Class
NumCosmoClusterMassSelection
Description [src]
class NumCosmo.ClusterMassSelection : NumCosmo.ClusterMass
{
/* No available fields */
}
Cluster mass distribution model based on Selection et al.
Instance methods
nc_cluster_mass_selection_get_mean
Computes the mean of the richness distribution with the cut correction.
nc_cluster_mass_selection_get_std
Computes the standard deviation of the richness distribution with the cut correction.
nc_cluster_mass_selection_get_std_richness
Computes the standard deviation of the richness distribution.
nc_cluster_mass_selection_peek_completeness
Get the spline for the completeness as function of $\ln(M)$ and $z$.
nc_cluster_mass_selection_peek_ipurity
Get the spline for the inverse of purity as function of $\ln(M_obs)$ and $z$.
Methods inherited from NcClusterMass (15)
nc_cluster_mass_free
Atomically decrements the reference count of clusterm by one. If the reference count drops to 0,
all memory allocated by clusterm is released.
nc_cluster_mass_intp
It computes the clusterm probability distribution of lnM lying
in the range $[]$, namely,
$$ intp = \int_{\ln M^{obs}{min}}^{\ln M^{obs}{max}} p \, d\ln M^{obs},$$
where $p$ is [nc_cluster_mass_p()].
nc_cluster_mass_intp_bin
Computes the integrated probability over the observed mass bin.
nc_cluster_mass_n_limits
Computes the mass limits for the cluster abundance calculation.
The function which will call this one is responsible to allocate memory for lnM_lower and lnM_upper.
nc_cluster_mass_p
Computes the probability distribution $P(\ln M_{\mathrm{obs}}|\ln M, z)$.
nc_cluster_mass_p_bin_limits
Computes the integration limits for the true mass given the observed mass bin boundaries.
nc_cluster_mass_p_limits
Computes the integration limits for the true mass given the observed mass and its parameters.
nc_cluster_mass_p_vec_z_lnMobs
This method computes the probability distribution of lnM for each redshift in z
given the true mass lnM and the observed mass proxies lnM_obs and their parameters lnM_obs_params.
nc_cluster_mass_plcl_Msz_Ml_p_ndetone
This function computes the i-th term of the posterior given flat priors for the selection function and mass function. See function nc_cluster_pseudo_counts_posterior_ndetone().
nc_cluster_mass_plcl_pdf
Compute the joint probability density used internally by the PL-CL mass model. Integrals in $M_{sz}$ and $M_l$ are performed in the dimensionless quantities $\ln (M_{sz} / M_0)$ and $\ln (M_l / M_0)$, respectively. The Gaussian distributions between $M_{Pl}$ and $M_{CL}$ are written in terms of the dimensionless quantities $M_{Pl}/M_0$, $M_{CL}/M_0$, $\sigma_{Pl}/M_0$ and $\sigma_{CL}/M_0$.
nc_cluster_mass_plcl_pdf_only_lognormal
nc_cluster_mass_ref
Increases the reference count of clusterm by one.
nc_cluster_mass_resample
Generates a random sample of the observed mass proxies given the true mass and redshift.
nc_cluster_mass_resample_vec
Generates a random sample of the observed mass proxies given the true mass and redshift.
This is a convenience wrapper around nc_cluster_mass_resample() that uses NcmVector
for proper Python bindings support.
nc_cluster_mass_volume
Computes the effective volume in the observable mass space.
Properties
NumCosmo.ClusterMassSelection:M0
Pivot (reference) mass used to make observed and model masses dimensionless. The property default and allowed range are declared in the property registration below (see g_param_spec_double).
Properties inherited from NcmModel (9)
NumCosmoMath.Model:implementation
NumCosmoMath.Model:name
NumCosmoMath.Model:nick
NumCosmoMath.Model:params-types
NumCosmoMath.Model:reparam
NumCosmoMath.Model:scalar-params-len
NumCosmoMath.Model:sparam-array
NumCosmoMath.Model:submodel-array
NumCosmoMath.Model:vector-params-len
Signals
Signals inherited from GObject (1)
GObject::notify
The notify signal is emitted on an object when one of its properties has its value set through g_object_set_property(), g_object_set(), et al.