def paircount_data_random(datara,datadec,dataz,randomra,randomdec,randomz,cosmo_model,rmin,rmax,nbins,nproc=None,log=None,file=None,wdata=None,wrandom=None):
"""
r,dd,rr,dr=paircount_data_random(datara,datadec,dataz,randomra,randomdec,randomz,cosmo,rmin,rmax,nbins,log=None,file=None,wdata=None,wrandom=None)
Returns the R,DD,RR,DR for a given set of data and random and a given cosmology
"""
# calculate proper distance for each object (data and random)
pi=np.pi
params=cosmo_model[0:4]
h=cosmo_model[4]
rdata=cosmology.get_dist(dataz,type='prop',params=params,h=h)*1000*h
thdata=(90-datadec)*pi/180
phdata=datara*pi/180
rrandom=cosmology.get_dist(randomz,type='prop',params=params,h=h)*1000*h
thrandom=(90-randomdec)*pi/180
phrandom=randomra*pi/180
# Count pairs
r,dd,rr,dr=get_pairs(rdata,thdata,phdata,rrandom,thrandom,phrandom,rmin,rmax,nbins,nproc=nproc,log=log,wdata=wdata,wrandom=wrandom)
# Write to file if required
if file is not None:
outfile=open(file,'w')
outfile.write("Ng=%s Nr=%s \n" % (np.size(datara), np.size(randomra)))
for xr,xdd,xrr,xdr in zip(r,dd,rr,dr):
outfile.write("%s %s %s %s\n" % (xr,xdd,xrr,xdr))
outfile.close()
# return result
return(r,dd,rr,dr)
def paircount_data_random(datara,
datadec,
dataz,
randomra,
randomdec,
randomz,
cosmo_model,
rmin,
rmax,
nbins,
nproc=None,
log=None,
file=None,
wdata=None,
wrandom=None):
"""
r,dd,rr,dr=paircount_data_random(datara,datadec,dataz,randomra,randomdec,randomz,cosmo,rmin,rmax,nbins,log=None,file=None,wdata=None,wrandom=None)
Returns the R,DD,RR,DR for a given set of data and random and a given cosmology
"""
# calculate proper distance for each object (data and random)
pi = np.pi
params = cosmo_model[0:4]
h = cosmo_model[4]
rdata = cosmology.get_dist(dataz, type='prop', params=params,
h=h) * 1000 * h
thdata = (90 - datadec) * pi / 180
phdata = datara * pi / 180
rrandom = cosmology.get_dist(randomz, type='prop', params=params,
h=h) * 1000 * h
thrandom = (90 - randomdec) * pi / 180
phrandom = randomra * pi / 180
# Count pairs
r, dd, rr, dr = get_pairs(rdata,
thdata,
phdata,
rrandom,
thrandom,
phrandom,
rmin,
rmax,
nbins,
nproc=nproc,
log=log,
wdata=wdata,
wrandom=wrandom)
# Write to file if required
if file is not None:
outfile = open(file, 'w')
outfile.write("Ng=%s Nr=%s \n" % (np.size(datara), np.size(randomra)))
for xr, xdd, xrr, xdr in zip(r, dd, rr, dr):
outfile.write("%s %s %s %s\n" % (xr, xdd, xrr, xdr))
outfile.close()
# return result
return (r, dd, rr, dr)
h=0.7
om_global = 0.3
om_region_vide = 0.
om_region_dense = ((x1-x0)*om_global - (xe-xs)*om_region_vide) / ((xs-x0) + (x1-xe))
params_region_vide = [om_region_vide,0,-1,0]
params_region_dense = [om_region_dense,0,-1,0]
params_global = [om_global, 0, -1, 0]
nn = 1000
c=3e8
H0=1000*1000*h*100
zz = linspace(0,zmax, nn)
hz_region_vide = cosmo.get_dist(zz,type='hz',params=params_region_vide, h=h)/H0
hz_region_dense = cosmo.get_dist(zz,type='hz',params=params_region_dense, h=h)/H0
hz_global = cosmo.get_dist(zz,type='hz',params=params_global, h=h)/H0
dp_region_vide = cosmo.get_dist(zz,type=dist_type,params=params_region_vide, h=h)
dp_region_dense = cosmo.get_dist(zz,type=dist_type,params=params_region_dense, h=h)
dp_global = cosmo.get_dist(zz,type=dist_type,params=params_global, h=h)
clf()
subplot(1,2,1)
plot(zz,hz_global,'b',label='$\Omega_m = {0:4.2f}$'.format(om_global))
plot(zz,hz_region_vide,'r',label='$\Omega_m = {0:4.2f}$'.format(om_region_vide))
plot(zz,hz_region_dense,'g',label='$\Omega_m = {0:4.2f}$'.format(om_region_dense))
xlabel('z')
ylabel('H(z)')
legend(loc='upper left')
subplot(1,2,2)
plot(zz,dp_global,'b')