Class
NumCosmoClusterMass
Description [src]
abstract class NumCosmo.ClusterMass : NumCosmoMath.Model
{
/* No available fields */
}Abstract class for cluster mass distributions.
NcClusterMass is the abstract class designed to abridge the functions that any cluster mass distribution should implement, see NcClusterMassImpl. Its parent_class is NcmModel.
Functions
nc_cluster_mass_log_all_models
This function lists all implemented models of cluster mass distributions.
Instance methods
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_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_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_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.
Properties
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.
Class structure
struct NumCosmoClusterMassClass {
gdouble (* P) (
NcClusterMass* clusterm,
NcHICosmo* cosmo,
const gdouble lnM,
const gdouble z,
const gdouble* lnM_obs,
const gdouble* lnM_obs_params
);
gdouble (* intP) (
NcClusterMass* clusterm,
NcHICosmo* cosmo,
const gdouble lnM,
const gdouble z
);
gdouble (* intP_bin) (
NcClusterMass* clusterm,
NcHICosmo* cosmo,
const gdouble lnM,
const gdouble z,
const gdouble* lnM_obs_lower,
const gdouble* lnM_obs_upper,
const gdouble* lnM_obs_params
);
gboolean (* resample) (
NcClusterMass* clusterm,
NcHICosmo* cosmo,
const gdouble lnM,
const gdouble z,
gdouble* lnM_obs,
const gdouble* lnM_obs_params,
NcmRNG* rng
);
void (* P_limits) (
NcClusterMass* clusterm,
NcHICosmo* cosmo,
const gdouble* lnM_obs,
const gdouble* lnM_obs_params,
gdouble* lnM_lower,
gdouble* lnM_upper
);
void (* P_bin_limits) (
NcClusterMass* clusterm,
NcHICosmo* cosmo,
const gdouble* lnM_obs_lower,
const gdouble* lnM_obs_upper,
const gdouble* lnM_obs_params,
gdouble* lnM_lower,
gdouble* lnM_upper
);
void (* N_limits) (
NcClusterMass* clusterm,
NcHICosmo* cosmo,
gdouble* lnM_lower,
gdouble* lnM_upper
);
gdouble (* volume) (
NcClusterMass* clusterm
);
void (* P_vec_z_lnMobs) (
NcClusterMass* clusterm,
NcHICosmo* cosmo,
const gdouble lnM,
const NcmVector* z,
const NcmMatrix* lnM_obs,
const NcmMatrix* lnM_obs_params,
NcmVector* res
);
}No description available.
Class members
P: gdouble (* P) ( NcClusterMass* clusterm, NcHICosmo* cosmo, const gdouble lnM, const gdouble z, const gdouble* lnM_obs, const gdouble* lnM_obs_params )No description available.
intP: gdouble (* intP) ( NcClusterMass* clusterm, NcHICosmo* cosmo, const gdouble lnM, const gdouble z )No description available.
intP_bin: gdouble (* intP_bin) ( NcClusterMass* clusterm, NcHICosmo* cosmo, const gdouble lnM, const gdouble z, const gdouble* lnM_obs_lower, const gdouble* lnM_obs_upper, const gdouble* lnM_obs_params )No description available.
resample: gboolean (* resample) ( NcClusterMass* clusterm, NcHICosmo* cosmo, const gdouble lnM, const gdouble z, gdouble* lnM_obs, const gdouble* lnM_obs_params, NcmRNG* rng )No description available.
P_limits: void (* P_limits) ( NcClusterMass* clusterm, NcHICosmo* cosmo, const gdouble* lnM_obs, const gdouble* lnM_obs_params, gdouble* lnM_lower, gdouble* lnM_upper )No description available.
P_bin_limits: void (* P_bin_limits) ( NcClusterMass* clusterm, NcHICosmo* cosmo, const gdouble* lnM_obs_lower, const gdouble* lnM_obs_upper, const gdouble* lnM_obs_params, gdouble* lnM_lower, gdouble* lnM_upper )No description available.
N_limits: void (* N_limits) ( NcClusterMass* clusterm, NcHICosmo* cosmo, gdouble* lnM_lower, gdouble* lnM_upper )No description available.
volume: gdouble (* volume) ( NcClusterMass* clusterm )No description available.
P_vec_z_lnMobs: void (* P_vec_z_lnMobs) ( NcClusterMass* clusterm, NcHICosmo* cosmo, const gdouble lnM, const NcmVector* z, const NcmMatrix* lnM_obs, const NcmMatrix* lnM_obs_params, NcmVector* res )No description available.
Virtual methods
NumCosmo.ClusterMassClass.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.
NumCosmo.ClusterMassClass.P
Computes the probability distribution $P(\ln M_{\mathrm{obs}}|\ln M, z)$.
NumCosmo.ClusterMassClass.P_bin_limits
Computes the integration limits for the true mass given the observed mass bin boundaries.
NumCosmo.ClusterMassClass.P_limits
Computes the integration limits for the true mass given the observed mass and its parameters.
NumCosmo.ClusterMassClass.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.
NumCosmo.ClusterMassClass.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()].
NumCosmo.ClusterMassClass.resample
Generates a random sample of the observed mass proxies given the true mass and redshift.
Class methods
nc_cluster_mass_class_obs_len
The number of observable masses (or just the observable which is related to the cluster mass) of each cluster, e.g., 1 - SZ mass, 1 - X-ray mass, 1 - Lensing mass, 2 - SZ and X-ray masses, 3 - SZ, X-ray and lensing masses.
nc_cluster_mass_class_obs_params_len
The number of parameters related to the observable masses of each cluster, e.g., 1 - error of the SZ mass, 1 - error of the X-ray mass, 2 - errors of SZ and X-ray masses.