def repeat_sat_cleanup(sagatable): sats = sagatable['SATS'] == 1 #& s['ZQUALITY'] > 2 for s in sagatable[sats]: if s['REMOVE'] == -1: rsat = s['RA'] dsat = s['DEC'] m1,m2,d = sm.spherematch(sagatable['RA'], sagatable['DEC'],\ [rsat],[dsat], 10./3600) m = d != 0 if np.sum(m): r = m1[m] k = m1[d ==0] sagatable['REMOVE'][r] = 3 sagatable['REMOVE'][k] = -1 sagatable['SATS'][r] = -99 sagatable['SATS'][k] = 1 return sagatable
def gri_completeness(base, spec):
gmag = base['g'] - base['EXTINCTION_G']
rmag = base['r'] - base['EXTINCTION_R']
imag = base['i'] - base['EXTINCTION_I']
gr = gmag - rmag
ri = rmag - imag
grerr = np.sqrt(base['g_err']**2 + base['r_err']**2)
rierr = np.sqrt(base['r_err']**2 + base['i_err']**2)
cgmr = gr - 2.*grerr
crmi = ri - 2.*rierr
msk1 = cgmr < 0.85
msk2 = crmi < 0.55
grimsk = msk1&msk2
ngri = np.sum(msk1&msk2)
id1,id2,d = sm.spherematch(base['RA'][grimsk], base['DEC'][grimsk],spec['RA'], spec['DEC'],1./3600,nnearest=1)
ngri_spec = np.size(d)
p = 100.*ngri_spec/ngri
compl = '{:02.0f}% ({}/{})'.format(p,ngri_spec,ngri)
return compl
def photoflags(addlist, sagatable):
"""
SET REMOVE FLAG = 3 for bad SDSS Photo Flags
SET BACK TO REMOVE = -1 if in by-hand list
"""
binned1 = sagatable['BINNED1'] == 0
saturated = sagatable['SATURATED'] != 0
baderr = sagatable['BAD_COUNTS_ERROR'] != 0
# SET REMOVE FOR BAD PHOTOFLAGS
flgs = binned1 | saturated | baderr
sagatable['REMOVE'][flgs] = 3
# SET REMOVE FLAG FOR BRIGHT POORLY MEASURED OBJECTS
rdiff = np.abs(sagatable['PETRORAD_R'] - sagatable['PETRORAD_G'])
msk = (rdiff > 40) & (sagatable['r'] < 18)
sagatable['REMOVE'][msk] = 4
rdiff = np.abs(sagatable['PETRORAD_R'] - sagatable['PETRORAD_I'])
msk = (rdiff > 40) & (sagatable['r'] < 18)
sagatable['REMOVE'][msk] = 4
raderr = np.average([
sagatable['PETRORADERR_G'], sagatable['PETRORADERR_R'],
sagatable['PETRORADERR_I']
], 0)
msk = (sagatable['SB_EXP_R'] > 24) & (raderr == -1000)
sagatable['REMOVE'][msk] = 5
# LOOSER CONSTRAINT FOR BRIGHT
raderr = np.median([
sagatable['PETRORADERR_G'], sagatable['PETRORADERR_R'],
sagatable['PETRORADERR_I']
], 0)
msk = (sagatable['SB_EXP_R'] > 24) & (raderr
== -1000) & (sagatable['r'] < 18)
sagatable['REMOVE'][msk] = 5
# SET REMOVE FOR BAD PHOTOMETRIC ERRORS
err = [sagatable['g_err'], sagatable['r_err'], sagatable['i_err']]
merr = np.median(err, 0)
msk = np.abs(merr) > 0.5
sagatable['REMOVE'][msk] = 3
merr_zero = sagatable['r_err'] <= 0
print 'ZERO ERROR = ', np.sum(merr_zero)
# MATCH sql OBJECTS TO THOSE IN GOOGLE DOC ADD LIST
id1,id2,d = sm.spherematch(sagatable['RA'], sagatable['DEC'],\
addlist.field('Targ_RA'), addlist.field('Targ_Dec'),\
1./3600,nnearest=1)
nmatch = np.size((d > 0.0).nonzero())
print "add list objects = ", nmatch
# SET REMOVED FLAG BACK TO -1
if (nmatch > 0):
sagatable['REMOVE'][id1] = -1
return sagatable
def gri_completeness(base, spec):
gmag = base['g'] - base['EXTINCTION_G']
rmag = base['r'] - base['EXTINCTION_R']
imag = base['i'] - base['EXTINCTION_I']
gr = gmag - rmag
ri = rmag - imag
grerr = np.sqrt(base['g_err']**2 + base['r_err']**2)
rierr = np.sqrt(base['r_err']**2 + base['i_err']**2)
cgmr = gr - 2. * grerr
crmi = ri - 2. * rierr
msk1 = cgmr < 0.85
msk2 = crmi < 0.55
grimsk = msk1 & msk2
ngri = np.sum(msk1 & msk2)
id1, id2, d = sm.spherematch(base['RA'][grimsk],
base['DEC'][grimsk],
spec['RA'],
spec['DEC'],
1. / 3600,
nnearest=1)
ngri_spec = np.size(d)
p = 100. * ngri_spec / ngri
compl = '{:02.0f}% ({}/{})'.format(p, ngri_spec, ngri)
return compl
def photoflags(addlist,sagatable):
"""
SET REMOVE FLAG = 3 for bad SDSS Photo Flags
SET BACK TO REMOVE = -1 if in by-hand list
"""
binned1 = sagatable['BINNED1'] == 0
saturated = sagatable['SATURATED'] != 0
baderr = sagatable['BAD_COUNTS_ERROR'] != 0
flgs = binned1 | saturated | baderr
sagatable['REMOVE'][flgs] = 3
# MATCH sql OBJECTS TO THOSE IN GOOGLE DOC ADD LIST
id1,id2,d = sm.spherematch(sagatable['RA'], sagatable['DEC'],\
addlist.field('Targ_RA'), addlist.field('Targ_Dec'),\
1./3600,nnearest=1)
nmatch = np.size((d > 0.0).nonzero())
print "add list objects = ",nmatch
# SET REMOVED FLAG BACK TO -1
if (nmatch > 0):
sagatable['REMOVE'][id1] = -1
return sagatable
def repeat_sat_cleanup(sagatable):
# FIND REPEAT SATELLITES
sats = sagatable['SATS'] == 1 #& s['ZQUALITY'] > 2
for s in sagatable[sats]:
if s['REMOVE'] == -1:
rsat = s['RA']
dsat = s['DEC']
m1,m2,d = sm.spherematch(sagatable['RA'], sagatable['DEC'],\
[rsat],[dsat], 20./3600)
m = d != 0
if np.sum(m):
r = m1[m]
k = m1[d == 0]
sagatable['REMOVE'][r] = 3
sagatable['REMOVE'][k] = -1
sagatable['SATS'][r] = -99
sagatable['SATS'][k] = 1
# FIND REPEAT LOWZ satellites
sats = sagatable['SATS'] == 2 #& s['ZQUALITY'] > 2
for s in sagatable[sats]:
if s['REMOVE'] == -1:
rsat = s['RA']
dsat = s['DEC']
m1,m2,d = sm.spherematch(sagatable['RA'], sagatable['DEC'],\
[rsat],[dsat], 20./3600)
m = d != 0
if np.sum(m):
r = m1[m]
k = m1[d == 0]
sagatable['REMOVE'][r] = 3
sagatable['REMOVE'][k] = -1
sagatable['SATS'][r] = -99
sagatable['SATS'][k] = 2
return sagatable
def ML_completeness(base, spec, prob):
ML_msk = base['PCLASS_1'] > prob
nML = np.sum(ML_msk)
id1,id2,d = sm.spherematch(base['RA'][ML_msk], base['DEC'][ML_msk],spec['RA'], spec['DEC'],1./3600,nnearest=1)
nML_spec = np.size(d)
p = 100.*nML_spec/nML
compl = '{:02.0f}% ({}/{})'.format(p,nML_spec,nML)
return compl
def rm_removelist_obj(removelist,sagatable):
# MATCH sql OBJECTS TO THOSE IN GOOGLE DOC REMOVE LIST
id1,id2,d = sm.spherematch(sagatable['RA'], sagatable['DEC'],\
removelist.field('Targ_RA'), removelist.field('Targ_Dec'),\
1./3600,nnearest=1)
nmatch = np.size((d > 0.0).nonzero())
# SET REMOVED FLAG TO 1
if (nmatch > 0):
sagatable['REMOVE'][id1] = 1
print "Cleaning remove list objects = ",nmatch
return sagatable
def onclick(event):
if event.button !=3:
coords = np.vstack((event.xdata,667-event.ydata)).T
world = w.wcs_pix2world(coords,1)
result = psm.spherematch(world[:,0],world[:,1], self.ra_all, self.dec_all, nnearest=1)
if (result[0] < 1./3600.):
xpix,ypix = w.wcs_world2pix(self.ra_all[result[1].astype(int)], self.dec_all[result[1].astype(int)],1)
if (((xpix == self.xpix) & (ypix == self.ypix)).any() == False):
self.xpix = np.append(self.xpix,xpix)
self.ypix = np.append(self.ypix,ypix)
self.ra = np.append(self.ra, self.ra_all[result[1].astype(int)])
self.dec = np.append(self.dec, self.dec_all[result[1].astype(int)])
self.gr_color = np.append(self.gr_color, self.gr_color_all[result[1].astype(int)])
self.gi_color = np.append(self.gi_color, self.gi_color_all[result[1].astype(int)])
self.ri_color = np.append(self.ri_color, self.ri_color_all[result[1].astype(int)])
self.iz_color = np.append(self.iz_color, self.iz_color_all[result[1].astype(int)])
self.rz_color = np.append(self.rz_color, self.rz_color_all[result[1].astype(int)])
self.g_mag = np.append(self.g_mag, galaxy['mag_auto_g'][result[1].astype(int)])
self.r_mag = np.append(self.r_mag, galaxy['mag_auto_r'][result[1].astype(int)])
self.i_mag = np.append(self.i_mag, galaxy['mag_auto_i'][result[1].astype(int)])
self.z_mag = np.append(self.z_mag, galaxy['mag_auto_z'][result[1].astype(int)])
else:
keep = where(((xpix == self.xpix) & (ypix == self.ypix))==False)
self.xpix = self.xpix[keep]
self.ypix = self.ypix[keep]
self.ra = self.ra[keep]
self.dec = self.dec[keep]
self.gr_color = self.gr_color[keep]
self.gi_color = self.gi_color[keep]
self.ri_color = self.ri_color[keep]
self.iz_color = self.iz_color[keep]
self.rz_color = self.rz_color[keep]
self.g_mag = self.g_mag[keep]
self.r_mag = self.r_mag[keep]
self.i_mag = self.i_mag[keep]
self.z_mag = self.z_mag[keep]
self.temp_xpix=xpix
self.temp_ypix=ypix
self.temp_gr_color=self.gr_color_all[result[1].astype(int)]
self.temp_gi_color=self.gi_color_all[result[1].astype(int)]
self.temp_ri_color=self.ri_color_all[result[1].astype(int)]
self.temp_iz_color=self.iz_color_all[result[1].astype(int)]
self.temp_rz_color=self.rz_color_all[result[1].astype(int)]
self.temp_r_mag=galaxy['mag_auto_r'][result[1].astype(int)]
self.temp_i_mag=galaxy['mag_auto_i'][result[1].astype(int)]
display_ax0()
display_bx()
def gri_completeness(base, spec):
