def __init__(self,fbase,wdir,nbar2d=None,nbar3d=None,tasklist = [0,1,3],icovlist=[None,None,None]):
"""
tasklist matches whichtask convention in catalog.callxi
for each task, you can specify an icov matrix.
"""
self.fbase = fbase
self.wdir = wdir
if 0 in tasklist:
cut=0.533655
## remove the hard-coding here soon!
try:
indx = np.where(np.array(tasklist) == 0)[0]
icovfname = icovlist[indx]
except:
icovfname = None
self.xiell = xiell.xiellfromDR(wdir+"outputdr12-xiell/"+fbase,nell=2,binfile=wdir+"xibinfiles/bin1fineMU.txt",rperpcut=cut,icovfname=icovfname)
if 1 in tasklist:
try:
indx = np.where(np.array(tasklist) == 1)[0]
icovfname = icovlist[indx]
except:
icovfname = None
self.wp = wp.wpfromDR(fbase=wdir+"outputdr12-xigrid/"+fbase,rpimax=80.0)
if 3 in tasklist:
try:
indx = np.where(np.array(tasklist) == 3)[0]
icovfname = icovlist[indx]
except:
icovfname = None
if nbar2d is None or nbar3d is None:
print 'cannot compute wpcross without number densities!'
else:
self.nbar2d = nbar2d
self.nbar3d = nbar3d
self.wpcross = wp.wpcrossHogg(wdir+"outputdr12-wpcross/"+fbase,nbar2d=nbar2d,nbar3d=nbar3d)
def __init__(self,
fbase,
wdir,
nbar2d=None,
nbar3d=None,
tasklist=[0, 1, 3],
icovlist=[None, None, None]):
"""
tasklist matches whichtask convention in catalog.callxi
for each task, you can specify an icov matrix.
"""
self.fbase = fbase
self.wdir = wdir
if 0 in tasklist:
cut = 0.533655
## remove the hard-coding here soon!
try:
indx = np.where(np.array(tasklist) == 0)[0]
icovfname = icovlist[indx]
except:
icovfname = None
self.xiell = xiell.xiellfromDR(wdir + "outputdr12-xiell/" + fbase,
nell=2,
binfile=wdir +
"xibinfiles/bin1fineMU.txt",
rperpcut=cut,
icovfname=icovfname)
if 1 in tasklist:
try:
indx = np.where(np.array(tasklist) == 1)[0]
icovfname = icovlist[indx]
except:
icovfname = None
self.wp = wp.wpfromDR(fbase=wdir + "outputdr12-xigrid/" + fbase,
rpimax=80.0)
if 3 in tasklist:
try:
indx = np.where(np.array(tasklist) == 3)[0]
icovfname = icovlist[indx]
except:
icovfname = None
if nbar2d is None or nbar3d is None:
print 'cannot compute wpcross without number densities!'
else:
self.nbar2d = nbar2d
self.nbar3d = nbar3d
self.wpcross = wp.wpcrossHogg(wdir + "outputdr12-wpcross/" +
fbase,
nbar2d=nbar2d,
nbar3d=nbar3d)
def getbootcov(bootfile, basedir, outdirbase = 'outputdr12', covoutfname=None, NSortot=2, nboot = 5000000, \
rpimax=80.,wpstart=1,wpend=19,\
nell=3,rperpcut=-1.,smallRRcut=-1.,\
dfacs=1,dfacmu=1,icovfname=None,smincut=-1.,smaxcut=1.e12,\
binfname_xiell='xibinfiles/bin1fineMU.txt',\
nbar2d=[-1.,-1.],nbar3d=[-1.,-1],\
whichtask=4):
## resurrect these later.
# splitxi0=5,splitxi2=6,splitwp=7):
"""
Get covariance matrix.
We're going to do all tasks at once by default (4).
whichtask = 0: xiell
whichtask = 1: wp (compute xi(rp,rpi))
whichtask = 2: wtheta
whichtask = 3: Hogg spec-im cross-correlation.
whichtask = 4: combine xiell and wp in usual way.
