dms_orig = '12:34:56.78'
decimal = astCoords.dms2decimal(dms_orig, ':')
dms_new = astCoords.decimal2dms(decimal, ':')
self.assertEqual(dms_new, dms_orig)
def wds9reg(self,
regfile=None,
color='red',
circlesize=10,
width=1,
xcol='X_IMAGE',
ycol='Y_IMAGE',
textcol=None,
criteria=None):
""" write sources to a ds9 region file.
circlesize may be a scalar or an array with one size
for each object in the catalog. Criteria can now be used to only write certian regions
to the file from the catelog. criteria is a tuple with values (colname,comparison_operator,value).
Eg. criteria = ('EXT_IMAGE','==',1)
"""
import numpy as np
import os
#import exceptions
if (xcol not in self.colnames or ycol not in self.colnames):
print("ERROR: cannot make a ds9 region file without %s,%s" %
(xcol, ycol))
return (-1)
xcolname = xcol.lower()
convertRADEC = False
if ('alpha' in xcolname) or ('ra' in xcolname) or (
'r.a.' in xcolname) or ('world' in xcolname):
if isinstance(self.coldata[xcol][0], float):
try:
from astLib import astCoords
print(
"Converting RA,DEC from decimal degrees to hh:mm:ss,dd:mm:ss"
)
convertRADEC = True
except:
print("Can't load astLib for RA,DEC conversion!")
return (-1)
if not regfile:
regfile = os.path.splitext(self.filename)[0] + '.reg'
fout = open(regfile, 'w')
print >> fout, "# Region file format: DS9 version 5.4"
print >> fout, """global color=%s font="times 16 bold" select=1 edit=1 move=0 delete=1 include=1 fixed=0 width=%i""" % (
color, width)
for irow in range(self.nrows):
if np.iterable(circlesize): cs = circlesize[irow]
else: cs = circlesize
textstr = ''
if textcol:
# textcol may be a comma-sep'd list of col names.
textvals = []
for tc in textcol.split(','):
tval = self.coldata[tc][irow]
if type(tval) in [
int, np.int, np.int16, np.int32, np.int64, np.int8,
np.int_
]:
textvals.append('%i' % tval)
elif type(tval) in [
float, np.float, np.float32, np.float64,
np.float128, np.float_
]:
textvals.append('%.2f' % tval)
else:
textvals.append(str(tval))
textstr = '# text={%s}' % ':'.join(textvals)
#Only write the line to the file if it passes the criteria passed to this function.
#This allows us to separate extensions for makeing flt region files in the fakes
if criteria is None: write_line = True
else:
write_line = eval("self.coldata['%s'][irow] %s %s" % criteria)
if write_line:
cstr = '%.1f' % cs
x, y = self.coldata[xcol][irow], self.coldata[ycol][irow]
if isinstance(x, float):
xstr, ystr = '%.8f' % x, '%.8f' % y
if convertRADEC:
xstr = astCoords.decimal2hms(x, delimiter=':')
ystr = astCoords.decimal2dms(y, delimiter=':')
if cs > 1: cs = min(0.75, cs * 0.06)
cstr = '%.3f"' % (cs)
print >> fout, 'circle(%s,%s,%s)%s' % (xstr, ystr, cstr,
textstr)
fout.close()
return (regfile)
def dms(dec):
try:
return astCoords.decimal2dms(dec, ':')
except UnboundLocalError:
return 'NaN'
def main(round=3):
''' This creates a simple latex table with the results using the columns
specified below. A few things will need to be done by hand after this is
created. The corrected errors to redshifts, and corrected Ngals will need
to be manually added by looking at the results images. The cluster finder
doesn't save those columns by default.