gmr = base['g'] - base['r'] - 2*base['g_err'] - 2*base['r_err']
rmi = base['r'] - base['i'] - 2*base['r_err'] - 2*base['i_err']
msk1 = gmr < 1.0
msk2 = rmi < 0.5
grimsk = msk1&msk2
ngri = np.sum(msk1&msk2)
id1,id2,d = sm.spherematch(base['RA'][grimsk], base['DEC'][grimsk],spec['RA'], spec['DEC'],1./3600,nnearest=1)
ngri_spec = np.size(d)
p = 100.*ngri_spec/ngri
compl = '{:02.0f}% ({}/{})'.format(p,ngri_spec,ngri)
return compl
def rm_removelist_obj(removelist, sagatable):
# MATCH sql OBJECTS TO THOSE IN GOOGLE DOC REMOVE LIST
id1,id2,d = sm.spherematch(sagatable['RA'], sagatable['DEC'],\
removelist.field('Targ_RA'), removelist.field('Targ_Dec'),\
1./3600,nnearest=1)
nmatch = np.size((d > 0.0).nonzero())
# SET REMOVED FLAG TO 1
if (nmatch > 0):
sagatable['REMOVE'][id1] = 1
print "Cleaning remove list objects = ", nmatch
# CATCH THINGS CLOSE TO HOST
m = sagatable['RHOST_KPC'] < 10
sagatable['REMOVE'][m] = 1
return sagatable
def add_saga_spec(sagaspec,sqltable): # MATCH sql OBJECTS TO THOSE IN SAGA SPEC id1,id2,d = sm.spherematch(sqltable['RA'], sqltable['DEC'],\ sagaspec['RA'], sagaspec['DEC'],\ 1./3600,nnearest=1) nmatch = np.size((d >= 0.0).nonzero()) print "adding existing SAGA SPECTRA = ",nmatch if (nmatch > 0): sqltable['SPEC_Z'][id1] = sagaspec['SPEC_Z'][id2] sqltable['ZQUALITY'][id1] = sagaspec['ZQUALITY'][id2] sqltable['TELNAME'][id1] = sagaspec['TELNAME'][id2] sqltable['MASKNAME'][id1] = sagaspec['MASKNAME'][id2] sqltable['SPECOBJID'][id1] = sagaspec['SPECOBJID'][id2] sqltable['SPEC_REPEAT'][id1] = sagaspec['SPEC_REPEAT'][id2] sqltable['SATS'][id1] = sagaspec['SATS'][id2] # sqltable['REMOVE'][id1] = sagaspec['REMOVE'][id2] return sqltable
def add_saga_spec(sagaspec, sqltable):
# MATCH sql OBJECTS TO THOSE IN SAGA SPEC
id1,id2,d = sm.spherematch(sqltable['RA'], sqltable['DEC'],\
sagaspec['RA'], sagaspec['DEC'],\
1./3600,nnearest=1)
nmatch = np.size((d >= 0.0).nonzero())
print "adding existing SAGA SPECTRA = ", nmatch
if (nmatch > 0):
sqltable['SPEC_Z'][id1] = sagaspec['SPEC_Z'][id2]
sqltable['ZQUALITY'][id1] = sagaspec['ZQUALITY'][id2]
sqltable['TELNAME'][id1] = sagaspec['TELNAME'][id2]
sqltable['MASKNAME'][id1] = sagaspec['MASKNAME'][id2]
sqltable['SPECOBJID'][id1] = sagaspec['SPECOBJID'][id2]
sqltable['SPEC_REPEAT'][id1] = sagaspec['SPEC_REPEAT'][id2]
sqltable['SPEC_SN'][id1] = sagaspec['SPEC_SN'][id2]
sqltable['SPEC_HA_EW'][id1] = sagaspec['SPEC_HA_EW'][id2]
sqltable['SPEC_HA_EWERR'][id1] = sagaspec['SPEC_HA_EWERR'][id2]
sqltable['SATS'][id1] = sagaspec['SATS'][id2]
sqltable['REMOVE'][id1] = sagaspec['REMOVE'][id2]
return sqltable
def nsa_cleanup(nsa,sagatable):
# MATCH NSA to SAGA, BEGIN WITH SMALLER RADIUS
id2,id1,d = sm.spherematch(nsa['RA'], nsa['DEC'],\
sagatable['RA'], sagatable['DEC'],\
5./3600,nnearest = 1)
nmatch = np.size(id1)
# FOR EACH UNIQUE NSA MATCH
for i in range(0,nmatch-1):
nid = id2[i]
sid = id1[i]
nra = nsa['RA'][nid]
ndec= nsa['DEC'][nid]
# FIRST PASS USING SPHEREMATCH
reff_nsa = 3*nsa['PETROTH90'][nid]
m1,m2,dd = sm.spherematch(sagatable['RA'], sagatable['DEC'],\
[nra],[ndec],reff_nsa/3600)
# FIND POINTS INSIDE ELLIPSE
a = 2.*nsa['PETROTH90'][nid]
b = nsa['SERSIC_BA'][nid] * a
th = (np.pi/180) * (nsa['SERSIC_PHI'][nid]+270)
sth = np.sin(th)
cth = np.cos(th)
x = 3600*(sagatable['RA'][m1] - nra)
y = 3600*(sagatable['DEC'][m1] - ndec)
tmp1 = (x*cth) - (y*sth)
tmp2 = (x*sth) + (y*cth)
rem = (tmp1/a)**2 + (tmp2/b)**2 <= 1. # true for points inside ellipse
# REMOVE SHREDDED OBJECTS NEAR NSA
sagatable['REMOVE'][m1[rem]] = 2
# EXPLICITLY ADD NSA PROPERTIES BACK INTO DATABASE
sagatable['REMOVE'][sid] = -1
sagatable['ZQUALITY'][sid] = 4
sagatable['TELNAME'][sid] = 'NSA'
sagatable['PHOTPTYPE'][sid]= 3
sagatable['PHOT_SG'][sid] = 'GALAXY'
sagatable['RA'][sid] = nra
sagatable['DEC'][sid] = ndec
sagatable['SPEC_Z'][sid] = nsa['Z'][nid]
sagatable['SPEC_Z_WARN'][sid] = 0
sagatable['MASKNAME'][sid] = nsa['ZSRC'][nid]
sagatable['OBJ_NSAID'][sid]= nsa['NSAID'][nid]
# REPLACE PHOTOMETRY
mag = 22.5 - 2.5*np.log10(nsa['SERSICFLUX'][nid])
mag[np.isnan(mag)]= -99
sagatable['u'][sid]= mag[2]
sagatable['g'][sid]= mag[3]
sagatable['r'][sid]= mag[4]
sagatable['i'][sid]= mag[5]
sagatable['z'][sid]= mag[6]
# sagatable['expRad_r'][sid] = nsa['SERSIC_TH50'][nid]
# sagatable['sb_exp_r'][sid] = -99#nsa['PETROTH90']
# sagatable['petroR90_r'][sid] = nsa['PETROTH90'][nid]#
# sagatable['petroR50_r'][sid] = nsa['PETROTH50'][nid]
# sagatable['petroMag_r'][sid] = -99#nsa['PETROTH90']
return sagatable
def nsa_cleanup(nsa, sagatable):
# MATCH NSA to SAGA, BEGIN WITH SMALLER RADIUS
id2,id1,d = sm.spherematch(nsa['RA'], nsa['DEC'],\
sagatable['RA'], sagatable['DEC'],\
5./3600,nnearest = 1)
nmatch = np.size(id1)
# FOR EACH UNIQUE NSA MATCH
for i in range(0, nmatch):
nid = id2[i]
sid = id1[i]
nra = nsa['RA'][nid]
ndec = nsa['DEC'][nid]
# FIRST PASS USING SPHEREMATCH
reff_nsa = 3 * nsa['PETROTH90'][nid]
m1,m2,dd = sm.spherematch(sagatable['RA'], sagatable['DEC'],\
[nra],[ndec],reff_nsa/3600)
# FIND POINTS INSIDE ELLIPSE
a = 2. * nsa['PETROTH90'][nid]
b = nsa['SERSIC_BA'][nid] * a
th = (np.pi / 180) * (nsa['SERSIC_PHI'][nid] + 270)
sth = np.sin(th)
cth = np.cos(th)
x = 3600 * (sagatable['RA'][m1] - nra)
y = 3600 * (sagatable['DEC'][m1] - ndec)
tmp1 = (x * cth) - (y * sth)
tmp2 = (x * sth) + (y * cth)
rem = (tmp1 / a)**2 + (tmp2 /
b)**2 <= 1. # true for points inside ellipse
# REMOVE SHREDDED OBJECTS NEAR NSA
sagatable['REMOVE'][m1[rem]] = 2
# EXPLICITLY ADD NSA PROPERTIES BACK INTO DATABASE
sagatable['REMOVE'][sid] = -1
sagatable['ZQUALITY'][sid] = 4
sagatable['TELNAME'][sid] = 'NSA'
sagatable['PHOTPTYPE'][sid] = 3
sagatable['PHOT_SG'][sid] = 'GALAXY'
sagatable['RA'][sid] = nra
sagatable['DEC'][sid] = ndec
sagatable['SPEC_Z'][sid] = nsa['Z'][nid]
sagatable['SPEC_HA_EW'][sid] = nsa['HAEW'][nid]
sagatable['SPEC_HA_EWERR'][sid] = nsa['HAEWERR'][nid]
sagatable['SPEC_REPEAT'][sid] = 'SDSS+NSA'
sagatable['MASKNAME'][sid] = nsa['ZSRC'][nid]
sagatable['OBJ_NSAID'][sid] = nsa['NSAID'][nid]
# REPLACE PHOTOMETRY
mag = 22.5 - 2.5 * np.log10(nsa['SERSICFLUX'][nid])
var = 1. / nsa['SERSICFLUX_IVAR'][nid]
tmp1 = 2.5 / (nsa['SERSICFLUX'][nid] * np.log(10.))
mag_err = np.sqrt(var * tmp1**2) # IS THIS RIGHT??
mag[np.isnan(mag)] = -99
mag_err[np.isnan(mag_err)] = -99
sagatable['u'][sid] = mag[2]
sagatable['g'][sid] = mag[3]
sagatable['r'][sid] = mag[4]
sagatable['i'][sid] = mag[5]
sagatable['z'][sid] = mag[6]
sagatable['u_err'][sid] = mag_err[2]
sagatable['g_err'][sid] = mag_err[3]
sagatable['r_err'][sid] = mag_err[4]
sagatable['i_err'][sid] = mag_err[5]
sagatable['z_err'][sid] = mag_err[6]
# print nsa['NSAID'][nid],np.sum(rem)
# sagatable['expRad_r'][sid] = nsa['SERSIC_TH50'][nid]
sagatable['SB_EXP_R'][sid] = mag[4] + 2.5 * np.log10(
2 * np.pi * nsa['PETROTH50'][nid]**2 + 1e-20)
sagatable['PETROR90_R'][sid] = nsa['PETROTH90'][nid] #
sagatable['PETROR50_R'][sid] = nsa['PETROTH50'][nid]
return sagatable
cat2x='glon_cen',
cat2y='glat_cen')
matchnames_peak_v1 = []
matchdist_peak_v1 = []
matchxdiff_peak_v1 = []
matchydiff_peak_v1 = []
matchcatnum_peak_v1 = []
v1matches_peak = bolocatv1.flux * 0
glonv1_peak = bolocatv1.glon_peak - (360 * (bolocatv1.glon_peak > 345))
glonv2_peak = bgpsv2_nonew.glon_peak - (360 * (bgpsv2_nonew.glon_peak > 345))
# find nearest v1 source to each v2 source
indv2v1, matchindv2v1, distv2v1 = pyspherematch.spherematch(
bgpsv2_nonew['glon_peak'], bgpsv2_nonew['glat_peak'],
bolocatv1['glon_peak'], bolocatv1['glat_peak'])
for name, catnum, glon_peak, glat_peak, ii, mi, dd in \
zip(bgpsv2_nonew['name'], bgpsv2_nonew['cnum'], glonv2_peak,
bgpsv2_nonew['glat_peak'], indv2v1, matchindv2v1, distv2v1):
# finding nearest v1 to v2
dx = (glonv1_peak[mi] - glon_peak)
dy = (bolocatv1['glat_peak'][mi] - glat_peak)
#dd = ( dx**2 + dy**2 ) **0.5
#closest = dd.argmin()
matchnames_peak_v1.append(bolocatv1.name[mi])
matchdist_peak_v1.append(dd)
matchxdiff_peak_v1.append(dx)
def match_zspec_zphoto_cmass():
''' Match photometric redshift to spectroscopic redshift. Spherematch
photometric and spectroscopic catalogs to determine redshift errors of
photmetric redshifts wrt spectroscopic redshifts.