Third tier of stuff goes directly to xiellfromDR
rpimax is for wp, default is 80.
nbar2d,nbar3d needs to be computed separately for N and S.
"""
nsub, nsubdir, pixelfname, fbase, fbasetotN, fbasetotS = parsebootinfo(bootfile=basedir+bootfile)
NSlist = [0,1]
NStaglist = ['N','S']
for xx in [nsub, nsubdir, pixelfname, fbase, fbasetotN, fbasetotS]:
if xx is None:
print 'bad bootfile!'
return None
b = boot.bootpix()
b.readregions(basedir + pixelfname)
assert b.nsub == nsub
## this list will be filled
DRinfolist = [-1,-1,-1,-1]
taglist= ['-xiell','-xigrid','-wtheta','-wpcross']
## get global DR factors for taglist.
for ii in range(len(taglist)-1):
tag = taglist[ii]
tmp = np.zeros([2,2]) # first index is N or S. DRfac, fixRR stored for each.
for NS, NStag, ff in zip(NSlist, NStaglist,[fbasetotN,fbasetotS]):
try:
#if 0==0:
tmp[NS,0], tmp[NS,1] = ximisc.getDRfactors(basedir + '/'+outdirbase + tag +'/'+ff)
except:
tmp[NS,:] = -1.
DRinfolist[ii] = tmp.copy()
## now get DR info for wpcross.
### nevermind! we reduce this to two ratios.
## DRinfolist[3] = np.zeros([2,4,2])
DRinfolist[3] = np.zeros([2,2])
tag = taglist[3]
for NS, NStag, ff in zip(NSlist, NStaglist,[fbasetotN,fbasetotS]):
try:
normfac = ximisc.getDRnormswpcross(basedir + '/'+outdirbase + tag +'/'+ff)
DRinfolist[3][NS][0] = normfac[0,0]/normfac[2,0]
DRinfolist[3][NS][1] = normfac[0,1]/normfac[1,1]
except:
DRinfolist[3][NS][:] = -1.
tasklist = np.zeros(4,dtype='int')
if whichtask == 4:
tasklist = np.array([1,1,0,1],dtype='int')
else:
tasklist[whichtask] = 1
if tasklist[3] > 0:
assert (nbar2d[:] > 0).all()
assert (nbar3d[:] > 0).all()
assert (DRinfolist[3][:,:].flatten() > 0).all()
for ns in range(nsub):
xx = np.where(b.pixlist['PID'] == ns)[0]
assert len(xx) == 1
assert xx[0] == ns
NorSval = b.pixlist['NorS'][xx[0]]
for tt in range(len(tasklist)):
if tasklist[tt] == 0: continue
tag = taglist[tt]
ff = basedir+'/'+outdirbase + tag +'/' + nsubdir + '/' + fbase + '.%04d.Np' % (ns)
if tt == 0: #xiell
xitmp = xiell.xiellfromDR(ff,binfile=binfname_xiell,rperpcut=rperpcut,nell=nell,smallRRcut=smallRRcut,dfacs=dfacs,dfacmu=dfacmu,smincut=smincut,smaxcut=smaxcut,DRfacinfo=DRinfolist[tt][NorSval])
dvec = xitmp.xilong
if tt == 1: #wp
wptmp = wp.wpfromDR(ff,DRfacinfo=DRinfolist[tt][NorSval],rpimax=rpimax)
dvec = wptmp.wp
if tt == 2: #wtheta
wttmp = wtheta.wthetafromDR(ff,DRfacinfo=DRinfolist[tt][NorSval])
dvec = wttmp.wtheta
if tt == 3: #wpcross
wpcrosstmp = wp.wpcrossHogg(ff,DRfacinfo=DRinfolist[tt][NorSval],nbar2d=nbar2d[NorSval],nbar3d=nbar3d[NorSval])
dvec = wpcrosstmp.wp
if whichtask == 4:
dvec = xiwpvec(xitmp,wptmp,wpcrosstmp,wpstart,wpend)
if ns == 0: ## allocate!