'''
# the confirmed = True gets the 12 confirmed clusters
results = loadClusters(round=round, confirmed=True)
# load the master spreadsheet
t_ss = Table.read('../catalogs/PSZ2_unconfirmed_catalog - current.csv')
df_ss = t_ss.to_pandas()
observed = df_ss.loc[~df_ss['MOSAIC Imaging'].isnull()]
confirmed = observed.merge(results, left_on='Name', right_on='Cluster',
how='left')
# load the PSZ1 catalog
t_1 = Table.read('../catalogs/PSZ1v2.1.fits')
df1 = t_1.to_pandas()
# now we add all of the extra info
# Berrena paper
Bpaper = Table.read('../papers/1803.05764/Barrena_tbl3.csv')
df_paper = Bpaper.to_pandas()
complete = confirmed.merge(df_paper, left_on='Name', right_on='Planck Name',
how='left')
# tack on the PSZ1 catalog
complete = complete.merge(df1, left_on='PSZ1 Indx', right_on='INDEX',
how='left')
# combine some columns to get extra info
complete['z_extern'] = complete['PSZ1 Redshift'].fillna(complete['z_cl'])
complete['S/N'] = complete['SNR_PSZ2'].fillna(complete['SNR_PSZ1'])
# get the columns we want
cols = ['Name', 'PSZ1 Indx', 'PSZ2 Indx', 'S/N', 'RA_SEX', 'DEC_SEX',
'dist_BCG', 'z_cl_boada', 'z_clerr_boada', 'Ngal_c_boada', 'Cmag_i',
'z_extern', 'REDSHIFT_SOURCE', 'BCG_boada']
c = complete.loc[:, cols]
c.loc[:, ('RA_SEX', 'DEC_SEX')] = nan
c.loc[(~c['z_extern'].isnull()) & (c['REDSHIFT_SOURCE'] == -1.0),
'REDSHIFT_SOURCE'] = 99
# let's the the RA/DEC of our BCGs
m = c.loc[c['BCG_boada'].notnull()]
for i, row in m.iterrows():
mems = loadMembers('boada', row['Name'], round=round)
try:
ra = mems.loc[mems['ID'] == row['BCG_boada'], 'RA'].values[0]
except IndexError:
continue
dec = mems.loc[mems['ID'] == row['BCG_boada'], 'DEC'].values[0]
# convert to sexigesimal
ra_sex = astCoords.decimal2hms(ra, ':')
dec_sex = astCoords.decimal2dms(dec, ':')
# compute the distance to the PSZ position
psz_ra = complete.iloc[i]['RA_x']
psz_dec = complete.iloc[i]['DEC_x']
m.loc[i, 'dist_BCG'] = astCoords.calcAngSepDeg(psz_ra,
psz_dec, ra, dec) * 60
# write it back into the main frame
m.loc[i, 'RA_SEX'] = ra_sex
m.loc[i, 'DEC_SEX'] = dec_sex
return m
reader = open(inFile, "r")
lines = reader.readlines()
reader.close()
writer = open(outFile, "w")
for row in lines:
if len(row)>1:
if "#" not in row[:1]:
rowBits = row.split("\t")
if way == "to_decimal":
RADeg = astCoords.hms2decimal(rowBits[RACol], delimiter)
decDeg = astCoords.dms2decimal(rowBits[decCol], delimiter)
if way == "to_hmsdms":
RADeg = astCoords.decimal2hms(float(rowBits[RACol]),
delimiter)
decDeg = astCoords.decimal2dms(float(rowBits[decCol]),
delimiter)
writeString = ""
for i in range(len(rowBits)):
if i == RACol:
writeString = writeString+str(RADeg)+"\t"
elif i == decCol:
writeString = writeString+str(decDeg)+"\t"
elif rowBits[i].find("\n") != -1:
writeString = writeString+str(rowBits[i])
else:
writeString = writeString+str(rowBits[i])+"\t"
# new line character already included
writer.write(writeString.replace("\n", "").replace("\t",
colDelim)+"\n")
else:
writer.write(row.replace("\t", colDelim))
def testRandomizer():
#calculate a test case
conversion = 0.000277777778 # degree to arcsecond
#random distance between z = 0 and 5
z = np.random.rand() * 5.0
#random separation of the main galaxy and the subhalo
physical_distance = np.random.rand() * 1e3 #in kpc
#get the angular diameter distance to the galaxy
dd1 = cosmocalc(z, 71.0, 0.28)['PS_kpc'] #in kpc / arc seconds
dd = (physical_distance / dd1) * conversion # to degrees
# RA and DEC of the main galaxy, first one in GOODS south
ra_main = 52.904892 #in degrees
dec_main = -27.757082 #in degrees
# get the random position
rds = rand.randomUnitSphere(points=1)
# convert the position to Cartesian coord
# when dd is the radius of the sphere coordinates
# the dd is in units of degrees here so the results
# are also in degrees.
rd = conv.convertSphericalToCartesian(dd,
rds['theta'],
rds['phi'])