Returns [z_spec, z_photo]
--------------------------------------------------------------------------
Parameters
--------------------------------------------------------------------------
None
--------------------------------------------------------------------------
Notes
--------------------------------------------------------------------------
* Using pyspherematch
* What is photometric redshift error in photometric catalog?
* Details on CMASS redshifts in: https://trac.sdss3.org/wiki/BOSS/clustering/WGCatalogCode
'''
# read in photometric catalog. See notes for
# catalog details
photo_file = ''.join([
'/mount/riachuelo1/hahn/photoz/',
'DR8LRG_CMASS_phtz_VF.cat'
])
photo_ra, photo_dec, photo_z, photo_zerr = np.loadtxt(
photo_file,
unpack=True,
skiprows=1,
usecols=[0,1,2,3])
# read in spectroscopic catalog. DR12v4 Full
# catalog.
spec_file = ''.join([
'/mount/riachuelo1/hahn/data/CMASS/',
'cmass-dr12v4-N-Reid-full.dat.fits'
])
spec = mrdfits(spec_file)
spec_ra = spec.ra
spec_dec = spec.dec
spec_z = spec.z
spec_imatch = spec.imatch
# spherematch spectroscopic catalog RA and Decl to
# photometric catalog RA and Decl. Afterwards, loop
# through each of the matches and only keep galaxies
# that have spectroscopic redshifts. This way we can
# calculate the errors in photometric redshift.
match_spec, match_photo, d = pysph.spherematch(
spec_ra, spec_dec, photo_ra, photo_dec, tol=None)
zspec, zphoto = [], []
for i_spec, i_m in enumerate(match_spec):
i_match = spec_imatch[i_m]
# imatch==0: Not matched to a redshift.
# imatch==1: Matched to a new BOSS redshift.
# imatch==2: Matched to an old SDSS redshift.
# imatch==3: Fiber collision corrected (using fiberc_zfail)
# imatch==4: Star (remove from target list when computing completeness).
# imatch==5: Redshift failure corrected (using fiberc_zfail)
# imatch==6: Fiber collision, but we cannot find a galaxy*
# redshift for it, this is used for flagging the collision, but if it is not
# overwritten by fiberc_zfail as we find a nearest neighbor (imatch=3),
# it will remain to be 6.
# imatch==7: Redshift failure, but we cannot find a galaxy*
# redshift for it, this is initially used for flagging the redshift failures,
# but if it is not overwritten by fiberc_zfail as we find a nearest neighbor
# (imatch=5), it will remain to be 7.
if i_match not in (1,2):
continue
if d[i_m] > 10**-10:
continue
zspec.append(spec_z[i_spec])
zphoto.append(photo_z[match_photo[i_m]])
zspec = np.array(zspec)
zphoto = np.array(zphoto)
return [zspec, zphoto]
def compile_saga_spectra(flagged_obs_hosts=False):
# RUN EITHER FULL HOST LIST OR JUST FLAG ZERO HOSTS, default to flag zero
if flagged_obs_hosts:
sheet = GoogleSheets('1GJYuhqfKeuJr-IyyGF_NDLb_ezL6zBiX2aeZFHHPr_s', 0)
else:
sheet = GoogleSheets('1b3k2eyFjHFDtmHce1xi6JKuj3ATOWYduTBFftx5oPp8',
448084634)
hostdata = sheet.load()
# READ ALL NON-SDSS SPECTRA AND COMBINE INTO SINGLE TABLE
gama_table = read_saga_spectra.read_gama()
mmt_table = read_saga_spectra.read_mmt()
aat_table = read_saga_spectra.read_aat()
aat_table_mz = read_saga_spectra.read_aat_mz()
imacs_table = read_saga_spectra.read_imacs()
wiyn_table = read_saga_spectra.read_wiyn()
deimos_table = read_saga_spectra.read_deimos()
# LEAST TO MOST IMPORTANT
sagaspec = table.vstack([wiyn_table,imacs_table,gama_table,deimos_table,aat_table,mmt_table,aat_table_mz],\
metadata_conflicts='silent')
# WRITE FILE WITH ALL SPECTRA
file = os.path.join(SAGA_DIR, 'data', 'saga_spectra_raw.fits.gz')
write_fits(sagaspec, file)
# COMBINE MULTIPLE SPECTRA
# read_saga_spectra.spec_combine(sagaspec)
spec = sagaspec
sagaspec = read_saga_spectra.find_uniques(spec)
# FOR EACH FLAG ZERO HOST OR NON-FLAG ZERO OBSERVED HOST
# READ BASE SDSS FILE
# KEEP ONLY SDSS SPECTRA AND MATCHES FROM OTHER SOURCES
nhost = 0
for host in hostdata:
flag = host['flag'] # SELECT ONLY NON_FLAG0#
if flag == 0:
nra = host['RA']
ndec = host['Dec']
nsaid = host['NSAID'] # NAME OF BASE SQL FILES
basefile = os.path.join(
SAGA_DIR, 'base_catalogs',
'base_sql_nsa{0}.fits.gz'.format(nsaid))
basetable = Table.read(basefile)
print nsaid
# CALCULATE OBJECT DISTANCE FROM HOST
catsc = SkyCoord(u.Quantity(sagaspec['RA'], u.deg),
u.Quantity(sagaspec['DEC'], u.deg))
hostcoords = SkyCoord(nra * u.deg, ndec * u.deg)
seps = catsc.separation(hostcoords)
rhost = seps.to(u.deg).value
host_spec_objs = rhost < 1.0
# COMBINE SDSS SPECTRA AND SAGA SPECTRA
sdss_table = read_saga_spectra.read_sdss(basetable)
hostspec = table.vstack([sdss_table, sagaspec[host_spec_objs]])
tmp = hostspec
hostspec = read_saga_spectra.find_uniques(tmp)
id2, id1, d = sm.spherematch(hostspec['RA'],
hostspec['DEC'],
basetable['RA'],
basetable['DEC'],
3. / 3600,
nnearest=1)
basetable['TELNAME'][id1] = hostspec['TELNAME'][id2]
basetable['MASKNAME'][id1] = hostspec['MASKNAME'][id2]
basetable['ZQUALITY'][id1] = hostspec['ZQUALITY'][id2]
basetable['SPEC_Z'][id1] = hostspec['SPEC_Z'][id2]
basetable['SPEC_Z_ERR'][id1] = hostspec['SPEC_Z_ERR'][id2]
basetable['SPECOBJID'][id1] = hostspec['specobjid'][id2]
basetable['SPEC_REPEAT'][id1] = hostspec['SPEC_REPEAT'][id2]
m = basetable['SPEC_Z'] != -1
m2 = basetable['TELNAME'][m] == ''
print 'number with telname = ', np.sum(m2)
# COMBINE INTO SINGLE ALLSPEC FILE
if (nhost == 0):
allspec = basetable[m]
if (nhost > 0):
allspec = table.vstack([allspec, basetable[m]]) # APPEND
nhost = nhost + 1
# INITIALIZE SATS ARRAY (3=primary, 2=lowz, 1=satellite)
allspec = saga_tools.fill_sats_array(allspec)
# CLEAN UP REPEAT ENTRY OF SATELLITES
allspec = saga_tools.repeat_sat_cleanup(allspec)
# WRITE ALL SPECTRA TAKEN
file = os.path.join(SAGA_DIR, 'data', 'saga_spectra_dirty.fits.gz')
write_fits(allspec, file)
# WRITE ALL GOOD SPECTRA
# KEEP ALL GOOD SPECTRA WHICH ARE GALAXIES
zql = allspec['ZQUALITY'] >= 3
rml = allspec['REMOVE'] == -1
galonly = allspec['PHOTPTYPE'] == 3
clean = zql & rml & galonly
allclean = allspec[clean]
file = os.path.join(SAGA_DIR, 'data', 'saga_spectra_clean.fits.gz')
write_fits(allclean, file)
# WRITE TEXT FILE OF SATELLITES WHICH CAN BE EDITED
# file = os.path.join(SAGA_DIR, 'data', 'saga_satellites.dat')
# allsats = allclean['SATS' == 1]
# write_satellite_file(allsats,file)
return allspec
def create_base_catalog(nsaid, host,nowise,noML,nosaga):
"""
Create single base catalog from SQL request
with value-added quantities
"""
# READ SQL FILE
sqlfile = os.path.join(SAGA_DIR, 'base_catalogs', 'sql_nsa{0}.fits.gz'.format(nsaid))
sqltable = Table.read(sqlfile)
# GET BASIC HOST PARAMETERS FROM GOOGLE HOST LIST
hostra = host['RA'] #RA
hostdec = host['Dec'] #DEC
hostdist = host['distance'] #DISTANCE
hostv = host['vhelio'] #VHELIO
hostMK = host['M_K']
hostMr = host['M_r']
hostMg = host['M_g']
# hostflag = host['flag'] #HOST FLAG
# CALCULATE OBJECT DISTANCE FROM HOST
catsc = SkyCoord(u.Quantity(sqltable['RA'], u.deg), u.Quantity(sqltable['DEC'], u.deg))
hostcoords = SkyCoord(hostra, hostdec,unit='deg')
seps = catsc.separation(hostcoords)
rhost_arcm = seps.to(u.arcmin).value
rhost_kpc = 1000.*hostdist*np.sin(np.deg2rad(rhost_arcm/60.))
