def __init__(self,
massdef='mean',
delta_mdef=200,
halo_profile_model='nfw'):
Ncm.cfg_init()
self.backend = 'nc'
self.set_cosmo(None)
self.mdef_dict = {
'mean': Nc.HaloDensityProfileMassDef.MEAN,
'critical': Nc.HaloDensityProfileMassDef.CRITICAL,
'virial': Nc.HaloDensityProfileMassDef.VIRIAL
}
self.hdpm_dict = {
'nfw': Nc.HaloDensityProfileNFW.new,
'einasto': Nc.HaloDensityProfileEinasto.new,
'hernquist': Nc.HaloDensityProfileHernquist.new
}
self.halo_profile_model = ''
self.massdef = ''
self.delta_mdef = 0
self.hdpm = None
self.set_halo_density_profile(halo_profile_model, massdef, delta_mdef)
def __init__(self, massdef='mean', delta_mdef=200, halo_profile_model='nfw'):
CLMModeling.__init__(self)
# Update class attributes
Ncm.cfg_init()
self.backend = 'nc'
self.mdef_dict = {
'mean': Nc.HaloDensityProfileMassDef.MEAN,
'critical': Nc.HaloDensityProfileMassDef.CRITICAL,
'virial':Nc.HaloDensityProfileMassDef.VIRIAL}
self.hdpm_dict = {
'nfw': Nc.HaloDensityProfileNFW.new,
'einasto': Nc.HaloDensityProfileEinasto.new,
'hernquist': Nc.HaloDensityProfileHernquist.new}
# Set halo profile and cosmology
self.set_halo_density_profile(halo_profile_model, massdef, delta_mdef)
self.set_cosmo(None)
def __init__(self, z_min, z_max, z_sigma, lnM_min,
lnM_max, area, observable):
Ncm.cfg_init()
self.cosmo = Nc.HICosmo.new_from_name(Nc.HICosmo, "NcHICosmoDEXcdm")
dist = Nc.Distance.new(z_max*1.5)
wp = Nc.Window.new_from_name("NcWindowTophat")
tf = Nc.TransferFunc.new_from_name("NcTransferFuncEH")
vp = Nc.MatterVar.new(Nc.MatterVarStrategy.FFT, wp, tf)
gf = Nc.GrowthFunc.new()
mulf = Nc.MultiplicityFunc.new_from_name("NcMultiplicityFuncTinkerCrit{'Delta':<500.0>}")
mf = Nc.MassFunction.new(dist, vp, gf, mulf)
if observable == 'SZ':
cluster_m = Nc.ClusterMass.new_from_name("NcClusterMassBenson{'M0':<3e14>, 'z0':<0.6>, 'signif-obs-min':<5.0>,'Asz':<6.24>, 'Bsz':<1.33>, 'Csz':<0.83>, 'Dsz':<0.24>}")
elif observable == 'true_mass':
cluster_m = Nc.ClusterMass.new_from_name("NcClusterMassNodist{'lnM-min':<% 20.15g>, 'lnM-max':<% 20.15g>}" % (lnM_min, lnM_max))
else:
raise NameError('Invalid observable choice. Should be ' +
'"true_mass" or "SZ"')
cluster_z = Nc.ClusterRedshift.new_from_name("NcClusterPhotozGaussGlobal{'pz-min':<%f>, 'pz-max':<%f>, 'z-bias':<0.0>, 'sigma0':<%f>}" % (z_min, z_max, z_sigma))
cad = Nc.ClusterAbundance.new(mf, None, cluster_z, cluster_m)
self.ncdata = Nc.DataClusterNCount.new(cad)
self.mset = Ncm.MSet()
self.mset.set(self.cosmo)
self.mset.set(cluster_m)
self.rng = Ncm.RNG.pool_get("example_ca_sampling");
self.ncdata.init_from_sampling(self.mset, cluster_z, cluster_m,
area * (pi/180.0) ** 2, self.rng)
del dist
del vp
del gf
del mulf
del mf
del cad
del cluster_z
del cluster_m
import math
import numpy as np
import matplotlib.pyplot as plt
try:
import gi
gi.require_version('NumCosmo', '1.0')
gi.require_version('NumCosmoMath', '1.0')
except:
pass
from gi.repository import NumCosmo as Nc
from gi.repository import NumCosmoMath as Ncm
Ncm.cfg_init()
#
# New homogeneous and isotropic cosmological model NcHICosmoDEXcdm
#
cosmo = Nc.HICosmo.new_from_name(Nc.HICosmo, "NcHICosmoDEXcdm")
cosmo.omega_x2omega_k()
cosmo.param_set_by_name("Omegak", 0.0)
