def write_matches(savefilename):
apokasc= match_apokasc_saga()
#Perform RC selection
logg= apokasc['KASC_RG_LOGG_SCALE_2']
teff= apokasc['TEFF']
z= 0.017*10.**apokasc['METALS']
jk= apokasc['J0']-apokasc['K0']
indx= (logg >= 1.8)\
*(logg <= 0.0018*(teff+382.5*apokasc['METALS']-4607)+2.5)\
*(jk < 0.8)\
*(jk >= 0.5)\
*(z <= 0.06)\
*(z <= rcmodel.jkzcut(jk,upper=True))\
*(z >= rcmodel.jkzcut(jk))
print "Found %i RC stars in APOKASC" % numpy.sum(indx)
rcdists= numpy.zeros(len(apokasc))-1
rcd= rcdist('../data/rcmodel_mode_jkz_ks_parsec_newlogg.sav')
rcdists[indx]= rcd(jk[indx],z[indx],apokasc['K0'][indx])
pindx= (rcdists > 0.)*(apokasc['DIST_SEISMO'] > 0.)
apokasc= apokasc[pindx]
rcdists= rcdists[pindx]
print "Found %i RC stars in APOKASC with seismic distances" % numpy.sum(pindx)
savefile= open(savefilename,'w')
savefile.write('#ID,RCDIST(pc),SEISMODIST(SCALE,MO,pc),(SEISMODIST-RCDIST)/RCDIST\n')
csvwriter = csv.writer(savefile, delimiter=',')
for ii in range(len(apokasc)):
csvwriter.writerow([apokasc['KEPLER ID'][ii],
rcdists[ii]*1000.,
apokasc['DIST_SEISMO'][ii]*1000.,
(apokasc['DIST_SEISMO'][ii]-rcdists[ii])/rcdists[ii]])
savefile.close()
def compare_seismic_distances(plotfilename):
apokasc= match_apokasc_saga()
#Perform RC selection
logg= apokasc['KASC_RG_LOGG_SCALE_2']
teff= apokasc['TEFF']
z= 0.017*10.**apokasc['METALS']
jk= apokasc['J0']-apokasc['K0']
indx= (logg >= 1.8)\
*(logg <= 0.0018*(teff+382.5*apokasc['METALS']-4607)+2.5)\
*(jk < 0.8)\
*(jk >= 0.5)\
*(z <= 0.06)\
*(z <= rcmodel.jkzcut(jk,upper=True))\
*(z >= rcmodel.jkzcut(jk))#\
#*(apokasc['SEISMO EVOL'] == 'CLUMP')
print "Found %i RC stars in APOKASC" % numpy.sum(indx)
rcdists= numpy.zeros(len(apokasc))-1
rcd= rcdist('../data/rcmodel_mode_jkz_ks_parsec_newlogg.sav')
rcdists[indx]= rcd(jk[indx],z[indx],apokasc['K0'][indx])
pindx= (rcdists > 0.)*(apokasc['DIST_SEISMO'] > 0.)
print "Found %i RC stars in APOKASC with seismic distances" % numpy.sum(pindx)
#Setup plot
bovy_plot.bovy_print(fig_height=7.)
dx= 0.6
left, bottom, width, height= 0.1, 0.9-dx, 0.8, dx
axTop= pyplot.axes([left,bottom,width,height])
fig= pyplot.gcf()
fig.sca(axTop)
bovy_plot.bovy_plot([0.,20.],[0.,20.],'k-',lw=2.,color='0.4',
overplot=True,zorder=0)
bovy_plot.bovy_plot(rcdists[pindx],apokasc['DIST_SEISMO'][pindx],
'k.',overplot=True,zorder=10)
if False:
pyplot.errorbar(rcdists[pindx],
apokasc['DIST_SEISMO'][pindx],
xerr=0.05*rcdists[pindx],
yerr=apokasc['E_DIST_SEISMO'][pindx],
marker=',',color='k',
linestyle='none')
thisax= pyplot.gca()
thisax.set_ylim(0.,5.)
pyplot.xlim(0.,5.)
