def __init__(self, *args, **kwargs):
super(TestHMF, self).__init__(*args, **kwargs)
iniFile = "tests/unitTests.ini"
Config = SafeConfigParser()
Config.optionxform = str
Config.read(iniFile)
self.testname = Config.get('general', 'testName')
ms = listFromConfig(Config, self.testname, 'mexp')
self.marray = np.arange(ms[0], ms[1], ms[2])
self.zs = listFromConfig(Config, self.testname, 'zs')
#expList = ['S4-1.0-0.4','S4-1.5-0.4','S4-1.5-0.7','S4-1.5-0.3','S4-1.5-0.2','S4-1.5-0.1','S4-1.5-0.05','S4-2.0-0.4','S4-2.5-0.4','S4-3.0-0.4']
#expList = ['S4-1.5-0.3','S4-1.5-0.2','S4-1.5-0.1']
expList = ['SO-v2'] #'S4-1.5-0.3','S4-1.5-0.2','S4-1.5-0.1']
calList = ['CMB_all', 'CMB_pol', 'CMB_all_miscentered', 'CMB_pol_miscentered']
gridName = "grid-default"
from configparser import SafeConfigParser
iniFile = "input/pipeline.ini"
Config = SafeConfigParser()
Config.optionxform = str
Config.read(iniFile)
bigDataDir = Config.get('general', 'bigDataDirectory')
version = Config.get('general', 'version')
zs = listFromConfig(Config, gridName, 'zrange')
z_edges = np.arange(zs[0], zs[1] + zs[2], zs[2])
numCores = z_edges.size
for exp in expList:
for cal in calList:
massGridName = bigDataDir + "lensgrid_" + exp + "_" + gridName + "_" + cal + "_v" + version + ".pkl"
cmd = "nohup wq sub -r \"mode:bycore;N:" + str(
numCores
) + ";hostfile: auto;job_name: " + exp + "_" + cal + ";priority:med\" -c \"source ~/.bash_profile ; source ~/.bashrc ; cd ~/repos/szar ; mpirun -hostfile %hostfile% python bin/makeS8Derivs.py " + exp + " " + gridName + " " + cal + " " + massGridName + " \" > output" + str(
time.time()) + "_cmbderiv_" + exp + "_" + cal + ".log &"
',')
# Load other Fisher matrices to add
otherFisher = loadFishers(Config.get('fisher', 'otherFishers').split(','))
# Get CMB noise functions and ell ranges. Note that the same overriding is possible but here the beams and noises have to be lists for the different frequencies.
fnTT, fnEE = noiseFromConfig(Config,
expName,
TCMB=TCMB,
beamsOverride=None,
noisesOverride=None,
lkneeTOverride=None,
lkneePOverride=None,
alphaTOverride=None,
alphaPOverride=None)
tellmin, tellmax = listFromConfig(Config, expName, 'tellrange')
pellmin, pellmax = listFromConfig(Config, expName, 'pellrange')
# Pad CMB lensing noise with infinity outside L ranges
kellmin, kellmax = listFromConfig(Config, 'lensing', 'Lrange')
fnKK = cmb.noise_pad_infinity(
interp1d(ls, Nls, fill_value=np.inf, bounds_error=False), kellmin,
kellmax)
# Decide on what ell range to calculate the Fisher matrix
ellrange = np.arange(min(tellmin, pellmin, kellmin),
max(tellmax, pellmax, kellmax)).astype(int)
# Get fsky
fsky = Config.getfloat(expName, 'fsky')
# Calculate the Fisher matrix and add to other Fishers
# Fisher = otherFisher+calcFisher(paramList,ellrange,fidCls,dCls,fnTT,fnEE,fnKK,fsky,verbose=True)
clttfile = Config.get('general', 'clttfile')