#
# New cosmological distance objects optimizied to perform calculations
# up to redshift 2.0.
#
dist = Nc.Distance.new(1.0)
#
gi.require_version('NumCosmo', '1.0')
gi.require_version('NumCosmoMath', '1.0')
except:
pass
import math
from gi.repository import NumCosmo as Nc
from gi.repository import NumCosmoMath as Ncm
#import threading
#from numpy import pi
import os
import os.path
import math
Ncm.cfg_init ()
z_max = 1.32
z_min = 0.3
area = 2500
#
# New homogeneous and isotropic cosmological model NcHICosmoDEXcdm
#
cosmo = Nc.HICosmo.new_from_name (Nc.HICosmo, "NcHICosmoDEXcdm{'H0':<71.15>, 'Omegac':<0.218>, 'Omegab':<0.044>, 'w':<-1.01>, 'Omegac-fit':<1>, 'w-fit':<1>}")
cosmo.omega_x2omega_k ()
cosmo.param_set_by_name ("Omegak", 0.0);
(Found, w_i) = cosmo.param_index_from_name ("w")
cosmo.param_set_lower_bound (w_i, -3.0)
cosmo.param_set_upper_bound (w_i, 0.0)
import gi
gi.require_version('NumCosmo', '1.0')
gi.require_version('NumCosmoMath', '1.0')
except:
pass
import math
from gi.repository import GObject
from gi.repository import NumCosmo as Nc
from gi.repository import NumCosmoMath as Ncm
#
# Initializing the library objects, this must be called before
# any other library function.
#
Ncm.cfg_init ()
#
# New ModelBuilder object, defines a new model NcHIPrimExample implementing
# the Nc.HIPrim abstract class.
#
mb = Ncm.ModelBuilder.new (Nc.HIPrim, "NcHIPrimExample", "A example primordial model")
#
# New parameter A_s to describe the spectrum amplitud (it is usually better
# to work with ln(10^10As))
#
mb.add_sparam ("A_s", "As", 0.0, 1.0, 0.1, 0.0, 1.0e-9, Ncm.ParamType.FREE)
#
# New parameter n_s to describe the spectral index
gi.require_version('NumCosmo', '1.0')
gi.require_version('NumCosmoMath', '1.0')
except:
pass
from math import *
import matplotlib.pyplot as plt
from gi.repository import GObject
from gi.repository import NumCosmo as Nc
from gi.repository import NumCosmoMath as Ncm
#
# Initializing the library objects, this must be called before
# any other library function.
#
Ncm.cfg_init()
#
# New homogeneous and isotropic cosmological model NcHICosmoDEXcdm
#
cosmo = Nc.HICosmo.new_from_name(Nc.HICosmo, "NcHICosmoDEXcdm")
#
# Setting values for the cosmological model, those not set stay in the
# default values. Remeber to use the _orig_ version to set the original
# parameters in case when a reparametrization is used.
#
#
# OO-like
#
try:
import gi
gi.require_version('NumCosmo', '1.0')
gi.require_version('NumCosmoMath', '1.0')
except:
pass
from gi.repository import GObject
from gi.repository import NumCosmo as Nc
from gi.repository import NumCosmoMath as Ncm
#
# Initializing the library objects, this must be called before
# any other library function.
#
Ncm.cfg_init ()
#
# Instantiating a new SLine model object and setting
# some values for its parameters.
#
mrb = Ncm.ModelRosenbrock ()
#
# New Model set object including slm with parameters
# set as free.
#
mset = Ncm.MSet.empty_new ()
mset.set (mrb)
mset.param_set_all_ftype (Ncm.ParamType.FREE)
mset.prepare_fparam_map ()
try:
import gi
gi.require_version('NumCosmo', '1.0')
gi.require_version('NumCosmoMath', '1.0')
except:
pass
from gi.repository import GObject
from gi.repository import NumCosmo as Nc
from gi.repository import NumCosmoMath as Ncm
#
# Initializing the library objects, this must be called before
# any other library function.
#
Ncm.cfg_init()
dim = 10
#
# Instantiating a new SLine model object and setting
# some values for its parameters.
#
mrb = Ncm.ModelFunnel.new(dim - 1)