bovy_plot._add_ticks()
nullfmt = NullFormatter() # no labels
axTop.xaxis.set_major_formatter(nullfmt)
bovy_plot._add_ticks()
pyplot.ylabel(r'$\mathrm{seismic\ distance}\,(\mathrm{kpc})$')
#Second plot
left, bottom, width, height= 0.1, 0.1, 0.8, 0.8-dx
thisax= pyplot.axes([left,bottom,width,height])
fig.sca(thisax)
bovy_plot.bovy_plot([0.,20.],[0.,0.],'k-',lw=2.,color='0.4',
overplot=True,zorder=0)
bovy_plot.bovy_plot(rcdists[pindx],
(apokasc['DIST_SEISMO'][pindx]-rcdists[pindx])/rcdists[pindx],
'k.',overplot=True,zorder=10)
thisax= pyplot.gca()
thisax.set_ylim(-0.2,0.2)
pyplot.xlim(0.,5.)
bovy_plot._add_ticks()
nullfmt = NullFormatter() # no labels
bovy_plot._add_ticks()
pyplot.ylabel(r'$\mathrm{relative\ differene}$')
pyplot.xlabel(r'$\mathrm{RC\ distance}\,(\mathrm{kpc})$')
medoffset= numpy.median((apokasc['DIST_SEISMO'][pindx]-rcdists[pindx])/rcdists[pindx])
medsig= 1.4826*numpy.median(numpy.fabs((apokasc['DIST_SEISMO'][pindx]-rcdists[pindx])/rcdists[pindx]-medoffset))
bovy_plot.bovy_text(2.75,-0.125,r'$\mathrm{diff} = %.3f\pm%.3f$' % \
(medoffset,medsig),size=14.)
bovy_plot.bovy_end_print(plotfilename)
def _calc_one(z, options, nages, lages, dlages):
print z
if options.allapogee or options.redapogee:
rc = rcmodel.rcmodel(
Z=z,
loggmax=3.5,
band=options.band,
basti=options.basti,
imfmodel=options.imfmodel,
parsec=options.parsec,
eta=options.eta,
)
else:
rc = rcmodel.rcmodel(
Z=z,
loggmin=1.8,
loggmax="custom",
band=options.band,
basti=options.basti,
imfmodel=options.imfmodel,
parsec=options.parsec,
eta=options.eta,
)
out = numpy.zeros(nages)
for jj in range(nages):
jk = rc._jks
aindx = (rc._lages <= lages[jj] + dlages) * (rc._lages > lages[jj] - dlages)
if options.allapogee:
aindx *= jk > 0.5
elif options.redapogee:
aindx *= jk > 0.8
else:
rcd = rcmodel.rcdist("../../rcdist-apogee/data/rcmodel_mode_jkz_ks_parsec_newlogg.sav")
predH = numpy.array([rcd(j, z) for j in jk])
predH = numpy.reshape(predH, len(jk))
aindx *= (
(jk < 0.8)
* (jk > 0.5)
* (z <= rcmodel.jkzcut(jk, upper=True))
* (z >= rcmodel.jkzcut(jk))
* (z <= 0.06)
* (rc._sample[:, 1] > (predH - 0.4))
* (rc._sample[:, 1] < (predH + 0.4))
* (rc._sample[:, 1] > -3.0)
* (rc._loggs[:, 0] <= 3.5)
)
if options.type == "omega":
try:
out[jj] = numpy.mean(rc._massweights[aindx])
except ValueError:
out[jj] = numpy.nan
elif options.type == "numfrac":
try:
out[jj] = numpy.mean(rc._weights[aindx])
except ValueError:
out[jj] = numpy.nan
elif options.type == "mass":
try:
out[jj] = numpy.sum(rc._masses[aindx] * rc._weights[aindx]) / numpy.sum(rc._weights[aindx])
except ValueError:
out[jj] = numpy.nan
return out
def make_rcsample(parser):
options,args= parser.parse_args()
savefilename= options.savefilename
if savefilename is None:
#Create savefilename if not given
savefilename= os.path.join(appath._APOGEE_DATA,
'rcsample_'+appath._APOGEE_REDUX+'.fits')
print "Saving to %s ..." % savefilename
#Read the base-sample
data= apread.allStar(adddist=_ADDHAYDENDIST,rmdups=options.rmdups)
#Remove a bunch of fields that we do not want to keep
data= esutil.numpy_util.remove_fields(data,
['TARGET_ID',
'FILE',
'AK_WISE',
'SFD_EBV',
'SYNTHVHELIO_AVG',
'SYNTHVSCATTER',
'SYNTHVERR',
'SYNTHVERR_MED',
'RV_TEFF',
'RV_LOGG',
'RV_FEH',
'RV_CCFWHM',
'RV_AUTOFWHM',
'SYNTHSCATTER',
'CHI2_THRESHOLD',
'APSTAR_VERSION',
'ASPCAP_VERSION',
'RESULTS_VERSION',
'REDUCTION_ID',
'SRC_H',
'PM_SRC'])
if int(appath._APOGEE_REDUX[1:]) < 500:
data= esutil.numpy_util.remove_fields(data,
['ELEM'])
#Select red-clump stars
jk= data['J0']-data['K0']
z= isodist.FEH2Z(data['METALS'],zsolar=0.017)
if int(appath._APOGEE_REDUX[1:]) > 600:
from apogee.tools import paramIndx
if False:
#Use my custom logg calibration that's correct for the RC
logg= (1.-0.042)*data['FPARAM'][:,paramIndx('logg')]-0.213
lowloggindx= data['FPARAM'][:,paramIndx('logg')] < 1.