# Make the assumption that x is towards the observer
# z is north and y is west. Now if we assume that our z and y
# are Standard Coordinates, i.e., the projection of the RA and DEC
# of an object onto the tangent plane of the sky. We can now
# assume that the y coordinate is aligned with RA and the z coordinate
# is aligned with DEC. The origin of this system is at the tangent point
# in the dark matter halo.
# Poor man's solution to the problem would be:
new_ra = ra_main - (rd['y'][0] / np.cos(rd['z'][0]))
new_dec = dec_main + rd['z'][0]
# However, this only works if one is away from the pole.
# More general solution can be derived using spherical geometry:
data = {}
data['CD'] = np.matrix('-1 0; 0 1')
data['RA'] = ra_main
data['DEC'] = dec_main
data['X'] = rd['y'][0]
data['Y'] = rd['z'][0]
result = conv.RAandDECfromStandardCoordinates(data)
#print the output
print 'Redshift of the galaxy is %.3f while the subhaloes distance is %0.2f kpc' % (z, physical_distance)
print '\nCoordinates of the main halo galaxy are (RA and DEC):'
print '%.7f %.7f' % (ra_main, dec_main)
print astCoords.decimal2hms(ra_main, ':'), astCoords.decimal2dms(dec_main, ':')
print '\nCoordinates for the subhalo galaxy are (RA and DEC):'
print '%.7f %.7f' % (new_ra, new_dec)
print astCoords.decimal2hms(new_ra, ':'), astCoords.decimal2dms(new_dec, ':')
print 'or when using more accurate technique'
print '%.7f %.7f' % (result['RA'], result['DEC'])
print astCoords.decimal2hms(result['RA'], ':'), astCoords.decimal2dms(result['DEC'], ':')
#print 'Shift in RA and DEC [degrees]:'
#print rd['y'][0], (rd['z'][0]/np.cos(rd['z'][0]))
print '\nShift in RA and DEC [seconds]:'
print -rd['y'][0] / np.cos(rd['z'][0]) / conversion, rd['z'][0] / conversion
print 'or again with the better method:'
print (result['RA'] - ra_main) / conversion, (result['DEC'] - dec_main) / conversion
def main():
__version_info__ = (0, 0, 1)
__version__ = ".".join(map(str, __version_info__))
for i, arg in enumerate(sys.argv):
if (arg[0] == '-') and arg[1].isdigit(): sys.argv[i] = ' ' + arg
parser = ArgumentParser(
description=
'Image based stacking tool S Makhathini <*****@*****.**>')
add = parser.add_argument
add("-v",
"--version",
action='version',
version='{:s} version {:s}'.format(parser.prog, __version__))
add("-i", "--image", help="FITS image name")
add("-c",
"--catalog",
metavar="CATALOG_NAME:DELIMITER",
help=
"Catalog name. Default delimiter is a comma. Format: 'ra,dec,freq' ")
add("-p",
"--prefix",
default="gota_stackem_all",
help="Prefix for output products.")
add("-w",
"--width",
type=float,
default=0,
help=
"For line stacking: Band width [MHz] to sample across frequency (for line stacking). Default is 1."
"For continuum stacking: Width (in beams) of subregion to stack. Default is 10 beams"
)
add("-vbl",
"--vebosity-level",
dest="vbl",
choices=["0", "1", "2", "3"],
default="0",
help=
"Verbosity level. 0-> INFO, 1-> DEBUG, 2-> ERROR, 3-> CRITICAL. Default is 0"
)
add("-b",
"--beam",
metavar="BMIN[:BMIN:BPA]",
help="PSF (a.k.a dirty beam) FWHM in degrees. No default")
add("-b2p",
"--beam2pix",
action="store_true",
help="Do Jy/beam to Jy/pixel conversion")
add("-L", "--line", action="store_true", help="Do line stacking")
add("-C", "--cont", action="store_true", help="Do continuum stacking")
add("-mc",
"--monte-carlo",
metavar="SAMPLES:START:FINISH:N",
default=False,
help="Do a monte carlo analysis of the noise. That is, "
"stack on START random positions NSAMPLES times. "
"Repeat this N times with (FINISH-START)/N increments."
