def raveRC():
data= readRave()
jk= data['Jmag2']-data['Kmag2']-0.17*numpy.exp(data['Av'])
z= isodist.FEH2Z(data['[M/H]K'],zsolar=0.017)
logg= data['loggK']
indx= (jk < 0.8)*(jk >= 0.5)\
*(z <= 0.06)\
*(z <= rcmodel.jkzcut(jk,upper=True))\
*(z >= rcmodel.jkzcut(jk))\
*(logg >= rcmodel.loggteffcut(data['TeffK'],z,upper=False))\
*(logg <= rcmodel.loggteffcut(data['TeffK'],z,upper=True))
data= data[indx]
#To allow for XY pixelization
data= esutil.numpy_util.add_fields(data,[('RC_GALR', float),
('RC_GALPHI', float),
('RC_GALZ', float),
('VHELIO_AVG', float)])
XYZ= bovy_coords.lbd_to_XYZ(data['GLON'],
data['GLAT'],
data['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
data['VHELIO_AVG']= data['HRV']
return data
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
onedhists=False,onedhistxnormed=True,
onedhistynormed=True,onedhistec='r',bins=20)
bovy_plot.bovy_plot(data['J0'][rcclumpseismo]-data['K0'][rcclumpseismo],
data['KASC_RG_LOGG_SCALE_2'][rcclumpseismo],
'bo',mec='none',overplot=True,zorder=1,
onedhists=False,onedhistxnormed=True,
onedhistynormed=True,onedhistec='b',bins=20)
bovy_plot.bovy_plot(data['J0'][rcindx]-data['K0'][rcindx],
data['KASC_RG_LOGG_SCALE_2'][rcindx],
'k.',overplot=True,zorder=0,
onedhists=False,onedhistxnormed=True,
onedhistynormed=True,onedhistec='k',bins=20)
bovy_plot.bovy_end_print('apokasc_rc_loggjk.png')
#Statistics using simple seismo logg cut
clumplogg= (data['KASC_RG_LOGG_SCALE_2'] > 1.8)\
*(data['KASC_RG_LOGG_SCALE_2'] < rcmodel.loggteffcut(data['TEFF'],
isodist.FEH2Z(data['METALS'],zsolar=0.017),upper=True))#2.8)
rcclumplogg= clumplogg*(data['RC'] == 1)
print "%i / %i = %i%% APOKASC logg clump stars are in the RC catalog" % (numpy.sum(rcclumplogg),numpy.sum(clumplogg),float(numpy.sum(rcclumplogg))/numpy.sum(clumplogg)*100)
rcnoclumplogg= (True-clumplogg)*(data['RC'] == 1)
print "%i / %i = %i%% APOKASC logg non-clump stars are in the RC catalog" % (numpy.sum(rcnoclumplogg),numpy.sum(True-clumplogg),float(numpy.sum(rcnoclumplogg))/numpy.sum(True-clumplogg)*100.)
print "%i / %i = %i%% APOKASC logg non-clump stars out of all stars are in the RC catalog" % (numpy.sum(rcnoclumplogg),numpy.sum(data['RC'] == 1),float(numpy.sum(rcnoclumplogg))/numpy.sum(data['RC'] == 1)*100.)
bovy_plot.bovy_print()
bovy_plot.bovy_plot(data['METALS'][rcnoclumplogg],
data['ALPHAFE'][rcnoclumplogg],
'ro',ms=4.5,
xrange=[-1.,0.7],
yrange=[-0.15,0.35],
xlabel=r'$[\mathrm{Fe/H}]$',
ylabel=r'$[\alpha/\mathrm{Fe}]$',onedhists=True,
mec='none',
onedhistxnormed=True,onedhistynormed=True,
