true2d = get_nfw(true_mass)
kellmin = 200
kellmax = 8500
true2d = enmap.ndmap(fmaps.filter_map(true2d,true2d*0.+1.,modlmap,lowPass=kellmax,highPass=kellmin),wcs)
Nsims = 1000
cov = np.ones((1,1,8500))*0.00000001
ngen = enmap.MapGen(shape,wcs,cov)
out_dir = os.environ['WWW']+"plots/cgauss_"
# Efficiently distribute sims over MPI cores
num_each,each_tasks = mpi_distribute(Nsims,numcores)
# Initialize a container for stats and stacks
mpibox = MPIStats(comm,num_each,tag_start=333)
if rank==0: print(("At most ", max(num_each) , " tasks..."))
# What am I doing?
my_tasks = each_tasks[rank]
for k,index in enumerate(my_tasks):
noise = ngen.get_map()
mkappa = true2d+noise
if k==0 and rank==0: io.quickPlot2d(noise,out_dir+"nstamp.png")
print(k)
cents, prof = rbinner.bin(mkappa)
mpibox.add_to_stats('prof',prof)
mpibox.add_to_stack('mkappa',mkappa)
mpibox.add_to_stats("TT", cltt)
mpibox.add_to_stats("EE", clee)
mpibox.add_to_stats("BB", clbb)
mpibox.add_to_stats("TE", clte)
mpibox.add_to_stats("EB", cleb)
mpibox.add_to_stats("TB", cltb)
return ells
Ntot = 8
# Efficiently distribute sims over MPI cores
num_each, each_tasks = mpi_distribute(Ntot, numcores)
# Initialize a container for stats and stacks
mpibox = MPIStats(comm, num_each, tag_start=333)
if rank == 0: print(("At most ", max(num_each), " tasks..."))
# What am I doing?
my_tasks = each_tasks[rank]
k = -1
for index in my_tasks:
k += 1
cmb_map = load_fullsky(sim_root, "fullsky_curved_lensed_car", index)
print((rank, k, cmb_map.shape))
ells = map2power(cmb_map, mpibox)
import orphics.tools.stats as stats
import orphics.tools.cmb as cmb
import flipper.liteMap as lm
import flipper.fftTools as ft
import orphics.tools.io as io
import numpy as np
# Get MPI comm
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
numcores = comm.Get_size()
Ntot = 256
num_each, each_tasks = mpi_distribute(Ntot, numcores)
mpibox = MPIStats(comm, num_each, tag_start=333)
if rank == 0: print(("At most ", max(num_each), " tasks..."))
my_tasks = each_tasks[rank]
nside = 4096
deg = 10.
px = 0.5
bin_edges = np.arange(100, 4000, 40)
theory_file_root = "data/Aug6_highAcc_CDM"
theory = cmb.loadTheorySpectraFromCAMB(theory_file_root,
unlensedEqualsLensed=False,
useTotal=False,
TCMB=2.7255e6,
lpad=9000,
#if save is not None: save_func = lambda x: save_dir + "/"+save+"_"+str(x).zfill(9)+".fits"
# How many sims? Should I use saved files?
if Nsims is None: Nsims = 320
sigurd_cmb_file = lambda x: "/gpfs01/astro/workarea/msyriac/data/sims/sigurd/cori/v5/" + region + "_curved_lensed_car_" + str(
x).zfill(2) + ".fits"
sigurd_kappa_file = lambda x: "/gpfs01/astro/workarea/msyriac/data/sims/sigurd/cori/v5/" + region + "_curved_kappa_car_" + str(
x).zfill(2) + ".fits"
Ntot = Nsims
# Efficiently distribute sims over MPI cores
num_each, each_tasks = mpi_distribute(Ntot, numcores)
# Initialize a container for stats and stacks
mpibox = MPIStats(comm, num_each, tag_start=333)
if rank == 0: print(("At most ", max(num_each), " tasks..."))
# What am I doing?
my_tasks = each_tasks[rank]
if rank == 0: print("Reading config...")
# Read config
iniFile = "../halofg/input/recon.ini"
Config = SafeConfigParser()
Config.optionxform = str
Config.read(iniFile)
if rank == 0: print("Params...")
rank = comm.Get_rank()
numcores = comm.Get_size()
gradCut = 2000 #None #2000
date = '190404_'
ksz = 2 # Options: 0,1,2
ksz_name = ['', 'reionKSZ_', 'bothKSZ_']
# i/o directories
out_dir = "output/" + date + expf_name + "_" + str(gradCut) + "_" + ksz_name[
ksz] # for plots
# Efficiently distribute sims over MPI cores
num_each, each_tasks = mpi_distribute(Ntot, numcores)
# Initialize a container for stats and stacks
mpibox = MPIStats(comm, num_each, tag_start=333)
if rank == 0: print "At most ", max(num_each), " tasks..."