"if set -mc/--mont-carlo=yes, default is '400:1000:8000:7'")
args = parser.parse_args()
if args.catalog:
catalog_string = args.catalog.split(":")
if len(catalog_string) > 1:
catalgname, delimiter = catalog_string
else:
catalogname, delimiter = catalog_string[0], ","
if args.beam:
beam = args.beam.split(":")
if len(beam) == 1:
beam = float(beam[0])
elif len(beam) == 2:
beam = map(float, beam) + [0]
else:
beam = map(float, beam)
else:
beam = None
pylab.clf()
prefix = args.prefix or "stackem_default"
pylab.figure(figsize=(15, 10))
if args.line:
from Stackem import LineStacker
stack = LineStacker.load(args.image,
catalogname,
delimiter=delimiter,
beam=beam,
width=args.width,
beam2pix=args.beam2pix,
verbosity=args.vbl)
stacked_line = stack.stack() * 1e6 # convert to uJy
peak, nu, sigma = gfit_params = stack.fit_gaussian(stacked_line)
gfit = utils.gauss(range(stack.width), *gfit_params)
freqs = (numpy.linspace(-stack.width / 2, stack.width / 2, stack.width)
* stack.dfreq - stack.freq0) * 1e-9 # convert to GHz
# plot profile
pylab.plot(freqs, stacked_line, "r.", label="stacked profile")
pylab.plot(freqs, gfit, "k-", label="Gaussian fit")
pylab.grid()
pylab.xlim(freqs[0], freqs[-1])
pylab.xlabel("Frequency [GHz]")
pylab.ylabel("Flux density [mJy/{:s}]".format(
"beam" if args.beam2pix else "pixel"))
pylab.legend(loc=1)
pylab.savefig(prefix + "-line.png")
pylab.clf()
# save
numpy.savetxt(prefix + "-line.txt", stacked_line, delimiter=",")
with open(prefix + "-line_stats.txt", "w") as info:
tot = sigma * peak * math.sqrt(2 * math.pi)
stack.log.info("Gaussian Fit parameters.")
info.write("Gaussian Fit parameters\n")
info.write("Peak Flux : {:.4g} uJy\n".format(peak))
stack.log.info("Peak Flux : {:.4g} uJy".format(peak))
info.write("Integrated Flux : {:.4g} uJy\n".format(tot))
stack.log.info("Integrated Flux : {:.4g} uJy".format(tot))
info.write("Profile width : {:.4g} MHz \n".format(sigma *
stack.dfreq))
stack.log.info("Profile width : {:.4g} kHz".format(
sigma * stack.dfreq * 1e-3))
stack.log.info(
"Line stacking ran successfully. Find your outputs at {:s}-line*".
format(prefix))
if args.cont:
pylab.figure(figsize=(20, 20))
from Stackem import ContStacker
stack = ContStacker.load(args.image,
catalogname,
delimiter=delimiter,
beam=beam,
beam2pix=args.beam2pix,
width=int(args.width),
verbosity=args.vbl)
stacked = stack.stack()
mask = utils.elliptical_mask(stacked, stack.bmajPix / 2.,
stack.bminPix / 2., stack.bpa)
flux = utils.gauss_weights(stacked,
stack.bmajPix / 2.,
stack.bmajPix / 2.,
mask=mask)
flux = flux.sum()
rms = utils.negnoise(stacked)
with open(prefix + "-cont.txt", "w") as cont:
stack.log.info("Stacked flux: {:.3g} +/- {:.3g} uJy".format(
flux * 1e6, rms * 1e6))
cont.write("Stacked flux: {:.3g} +/- {:.3g} uJy/beam".format(
flux * 1e6, rms * 1e6))
# Plot stacked image, and cross-sections
rotated = numpy.rot90(stacked.T)
import matplotlib.gridspec as gridspec
gs = gridspec.GridSpec(2, 2, width_ratios=[4, 1], height_ratios=[1, 4])
gs.update(wspace=0.05, hspace=0.05)
ax1 = pylab.subplot(gs[2])
ax2 = pylab.subplot(gs[0], sharex=ax1)
ax3 = pylab.subplot(gs[3], sharey=ax1)
pylab.setp(ax3.get_yticklabels(), visible=False)
pylab.setp(ax3.get_xticklabels(), rotation=90)
pylab.setp(ax2.get_xticklabels(), visible=False)
ax1.imshow(stacked, interpolation="nearest")
ax1.set_aspect("auto")
ra0, dec0 = stack.wcs.getCentreWCSCoords()
ras = numpy.linspace(stack.width / 2, -stack.width / 2,
stack.width) * stack.cell - ra0
decs = numpy.linspace(-stack.width / 2, stack.width / 2,
stack.width) * stack.cell - dec0
ax1.set_xticklabels(map(lambda x: coords.decimal2hms(x, ":"), ras))
ax1.set_yticklabels(map(lambda x: coords.decimal2dms(x, ":"), decs))
ax1.set_xlabel("RA [hms]")
ax1.set_ylabel("DEC [dms]")
pylab.setp(ax1.get_xticklabels(), rotation=90)
ax2.plot(rotated[:, stack.width / 2] * 1e6)