#
# New Model set object including slm with parameters
# set as free.
#
mset = Ncm.MSet.empty_new()
mset.set(mrb)
mset.param_set_all_ftype(Ncm.ParamType.FREE)
#!/usr/bin/python2
#from math import *
import gi
gi.require_version('NumCosmo', '1.0')
gi.require_version('NumCosmoMath', '1.0')
from gi.repository import GObject
from gi.repository import NumCosmo as Nc
from gi.repository import NumCosmoMath as Ncm
Ncm.cfg_init ()
NT = 3 # Number of threads
NClusters = 21 # Number of clusters
NWalkers = 100 # Number of walkers / chains
# Cosmological model: XCDM, DE eqos - w = constant
cosmo = Nc.HICosmo.new_from_name (Nc.HICosmo, "NcHICosmoDEXcdm")
dist = Nc.Distance.new (4.0)
# Primordial power spectrum - power law
prim = Nc.HIPrimPowerLaw.new ()
reion = Nc.HIReionCamb.new ()
# Transfer function
tf = Nc.TransferFunc.new_from_name ("NcTransferFuncEH")
# Linear matter power spectrum
ps_ml = Nc.PowspecMLTransfer.new (tf)
psf = Ncm.PowspecFilter.new (ps_ml, Ncm.PowspecFilterType.TOPHAT)
mulf = Nc.MultiplicityFunc.new_from_name ("NcMultiplicityFuncTinkerCrit{'Delta':<500.0>}")
mf = Nc.HaloMassFunction.new (dist, psf, mulf)
pass import timeit import sys import time import math import numpy as np from gi.repository import NumCosmo as Nc from gi.repository import NumCosmoMath as Ncm # # Initializing the library objects, this must be called before # any other library function. # sys.argv = Ncm.cfg_init_full (sys.argv) cosmo = Nc.HICosmo.new_from_name (Nc.HICosmo, "NcHICosmoDEXcdm") cosmo.props.H0 = 70.0 cosmo.props.Omegab = 0.05 cosmo.props.Omegac = 0.25 cosmo.props.Omegax = 0.70 cosmo.props.Tgamma0 = 2.72 cosmo.props.w = -1.0 # # Creating a new Modelset and set cosmo as the HICosmo model to be used. # mset = Ncm.MSet ()
# # Creating a Fit object of type NLOPT using the fitting algorithm ln-neldermead to # fit the Modelset mset using the Likelihood lh and using a numerical differentiation # algorithm (NUMDIFF_FORWARD) to obtain the gradient (if needed). # fit = Ncm.Fit.new (Ncm.FitType.NLOPT, "ln-neldermead", lh, mset, Ncm.FitGradType.NUMDIFF_FORWARD) # # Printing fitting informations. # fit.log_info () # # Setting single thread calculation. # Ncm.func_eval_set_max_threads (1) Ncm.func_eval_log_pool_stats () # # New Gaussian prior to provide the initial points for the chain. # It was created with size 0 (number of parameters), but once # initialized with mset the correct size is assigned. # # The initial sampler will use a diagonal covariance with the # diagonal terms being the parameters scale set by each model. # init_sampler = Ncm.MSetTransKernGauss.new (0) init_sampler.set_mset (mset) init_sampler.set_prior_from_mset () init_sampler.set_cov_from_rescale (1.0)
#!/usr/bin/python2
#from math import *
import gi
gi.require_version('NumCosmo', '1.0')
gi.require_version('NumCosmoMath', '1.0')
from gi.repository import GObject
from gi.repository import NumCosmo as Nc
from gi.repository import NumCosmoMath as Ncm
Ncm.cfg_init()
NT = 3 # Number of threads
NClusters = 21 # Number of clusters
NWalkers = 100 # Number of walkers / chains
# Cosmological model: XCDM, DE eqos - w = constant
cosmo = Nc.HICosmo.new_from_name(Nc.HICosmo, "NcHICosmoDEXcdm")
dist = Nc.Distance.new(4.0)
# Primordial power spectrum - power law
prim = Nc.HIPrimPowerLaw.new()
reion = Nc.HIReionCamb.new()
# Transfer function
tf = Nc.TransferFunc.new_from_name("NcTransferFuncEH")
# Linear matter power spectrum
ps_ml = Nc.PowspecMLTransfer.new(tf)
psf = Ncm.PowspecFilter.new(ps_ml, Ncm.PowspecFilterType.TOPHAT)
mulf = Nc.MultiplicityFunc.new_from_name(
"NcMultiplicityFuncTinkerCrit{'Delta':<500.0>}")
import matplotlib.pyplot as plt
import os.path
try:
import gi
gi.require_version('NumCosmo', '1.0')
gi.require_version('NumCosmoMath', '1.0')
except:
pass
from gi.repository import GObject
from gi.repository import NumCosmo as Nc
from gi.repository import NumCosmoMath as Ncm
__name___ = "NcContext"
Ncm.cfg_init()
Ncm.cfg_set_log_handler(
lambda msg: sys.stdout.write(msg) and sys.stdout.flush())
dim = 5
np.random.seed(seed=123)
p = np.random.random_sample((dim, ))
print(p)
rng = Ncm.RNG.seeded_new(None, 123)
fmodel = Ncm.ModelMVND.new(dim)
fdata = Ncm.DataGaussCovMVND.new_full(dim, 0.1, 0.4, 10.0, -1.0, 1.0, rng)
fdata.props.use_norma = True
except:
pass
import timeit
import sys
import time
import math
import numpy as np
from gi.repository import NumCosmo as Nc
from gi.repository import NumCosmoMath as Ncm
#
# Initializing the library objects, this must be called before
# any other library function.
#
sys.argv = Ncm.cfg_init_full(sys.argv)
rng = Ncm.RNG.new(None)
rng.set_random_seed(True)
mj = Ncm.MPIJobTest.new()
mj.set_rand_vector(12, rng)
ser = Ncm.Serialize.new(0)
mj.init_all_slaves(ser)
a = []
b = []
for t in np.arange(12.0):
a.append(Ncm.Vector.new_array([t]))
b.append(Ncm.Vector.new(1))