ndata = len(dvec)
dveclist = np.zeros([nsub,ndata],dtype='float128')
dveclist[ns,:] = dvec[:]
## check means with total counts.
nindx = np.where(b.pixlist['NorS'] == 0)[0]
sindx = np.where(b.pixlist['NorS'] == 1)[0]
nsindx = np.where((b.pixlist['NorS'] == 0) | (b.pixlist['NorS'] == 1))[0]
print 'N/S: ',len(nindx), len(sindx), len(nsindx)
assert len(nsindx) == nsub
assert (nsindx == np.arange(0,nsub,1,dtype='int')).all()
myindx= nsindx
## assume we want nsindx for this, but can restore N/S option later if I want.
dmean = (dveclist[myindx,:]).sum(axis=0)/float(len(myindx))
ntot = len(myindx)
ntotflt = float(ntot)
print 'hi beth'
print dmean
Cmat = np.zeros([ndata,ndata],dtype='float128')
for b in range(nboot):
rr = np.random.random_integers(0,ntot-1,ntot)
dtrial = (dveclist[rr,:]).sum(axis=0)/ntotflt
xvec = np.matrix([dtrial-dmean])
Cmat += (xvec.T*xvec)
Cmat = Cmat/float(nboot-1)
Cmat = np.matrix(Cmat,dtype='float64')
iCmat = Cmat.I ##
print 'not assuming any bootstrap unbias factor for now!'
if covoutfname is not None:
printcov(Cmat,covoutfname)
printcov(iCmat,covoutfname+'.inv')
printmean(dmean,covoutfname+'.mean')
return Cmat, iCmat, dmean
def getbootcov(bootfile, basedir, outdirbase = 'outputdr12', covoutfname=None, NSortot=2, nboot = 5000000, \
rpimax=80.,wpstart=1,wpend=19,\
nell=3,rperpcut=-1.,smallRRcut=-1.,\
dfacs=1,dfacmu=1,icovfname=None,smincut=-1.,smaxcut=1.e12,\
binfname_xiell='xibinfiles/bin1fineMU.txt',\
nbar2d=[-1.,-1.],nbar3d=[-1.,-1],\
whichtask=4):
## resurrect these later.
# splitxi0=5,splitxi2=6,splitwp=7):
"""
Get covariance matrix.
We're going to do all tasks at once by default (4).
whichtask = 0: xiell
whichtask = 1: wp (compute xi(rp,rpi))
whichtask = 2: wtheta
whichtask = 3: Hogg spec-im cross-correlation.
whichtask = 4: combine xiell and wp in usual way.
Third tier of stuff goes directly to xiellfromDR
rpimax is for wp, default is 80.
nbar2d,nbar3d needs to be computed separately for N and S.
"""
nsub, nsubdir, pixelfname, fbase, fbasetotN, fbasetotS = parsebootinfo(
bootfile=basedir + bootfile)
NSlist = [0, 1]
NStaglist = ['N', 'S']
for xx in [nsub, nsubdir, pixelfname, fbase, fbasetotN, fbasetotS]:
if xx is None:
print 'bad bootfile!'
return None
b = boot.bootpix()
b.readregions(basedir + pixelfname)
assert b.nsub == nsub
## this list will be filled
DRinfolist = [-1, -1, -1, -1]
taglist = ['-xiell', '-xigrid', '-wtheta', '-wpcross']
## get global DR factors for taglist.
for ii in range(len(taglist) - 1):
tag = taglist[ii]
tmp = np.zeros(
[2, 2]) # first index is N or S. DRfac, fixRR stored for each.
for NS, NStag, ff in zip(NSlist, NStaglist, [fbasetotN, fbasetotS]):
try:
#if 0==0:
tmp[NS, 0], tmp[NS, 1] = ximisc.getDRfactors(basedir + '/' +
outdirbase + tag +
'/' + ff)
except:
tmp[NS, :] = -1.