cc = ClusterCosmology(fparams, constDict, lmax=8000,
pickling=True) #clTTFixFile=clttfile)
fgs = fgNoises(cc.c,
ksz_battaglia_test_csv="data/ksz_template_battaglia.csv",
tsz_battaglia_template_csv="data/sz_template_battaglia.csv")
cf = 1
constraint_tag = ['', '_constrained']
#experimentName = "CMB-Probe-50cm"
experimentName = "CCATP-MSIP"
#experimentName = "CCATP-SO-MSIP"
beams = listFromConfig(Config, experimentName, 'beams')
noises = listFromConfig(Config, experimentName, 'noises')
freqs = listFromConfig(Config, experimentName, 'freqs')
lmax = int(Config.getfloat(experimentName, 'lmax'))
lknee = listFromConfig(Config, experimentName, 'lknee')[0]
alpha = listFromConfig(Config, experimentName, 'alpha')[0]
fsky = Config.getfloat(experimentName, 'fsky')
SZProfExample = SZ_Cluster_Model(clusterCosmology=cc,
clusterDict=clusterDict,
rms_noises=noises,
fwhms=beams,
freqs=freqs,
lmax=lmax,
lknee=lknee,
alpha=alpha)
import pickle as pickle
from orphics.tools.io import Plotter
from orphics.analysis.flatMaps import interpolateGrid
clusterParams = 'LACluster' # from ini file
cosmologyName = 'LACosmology' # from ini file
experimentName = "LATest"
iniFile = "input/params.ini"
Config = SafeConfigParser()
Config.optionxform = str
Config.read(iniFile)
outDir = os.environ['WWW']
beam = listFromConfig(Config, experimentName, 'beams')
noise = listFromConfig(Config, experimentName, 'noises')
freq = listFromConfig(Config, experimentName, 'freqs')
lmax = int(Config.getfloat(experimentName, 'lmax'))
lknee = Config.getfloat(experimentName, 'lknee')
alpha = Config.getfloat(experimentName, 'alpha')
fsky = Config.getfloat(experimentName, 'fsky')
cosmoDict = dictFromSection(Config, cosmologyName)
constDict = dictFromSection(Config, 'constants')
clusterDict = dictFromSection(Config, clusterParams)
cc = ClusterCosmology(
cosmoDict, constDict,
clTTFixFile="data/cltt_lensed_Feb18.txt") #,skipCls=True)
mfile = "data/S4-7mCMB_all.pkl"
clusterParams = 'cluster_params' # from ini file
cosmologyName = 'params' # from ini file
iniFile = "../szar/input/pipeline.ini"
Config = SafeConfigParser()
Config.optionxform = str
Config.read(iniFile)
cosmoDict = dictFromSection(Config, cosmologyName)
constDict = dictFromSection(Config, 'constants')
clusterDict = dictFromSection(Config, clusterParams)
bigDataDir = Config.get('general', 'bigDataDirectory')
beam = listFromConfig(Config, expName, 'beams')
noise = listFromConfig(Config, expName, 'noises')
freq = listFromConfig(Config, expName, 'freqs')
lkneeT, lkneeP = listFromConfig(Config, expName, 'lknee')
alphaT, alphaP = listFromConfig(Config, expName, 'alpha')
tellmin, tellmax = listFromConfig(Config, expName, 'halo_tellrange')
pellmin, pellmax = listFromConfig(Config, expName, 'halo_pellrange')
try:
doFg = Config.getboolean(expName, 'do_foregrounds')
except:
print("NO FG OPTION FOUND IN INI. ASSUMING TRUE.")