# What am I doing?
my_tasks = each_tasks[rank]
# Read config
iniFile = "input/recon_astro2020.ini"
Config = SafeConfigParser()
Config.optionxform = str
Config.read(iniFile)
pol = False
shape_sim, wcs_sim, shape_dat, wcs_dat = aio.enmaps_from_config(
Config, sim_section, analysis_section, pol=pol)
parray_dat = aio.patch_array_from_config(Config,
expf_name,
shape_dat,
wcs_dat,
dimensionless=False)
parray_sim = aio.patch_array_from_config(Config,
expf_name,
shape_sim,
wcs_sim,
dimensionless=False)
arcmap = parray_sim.modrmap * 180. * 60. / np.pi
# Efficiently distribute sims over MPI cores
num_each, each_tasks = mpi_distribute(Nsims, numcores)
# Initialize a container for stats and stacks
mpibox = MPIStats(comm, num_each, tag_start=333)
if rank == 0: print(("At most ", max(num_each), " tasks..."))
# What am I doing?
my_tasks = each_tasks[rank]
# === COSMOLOGY ===
theory, cc, lmax = aio.theory_from_config(Config,
cosmology_section,
dimensionless=False)
parray_dat.add_theory(theory=theory, lmax=lmax, orphics_is_dimensionless=False)
parray_sim.add_theory(theory=theory, lmax=lmax, orphics_is_dimensionless=False)
lb = aio.ellbounds_from_config(Config, recon_section, min_ell)
tellmin = lb['tellminY']
tellmax = lb['tellmaxY']
pellmin = lb['pellminY']
polsims = Config.getboolean("general","pol")
pol = False
shape_sim, wcs_sim, shape_dat, wcs_dat = aio.enmaps_from_config(Config,sim_section,analysis_section,pol=pol)
analysis_resolution = np.min(enmap.extent(shape_dat,wcs_dat)/shape_dat[-2:])*60.*180./np.pi
pixratio = analysis_resolution/Config.getfloat(sim_section,"pixel_arcmin")
min_ell = fmaps.minimum_ell(shape_dat,wcs_dat)
parray_dat = aio.patch_array_from_config(rConfig,expf_name,shape_dat,wcs_dat,dimensionless=False)
# Efficiently distribute sims over MPI cores
Nuse = Nsims if args.num_sims is None else args.num_sims
assert args.num_sims < Nsims
num_each,each_tasks = mpi_distribute(Nuse,numcores)
# Initialize a container for stats and stacks
mpibox = MPIStats(comm,num_each,tag_start=333)
if rank==0: print(("At most ", max(num_each) , " tasks..."))
# What am I doing?
my_tasks = each_tasks[rank]
# === COSMOLOGY ===
theory, cc, lmax = aio.theory_from_config(Config,cosmology_section,dimensionless=False)
parray_dat.add_theory(cc,theory,lmax,orphics_is_dimensionless=False)
lxmap_dat,lymap_dat,modlmap_dat,angmap_dat,lx_dat,ly_dat = fmaps.get_ft_attributes_enmap(shape_dat,wcs_dat)
lb = aio.ellbounds_from_config(rConfig,recon_section,min_ell*8)
tellmin = lb['tellminY']
tellmax = lb['tellmaxY']
pellmin = lb['pellminY']
Ntotks = [Ntotk]
Ntotcs = [Ntotc]
for i in range(1, numcores):
Ntotks.append(comm.recv(source=i, tag=99))
Ntotcs.append(comm.recv(source=i, tag=88))
Nmin = min(min(Ntotks, Ntotcs))
Nmin = comm.bcast(Nmin, root=0)
if rank == 0: print(("Nmin : ", Nmin))
cmb_glob = cmb_glob[:Nmin]
kappa_glob = kappa_glob[:Nmin]
Ntot = Nmin
# Efficiently distribute sims over MPI cores
num_each, each_tasks = mpi_distribute(Ntot, numcores)
# Initialize a container for stats and stacks
mpibox = MPIStats(comm, num_each, tag_start=333)
if rank == 0: print(("At most ", max(num_each), " tasks..."))
# What am I doing?
my_tasks = each_tasks[rank]
my_kappa_files = [kappa_glob[i] for i in my_tasks]
my_cmb_files = [cmb_glob[i] for i in my_tasks]
# Read config
iniFile = "input/recon.ini"
Config = SafeConfigParser()
Config.optionxform = str
Config.read(iniFile)
pol = False
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
numcores = comm.Get_size()
# i/o directories
out_dir = os.environ['WWW']+"plots/mass_"+str(cluster_mass)+"_"+str(grad_cut)+"_unlensed_"+str(nolens)+"_fake_"+str(args.fake)+"_" # for plots
Ntot = Nsims
# Efficiently distribute sims over MPI cores
num_each,each_tasks = mpi_distribute(Ntot,numcores)
# Initialize a container for stats and stacks
mpibox = MPIStats(comm,num_each,tag_start=333)
if rank==0: print(("At most ", max(num_each) , " tasks..."))
# What am I doing?
my_tasks = each_tasks[rank]
# Read config
iniFile = "../halofg/input/recon.ini"
Config = SafeConfigParser()
Config.optionxform=str
Config.read(iniFile)
pol = False
shape_sim, wcs_sim, shape_dat, wcs_dat = aio.enmaps_from_config(Config,sim_section,analysis_section,pol=pol)