def testAgainstKSmith(pmax, beamFWHMArcmin, dCls, lclbb, rExp, rInFid, fCls, fsky): from orphics.io import Plotter pl = Plotter(scaleX='log', scaleY='log') pnoiserange = np.logspace(np.log10(0.5), np.log10(50.), num=100) for pmin in [2, 5, 10, 40]: sigs = [] for deltaP in pnoiserange: ellBBRange = range(pmin, pmax) sigs.append( rSigma(fsky, ellBBRange, beamFWHMArcmin, deltaP, dCls[:, 2], lclbb, rExp * fCls[:, 2] / rInFid)) kn, kr = np.loadtxt("data/k" + str(pmin) + ".csv", delimiter=',', unpack=True) pl.add(kn, kr, ls='--') pl.add(pnoiserange, sigs, label="$\\ell_{\mathrm{min}}=" + str(pmin) + "$") pl.legendOn() pl._ax.set_xlim(0.5, 50.) pl._ax.set_ylim(1.e-5, 1.e-1) pl.done("kenplot.png")
statsRecon[polComb] = get_stats(listAllReconPower[polComb]) fp = interp1d(centers,statsRecon[polComb]['mean'],fill_value='extrapolate') pl.add(ellkk,(fp(ellkk))-Clkk,color=col,lw=2) Nlkk2d = qest.N.Nlkk[polComb] ncents, npow = stats.bin_in_annuli(Nlkk2d, p2d.modLMap, bin_edges) pl.add(ncents,npow,color=col,lw=2,ls="--") avgInputPower = totAllInputPower/N pl.add(centers,avgInputPower,color='cyan',lw=3) # ,label = "input x input" pl.legendOn(labsize=10,loc='lower left') pl._ax.set_xlim(kellmin,kellmax) pl.done("tests/output/power.png") # cross compare to power of input (percent) pl = Plotter() for polComb,col in zip(polCombList,colorList): cross = statsCross[polComb]['mean'] pl.add(centers,(cross-avgInputPower)*100./avgInputPower,label=polComb,color=col,lw=2) pl.legendOn(labsize=10,loc='upper right')
zmin = outzgrid[0] zmax = outzgrid[-1] jointgridsqinv += (old_div(1.,outerrgrid**2.)) jointgrid = np.sqrt(old_div(1.,jointgridsqinv)) snjoint = old_div(1.,jointgrid) for ind in mindicesList: pl.add(outzgrid,snjoint[ind,:].ravel(),ls="-.") print(mexpgrid[ind]) pl.legendOn(loc='upper right',labsize=10) pl.done(outDir+"slice"+cmbtype+".pdf") #pl.legendOn(loc='upper right',labsize=8) #pl.done(outDir+"slice.pdf") #from orphics.io import Plotter pgrid = np.rot90(old_div(1.,jointgrid)) pl = Plotter(labelX="$\\mathrm{log}_{10}(M)$",labelY="$z$",ftsize=14) pl.plot2d(pgrid,extent=[mmin,mmax,zmin,zmax],levels=[1.0,3.0,5.0],labsize=14) pl.done(outDir+"joint"+cmbtype+".png") #savefile = "/astro/astronfs01/workarea/msyriac/data/SZruns/v0.6/lensgrid_S4-1.0-0.4_grid-default_CMB_all_joint_v0.5.pkl"
khup,Pup = np.loadtxt(dRoot+"Up_matterpower_"+str(z)+".dat",unpack=True) khdn,Pdn = np.loadtxt(dRoot+"Dn_matterpower_"+str(z)+".dat",unpack=True) assert np.all(np.isclose(khup,khdn)) stepF = float(step) dP = old_div((Pup-Pdn),stepF) #if z<2.5: continue if z>0.2: continue #alph = 1.-z/3.0 alph = 1. pl.add(khup,-dP,color=col,alpha=alph) pl.add(khup,-dP*0.,color=col,alpha=1.,ls="-",label=step) pl.legendOn() pl.done(os.environ['WWW']+"dps.png") fparams = {} # the for (key, val) in Config.items('params'): if ',' in val: param, step = val.split(',') fparams[key] = float(param) else: fparams[key] = float(val) passParams = fparams from szar.counts import ClusterCosmology,Halo_MF cc = ClusterCosmology(passParams,constDict,clTTFixFile=clttfile)
xerrs.append(xerr) s8now = np.mean(s81zs[np.logical_and(zrange >= zleft, zrange < zright)]) print(lab, zleft, zright, yerr, s8now, yerr * 100. / s8now, "%") #s8now = np.mean(s81zs[np.logical_and(zrange>=zleft,zrange<zright)])/s81 #yerrsq = (1./sum([1/x**2. for x in errselect])) #yerr = (s8now/s80mean)*np.sqrt(yerrsq/s8now**2. + yerrsq0/s80mean**2.) errcents.append(yerr) ms8.append(s8now) currentAxis.add_patch( Rectangle((zcent - xerr + pad, 1. - old_div(yerr, s8now)), 2 * xerr - old_div(pad, 2.), 2. * yerr / s8now, facecolor=col)) print("=====================") pl._ax.fill_between(zrange, 1., 1., label=lab, alpha=0.75, color=col) #pl.add(zrange,s82zs/s81zs,label="$w=-0.97$",color='red',alpha=0.5) pl.add(zrange, old_div(s81zs, s81zs), color='black', alpha=0.5, ls="--") #,label="$w=-1$") # pl.add(zrange,s82zs/s81zs/s82*s81,label="$w=-0.97$",color='red',alpha=0.5) # pl.add(zrange,s81zs*0.+1.,label="$w=-1$",color='black',alpha=0.5,ls="--") pl.legendOn(labsize=9) #pl._ax.set_ylim(0.9,1.1) # res #pl._ax.set_ylim(0.95,1.05) # fsky #pl._ax.text(0.8,.82,"Madhavacheril et. al. in prep") pl.done(outDir + "S4_" + cal + "_fsky.png") #pl.done(outDir+"s8SO.png")