DRinfolist[ii] = tmp.copy()
## now get DR info for wpcross.
### nevermind! we reduce this to two ratios.
## DRinfolist[3] = np.zeros([2,4,2])
DRinfolist[3] = np.zeros([2, 2])
tag = taglist[3]
for NS, NStag, ff in zip(NSlist, NStaglist, [fbasetotN, fbasetotS]):
try:
normfac = ximisc.getDRnormswpcross(basedir + '/' + outdirbase +
tag + '/' + ff)
DRinfolist[3][NS][0] = normfac[0, 0] / normfac[2, 0]
DRinfolist[3][NS][1] = normfac[0, 1] / normfac[1, 1]
except:
DRinfolist[3][NS][:] = -1.
tasklist = np.zeros(4, dtype='int')
if whichtask == 4:
tasklist = np.array([1, 1, 0, 1], dtype='int')
else:
tasklist[whichtask] = 1
if tasklist[3] > 0:
assert (nbar2d[:] > 0).all()
assert (nbar3d[:] > 0).all()
assert (DRinfolist[3][:, :].flatten() > 0).all()
for ns in range(nsub):
xx = np.where(b.pixlist['PID'] == ns)[0]
assert len(xx) == 1
assert xx[0] == ns
NorSval = b.pixlist['NorS'][xx[0]]
for tt in range(len(tasklist)):
if tasklist[tt] == 0: continue
tag = taglist[tt]
ff = basedir + '/' + outdirbase + tag + '/' + nsubdir + '/' + fbase + '.%04d.Np' % (
ns)
if tt == 0: #xiell
xitmp = xiell.xiellfromDR(ff,
binfile=binfname_xiell,
rperpcut=rperpcut,
nell=nell,
smallRRcut=smallRRcut,
dfacs=dfacs,
dfacmu=dfacmu,
smincut=smincut,
smaxcut=smaxcut,
DRfacinfo=DRinfolist[tt][NorSval])
dvec = xitmp.xilong
if tt == 1: #wp
wptmp = wp.wpfromDR(ff,
DRfacinfo=DRinfolist[tt][NorSval],
rpimax=rpimax)
dvec = wptmp.wp
if tt == 2: #wtheta
wttmp = wtheta.wthetafromDR(ff,
DRfacinfo=DRinfolist[tt][NorSval])
dvec = wttmp.wtheta
if tt == 3: #wpcross
wpcrosstmp = wp.wpcrossHogg(ff,
DRfacinfo=DRinfolist[tt][NorSval],
nbar2d=nbar2d[NorSval],
nbar3d=nbar3d[NorSval])
dvec = wpcrosstmp.wp
if whichtask == 4:
dvec = xiwpvec(xitmp, wptmp, wpcrosstmp, wpstart, wpend)
if ns == 0: ## allocate!
ndata = len(dvec)
dveclist = np.zeros([nsub, ndata], dtype='float128')
dveclist[ns, :] = dvec[:]
## check means with total counts.
nindx = np.where(b.pixlist['NorS'] == 0)[0]
sindx = np.where(b.pixlist['NorS'] == 1)[0]
nsindx = np.where((b.pixlist['NorS'] == 0) | (b.pixlist['NorS'] == 1))[0]
print 'N/S: ', len(nindx), len(sindx), len(nsindx)
assert len(nsindx) == nsub
assert (nsindx == np.arange(0, nsub, 1, dtype='int')).all()
myindx = nsindx
## assume we want nsindx for this, but can restore N/S option later if I want.
dmean = (dveclist[myindx, :]).sum(axis=0) / float(len(myindx))
ntot = len(myindx)
ntotflt = float(ntot)
print 'hi beth'
print dmean
Cmat = np.zeros([ndata, ndata], dtype='float128')
for b in range(nboot):
rr = np.random.random_integers(0, ntot - 1, ntot)
dtrial = (dveclist[rr, :]).sum(axis=0) / ntotflt
xvec = np.matrix([dtrial - dmean])
Cmat += (xvec.T * xvec)
Cmat = Cmat / float(nboot - 1)
Cmat = np.matrix(Cmat, dtype='float64')
iCmat = Cmat.I ##
print 'not assuming any bootstrap unbias factor for now!'
if covoutfname is not None:
printcov(Cmat, covoutfname)
printcov(iCmat, covoutfname + '.inv')
printmean(dmean, covoutfname + '.mean')
return Cmat, iCmat, dmean