def __init__(self,
paramDict=cosmo.defaultCosmology,
constDict=cosmo.defaultConstants,
lmax=None,
clTTFixFile=None,
skipCls=False,
pickling=False,
fill_zero=True,
dimensionless=True,
verbose=True,
skipPower=True,
skip_growth=True,
low_acc=False):
Cosmology.__init__(self,
paramDict,
constDict,
lmax,
clTTFixFile,
skipCls,
pickling,
fill_zero,
dimensionless=dimensionless,
verbose=verbose,
skipPower=skipPower,
skip_growth=skip_growth,
low_acc=low_acc,
nonlinear=False)
self.om = (self.omch2 + self.ombh2) / self.h**2.
self.rhoc0om = self.rho_crit0H100 * self.om
def lensNoise(Config,
expName,
lensName,
beamOverride=None,
noiseTOverride=None,
lkneeTOverride=None,
lkneePOverride=None,
alphaTOverride=None,
alphaPOverride=None,
tellminOverride=None,
pellminOverride=None,
tellmaxOverride=None,
pellmaxOverride=None,
deg=5.,
px=1.0,
gradCut=10000,
bigell=9000,
plot=False,
theoryOverride=None,
lensedEqualsUnlensed=True,
noiseFuncT=None,
noiseFuncP=None):
from orphics.io import list_from_config
beam = list_from_config(Config, expName, 'beams')
noise = list_from_config(Config, expName, 'noises')
freq = list_from_config(Config, expName, 'freqs')
lkneeT, lkneeP = list_from_config(Config, expName, 'lknee')
alphaT, alphaP = list_from_config(Config, expName, 'alpha')
if (noiseFuncT is None) and (noiseFuncP is None):
print 'Not using noise files for generating lensing noise'
else:
print 'Using noise files for generating lensing noise'
tellmin, tellmax = list_from_config(Config, expName, 'tellrange')
if tellminOverride is not None: tellmin = tellminOverride
if tellmaxOverride is not None: tellmax = tellmaxOverride
pellmin, pellmax = list_from_config(Config, expName, 'pellrange')
if pellminOverride is not None: pellmin = pellminOverride
if pellmaxOverride is not None: pellmax = pellmaxOverride
lmax = int(Config.getfloat(expName, 'lmax'))
pols = Config.get(lensName, 'polList').split(',')
freq_to_use = Config.getfloat(lensName, 'freq')
ind = np.where(np.isclose(freq, freq_to_use))
beamFind = np.array(beam)[ind]
noiseFind = np.array(noise)[ind]
assert beamFind.size == 1
assert noiseFind.size == 1
if beamOverride is not None:
beamX = beamY = beamOverride
else:
beamX = beamY = beamFind[0]
if noiseTOverride is not None:
noiseTX = noiseTY = noiseTOverride
else:
noiseTX = noiseTY = noiseFind[0]
if lkneeTOverride is not None: lkneeT = lkneeTOverride
if lkneePOverride is not None: lkneeP = lkneePOverride
if alphaTOverride is not None: alphaT = alphaTOverride
if alphaPOverride is not None: alphaP = alphaPOverride
from orphics.lensing import NlGenerator, getMax
from orphics import maps
#deg = 5.