ax3.plot(rotated[stack.width / 2, :][::-1] * 1e6, range(stack.width))
ax3.set_ylim(0, stack.width - 1)
ax2.set_xlim(0, stack.width - 1)
ax2.set_ylabel("Flux density [uJy/beam]")
ax3.set_xlabel("Flux density [uJy/beam]")
pylab.savefig(prefix + "-cont.png")
# save stacked image as fits
hdr = stack.hdr
hdr["crpix1"] = stack.width / 2
hdr["crpix2"] = stack.width / 2
pyfits.writeto(prefix + "-cont.fits", stacked, hdr, clobber=True)
stack.log.info(
"Continuum stacking ran successfully. Find your outputs at {:s}-line*"
.format(prefix))
if args.monte_carlo:
if args.monte_carlo in ["yes", "1", "True", "true"]:
runs, stacks = 400, xrange(1000, 8000, 1000)
else:
a, b, c, d = map(int, args.monte_carlo.split(":"))
runs, stacks = a, xrange(b, c, (c - b) / d)
from Stackem import ContStacker
noise = ContStacker.mc_noise_stack(args.image,
runs=runs,
stacks=stacks,
beam=beam,
beam2pix=args.beam2pix,
width=args.width,
verbosity=args.vbl)
pylab.clf()
pylab.loglog(stacks, noise)
pylab.grid()
pylab.ylabel("Log (Noise [Jy/beam])")
pylab.xlabel("Log (Random Stacks). {:d} Samples".format(runs))
pylab.savefig(prefix + "-cont_mc.png")
pylab.clf()
def testRandomizer():
#calculate a test case
conversion = 0.000277777778 # degree to arcsecond
#random distance between z = 0 and 5
z = np.random.rand() * 5.0
#random separation of the main galaxy and the subhalo
physical_distance = np.random.rand() * 1e3 #in kpc
#get the angular diameter distance to the galaxy
dd1 = cosmocalc(z, 71.0, 0.28)['PS_kpc'] #in kpc / arc seconds
dd = (physical_distance / dd1) * conversion # to degrees
# RA and DEC of the main galaxy, first one in GOODS south
ra_main = 52.904892 #in degrees
dec_main = -27.757082 #in degrees
# get the random position
rds = rand.randomUnitSphere(points=1)
# convert the position to Cartesian coord
# when dd is the radius of the sphere coordinates
# the dd is in units of degrees here so the results
# are also in degrees.
rd = conv.convertSphericalToCartesian(dd, rds['theta'], rds['phi'])
# Make the assumption that x is towards the observer
# z is north and y is west. Now if we assume that our z and y
# are Standard Coordinates, i.e., the projection of the RA and DEC
# of an object onto the tangent plane of the sky. We can now
# assume that the y coordinate is aligned with RA and the z coordinate
# is aligned with DEC. The origin of this system is at the tangent point
# in the dark matter halo.
# Poor man's solution to the problem would be:
new_ra = ra_main - (rd['y'][0] / np.cos(rd['z'][0]))
new_dec = dec_main + rd['z'][0]
# However, this only works if one is away from the pole.
# More general solution can be derived using spherical geometry:
data = {}
data['CD'] = np.matrix('-1 0; 0 1')
data['RA'] = ra_main
data['DEC'] = dec_main
data['X'] = rd['y'][0]
data['Y'] = rd['z'][0]
result = conv.RAandDECfromStandardCoordinates(data)
#print the output
print 'Redshift of the galaxy is %.3f while the subhaloes distance is %0.2f kpc' % (
z, physical_distance)
print '\nCoordinates of the main halo galaxy are (RA and DEC):'
print '%.7f %.7f' % (ra_main, dec_main)
print astCoords.decimal2hms(ra_main,
':'), astCoords.decimal2dms(dec_main, ':')
print '\nCoordinates for the subhalo galaxy are (RA and DEC):'
print '%.7f %.7f' % (new_ra, new_dec)
print astCoords.decimal2hms(new_ra,
':'), astCoords.decimal2dms(new_dec, ':')
print 'or when using more accurate technique'
print '%.7f %.7f' % (result['RA'], result['DEC'])
print astCoords.decimal2hms(result['RA'], ':'), astCoords.decimal2dms(
result['DEC'], ':')
#print 'Shift in RA and DEC [degrees]:'
#print rd['y'][0], (rd['z'][0]/np.cos(rd['z'][0]))
print '\nShift in RA and DEC [seconds]:'
print -rd['y'][0] / np.cos(
rd['z'][0]) / conversion, rd['z'][0] / conversion
print 'or again with the better method:'
print(result['RA'] - ra_main) / conversion, (result['DEC'] -
dec_main) / conversion