logg[lowloggindx]= data['FPARAM'][lowloggindx,paramIndx('logg')]-0.255
hiloggindx= data['FPARAM'][:,paramIndx('logg')] > 3.8
logg[hiloggindx]= data['FPARAM'][hiloggindx,paramIndx('logg')]-0.3726
else:
#Use my custom logg calibration that's correct on average
logg= (1.+0.03)*data['FPARAM'][:,paramIndx('logg')]-0.37
lowloggindx= data['FPARAM'][:,paramIndx('logg')] < 1.
logg[lowloggindx]= data['FPARAM'][lowloggindx,paramIndx('logg')]-0.34
hiloggindx= data['FPARAM'][:,paramIndx('logg')] > 3.8
logg[hiloggindx]= data['FPARAM'][hiloggindx,paramIndx('logg')]-0.256
else:
logg= data['LOGG']
indx= (jk < 0.8)*(jk >= 0.5)\
*(z <= 0.06)\
*(z <= rcmodel.jkzcut(jk,upper=True))\
*(z >= rcmodel.jkzcut(jk))\
*(logg >= rcmodel.loggteffcut(data['TEFF'],z,upper=False))\
*(logg <= rcmodel.loggteffcut(data['TEFF'],z,upper=True))
data= data[indx]
#Add more aggressive flag cut
data= esutil.numpy_util.add_fields(data,[('ADDL_LOGG_CUT',numpy.int32)])
data['ADDL_LOGG_CUT']= ((data['TEFF']-4800.)/1000.+2.75) > data['LOGG']
if options.loggcut:
data= data[data['ADDL_LOGG_CUT'] == 1]
print "Making catalog of %i objects ..." % len(data)
#Add distances
data= esutil.numpy_util.add_fields(data,[('RC_DIST', float),
('RC_DM', float),
('RC_GALR', float),
('RC_GALPHI', float),
('RC_GALZ', float)])
rcd= rcmodel.rcdist('../../rcdist-apogee/data/rcmodel_mode_jkz_ks_parsec_newlogg.sav')
jk= data['J0']-data['K0']
z= isodist.FEH2Z(data['METALS'],zsolar=0.017)
data['RC_DIST']= rcd(jk,z,appmag=data['K0'])*options.distfac
data['RC_DM']= 5.*numpy.log10(data['RC_DIST'])+10.
XYZ= bovy_coords.lbd_to_XYZ(data['GLON'],
data['GLAT'],
data['RC_DIST'],
degree=True)
R,phi,Z= bovy_coords.XYZ_to_galcencyl(XYZ[:,0],
XYZ[:,1],
XYZ[:,2],
Xsun=8.,Zsun=0.025)
data['RC_GALR']= R
data['RC_GALPHI']= phi
data['RC_GALZ']= Z
#Save
fitsio.write(savefilename,data,clobber=True)
if not options.nostat:
#Determine statistical sample and add flag
apo= apogee.select.apogeeSelect()
statIndx= apo.determine_statistical(data)
mainIndx= apread.mainIndx(data)
data= esutil.numpy_util.add_fields(data,[('STAT',numpy.int32),
('INVSF',float)])
data['STAT']= 0
data['STAT'][statIndx*mainIndx]= 1
for ii in range(len(data)):
if (statIndx*mainIndx)[ii]:
data['INVSF'][ii]= 1./apo(data['LOCATION_ID'][ii],
data['H'][ii])
else:
data['INVSF'][ii]= -1.