#px = 1.0
dell = 10
kellmin = 10
shape, wcs = maps.rect_geometry(width_deg=deg, px_res_arcmin=px)
kellmax = max(tellmax, pellmax)
if theoryOverride is None:
from orphics.cosmology import Cosmology
cc = Cosmology(lmax=int(kellmax), pickling=True)
theory = cc.theory
else:
theory = theoryOverride
cc = None
bin_edges = np.arange(kellmin, kellmax, dell)
myNls = NlGenerator(shape,
wcs,
theory,
bin_edges,
gradCut=gradCut,
bigell=bigell,
unlensedEqualsLensed=lensedEqualsUnlensed)
myNls.updateNoise(beamX,
noiseTX,
np.sqrt(2.) * noiseTX,
tellmin,
tellmax,
pellmin,
pellmax,
beamY=beamY,
noiseTY=noiseTY,
noisePY=np.sqrt(2.) * noiseTY,
lkneesX=(lkneeT, lkneeP),
lkneesY=(lkneeT, lkneeP),
alphasX=(alphaT, alphaP),
alphasY=(alphaT, alphaP),
noiseFuncTX=noiseFuncT,
noiseFuncTY=noiseFuncT,
noiseFuncPX=noiseFuncP,
noiseFuncPY=noiseFuncP)
lsmv, Nlmv, ells, dclbb, efficiency = myNls.getNlIterative(pols,
kellmin,
kellmax,
tellmax,
pellmin,
pellmax,
dell=dell,
halo=True,
plot=plot)
return lsmv, Nlmv, ells, dclbb, efficiency, cc
from enlib import enmap #import orphics.m as fmaps import orphics.maps as maps import orphics.io as io import orphics.stats as stats from orphics.cosmology import Cosmology import numpy as np import os, sys out_dir = os.environ['WWW'] + "plots/pureTest_" cc = Cosmology(lmax=6000, pickling=True, dimensionless=False) theory = cc.theory deg = 20. px = 1.0 shape, wcs = maps.rect_geometry(width_deg=deg, px_res_arcmin=px, pol=True) pa = maps.PatchArray(shape, wcs, cc=cc, orphics_is_dimensionless=False) ulensed = pa.get_unlensed_cmb() kappa = pa.get_grf_kappa() cmb = pa.get_lensed(ulensed, order=5) # io.highResPlot2d(cmb[0],out_dir+"t.png") # io.highResPlot2d(cmb[1],out_dir+"q.png") # io.highResPlot2d(cmb[2],out_dir+"u.png") modlmap = enmap.modlmap(shape, wcs) fc = maps.FourierCalc(shape, wcs) lbin_edges = np.arange(200, 6000, 40) lbinner = stats.bin2D(modlmap, lbin_edges) def plot_powers(cmb, suffix, power=None, w2=1.):
fgFuncY = None
import flipper.liteMap as lm
from alhazen.quadraticEstimator import NlGenerator, getMax
deg = 5.
px = 1.0
dell = 10
gradCut = 2000
kellmin = 10
lmap = lm.makeEmptyCEATemplate(raSizeDeg=deg,
decSizeDeg=deg,
pixScaleXarcmin=px,
pixScaleYarcmin=px)
kellmax = max(tellmax, pellmax)
from orphics.cosmology import Cosmology
cc = Cosmology(lmax=int(kellmax), pickling=True)
theory = cc.theory
bin_edges = np.arange(kellmin, kellmax, dell)
myNls = NlGenerator(lmap, theory, bin_edges, gradCut=gradCut)
nTX, nPX, nTY, nPY = myNls.updateNoiseAdvanced(
beamTX, noiseTX, beamPX, noisePX, tellminX, tellmaxX, pellminX,
pellmaxX, beamTY, noiseTY, beamPY, noisePY, tellminY, tellmaxY,
pellminY, pellmaxY, (lkneeTX, lkneePX), (alphaTX, alphaPX),
(lkneeTY, lkneePY), (alphaTY, alphaPY), None, None, None, None,
None, None, None, None, fgFuncX, fgFuncY, None, None, None,
None, None, None, None, None)
ls, Nls, ells, dclbb, efficiency = myNls.getNlIterative(pols,
kellmin,
kellmax,
tellmax,
# differentiating between small and large telescope for future compatibility
assert spellmin<=pellmin, "Why does your large telescope have a smaller lmin_P than the small one?"
dFile = Config.get('rForecast','rDerivFile')
fFile = Config.get('rForecast','rFidFile')
rInFid = Config.getfloat('rForecast','rInFid')
rExp = Config.getfloat('rForecast','rExpected')
fgPer = Config.getfloat('rForecast','fgPer')
dCls = np.loadtxt(dFile,delimiter=",")
fCls = np.loadtxt(fFile,delimiter=",")
from orphics.cosmology import Cosmology
cc = Cosmology(lmax=int(max(pellmax,spellmax)),pickling=True)
theory = cc.theory
ellBBRange = np.arange(spellmin,spellmax)
fclbb = cosmology.noise_pad_infinity(interp1d(ellBBRange,theory.lCl('BB',ellBBRange)*TCMB**2.,fill_value=np.inf,bounds_error=False),spellmin,spellmax)
# clbbnow = theory.lCl('BB',ellBBRange)#*TCMB**2.
# pl = Plotter(scaleY='log',xscale='log')
# pl.add(ellBBRange,clbbnow*ellBBRange**2.)
# pl.add(ellbb,dlbb*ellbb**2.)
# # pl._ax.set_ylim(-max(Clkk),max(Clkk))
# pl.done("clbb.png")