# ADD EXTRA COLUMNS -
size = len(sqltable)
cols = [_filled_column('W1',-1.,size),
_filled_column('W1ERR',-1.,size),
_filled_column('W2',-1.,size),
_filled_column('W2ERR',-1.,size),
_filled_column('HOST_RA', hostra, size), #HOST
_filled_column('HOST_DEC', hostdec, size),
_filled_column('HOST_DIST', hostdist, size),
_filled_column('HOST_VHOST', hostv, size),
_filled_column('HOST_MK', hostMK, size),
_filled_column('HOST_MR', hostMr, size),
_filled_column('HOST_MG', hostMg, size),
_filled_column('HOST_NSAID', nsaid, size),
_filled_column('HOST_SAGA_NAME', ' '*48, size),
_filled_column('HOST_NGC_NAME', ' '*48, size),
Column(rhost_arcm, 'RHOST_ARCM'), #OBJECT
Column(rhost_kpc, 'RHOST_KPC'),
_filled_column('OBJ_NSAID', -1, size),
_filled_column('SATS', -1, size),
_filled_column('PROBABILITY_CLASS1', -1., size),
_filled_column('RESCALED_PROBABILITY_CLASS1', -1., size),
_filled_column('REMOVE', -1, size), # -1 = Good source; 1 = On remove list; 2 = Overlaps with NSA GALAXY
_filled_column('TELNAME', ' '*6, size), #SPECTRA
_filled_column('MASKNAME', ' '*48, size),
_filled_column('ZQUALITY', -1, size),
_filled_column('SPEC_CLASS', ' '*2, size),
_filled_column('SPECOBJID', ' '*48L, size),
_filled_column('SPEC_REPEAT', ' '*48, size),
_filled_column('SPEC_SN', -99., size),
_filled_column('SPEC_HA_EW', -99., size),
_filled_column('SPEC_HA_EWERR', -99., size)]
sqltable.add_columns(cols)
del cols
# ADD WISE NUMBERS
if not nowise:
wbasefile = os.path.join(SAGA_DIR, 'unwise', 'unwise_{0}.fits.gz'.format(nsaid))
print 'Read WISE catalog: ', wbasefile
wbasetable = FitsTable(wbasefile).load()
wbasetable['W1_MAG'][np.isnan(wbasetable['W1_MAG'])]=-1
wbasetable['W1_MAG_ERR'][np.isnan(wbasetable['W1_MAG_ERR'])]=-1
wbasetable['W2_MAG'][np.isnan(wbasetable['W2_MAG'])]=-1
wbasetable['W2_MAG_ERR'][np.isnan(wbasetable['W2_MAG_ERR'])]=-1
id1, id2, d = sm.spherematch(sqltable['RA'], sqltable['DEC'], wbasetable['RA'], wbasetable['DEC'], 1./3600)
sqltable['W1'][id1] = wbasetable['W1_MAG'][id2]
sqltable['W1ERR'][id1] = wbasetable['W1_MAG_ERR'][id2]
sqltable['W2'][id1] = wbasetable['W2_MAG'][id2]
sqltable['W2ERR'][id1] = wbasetable['W2_MAG_ERR'][id2]
# ADD ML PREDICTIONS USING OLD FILE
if not noML:
id1, id2, d = sm.spherematch(sqltable['RA'], sqltable['DEC'], ML['RA'], ML['DEC'], 1./3600)
sqltable['PROBABILITY_CLASS1'][id1] = ML['PROBABILITY_CLASS_1'][id2]
# INITALIZE SDSS SPECTRAL ENTRIES
msk = sqltable['SPEC_Z'] != -1
sqltable['TELNAME'][msk] = 'SDSS'
sqltable['MASKNAME'][msk] = 'SDSS'
sqltable['SPEC_REPEAT'][msk] = 'SDSS'
sqltable['ZQUALITY'][msk] = 4
# SET BAD SDSSS SPECTROSCOPY TO ZQ = -1
# THERE ARE A FEW RECOVERABLE SPECTRA WITH SPEC_Z_WARN = 4,
# BUT WILL NOT RECOVER THEM HERE
msk_badsdss = sqltable['SPEC_Z_WARN'] != 0
sqltable['ZQUALITY'][msk & msk_badsdss] = 1
# IF THIS IS A SAGA HOST, SET SAGA NAME
names = SAGANAMES.load()
sname = ''
ngc = ''
if nsaid in names['NSA']:
msk = names['NSA'] == nsaid
sname = names['SAGA'][msk]
ngc = names['NGC'][msk]
sqltable['HOST_SAGA_NAME'] = sname
sqltable['HOST_NGC_NAME'] = ngc
# ADD EXISTING SAGA SPECTRA TO FILE
sagaspec = SAGACAT.load()
if not nosaga:
sqltable = saga_tools.add_saga_spec(sagaspec,sqltable)
# SET REMOVE FLAGS
rmv = REMOVELIST.load()
sqltable = saga_tools.rm_removelist_obj(rmv, sqltable)
# CLEAN AND DE-SHRED USING NSAID
nsa = NSACAT.load()
print 'Cleaning on NSA catalog'
sqltable = saga_tools.nsa_cleanup(nsa, sqltable)
# CLEAN AND DE_SHRED HIGHER REDSHIFT OBJECTS
print 'Cleaning on SDSS catalog'
sqltable = saga_tools.sdss_cleanup(sqltable)
# REMOVE OBJECTS WITH BAD PHOTO-FLAGS, ADD OBJECTS BACK IN BY HAND
addlst = ADDLIST.load()
print 'Cleaning on PhotoFlags'
sqltable = saga_tools.photoflags(addlst,sqltable)
# FIX MAJOR PROBLEM SPECTRA BY HAND
sqltable = fix_byhand.fix_basecats(sqltable)
# FIX SATS ID BY HAND
clean_sagaspec = CLEAN.load()
sqltablle = fix_byhand.sat_hack(nsaid,sqltable,clean_sagaspec)
print
return sqltable
def compile_saga_spectra(flagged_obs_hosts=False):
# RUN EITHER FULL HOST LIST OR JUST FLAG ZERO HOSTS, default to flag zero
if flagged_obs_hosts:
sheet = GoogleSheets('1GJYuhqfKeuJr-IyyGF_NDLb_ezL6zBiX2aeZFHHPr_s', 0)
else:
sheet = GoogleSheets('1b3k2eyFjHFDtmHce1xi6JKuj3ATOWYduTBFftx5oPp8', 448084634)
hostdata = sheet.load()
# READ ALL NON-SDSS SPECTRA AND COMBINE INTO SINGLE TABLE
gama_table = read_saga_spectra.read_gama()
mmt_table = read_saga_spectra.read_mmt()
aat_table = read_saga_spectra.read_aat()
imacs_table = read_saga_spectra.read_imacs()
wiyn_table = read_saga_spectra.read_wiyn()
deimos_table = read_saga_spectra.read_deimos()
# LEAST TO MOST IMPORTANT
sagaspec = table.vstack([wiyn_table,imacs_table,gama_table,deimos_table,aat_table,mmt_table],\
metadata_conflicts='silent')
# zq = sagaspec['ZQUALITY'] > 2
# need to write script to resolve repeats properly
# sagaspec=sagaspec[zq]
# FOR EACH FLAG ZERO HOST OR NON-FLAG ZERO OBSERVED HOST
# READ BASE SDSS FILE
# KEEP ONLY SDSS SPECTRA AND MATCHES FROM OTHER SOURCES
nhost = 0
for host in hostdata:
flag = host['flag'] # SELECT ONLY NON_FLAG0#
if flag == 0:
nra = host['RA']
ndec = host['Dec']
nsaid = host['NSAID']# NAME OF BASE SQL FILES
basefile = os.path.join(SAGA_DIR, 'base_catalogs', 'base_sql_nsa{0}.fits.gz'.format(nsaid))
basetable = Table.read(basefile)
print nsaid
# CALCULATE OBJECT DISTANCE FROM HOST
catsc = SkyCoord(u.Quantity(sagaspec['RA'], u.deg), u.Quantity(sagaspec['DEC'], u.deg))
hostcoords = SkyCoord(nra*u.deg, ndec*u.deg)
seps = catsc.separation(hostcoords)
rhost = seps.to(u.deg).value
host_spec_objs = rhost < 1.0
# COMBINE SDSS SPECTRA AND SAGA SPECTRA
sdss_table = read_saga_spectra.read_sdss(basetable)
hostspec = table.vstack([sdss_table,sagaspec[host_spec_objs]])
# MATCH ALL SPECTRA TO BASECATALOG, ADD SPEC DETAILS
id2,id1,d = sm.spherematch(hostspec['RA'], hostspec['DEC'],basetable['RA'], basetable['DEC'],3./3600,nnearest=1)
basetable['TELNAME'][id1] = hostspec['TELNAME'][id2]
basetable['MASKNAME'][id1] = hostspec['MASKNAME'][id2]
basetable['ZQUALITY'][id1] = hostspec['ZQUALITY'][id2]
basetable['SPEC_Z'][id1] = hostspec['SPEC_Z'][id2]
basetable['SPECOBJID'][id1] = hostspec['specobjid'][id2]
basetable['SPEC_REPEAT'][id1] = hostspec['TELNAME'][id2]
m = basetable['SPEC_Z'] != -1
# COMBINE INTO SINGLE ALLSPEC FILE
if (nhost == 0):
allspec = basetable[m]
if (nhost > 0):
allspec = table.vstack([allspec,basetable[m]]) # APPEND
nhost=nhost+1
# INITIALIZE SATS ARRAY (3=primary, 2=lowz, 1=satellite)
allspec = saga_tools.fill_sats_array(allspec)
# CLEAN UP REPEAT ENTRY OF SATELLITES
allspec = saga_tools.repeat_sat_cleanup(allspec)
# HACK FOR THE MOMENT
# m1=allspec['REMOVE'] == 3
# m2=allspec['SATS'] == 1
# m=m1&m2
# allspec['REMOVE'][m] = -1 # keep remove = 3 satelites
# m1=allspec['REMOVE'] == 2
# m2=allspec['SATS'] == 1
# m=m1&m2
# allspec['SATS'][m] = -1 # remove remove=2 satellites
# WRITE ALL SPECTRA TAKEN
file = os.path.join(SAGA_DIR, 'data', 'saga_spectra_dirty.fits.gz')
write_fits(allspec, file)
# WRITE ALL GOOD SPECTRA
# KEEP ALL GOOD SPECTRA WHICH ARE GALAXIES
zql = allspec['ZQUALITY'] >= 3
rml = allspec['REMOVE'] == -1
galonly = allspec['PHOTPTYPE'] == 3
clean = zql & rml & galonly
allclean = allspec[clean]
file = os.path.join(SAGA_DIR, 'data', 'saga_spectra_clean.fits.gz')
write_fits(allclean,file)
return allspec
def __init__(self, catname,fitsname,jpegname,tracername,membername, boxname, bcgname, bcgname2, notesname, nedspec, photspec,choose_gal, readbcgs, xcs_z):
im = imread(jpegname)
scaled_image_data = im/255.