if options.nopm:
fitsio.write(savefilename,data,clobber=True)
return None
#Get proper motions
from astroquery.vizier import Vizier
import astroquery
from astropy import units as u
import astropy.coordinates as coord
pmfile= savefilename.split('.')[0]+'_pms.fits'
if os.path.exists(pmfile):
pmdata= fitsio.read(pmfile,1)
else:
pmdata= numpy.recarray(len(data),
formats=['f8','f8','f8','f8','f8','f8','i4'],
names=['RA','DEC','PMRA','PMDEC',
'PMRA_ERR','PMDEC_ERR','PMMATCH'])
rad= u.Quantity(4./3600.,u.degree)
v= Vizier(columns=['RAJ2000','DEJ2000','pmRA','pmDE','e_pmRA','e_pmDE'])
for ii in range(len(data)):
#if ii > 100: break
sys.stdout.write('\r'+"Getting pm data for point %i / %i" % (ii+1,len(data)))
sys.stdout.flush()
pmdata.RA[ii]= data['RA'][ii]
pmdata.DEC[ii]= data['DEC'][ii]
co= coord.ICRS(ra=data['RA'][ii],
dec=data['DEC'][ii],
unit=(u.degree, u.degree))
trying= True
while trying:
try:
tab= v.query_region(co,rad,catalog='I/322') #UCAC-4 catalog
except astroquery.exceptions.TimeoutError:
pass
else:
trying= False
if len(tab) == 0:
pmdata.PMMATCH[ii]= 0
print "Didn't find a match for %i ..." % ii
continue
else:
pmdata.PMMATCH[ii]= len(tab)
if len(tab[0]['pmRA']) > 1:
print "Found more than 1 match for %i ..." % ii
try:
pmdata.PMRA[ii]= float(tab[0]['pmRA'])
except TypeError:
jj= 1
while len(tab[0]['pmRA']) > 1 and jj < 4:
trad= u.Quantity((4.-jj)/3600.,u.degree)
trying= True
while trying:
try:
tab= v.query_region(co,trad,catalog='I/322') #UCAC-4 catalog
except astroquery.exceptions.TimeoutError:
pass
else:
trying= False
jj+= 1
if len(tab) == 0:
pmdata.PMMATCH[ii]= 0
print "Didn't find a unambiguous match for %i ..." % ii
continue
pmdata.PMRA[ii]= float(tab[0]['pmRA'])
pmdata.PMDEC[ii]= float(tab[0]['pmDE'])
pmdata.PMRA_ERR[ii]= float(tab[0]['e_pmRA'])
pmdata.PMDEC_ERR[ii]= float(tab[0]['e_pmDE'])
if numpy.isnan(float(tab[0]['pmRA'])): pmdata.PMMATCH[ii]= 0
sys.stdout.write('\r'+_ERASESTR+'\r')
sys.stdout.flush()
fitsio.write(pmfile,pmdata,clobber=True)
#To make sure we're using the same format below
pmdata= fitsio.read(pmfile,1)
#Match proper motions
try: #These already exist currently, but may not always exist
data= esutil.numpy_util.remove_fields(data,['PMRA','PMDEC'])
except ValueError:
pass
data= esutil.numpy_util.add_fields(data,[('PMRA', numpy.float),
('PMDEC', numpy.float),
('PMRA_ERR', numpy.float),
('PMDEC_ERR', numpy.float),
('PMMATCH',numpy.int32)])
data['PMMATCH']= 0
h=esutil.htm.HTM()
m1,m2,d12 = h.match(pmdata['RA'],pmdata['DEC'],
data['RA'],data['DEC'],
2./3600.,maxmatch=1)
data['PMRA'][m2]= pmdata['PMRA'][m1]