doFg = True
ind = np.where(np.isclose(freq, freq_to_use))
beamFind = np.array(beam)[ind]
noiseFind = np.array(noise)[ind]
fparams = {}
for (key, val) in Config.items('params'):
if ',' in val:
param, step = val.split(',')
if key=='sigR':
rayFid = float(param)
rayStep = float(step)
fparams[key] = float(param)
else:
fparams[key] = float(val)
constDict = dictFromSection(Config,'constants')
clusterDict = dictFromSection(Config,'cluster_params')
beam = listFromConfig(Config,expName,'beams')
noise = listFromConfig(Config,expName,'noises')
freq = listFromConfig(Config,expName,'freqs')
lknee = listFromConfig(Config,expName,'lknee')[0]
alpha = listFromConfig(Config,expName,'alpha')[0]
clttfile = Config.get('general','clttfile')
# get s/n q-bins
qs = listFromConfig(Config,'general','qbins')
qspacing = Config.get('general','qbins_spacing')
if qspacing=="log":
qbin_edges = np.logspace(np.log10(qs[0]),np.log10(qs[1]),int(qs[2])+1)
elif qspacing=="linear":
qbin_edges = np.linspace(qs[0],qs[1],int(qs[2])+1)
else:
#pl = Plotter(labelX="$z$",labelY="$N(z)$",ftsize=12)
colList = ['C0', 'C1', 'C2', 'C3', 'C4']
Ndict = {}
for expName, col, labres in zip(expList, colList, labList):
mgrid, zgrid, siggrid = pickle.load(
open(
bigDataDir + "szgrid_" + expName + "_" + gridName + "_v" +
version + ".pkl", 'rb'))
z_edges = zgrid
zrange = old_div((z_edges[1:] + z_edges[:-1]), 2.)
mexp_edges = mgrid
beam = listFromConfig(Config, expName, 'beams')
noise = listFromConfig(Config, expName, 'noises')
freq = listFromConfig(Config, expName, 'freqs')
lknee = listFromConfig(Config, expName, 'lknee')[0]
alpha = listFromConfig(Config, expName, 'alpha')[0]
fsky = Config.getfloat(expName, 'fsky')
HMF = Halo_MF(cc, mexp_edges, z_edges)
HMF.sigN = siggrid.copy()
SZProf = SZ_Cluster_Model(cc,
clusterDict,
rms_noises=noise,
fwhms=beam,
freqs=freq,
lknee=lknee,
alpha=alpha)
alphaTOverride=None,
alphaPOverride=None)
efficiencies.append(efficiency)
printC("Delensing efficiency: " + str(efficiency) + " %",
color="green",
bold=True)
# File root name for Fisher derivatives
# CLKK S/N ============================================
# Calculate Clkk S/N
#Clkk = fidCls[:,4]
kellmin, kellmax = listFromConfig(Config, 'lensing', 'Lrange')
fsky = fskyNow #Config.getfloat(expName,'fsky')
frange = np.arange(0, kellmax) #np.array(range(len(Clkk)))
Clkk = cc.theory.gCl("kk", frange)
snrange = np.arange(kellmin, kellmax)
LF = LensForecast()
LF.loadKK(frange, Clkk, ls, Nls)
sn, errs = LF.sn(snrange, fsky, "kk")
printC("Lensing autopower S/N: " + str(sn), color="green", bold=True)
# pl = Plotter(scaleY='log',scaleX='log')
# pl.add(frange,Clkk)
# pl.add(ls,Nls)
# pl._ax.set_ylim(-max(Clkk),max(Clkk))
# pl.done("clkk.png")
ells = np.arange(2, 8000, 1)
cltt = theory.lCl('TT', ells)
TCMB = 2.7255e6
out_dir = os.environ['WWW']
pl = io.Plotter(scaleY='log',
labelX="$\ell$",
labelY="$\ell^2 C_{\ell}$",
ftsize=20)
for expName, lab in zip(['S4-1.0-0.4-noatm', 'S4-1.0-0.4'],
['S4 1arc no atm', 'S4 1arc lknee=5500 (in paper)']):
beam = listFromConfig(Config, expName, 'beams')
noise = listFromConfig(Config, expName, 'noises')
freq = listFromConfig(Config, expName, 'freqs')
lkneeT, lkneeP = listFromConfig(Config, expName, 'lknee')
alphaT, alphaP = listFromConfig(Config, expName, 'alpha')
print((expName, beam, noise, lkneeT, lkneeP, alphaT, alphaP))
ind = np.where(np.isclose(freq, freq_to_use))
beamFind = np.array(beam)[ind]
noiseFind = np.array(noise)[ind]
nls = cmb.noise_func(ells,
beamFind,
noiseFind,
lknee=lkneeT,