self.im = scaled_image_data
imfit = pyfits.open(fitsname)
w = wcs.WCS(imfit[0].header)
self.wcs = w
# dt = [('ra',float), ('dec',float), ('mag_auto_g',float), ('magerr_auto_g',float), ('flags_g',float), ('class_star_g',float), ('spread_model_g',float), \
# ('mag_auto_r',float), ('magerr_auto_r',float), ('flags_r',float), ('class_star_r',float), ('spread_model_r',float),\
# ('mag_auto_i',float), ('magerr_auto_i',float), ('flags_i',float), ('class_star_i',float), ('spread_model_i',float),\
# ('mag_auto_z',float), ('magerr_auto_z',float), ('flags_z',float), ('class_star_z',float), ('spread_model_z',float)]
dt = [('ra',float), ('dec',float), ('mag_auto_g',float), ('magerr_auto_g',float), ('mag_auto_r',float), ('magerr_auto_r',float), ('mag_auto_i',float), ('magerr_auto_i',float), \
('mag_auto_z',float), ('magerr_auto_z',float), \
('mag_detmodel_g',float), ('magerr_detmodel_g',float), ('mag_detmodel_r',float), ('magerr_detmodel_r',float), ('mag_detmodel_i',float), ('magerr_detmodel_i',float), \
('mag_detmodel_z',float), ('magerr_detmodel_z',float)]
cnr1 = w.wcs_pix2world(imfit[0].header['NAXIS1'],imfit[0].header['NAXIS2'],1)
cnr2 = w.wcs_pix2world(imfit[0].header['NAXIS1'],0,1)
cnr3 = w.wcs_pix2world(0,imfit[0].header['NAXIS2'],1)
cnr4 = w.wcs_pix2world(0,0,1)
cnrra = [cnr1[0],cnr2[0],cnr3[0],cnr4[0]]
cnrdec = [cnr1[1],cnr2[1],cnr3[1],cnr4[1]]
maxra = max(cnrra)
minra = min(cnrra)
maxdec = max(cnrdec)
mindec = min(cnrdec)
# cut specz ad photoz galaxies
try:
if (nedspec != 0):
wkeep = where((nedspec['ra'] >= minra) & (nedspec['ra'] <= maxra) & (nedspec['dec'] >= mindec) & (nedspec['dec'] <= maxdec))
self.zra = nedspec[wkeep]['ra']
self.zdec = nedspec[wkeep]['dec']
self.zz = nedspec[wkeep]['z']
except:
self.zra = np.array([])
self.zdec = np.array([])
self.zz = np.array([])
try:
if (photspec != 0):
wkeep = where((photspec.field('ra') >= minra) & (photspec.field('ra') <= maxra) & (photspec.field('dec') >= mindec) & (photspec.field('dec') <= maxdec))
self.zra = np.append(self.zra, photspec[wkeep].field('ra'))
self.zdec = np.append(self.zdec, photspec[wkeep].field('dec'))
self.zz = np.append(self.zz, photspec[wkeep].field('z'))
except:
self.zra = np.array([])
self.zdec = np.array([])
self.zz = np.array([])
# read in all galaxies
galaxy = np.loadtxt(catname, dtype=dt, skiprows=(1), delimiter=',')
inside = ((galaxy['ra'] < maxra) & (galaxy['ra'] > minra) & (galaxy['dec'] < maxdec) & (galaxy['dec'] > mindec))
galaxy = galaxy[inside]
self.gr_mag_all = galaxy['mag_auto_r']
self.ri_mag_all = galaxy['mag_auto_r']
self.iz_mag_all = galaxy['mag_auto_i']
self.rz_mag_all = galaxy['mag_auto_i']
self.gi_mag_all = galaxy['mag_auto_i']
self.gr_color_all = galaxy['mag_detmodel_g'] - galaxy['mag_detmodel_r']
self.gi_color_all = galaxy['mag_detmodel_g'] - galaxy['mag_detmodel_i']
self.ri_color_all = galaxy['mag_detmodel_r'] - galaxy['mag_detmodel_i']
self.iz_color_all = galaxy['mag_detmodel_i'] - galaxy['mag_detmodel_z']
self.rz_color_all = galaxy['mag_detmodel_r'] - galaxy['mag_detmodel_z']
self.ra_all = galaxy['ra']
self.dec_all = galaxy['dec']
# open tracer files.
dt = [('ra',float), ('dec',float), ('g_mag',float)]
self.ra = np.array([])
self.dec = np.array([])
self.gr_color = np.array([])
self.ri_color = np.array([])
self.iz_color = np.array([])
self.rz_color = np.array([])
self.gi_color = np.array([])
self.g_mag = np.array([])
self.r_mag = np.array([])
self.i_mag = np.array([])
self.z_mag = np.array([])
try:
with open(membername):
cmrgalaxy = np.loadtxt(membername, dtype=dt, skiprows=(0), delimiter=' ')
m1 = np.zeros_like(cmrgalaxy['ra'], dtype=bool)
m2 = np.zeros_like(cmrgalaxy['dec'], dtype=bool)
m1[np.unique(cmrgalaxy['ra'], return_index=True)[1]] = True
m2[np.unique(cmrgalaxy['dec'], return_index=True)[1]] = True
keep = where((m1 == True) & (m2 == True))
if size(keep) > 0:
for kk in range (0,size(keep)):
try:
result = psm.spherematch(cmrgalaxy['ra'][keep][kk],cmrgalaxy['dec'][keep][kk], self.ra_all, self.dec_all, nnearest=1)
if (result[0] < 0.1/3600.):
self.ra = np.append(self.ra,self.ra_all[result[1].astype(int)])
self.dec = np.append(self.dec,self.dec_all[result[1].astype(int)])
self.gr_color = np.append(self.gr_color,self.gr_color_all[result[1].astype(int)])
self.gi_color = np.append(self.gi_color,self.gi_color_all[result[1].astype(int)])
self.ri_color = np.append(self.ri_color,self.ri_color_all[result[1].astype(int)])
self.iz_color = np.append(self.iz_color,self.iz_color_all[result[1].astype(int)])
self.rz_color = np.append(self.rz_color,self.rz_color_all[result[1].astype(int)])
self.g_mag = np.append(self.g_mag,galaxy['mag_auto_g'][result[1].astype(int)])
self.r_mag = np.append(self.r_mag,galaxy['mag_auto_r'][result[1].astype(int)])
self.i_mag = np.append(self.i_mag,galaxy['mag_auto_i'][result[1].astype(int)])
self.z_mag = np.append(self.z_mag,galaxy['mag_auto_z'][result[1].astype(int)])
except:
pass
except:
pass
dt = [('ra',float), ('dec',float), ('g_mag',float), ('r_mag',float),('i_mag',float),('z_mag',float),('gr_color',float), ('gi_color',float),('ri_color',float),('iz_color',float),('rz_color',float)]
try:
with open(tracername):
cmrgalaxy = np.loadtxt(tracername, dtype=dt, skiprows=(0), delimiter=' ')
m1 = np.zeros_like(cmrgalaxy['ra'], dtype=bool)
m2 = np.zeros_like(cmrgalaxy['dec'], dtype=bool)
m1[np.unique(cmrgalaxy['ra'], return_index=True)[1]] = True
m2[np.unique(cmrgalaxy['dec'], return_index=True)[1]] = True
keep = where((m1 == True) & (m2 == True))
if size(keep) > 0:
for kk in range (0,size(keep)):
try:
result = psm.spherematch(cmrgalaxy['ra'][keep][kk],cmrgalaxy['dec'][keep][kk], self.ra_all, self.dec_all, nnearest=1)
if (result[0] < 0.1/3600.):
self.ra = np.append(self.ra,self.ra_all[result[1].astype(int)])
self.dec = np.append(self.dec,self.dec_all[result[1].astype(int)])
self.gr_color = np.append(self.gr_color,self.gr_color_all[result[1].astype(int)])
self.gi_color = np.append(self.gi_color,self.gi_color_all[result[1].astype(int)])
self.ri_color = np.append(self.ri_color,self.ri_color_all[result[1].astype(int)])
self.iz_color = np.append(self.iz_color,self.iz_color_all[result[1].astype(int)])
self.rz_color = np.append(self.rz_color,self.rz_color_all[result[1].astype(int)])
self.g_mag = np.append(self.g_mag,galaxy['mag_auto_g'][result[1].astype(int)])
self.r_mag = np.append(self.r_mag,galaxy['mag_auto_r'][result[1].astype(int)])
self.i_mag = np.append(self.i_mag,galaxy['mag_auto_i'][result[1].astype(int)])
self.z_mag = np.append(self.z_mag,galaxy['mag_auto_z'][result[1].astype(int)])
except:
pass
except:
pass
if len(self.ra)>1:
m1 = np.zeros_like(np.array(self.ra), dtype=bool)
m2 = np.zeros_like(np.array(self.ra), dtype=bool)
m1[np.unique(self.ra, return_index=True)[1]] = True
m2[np.unique((np.array(self.ra))*(np.array(self.dec)), return_index=True)[1]] = True
keep = where((m1 == True) & (m2 == True))
self.ra=self.ra[keep]
self.dec=self.dec[keep]
self.gr_color=self.gr_color[keep]
self.gi_color=self.gi_color[keep]
self.ri_color=self.ri_color[keep]
self.iz_color=self.iz_color[keep]
self.rz_color=self.rz_color[keep]
self.g_mag=self.g_mag[keep]
self.r_mag=self.r_mag[keep]
self.i_mag=self.i_mag[keep]
self.z_mag=self.z_mag[keep]
#initialize BCG list
dt = [('ra',float), ('dec',float), ('g_mag',float), ('r_mag',float),('i_mag',float),('z_mag',float),('gr_color',float), ('gi_color',float),('ri_color',float),('iz_color',float),('rz_color',float)]
self.bcg_xpix = np.array([])
self.bcg_ypix = np.array([])
self.bcg_ra = np.array([])
self.bcg_dec = np.array([])
self.bcg_gr_color = np.array([])
self.bcg_gi_color = np.array([])
self.bcg_ri_color = np.array([])
self.bcg_iz_color = np.array([])
self.bcg_rz_color = np.array([])
self.bcg_g_mag = np.array([])
self.bcg_r_mag = np.array([])
self.bcg_i_mag = np.array([])
self.bcg_z_mag = np.array([])
if readbcgs:
try:
with open(bcgname):
bcggals=np.loadtxt(bcgname, dtype=dt, skiprows=(0), delimiter=' ')
xpixtemp, ypixtemp= w.wcs_world2pix(bcggals['ra'], bcggals['dec'],1)
self.bcg_xpix=np.append(self.bcg_xpix, xpixtemp)
self.bcg_ypix=np.append(self.bcg_ypix, ypixtemp)
self.bcg_ra=np.append(self.bcg_ra, bcggals['ra'])
self.bcg_dec=np.append(self.bcg_dec, bcggals['dec'])
self.bcg_gr_color=np.append(self.bcg_gr_color, bcggals['gr_color'])
self.bcg_gi_color=np.append(self.bcg_gi_color, bcggals['gi_color'])
self.bcg_ri_color=np.append(self.bcg_ri_color, bcggals['ri_color'])
self.bcg_iz_color=np.append(self.bcg_iz_color, bcggals['iz_color'])
self.bcg_rz_color=np.append(self.bcg_rz_color, bcggals['rz_color'])
self.bcg_g_mag=np.append(self.bcg_g_mag, bcggals['g_mag'])
self.bcg_r_mag=np.append(self.bcg_r_mag, bcggals['r_mag'])
self.bcg_i_mag=np.append(self.bcg_i_mag, bcggals['i_mag'])
self.bcg_z_mag=np.append(self.bcg_z_mag, bcggals['z_mag'])
except:
pass
try:
with open(bcgname2):
bcggals=np.loadtxt(bcgname2, dtype=dt, skiprows=(0), delimiter=' ')
xpixtemp, ypixtemp= w.wcs_world2pix(bcggals['ra'], bcggals['dec'],1)
self.bcg_xpix=np.append(self.bcg_xpix, xpixtemp)
self.bcg_ypix=np.append(self.bcg_ypix, ypixtemp)
self.bcg_ra=np.append(self.bcg_ra, bcggals['ra'])
self.bcg_dec=np.append(self.bcg_dec, bcggals['dec'])
self.bcg_gr_color=np.append(self.bcg_gr_color, bcggals['gr_color'])
