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")