def Forecast_Cellrsx(self, ellBinEdges, fsky, option='None'):
ellMids = old_div((ellBinEdges[1:] + ellBinEdges[:-1]), 2)
cls_rsx = self.fgs.rs_cross(self.evalells,self.freq[0]) / self.cc.c['TCMBmuK']**2. \
/ ((self.evalells+1.)*self.evalells) * 2.* np.pi
cls_rsx = old_div(cls_rsx, (self.fgs.rs_nu(
self.freq[0]))) # Normalized to get Cell^rsrs fiducial
LF = LensForecast()
if (option == 'None'):
LF.loadGenericCls("rr", self.evalells, cls_rsx, self.evalells,
self.N_ll_rsx)
elif (option == 'NoILC'):
LF.loadGenericCls("rr", self.evalells, cls_rsx, self.evalells,
self.N_ll_noILC)
else:
return "Wrong option"
sn, errs = LF.sn(ellBinEdges, fsky, "rr") # not squared
cls_out = np.interp(ellMids, self.evalells, cls_rsx)
return ellMids, cls_out, errs, sn
def Forecast_CellrsxEE(self, ellBinEdges, fsky, option='None'):
ellMids = old_div((ellBinEdges[1:] + ellBinEdges[:-1]), 2)
cls_rsxEE = self.fgs.rs_crossEE(
self.evalells, self.fgs.nu_rs) / self.cc.c['TCMBmuK']**2. / (
(self.evalells + 1.) * self.evalells) * 2. * np.pi
LF = LensForecast()
if (option == 'None'):
LF.loadGenericCls("ee", self.evalells, cls_rsxEE, self.evalells,
self.N_ll_rsxEE)
elif (option == 'NoILC'):
LF.loadGenericCls("ee", self.evalells, cls_rsxEE, self.evalells,
self.N_ll_rsx_NoFG)
elif (option == 'Onlyfg'):
LF.loadGenericCls("ee", self.evalells, cls_rsxEE, self.evalells,
self.N_ll_rsxEE - self.N_ll_rsx_NoFG)
else:
return "Wrong option"
sn, errs = LF.sn(ellBinEdges, fsky, "ee") # not squared
cls_out = np.interp(ellMids, self.evalells, cls_rsxEE)
return ellMids, cls_out, errs, sn
def Forecast_Cellyy(self, ellBinEdges, fsky, constraint='None'):
ellMids = old_div((ellBinEdges[1:] + ellBinEdges[:-1]), 2)
cls_tsz = self.fgs.tSZ(self.evalells,self.freq[0],self.freq[0]) / self.cc.c['TCMBmuK']**2. \
/ ((self.evalells+1.)*self.evalells) * 2.* np.pi
cls_yy = old_div(cls_tsz,
(f_nu(self.cc.c,
self.freq[0]))**2) # Normalized to get Cell^yy
LF = LensForecast()
if (constraint == 'None'):
LF.loadGenericCls("yy", self.evalells, cls_yy, self.evalells,
self.N_ll_tsz)
elif (constraint == 'cmb'):
LF.loadGenericCls("yy", self.evalells, cls_yy, self.evalells,
self.N_ll_tsz_c_cmb)
elif (constraint == 'cib'):
LF.loadGenericCls("yy", self.evalells, cls_yy, self.evalells,
self.N_ll_tsz_c_cib)
else:
return "Wrong option"
sn, errs = LF.sn(ellBinEdges, fsky, "yy") # not squared
cls_out = np.interp(ellMids, self.evalells, cls_yy)
return ellMids, cls_out, errs, sn
def Forecast_Cellcmb(self,ellBinEdges,fsky,constraint='None'):
ellMids = old_div((ellBinEdges[1:] + ellBinEdges[:-1]), 2)
cls_cmb = self.cc.clttfunc(self.evalells)
LF = LensForecast()
if (constraint=='None'):
LF.loadGenericCls("tt",self.evalells,cls_cmb,self.evalells,self.N_ll_cmb)
elif (constraint=='tsz'):
LF.loadGenericCls("tt",self.evalells,cls_cmb,self.evalells,self.N_ll_cmb_c_tsz)
else:
return "Wrong option"
sn,errs = LF.sn(ellBinEdges,fsky,"tt") # not squared
cls_out = np.interp(ellMids,self.evalells,cls_cmb)
return ellMids,cls_out,errs,sn
# get index of mnu and print marginalized constraint
indMnu = paramList.index('mnu')
mnu = np.sqrt(np.linalg.inv(Fisher)[indMnu,indMnu])*1000.
cprint("Sum of neutrino masses 1-sigma: "+ str(mnu) + " meV",color="green",bold=True)
mnus.append(mnu)
# CLKK S/N ============================================
# Calculate Clkk S/N
Clkk = fidCls[:,4]
frange = np.array(range(len(Clkk)))
snrange = np.arange(kellmin,kellmax)
LF = LensForecast()
LF.loadKK(frange,Clkk,ls,Nls)
sn,errs = LF.sn(snrange,fsky,"kk")
cprint("Lensing autopower S/N: "+ str(sn),color="green",bold=True)
# pl = Plotter(scaleY='log',xscale='log')
# pl.add(frange,Clkk)
# pl.add(ls,Nls)
# pl._ax.set_ylim(-max(Clkk),max(Clkk))
# pl.done("clkk.png")
sns.append(sn)
# r Forecast ============================================
spellmin,spellmax = list_from_config(Config,'rForecast','pellrange')