self.bcg_gi_color=np.append(self.bcg_gi_color, bcggals['gi_color'])
self.bcg_ri_color=np.append(self.bcg_ri_color, bcggals['ri_color'])
self.bcg_iz_color=np.append(self.bcg_iz_color, bcggals['iz_color'])
self.bcg_rz_color=np.append(self.bcg_rz_color, bcggals['rz_color'])
self.bcg_g_mag=np.append(self.bcg_g_mag, bcggals['g_mag'])
self.bcg_r_mag=np.append(self.bcg_r_mag, bcggals['r_mag'])
self.bcg_i_mag=np.append(self.bcg_i_mag, bcggals['i_mag'])
self.bcg_z_mag=np.append(self.bcg_z_mag, bcggals['z_mag'])
except:
pass
if len(self.bcg_ra)>1:
m1 = np.zeros_like(np.array(self.bcg_ra), dtype=bool)
m2 = np.zeros_like(np.array(self.bcg_ra), dtype=bool)
m1[np.unique(self.bcg_ra, return_index=True)[1]] = True
m2[np.unique((np.array(self.bcg_ra))*(np.array(self.bcg_dec)), return_index=True)[1]] = True
keep = where((m1 == True) & (m2 == True))
self.bcg_xpix=self.bcg_xpix[keep]
self.bcg_ypix=self.bcg_ypix[keep]
self.bcg_ra=self.bcg_ra[keep]
self.bcg_dec=self.bcg_dec[keep]
self.bcg_gr_color=self.bcg_gr_color[keep]
self.bcg_gi_color=self.bcg_gi_color[keep]
self.bcg_ri_color=self.bcg_ri_color[keep]
self.bcg_iz_color=self.bcg_iz_color[keep]
self.bcg_rz_color=self.bcg_rz_color[keep]
self.bcg_g_mag=self.bcg_g_mag[keep]
self.bcg_r_mag=self.bcg_r_mag[keep]
self.bcg_i_mag=self.bcg_i_mag[keep]
self.bcg_z_mag=self.bcg_z_mag[keep]
#open box files
dt = [('xbot',float), ('xtop',float), ('ybot',float), ('ytop',float)]
self.gr_xbot = np.array([])
self.gr_xtop = np.array([])
self.ri_xbot = np.array([])
self.ri_xtop = np.array([])
self.iz_xbot = np.array([])
self.iz_xtop = np.array([])
self.gi_xbot = np.array([])
self.gi_xtop = np.array([])
self.rz_xbot = np.array([])
self.rz_xtop = np.array([])
self.gr_ybot = np.array([])
self.gr_ytop = np.array([])
self.ri_ybot = np.array([])
self.ri_ytop = np.array([])
self.iz_ybot = np.array([])
self.iz_ytop = np.array([])
self.gi_ybot = np.array([])
self.gi_ytop = np.array([])
self.rz_ybot = np.array([])
self.rz_ytop = np.array([])
try:
with open(boxname):
boxit = np.loadtxt(boxname, dtype=dt, skiprows=(0))
self.gr_xbot = boxit[0]['xbot']
self.gr_xtop = boxit[0]['xtop']
self.gr_ybot = boxit[0]['ybot']
self.gr_ytop = boxit[0]['ytop']
self.ri_xbot = boxit[1]['xbot']
self.ri_xtop = boxit[1]['xtop']
self.ri_ybot = boxit[1]['ybot']
self.ri_ytop = boxit[1]['ytop']
self.iz_xbot = boxit[2]['xbot']
self.iz_xtop = boxit[2]['xtop']
self.iz_ybot = boxit[2]['ybot']
self.iz_ytop = boxit[2]['ytop']
self.gi_xbot = boxit[3]['xbot']
self.gi_xtop = boxit[3]['xtop']
self.gi_ybot = boxit[3]['ybot']
self.gi_ytop = boxit[3]['ytop']
self.rz_xbot = boxit[4]['xbot']
self.rz_xtop = boxit[4]['xtop']
self.rz_ybot = boxit[4]['ybot']
self.rz_ytop = boxit[4]['ytop']
except IOError:
self.gr_xbot = 0
self.gr_xtop = 0
self.gr_ybot = 0
self.gr_ytop = 0
self.ri_xbot = 0
self.ri_xtop = 0
self.ri_ybot = 0
self.ri_ytop = 0
self.iz_xbot = 0
self.iz_xtop = 0
self.iz_ybot = 0
self.iz_ytop = 0
self.gi_xbot = 0
self.gi_xtop = 0
self.gi_ybot = 0
self.gi_ytop = 0
self.rz_xbot = 0
self.rz_xtop = 0
self.rz_ybot = 0
self.rz_ytop = 0
# trim member, specz and photoz galaxies
if (len(self.ra) > 1):
a = len(self.ra)
xpix = np.zeros([len(self.ra)])
ypix = np.zeros([len(self.ra)])
for i in range(0,a):
xpix[i],ypix[i] = w.wcs_world2pix(self.ra[i],self.dec[i],1)
else:
xpix = np.array([0])
ypix = np.array([0])
m1 = np.zeros_like(xpix, dtype=bool)
m2 = np.zeros_like(ypix, dtype=bool)
m1[np.unique(xpix, return_index=True)[1]] = True
m2[np.unique(ypix, return_index=True)[1]] = True
keep = where((m1 == True) & (m2 == True) & (xpix != 0))
self.xpix = xpix[keep]
self.ypix = ypix[keep]
self.ra = self.ra[keep]
self.dec = self.dec[keep]
self.gr_color = self.gr_color[keep]
self.gi_color = self.gi_color[keep]
self.ri_color = self.ri_color[keep]
self.iz_color = self.iz_color[keep]
self.rz_color = self.rz_color[keep]
self.g_mag = self.g_mag[keep]
self.r_mag = self.r_mag[keep]
self.i_mag = self.i_mag[keep]
self.z_mag = self.z_mag[keep]
self.z_gr_color = np.array([])
self.z_gi_color = np.array([])
self.z_ri_color = np.array([])
self.z_iz_color = np.array([])
self.z_rz_color = np.array([])
self.z_gr_mag = np.array([])
self.z_gi_mag = np.array([])
self.z_ri_mag = np.array([])
self.z_iz_mag = np.array([])
self.z_rz_mag = np.array([])
self.z_member = np.array([])
self.z_member_z = np.array([])
if (len(self.zra) > 1 and len(self.ra_all) > 1):
a = len(self.zra)
for i in range(0,a):
# xpix,ypix = w.wcs_world2pix(self.zra[i],self.zdec[i],1)
# world = w.wcs_pix2world(xpix,667-ypix,1)
# result = psm.spherematch(world[0],world[1], self.ra_all, self.dec_all, nnearest=1)
result = psm.spherematch(self.zra[i],self.zdec[i], self.ra_all, self.dec_all, nnearest=1)
if (result[0] < 1./3600.):
self.z_gr_color = append(self.z_gr_color,self.gr_color_all[result[1].astype(int)])
self.z_gi_color = append(self.z_gi_color,self.gi_color_all[result[1].astype(int)])
self.z_ri_color = append(self.z_ri_color,self.ri_color_all[result[1].astype(int)])
self.z_iz_color = append(self.z_iz_color,self.iz_color_all[result[1].astype(int)])
self.z_rz_color = append(self.z_rz_color,self.rz_color_all[result[1].astype(int)])
self.z_gr_mag = append(self.z_gr_mag,self.gr_mag_all[result[1].astype(int)])
self.z_gi_mag = append(self.z_gi_mag,self.gi_mag_all[result[1].astype(int)])
self.z_ri_mag = append(self.z_ri_mag,self.ri_mag_all[result[1].astype(int)])
self.z_iz_mag = append(self.z_iz_mag,self.iz_mag_all[result[1].astype(int)])
self.z_rz_mag = append(self.z_rz_mag,self.rz_mag_all[result[1].astype(int)])
self.z_member = append(self.z_member,result[1].astype(int))
self.z_member_z = append(self.z_member_z, self.zz[i])
#start making figures
ion()
fig = plt.figure(num = 1, figsize=(12,12))
fig.clf()
ax = MultiPane_Subplot(fig, subplot_pos=(1, 1, 1), nrows_ncols = (2, 2), n_pane=4, pane_direction="row", axes_pad_inch=0.0)
fig.add_subplot(ax)
ax[0].imshow(scaled_image_data)
ax[1].imshow(scaled_image_data[:,:,0], cmap=plt.cm.Reds_r)
ax[2].imshow(scaled_image_data[:,:,1], cmap=plt.cm.Greens_r)
ax[3].imshow(scaled_image_data[:,:,2], cmap=plt.cm.Blues_r)
fig2 = plt.figure(num = 2, figsize=(18,9))
fig2.clf()
bx = MultiPane_Subplot(fig2, subplot_pos=(1, 1, 1), nrows_ncols = (2, 3), n_pane=6, pane_direction="row", axes_pad_inch=0.0)
fig2.add_subplot(bx)
self.temp_xpix=-100
self.temp_ypix=-100
self.temp_gr_color=-100
self.temp_gi_color=-100
self.temp_ri_color=-100
self.temp_iz_color=-100
self.temp_rz_color=-100
self.temp_r_mag=-100
self.temp_i_mag=-100
def display_ax0():
ax[0].cla()
ax[0].imshow(scaled_image_data)
for i in range(0,len(self.xpix)):
ellipse = Ellipse(xy=(self.xpix[i], 667-self.ypix[i]), width=30, height=30, edgecolor='g', fc='None', lw=2)
ax[0].add_patch(ellipse)
if (len(self.zra) > 0):
a = len(self.zra)
for i in range(a):
xpix,ypix = w.wcs_world2pix(self.zra[i],self.zdec[i],1)
left = xpix - 10
bottom = 667 - (ypix + 10)
rectangle = Rectangle((left,bottom), 20,20,edgecolor='c', fc='None', lw=1)
ax[0].add_patch(rectangle)
if (len(self.bcg_ra)>0):
a = len(self.bcg_ra)
for i in range(a):
xpix,ypix = w.wcs_world2pix(self.bcg_ra[i],self.bcg_dec[i],1)
left = xpix - 20
bottom = 667 - (ypix + 20)
rectangle = Rectangle((left,bottom), 40,40,edgecolor='r', fc='None', lw=1)
ax[0].add_patch(rectangle)
if self.temp_gr_color !=-100:
left = self.temp_xpix - 15
bottom = 667 - (self.temp_ypix + 15)
rectangle = Rectangle((left,bottom), 30, 30,edgecolor='g', fc='none', lw=1)
ax[0].add_patch(rectangle)
fig.suptitle('Measured Redshift = '+'{: .3f}'.format(xcs_z), fontsize=20)
fig.canvas.draw()
def display_bx():
bx[0].cla()
bx[1].cla()
bx[3].cla()
bx[4].cla()
bx[5].cla()
bx[0].text(20, 0.0, r'g-r', fontsize=15)
bx[1].text(20, 0.0, r'g-i', fontsize=15)
bx[3].text(20, 2, r'r-i', fontsize=15)
bx[4].text(20, 2, r'i-z', fontsize=15)
bx[5].text(20, 2, r'r-z', fontsize=15)
bx[0].scatter(self.gr_mag_all, self.gr_color_all,color="black", marker='.',s=1)
bx[1].scatter(self.gi_mag_all, self.gi_color_all,color="black", marker='.',s=1)
bx[3].scatter(self.ri_mag_all, self.ri_color_all,color="black", marker='.',s=1)
bx[4].scatter(self.iz_mag_all, self.iz_color_all,color="black", marker='.',s=1)
bx[5].scatter(self.rz_mag_all, self.rz_color_all,color="black", marker='.',s=1)
if len(self.ra) > 1:
bx[0].scatter(self.r_mag,self.gr_color,marker='o',s=40,color="blue")
bx[1].scatter(self.i_mag,self.gi_color,marker='o',s=40,color="green")
bx[3].scatter(self.r_mag,self.ri_color,marker='o',s=40,color="orange")
bx[4].scatter(self.i_mag,self.iz_color,marker='o',s=40,color="red")
bx[5].scatter(self.i_mag,self.rz_color,marker='o',s=40,color="magenta")
if len(self.zra) > 1:
bx[0].scatter(self.z_gr_mag,self.z_gr_color,color="cyan",marker='s',s=5)
bx[1].scatter(self.z_gi_mag,self.z_gi_color,color="cyan",marker='s',s=5)
bx[3].scatter(self.z_ri_mag,self.z_ri_color,color="cyan",marker='s',s=5)
bx[4].scatter(self.z_iz_mag,self.z_iz_color,color="cyan",marker='s',s=5)
bx[5].scatter(self.z_rz_mag,self.z_rz_color,color="cyan",marker='s',s=5)
if len(self.bcg_ra>1):
bx[0].scatter(self.bcg_r_mag,self.bcg_gr_color,color="red",marker=(5, 0),s=250, alpha=0.2)
bx[1].scatter(self.bcg_i_mag,self.bcg_gi_color,color="red",marker=(5, 0),s=250, alpha=0.2)
bx[3].scatter(self.bcg_r_mag,self.bcg_ri_color,color="red",marker=(5, 0),s=250, alpha=0.2)
