def getUVFlux(configOpts, logger):
logger.write('Measuring FUV fluxes ...', newLine=True)
uvheader, uvimage = open_image(configOpts['fuvImage'])
data_uv = configOpts['data_uv']
coords_uv = os.path.splitext(configOpts['fuvMaskFileRej'])[0] + '_Peaks.dat'
if os.path.exists(data_uv):
try:
columns = np.dtype([('PDRID', 'int',), ('RA', '|S14'), ('DEC', '|S14'), ('aperture', 'float'),
('mean_at_r', 'float'), ('bgflux', 'float'), ('cumulflux', 'float'),
('netflux', 'float'), ('sflux', 'float')])
fluxtable = read_array(data_uv, columns)
logger.write('... fluxes read from file {0} instead.'.format(data_uv))
logger.write('... {0} records read'.format(np.size(fluxtable.PDRID)))
return uvheader, fluxtable
except:
pass
#file does not exist, so we calculate. Force recalculation by removing the file.
#Variables in: uvheader, uvimage, uvcoords
#Variable out: fluxtable (includes uvcoords afterwards)
# fluxtable labels: PDRID, RA, DEC, aperture, mean_at_r, bgflux, cumulflux, netflux, sflux
logger.write('No previous flux measurements.')
uvcoords = at.read(coords_uv, delimiter=',')
logger.write('Flux will be measured at {0} positions on image {1} ...'.format(len(uvcoords), configOpts['fuvImage']))
logger.write('Fluxes will be scaled by a factor {0}'.format(configOpts['FUVscale']))
#This scaling is useful since clumpfind doesn't seem to work properly with ~1e-15 values.
fluxtable = fuv_flux(configOpts['fuvImage'], uvheader, uvcoords, configOpts, verbose=True)
#logger.write(fluxtable.RA, fluxtable.RA[0] #here fluxtable.RA[0] is simply a string
#Write: UV fluxes
fluxfile = open(data_uv, 'w')
#logger.write('#PDRID, aperture (arcsec), mean at r (units/arcsec^2), bg flux, cumul. flux, net flux'
fluxfile.write('#PDRID, RA, DEC, aperture (arcsec), mean at r (units/pixel), bg flux, cumul. flux, net flux, sigma net flux\n')
for n in range(len(fluxtable)):
#fedora bug: changed PDRID:>3 to PDRID:3g
#logger.write('{0.PDRID:3g}, {1.aperture:5.2f}, {1.mean_at_r:7.5e}, {1.bgflux:7.5e}, {1.cumulflux:7.5e}, ' +
# '{1.netflux:7.5e}'.format(uvcoords[n], fluxtable[n])
fluxfile.write('{0.PDRID:3g}, {0.RA}, {0.DEC}, {1.aperture:7.5e}, {1.mean_at_r:7.5e}, {1.bgflux:7.5e}, ' +
'{1.cumulflux:7.5e}, {1.netflux:7.5e}, {1.sflux:7.5e}\n'.format(uvcoords[n], fluxtable[n]))
fluxfile.close()
return uvheader, fluxtable
def getHI(configOpts, fluxtable):
print "Identifying HI patches ..."
data_hi = configOpts['data_hi']
hiImage = configOpts['hiImage']
hi_baselist = "{0}_Regions/{0}_Reg".format(os.path.splitext(hiImage)[0])
hi_logsbase = "{0}_Regions/{1}".format(os.path.splitext(hiImage)[0], configOpts['hi_logsbase'])
try:
dummy = file(data_hi, 'r')
print "... HI patch data read from file {0}".format(data_hi)
#Read: HI data (if already there); note that if the read fails, patches will be re-measured also
columns = np.dtype([('PDRID', 'int',), ('RA', '|S14'), ('DEC', '|S14'), ('NHI', 'float'), ('sNHI', 'float')])
hidata = pdr.read_array(data_hi, columns)
print " {0} records read".format(np.size(hidata))
#Very simple and incomplete check for enough data:
if (np.size(np.unique(hidata.PDRID)) != np.size(np.unique(fluxtable.PDRID))):
print "Fatal error: number of UV and HI PDRIDs do not match. Try regenerating the HI files."
exit(0)
except:
#File does not exist, so process HI postage stamp regions.
#Must have regions with names matching the PDRIDs
scale = configOpts['HIscale'] # 2.896e19 for NGC 628 (m?)Jy/beam to cm-2
hi_bg = configOpts['hiBackground']
print "Using map scaling of {0} cm-2".format(scale)
hiresults = [[] for dummy in xrange(5)] #PDRID, ra, dec, NHI, sNHI
#Warning: up to 999 files
for i in range(np.size(fluxtable.PDRID)):
fitsfile = hi_baselist + "{0:03d}.fits".format(int(fluxtable.PDRID[i]))
print "Calling SExtractor with file {0}".format(fitsfile)
catfile = pdr.call_SEx(fitsfile)
if catfile==1:
print "Fatal error: SExtractor call failed."
exit(0)
else:
logfile = hi_logsbase + "{0:03}.txt".format(int(fluxtable.PDRID[i]))
patches = pdr.read_secat(catfile, fitsfile, logfile, wcs=True)
#Patches are not background-subtracted, that will happen now:
for n in range(len(patches[0])):
if patches[2][n] > (hi_bg*2.):
#subtract the background and ignore patches that are fainter than hi_bg
hiresults[0].append(fluxtable.PDRID[i])
hiresults[1].append(patches[0][n])
hiresults[2].append(patches[1][n])
hiresults[3].append((patches[2][n]-hi_bg)*scale)
hiresults[4].append(hi_bg * scale * 0.5) #fix sN_HI to half the background value
else:
print "Patch too faint: ", patches[2][n]
if not np.size(np.where(hiresults[0] == fluxtable.PDRID[i])):
print "No suitable patches were found for PDRID ", fluxtable.PDRID[i], "; creating empty entry."
#With SExtractor, this is unlikely since it does not pick up the faintest patches
hiresults[0].append(fluxtable.PDRID[i])
hiresults[1].append(0)
hiresults[2].append(0)
hiresults[3].append(0)
hiresults[4].append(0)
#End for
#Finally, convert the results into a rec array and save the results
labels = 'PDRID, RA, DEC, NHI, sNHI'
hidata = pdr.records(hiresults, labels)
#Write: HI patches
hifile = fancyPrint(writeLog=True, logFile=data_hi, verbose=True)
print "HI patches:"
#print "#PDRID, RA, DEC, NHI, sNHI"
hifile.write("#PDRID, RA, DEC, NHI, sNHI\n")
for n in range(len(hidata)):
#print type(hidata[n].NHI)
#Apparently python 2.6 needs explicit conversion from numpy.float32, so workaround
#fedora bug: changed PDRID:>3 to PDRID:3g
#print "{0.PDRID:3g}, {0.RA:14s}, {0.DEC:14s}, {1:7.5g}, {2:7.5g}".format(hidata[n], float(hidata[n].NHI), float(hidata[n].sNHI))
hifile.write("{0.PDRID:3g}, {0.RA:14s}, {0.DEC:14s}, {1:7.5g}, {2:7.5g}\n".format(hidata[n], float(hidata[n].NHI), float(hidata[n].sNHI)))
#hifile.close()
#End of try/except
print
return hidata