data['PMDEC'][m2]= pmdata['PMDEC'][m1]
data['PMRA_ERR'][m2]= pmdata['PMRA_ERR'][m1]
data['PMDEC_ERR'][m2]= pmdata['PMDEC_ERR'][m1]
data['PMMATCH'][m2]= pmdata['PMMATCH'][m1].astype(numpy.int32)
pmindx= data['PMMATCH'] == 1
data['PMRA'][True-pmindx]= -9999.99
data['PMDEC'][True-pmindx]= -9999.99
data['PMRA_ERR'][True-pmindx]= -9999.99
data['PMDEC_ERR'][True-pmindx]= -9999.99
#Calculate Galactocentric velocities
data= esutil.numpy_util.add_fields(data,[('GALVR', numpy.float),
('GALVT', numpy.float),
('GALVZ', numpy.float)])
lb= bovy_coords.radec_to_lb(data['RA'],data['DEC'],degree=True)
XYZ= bovy_coords.lbd_to_XYZ(lb[:,0],lb[:,1],data['RC_DIST'],degree=True)
pmllpmbb= bovy_coords.pmrapmdec_to_pmllpmbb(data['PMRA'],data['PMDEC'],
data['RA'],data['DEC'],
degree=True)
vxvyvz= bovy_coords.vrpmllpmbb_to_vxvyvz(data['VHELIO_AVG'],
pmllpmbb[:,0],
pmllpmbb[:,1],
lb[:,0],lb[:,1],data['RC_DIST'],
degree=True)
vR, vT, vZ= bovy_coords.vxvyvz_to_galcencyl(vxvyvz[:,0],
vxvyvz[:,1],
vxvyvz[:,2],
8.-XYZ[:,0],
XYZ[:,1],
XYZ[:,2]+0.025,
vsun=[-11.1,30.24*8.,7.25])#Assumes proper motion of Sgr A* and R0=8 kpc, zo= 25 pc
data['GALVR']= vR
data['GALVT']= vT
data['GALVZ']= vZ
data['GALVR'][True-pmindx]= -9999.99
data['GALVT'][True-pmindx]= -9999.99
data['GALVZ'][True-pmindx]= -9999.99
#Get proper motions
pmfile= savefilename.split('.')[0]+'_pms_ppmxl.fits'
if os.path.exists(pmfile):
pmdata= fitsio.read(pmfile,1)
else:
pmdata= numpy.recarray(len(data),
formats=['f8','f8','f8','f8','f8','f8','i4'],
names=['RA','DEC','PMRA','PMDEC',
'PMRA_ERR','PMDEC_ERR','PMMATCH'])
rad= u.Quantity(4./3600.,u.degree)
v= Vizier(columns=['RAJ2000','DEJ2000','pmRA','pmDE','e_pmRA','e_pmDE'])
for ii in range(len(data)):
#if ii > 100: break
sys.stdout.write('\r'+"Getting pm data for point %i / %i" % (ii+1,len(data)))
sys.stdout.flush()
pmdata.RA[ii]= data['RA'][ii]
pmdata.DEC[ii]= data['DEC'][ii]
co= coord.ICRS(ra=data['RA'][ii],
dec=data['DEC'][ii],
unit=(u.degree, u.degree))
trying= True
while trying:
try:
tab= v.query_region(co,rad,catalog='I/317') #PPMXL catalog
except astroquery.exceptions.TimeoutError:
pass
else:
trying= False
if len(tab) == 0:
pmdata.PMMATCH[ii]= 0
print "Didn't find a match for %i ..." % ii
continue
else:
pmdata.PMMATCH[ii]= len(tab)
if len(tab[0]['pmRA']) > 1:
pass
#print "Found more than 1 match for %i ..." % ii
try:
pmdata.PMRA[ii]= float(tab[0]['pmRA'])
except TypeError:
#Find nearest
cosdists= numpy.zeros(len(tab[0]['pmRA']))
for jj in range(len(tab[0]['pmRA'])):
cosdists[jj]= cos_sphere_dist(tab[0]['RAJ2000'][jj],
tab[0]['DEJ2000'][jj],
data['RA'][ii],