bx[4].scatter(self.bcg_i_mag,self.bcg_iz_color,color="red",marker=(5, 0),s=250, alpha=0.2)
bx[5].scatter(self.bcg_i_mag,self.bcg_rz_color,color="red",marker=(5, 0),s=250, alpha=0.2)
if self.temp_gr_color !=-100:
bx[0].scatter(self.temp_r_mag, self.temp_gr_color, color="black", marker=(5, 2), s=250, alpha=0.4)
bx[1].scatter(self.temp_i_mag, self.temp_gi_color, color="black", marker=(5, 2), s=250, alpha=0.4)
bx[3].scatter(self.temp_r_mag, self.temp_ri_color, color="black", marker=(5, 2), s=250, alpha=0.4)
bx[4].scatter(self.temp_i_mag, self.temp_iz_color, color="black", marker=(5, 2), s=250, alpha=0.4)
bx[5].scatter(self.temp_i_mag, self.temp_rz_color, color="black", marker=(5, 2), s=250, alpha=0.4)
if (self.gr_xbot != 0):
rect = Rectangle( ( 0,0 ), 1, 1, alpha = 0.2, ec = "gray", fc = "CornflowerBlue", visible = True, axes=bx[0])
rect.set_width(self.gr_xtop - self.gr_xbot)
rect.set_height(self.gr_ytop - self.gr_ybot)
rect.set_xy((self.gr_xbot, self.gr_ybot))
bx[0].add_patch(rect)
if (self.gi_xbot != 0):
rect = Rectangle( ( 0,0 ), 1, 1, alpha = 0.2, ec = "gray", fc = "CornflowerBlue", visible = True, axes=bx[1])
rect.set_width(self.gi_xtop - self.gi_xbot)
rect.set_height(self.gi_ytop - self.gi_ybot)
rect.set_xy((self.gi_xbot, self.gi_ybot))
bx[1].add_patch(rect)
if (self.ri_xbot != 0):
rect = Rectangle( ( 0,0 ), 1, 1, alpha = 0.2, ec = "gray", fc = "CornflowerBlue", visible = True, axes=bx[3])
rect.set_width(self.ri_xtop - self.ri_xbot)
rect.set_height(self.ri_ytop - self.ri_ybot)
rect.set_xy((self.ri_xbot, self.ri_ybot))
bx[3].add_patch(rect)
if (self.iz_xbot != 0):
rect = Rectangle( ( 0,0 ), 1, 1, alpha = 0.2, ec = "gray", fc = "CornflowerBlue", visible = True, axes=bx[4])
rect.set_width(self.iz_xtop - self.iz_xbot)
rect.set_height(self.iz_ytop - self.iz_ybot)
rect.set_xy((self.iz_xbot, self.iz_ybot))
bx[4].add_patch(rect)
if (self.rz_xbot != 0):
rect = Rectangle( ( 0,0 ), 1, 1, alpha = 0.2, ec = "gray", fc = "CornflowerBlue", visible = True, axes=bx[5])
rect.set_width(self.rz_xtop - self.rz_xbot)
rect.set_height(self.rz_ytop - self.rz_ybot)
rect.set_xy((self.rz_xbot, self.rz_ybot))
bx[5].add_patch(rect)
bx.set_xlim(16, 24)
bx.set_ylim(-0.2, 3.5)
bx.axes_llc.set_xlabel("magnitude")
bx.axes_llc.set_ylabel("color")
fig2.suptitle('Measured Redshift = '+'{: .3f}'.format(xcs_z), fontsize=20)
fig2.canvas.draw()
display_ax0()
display_bx()
#start procedures to enable mouse actions
def on_press(event):
self.x0 = event.xdata
self.y0 = event.ydata
self.x0a = event.x
self.y0a = event.y
def on_release(event):
x0=self.x0
y0=self.y0
x0a=self.x0a
y0a=self.y0a
x1 = event.xdata
y1 = event.ydata
x1a = event.x
y1a = event.y
self.x1=x1
self.y1=y1
self.x1a=x1a
self.y1a=y1a
if ( y1>y0 ):
ytop = y1
ybot = y0
else:
ybot = y1
ytop = y0
if ( x1>x0 ):
xtop = x1
xbot = x0
else:
xbot = x1
xtop = x0
bbox = fig2.get_window_extent().transformed(fig2.dpi_scale_trans.inverted())
fullwidth = bbox.width*fig2.dpi
fullheight = bbox.height*fig2.dpi
bbox = bx.get_window_extent()
bxwidth = bbox.width
bxheight = bbox.height
padx = (fullwidth - bxwidth*3)/2.0
pady = (fullheight - bxheight*2)/2.0
panel0xmin = padx
panel0xmax = padx + bxwidth
panel0ymin = pady + bxheight
panel0ymax = pady + 2*bxheight
panel1xmin = padx + bxwidth
panel1xmax = padx + 2*bxwidth
panel1ymin = pady + bxheight
panel1ymax = pady + 2*bxheight
panel3xmin = padx
panel3xmax = padx + bxwidth
panel3ymin = pady
panel3ymax = pady + bxheight
panel4xmin = padx + bxwidth
panel4xmax = padx + 2*bxwidth
panel4ymin = pady
panel4ymax = pady + bxheight
panel5xmin = padx + 2*bxwidth
panel5xmax = padx + 3*bxwidth
panel5ymin = pady
panel5ymax = pady + bxheight
if ((x0a < panel0xmax) & (x0a > panel0xmin) & (y0a > panel0ymin) & (y0a < panel0ymax)):
self.gr_xbot = xbot
self.gr_xtop = xtop
self.gr_ybot = ybot
self.gr_ytop = ytop
elif ((x0a < panel3xmax) & (x0a > panel3xmin) & (y0a > panel3ymin) & (y0a < panel3ymax)):
self.ri_xbot = xbot
self.ri_xtop = xtop
self.ri_ybot = ybot
self.ri_ytop = ytop
elif ((x0a < panel1xmax) & (x0a > panel1xmin) & (y0a > panel1ymin) & (y0a < panel1ymax)):
self.gi_xbot = xbot
self.gi_xtop = xtop
self.gi_ybot = ybot
self.gi_ytop = ytop
elif ((x0a < panel4xmax) & (x0a > panel4xmin) & (y0a > panel4ymin) & (y0a < panel4ymax)):
self.iz_xbot = xbot
self.iz_xtop = xtop
self.iz_ybot = ybot
self.iz_ytop = ytop
elif ((x0a < panel5xmax) & (x0a > panel5xmin) & (y0a > panel5ymin) & (y0a < panel5ymax)):
self.rz_xbot = xbot
self.rz_xtop = xtop
self.rz_ybot = ybot
self.rz_ytop = ytop
display_bx()
def onclick(event):
if event.button !=3:
coords = np.vstack((event.xdata,667-event.ydata)).T
world = w.wcs_pix2world(coords,1)
result = psm.spherematch(world[:,0],world[:,1], self.ra_all, self.dec_all, nnearest=1)
if (result[0] < 1./3600.):
xpix,ypix = w.wcs_world2pix(self.ra_all[result[1].astype(int)], self.dec_all[result[1].astype(int)],1)
if (((xpix == self.xpix) & (ypix == self.ypix)).any() == False):
self.xpix = np.append(self.xpix,xpix)
self.ypix = np.append(self.ypix,ypix)
self.ra = np.append(self.ra, self.ra_all[result[1].astype(int)])
self.dec = np.append(self.dec, self.dec_all[result[1].astype(int)])
self.gr_color = np.append(self.gr_color, self.gr_color_all[result[1].astype(int)])
self.gi_color = np.append(self.gi_color, self.gi_color_all[result[1].astype(int)])
self.ri_color = np.append(self.ri_color, self.ri_color_all[result[1].astype(int)])
self.iz_color = np.append(self.iz_color, self.iz_color_all[result[1].astype(int)])
self.rz_color = np.append(self.rz_color, self.rz_color_all[result[1].astype(int)])
self.g_mag = np.append(self.g_mag, galaxy['mag_auto_g'][result[1].astype(int)])
self.r_mag = np.append(self.r_mag, galaxy['mag_auto_r'][result[1].astype(int)])
self.i_mag = np.append(self.i_mag, galaxy['mag_auto_i'][result[1].astype(int)])
self.z_mag = np.append(self.z_mag, galaxy['mag_auto_z'][result[1].astype(int)])
else:
keep = where(((xpix == self.xpix) & (ypix == self.ypix))==False)
self.xpix = self.xpix[keep]
self.ypix = self.ypix[keep]
self.ra = self.ra[keep]
self.dec = self.dec[keep]
self.gr_color = self.gr_color[keep]
self.gi_color = self.gi_color[keep]
self.ri_color = self.ri_color[keep]
self.iz_color = self.iz_color[keep]
self.rz_color = self.rz_color[keep]
self.g_mag = self.g_mag[keep]
self.r_mag = self.r_mag[keep]
self.i_mag = self.i_mag[keep]
self.z_mag = self.z_mag[keep]
self.temp_xpix=xpix
self.temp_ypix=ypix
self.temp_gr_color=self.gr_color_all[result[1].astype(int)]
self.temp_gi_color=self.gi_color_all[result[1].astype(int)]
self.temp_ri_color=self.ri_color_all[result[1].astype(int)]
self.temp_iz_color=self.iz_color_all[result[1].astype(int)]
self.temp_rz_color=self.rz_color_all[result[1].astype(int)]
self.temp_r_mag=galaxy['mag_auto_r'][result[1].astype(int)]
self.temp_i_mag=galaxy['mag_auto_i'][result[1].astype(int)]
display_ax0()
display_bx()
def onrightclick(event):
if event.button==3:
coords = np.vstack((event.xdata,667-event.ydata)).T
world = w.wcs_pix2world(coords,1)
result = psm.spherematch(world[:,0],world[:,1], self.ra_all, self.dec_all, nnearest=1)
if (result[0] < 1./3600.):
xpix,ypix = w.wcs_world2pix(self.ra_all[result[1].astype(int)], self.dec_all[result[1].astype(int)],1)
if (((xpix == self.bcg_xpix) & (ypix == self.bcg_ypix)).any() == False):
self.bcg_xpix = np.append(self.bcg_xpix,xpix)
self.bcg_ypix = np.append(self.bcg_ypix,ypix)
self.bcg_ra = np.append(self.bcg_ra, self.ra_all[result[1].astype(int)])
self.bcg_dec = np.append(self.bcg_dec, self.dec_all[result[1].astype(int)])
self.bcg_gr_color = np.append(self.bcg_gr_color, self.gr_color_all[result[1].astype(int)])
self.bcg_gi_color = np.append(self.bcg_gi_color, self.gi_color_all[result[1].astype(int)])
self.bcg_ri_color = np.append(self.bcg_ri_color, self.ri_color_all[result[1].astype(int)])
self.bcg_iz_color = np.append(self.bcg_iz_color, self.iz_color_all[result[1].astype(int)])
self.bcg_rz_color = np.append(self.bcg_rz_color, self.rz_color_all[result[1].astype(int)])
self.bcg_g_mag = np.append(self.bcg_g_mag, galaxy['mag_auto_g'][result[1].astype(int)])
self.bcg_r_mag = np.append(self.bcg_r_mag, galaxy['mag_auto_r'][result[1].astype(int)])
self.bcg_i_mag = np.append(self.bcg_i_mag, galaxy['mag_auto_i'][result[1].astype(int)])
self.bcg_z_mag = np.append(self.bcg_z_mag, galaxy['mag_auto_z'][result[1].astype(int)])
else:
keep = where(((xpix == self.bcg_xpix) & (ypix == self.bcg_ypix))==False)
self.bcg_xpix = self.bcg_xpix[keep]
self.bcg_ypix = self.bcg_ypix[keep]
self.bcg_ra = self.bcg_ra[keep]
self.bcg_dec = self.bcg_dec[keep]
self.bcg_gr_color = self.bcg_gr_color[keep]
self.bcg_gi_color = self.bcg_gi_color[keep]
self.bcg_ri_color = self.bcg_ri_color[keep]
self.bcg_iz_color = self.bcg_iz_color[keep]
self.bcg_rz_color = self.bcg_rz_color[keep]
self.bcg_g_mag = self.bcg_g_mag[keep]
self.bcg_r_mag = self.bcg_r_mag[keep]
self.bcg_i_mag = self.bcg_i_mag[keep]
self.bcg_z_mag = self.bcg_z_mag[keep]
display_bx()
display_ax0()
#link mouse action procedures with figures
cid = fig.canvas.mpl_connect('button_press_event', onclick)
cid = fig.canvas.mpl_connect('button_press_event', onrightclick)
cid = fig2.canvas.mpl_connect('button_press_event', on_press)
cid = fig2.canvas.mpl_connect('button_release_event', on_release)
# Print existing note if there is one.
if os.path.isfile(notesname) and os.path.getsize(notesname) > 0:
notesexist = True
notefile = open(notesname,'a+')
notefile.seek(0)
print "\nExisting notes:\n" + notefile.read()
else:
notesexist = False
#decide if figures will be shown or not
if (choose_gal == True):
# Add a note
valid = 0
while (valid ==0):
newnote = raw_input('Add a note? (y/n) -> ')
if newnote == 'y' or newnote == 'Y':
if notesexist: #if note exists already
notetext = raw_input('Type your note below then press enter. Your text will be appended to the existing note: \n')
notefile.write(time.strftime("%x") + ': ' + notetext + '\n')
valid = 1
else:
notetext = raw_input('Type your note below then press enter. \n')
if len(notetext) > 0:
notefile = open(notesname, 'a+')
notefile.write(time.strftime("%x") + ': ' + notetext + '\n')
valid = 1
elif newnote == 'n' or newnote == 'N':
valid = 1
else:
print 'Invalid option.\n'
# Flag the galaxy
valid = 0
while (valid == 0):
raiseflag = raw_input('Flag this cluster? (y/n) -> ')
if raiseflag == 'n' or raiseflag == 'N':
self.flagged = False
valid = 1
elif raiseflag == 'y' or raiseflag == 'Y':
self.flagged = True
valid = 1
else:
print 'Invalid option.\n'
raw_input('Press ENTER when you are ready to move on to the next cluster.')
show()
else:
plt.close(fig)
plt.close(fig2)
if os.path.isfile(notesname):
notefile.close()
def match_and_filter(self, exclusion=5 / 3600., tol=3 / 3600., plot=True):
'''
:param exclusion: if None, no prefiltering is done. If equal to a distance, ensures that the minimum distance between
stars of the reference catalog is larger than that distance (in degrees)
:param tol: maximum distance in degrees within a matched pair
:return:
'''
if (exclusion is not None):
# Performing pre-filtering on reference catalog star list. Make sure we keep only stars more distant than
# exclusion value from each other
idx1, idx2, ds = spherematch(self.ra_ref,
self.dec_ref,
self.ra_ref,
self.dec_ref,
nnearest=2)
# Now exclude one of the stars from each pair where distance is smaller than exclusion
ou = np.where((ds > exclusion))
self.ra_ref = self.ra_ref[ou]
self.dec_ref = self.dec_ref[ou]
self.xpix_ref = self.xpix_ref[ou]
self.ypix_ref = self.ypix_ref[ou]
self.mag_reg = self.mag_ref[ou]
# Do the same on the image star list
idx1, idx2, ds = spherematch(self.ra_orig,
self.dec_orig,
self.ra_orig,
self.dec_orig,
nnearest=2)
ou = np.where((ds > exclusion))
self.ra_orig = self.ra_orig[ou]
self.dec_orig = self.dec_orig[ou]
self.xpix_orig = self.xpix_orig[ou]
self.ypix_orig = self.ypix_orig[ou]
self.inst_magnitudes = self.inst_magnitudes[ou]
idx1, idx2, ds = spherematch(self.ra_orig,
self.dec_orig,
self.ra_ref,
self.dec_ref,
nnearest=1,
tol=tol)
self.ra_orig = self.ra_orig[idx1]
self.xpix_orig = self.xpix_orig[idx1]
self.dec_orig = self.dec_orig[idx1]
self.ypix_orig = self.ypix_orig[idx1]
self.inst_magnitudes = self.inst_magnitudes[idx1]
self.ra_ref = self.ra_ref[idx2]
self.dec_ref = self.dec_ref[idx2]
self.xpix_ref = self.xpix_ref[idx2]
self.ypix_ref = self.ypix_ref[idx2]
self.mag_ref = self.mag_ref[idx2]
self.distances = ds
if (plot):
plt.close()
apertures = CircularAperture((self.xpix_orig, self.ypix_orig), r=4)
ref_apertures = CircularAperture((self.xpix_ref, self.ypix_ref),
r=4)
norm = ImageNormalize(stretch=SqrtStretch())
plt.imshow(self.data, cmap='Greys', origin='lower', norm=norm)
apertures.plot(color='blue', lw=1.5, alpha=0.5)
ref_apertures.plot(color='red', lw=1.5, alpha=0.5)
plt.show()
def create_base_catalog(nsaid, host):
# READ SQL FILE
sqlfile = 'sql_nsa{0}.fits'.format(nsaid)
#sqlfile = os.path.join(SAGA_DIR, 'hosts', sqlfile)
sqltable = Table.read(sqlfile)
# GET BASIC HOST PARAMETERS FROM GOOGLE HOST LIST
hostra = host['RA'] #RA
hostdec = host['Dec'] #DEC
hostdist = host['distance'] #DISTANCE
hostv = host['vhelio'] #VHELIO
hostMK = host['K'] #M_K
hostflag = host['flag'] #HOST FLAG
# SET VIRIAL RADIUS = 300 kpc, EXCLUDE 20 kpc AROUND HOST
#rkpc = 300.
#rvir = np.rad2deg(np.arcsin(0.3/hostdist))
#rgal = np.rad2deg(np.arcsin(0.02/hostdist))
cdec = np.cos(np.deg2rad(hostdec))
dra = sqltable['RA'] - hostra
ddec = sqltable['DEC'] - hostdec
rhost_arcm = 60.*((dra * cdec) ** 2 + ddec ** 2) ** 0.5
rhost_kpc = 1000.*hostdist*np.sin(np.deg2rad(rhost_arcm/60.))
# ADD EXTRA COLUMNS -
size = len(sqltable)
cols = [_filled_column('HOST_RA', hostra, size), #HOST
_filled_column('HOST_DEC', hostdec, size),
_filled_column('HOST_DIST', hostdist, size),
_filled_column('HOST_VHOST', hostv, size),
_filled_column('HOST_MK', hostMK, size),
_filled_column('HOST_NSAID', nsaid, size),
_filled_column('HOST_FLAG', hostflag, size),
_filled_column('HOST_SAGA_NAME', ' '*48, size),
Column(rhost_arcm, 'RHOST_ARCM'), #OBJECT
Column(rhost_kpc, 'RHOST_KPC'),
_filled_column('OBJ_NSAID', -1, size),
_filled_column('SATS', -1, size),
_filled_column('PCLASS_1', -1, size),
_filled_column('PCLASS_1_WISE', -1, size),
_filled_column('REMOVE', -1, size), # -1 = Good source; 1 = On remove list; 2 = Overlaps with NSA GALAXY
_filled_column('TELNAME', ' '*4, size), #SPECTRA
_filled_column('MASKNAME', ' '*48, size),
_filled_column('ZQUALITY', -1, size),
_filled_column('SPEC_REPEAT', ' '*48, size)]
sqltable.add_columns(cols)
del cols
# ADD IN BEN'S PREDICTIONS
#id1, id2, d = sm.spherematch(sqltable['RA'], sqltable['DEC'], ML['RA'], ML['DEC'], 1./3600)
#sqltable['PCLASS_1'][id1] = ML['PROBABILITY_CLASS_1'][id2]
#sqltable['PCLASS_1_WISE'][id1] = ML['PROBABILITY_CLASS_1_WISE'][id2]
# REPLACE WISE NUMBERS
wise = 0
if wise:
wbasefile = os.path.join(SAGA_DIR, 'hosts', 'wise', 'base_sql_nsa{0}_nw1.fits',format(nsaid))
wbasetable = FitsTable(wbasefile).load()
id1, id2, d = sm.spherematch(sqltable['RA'], sqltable['DEC'], wbasetable['RA'], wbasetable['DEC'], 1./3600)
print 'Read WISE catalog: ', wbasefile
print id1.size, sqltable['ra'].size
#TODO: probably need to add columns to sqltable
sqltable['w1'][id1] = wbasetable['W1'][id2]
sqltable['w1err'][id1] = wbasetable['W1ERR'][id2]
sqltable['w2'][id1] = wbasetable['W2'][id2]
sqltable['w2err'][id1] = wbasetable['W2ERR'][id2]
sqltable['w1'][np.isnan(sqltable['w1'])] = 9999
sqltable['w1err'][np.isnan(sqltable['w1err'])] = 9999
# INITALIZE SDSS SPECTRAL ENTRIE
msk = (sqltable['SPEC_Z'] != -1) & (sqltable['SPEC_Z_WARN'] == 0)
sqltable['TELNAME'][msk] = 'SDSS'
sqltable['MASKNAME'][msk] = 'SDSS'
sqltable['SPEC_REPEAT'][msk] = 'SDSS'
sqltable['ZQUALITY'][msk] = 4
# IF THIS IS A SAGA HOST, SET SAGA NAME
#sqltable['HOST_SAGA_NAME'] = saga.saga_name(nsaid)
# SET REMOVE FLAGS
#sqltable = saga.rm_removelist_obj(remove_list, sqltable)
# CLEAN USING NSAID
#sqltable = saga.nsa_cleanup(nsa_catalog, sqltable)
return sqltable