data['DEC'][ii])
closest= numpy.argmax(cosdists)
pmdata.PMRA[ii]= float(tab[0]['pmRA'][closest])
pmdata.PMDEC[ii]= float(tab[0]['pmDE'][closest])
pmdata.PMRA_ERR[ii]= float(tab[0]['e_pmRA'][closest])
pmdata.PMDEC_ERR[ii]= float(tab[0]['e_pmDE'][closest])
if numpy.isnan(float(tab[0]['pmRA'][closest])): pmdata.PMMATCH[ii]= 0
else:
pmdata.PMDEC[ii]= float(tab[0]['pmDE'])
pmdata.PMRA_ERR[ii]= float(tab[0]['e_pmRA'])
pmdata.PMDEC_ERR[ii]= float(tab[0]['e_pmDE'])
if numpy.isnan(float(tab[0]['pmRA'])): pmdata.PMMATCH[ii]= 0
sys.stdout.write('\r'+_ERASESTR+'\r')
sys.stdout.flush()
fitsio.write(pmfile,pmdata,clobber=True)
#To make sure we're using the same format below
pmdata= fitsio.read(pmfile,1)
#Match proper motions to ppmxl
data= esutil.numpy_util.add_fields(data,[('PMRA_PPMXL', numpy.float),
('PMDEC_PPMXL', numpy.float),
('PMRA_ERR_PPMXL', numpy.float),
('PMDEC_ERR_PPMXL', numpy.float),
('PMMATCH_PPMXL',numpy.int32)])
data['PMMATCH_PPMXL']= 0
h=esutil.htm.HTM()
m1,m2,d12 = h.match(pmdata['RA'],pmdata['DEC'],
data['RA'],data['DEC'],
2./3600.,maxmatch=1)
data['PMRA_PPMXL'][m2]= pmdata['PMRA'][m1]
data['PMDEC_PPMXL'][m2]= pmdata['PMDEC'][m1]
data['PMRA_ERR_PPMXL'][m2]= pmdata['PMRA_ERR'][m1]
data['PMDEC_ERR_PPMXL'][m2]= pmdata['PMDEC_ERR'][m1]
data['PMMATCH_PPMXL'][m2]= pmdata['PMMATCH'][m1].astype(numpy.int32)
pmindx= data['PMMATCH_PPMXL'] == 1
data['PMRA_PPMXL'][True-pmindx]= -9999.99
data['PMDEC_PPMXL'][True-pmindx]= -9999.99
data['PMRA_ERR_PPMXL'][True-pmindx]= -9999.99
data['PMDEC_ERR_PPMXL'][True-pmindx]= -9999.99
#Calculate Galactocentric velocities
data= esutil.numpy_util.add_fields(data,[('GALVR_PPMXL', numpy.float),
('GALVT_PPMXL', numpy.float),
('GALVZ_PPMXL', numpy.float)])
lb= bovy_coords.radec_to_lb(data['RA'],data['DEC'],degree=True)
XYZ= bovy_coords.lbd_to_XYZ(lb[:,0],lb[:,1],data['RC_DIST'],degree=True)
pmllpmbb= bovy_coords.pmrapmdec_to_pmllpmbb(data['PMRA_PPMXL'],
data['PMDEC_PPMXL'],
data['RA'],data['DEC'],
degree=True)
vxvyvz= bovy_coords.vrpmllpmbb_to_vxvyvz(data['VHELIO_AVG'],
pmllpmbb[:,0],
pmllpmbb[:,1],
lb[:,0],lb[:,1],data['RC_DIST'],
degree=True)
vR, vT, vZ= bovy_coords.vxvyvz_to_galcencyl(vxvyvz[:,0],
vxvyvz[:,1],
vxvyvz[:,2],
8.-XYZ[:,0],
XYZ[:,1],
XYZ[:,2]+0.025,
vsun=[-11.1,30.24*8.,7.25])#Assumes proper motion of Sgr A* and R0=8 kpc, zo= 25 pc
data['GALVR_PPMXL']= vR
data['GALVT_PPMXL']= vT
data['GALVZ_PPMXL']= vZ
data['GALVR_PPMXL'][True-pmindx]= -9999.99
data['GALVT_PPMXL'][True-pmindx]= -9999.99
data['GALVZ_PPMXL'][True-pmindx]= -9999.99
#Save
fitsio.write(savefilename,data,clobber=True)
return None