Class
NumCosmoClusterAbundance
Description [src]
class NumCosmo.ClusterAbundance : GObject.Object
{
/* No available fields */
}
Cluster abundance distribution
This class is used to store the cluster abundance distribution and its properties.
Constructors
nc_cluster_abundance_new
This function allocates memory for a new NcClusterAbundance object and sets its properties to the values from
the input arguments.
nc_cluster_abundance_nodist_new
This function allocates memory for a new NcClusterAbundance object and sets its properties to the values from
the input arguments.
Functions
nc_cluster_abundance_clear
Atomically decrements the reference count of cad by one. If the reference count drops to 0,
all memory allocated by cad is released.
Instance methods
nc_cluster_abundance_d2n
This function computes $ \int_{\ln M^{obs} - 7\sigma_{\ln M}}^{\ln M^{obs} + 7\sigma_{\ln M}} d\ln M \, \frac{d^2N}{dzdlnM} * P(\ln M^{obs}|\ln M) $. The integral limits were determined requiring a precision to five decimal places.
nc_cluster_abundance_free
Atomically decrements the reference count of cad by one. If the reference count drops to 0,
all memory allocated by cad is released.
nc_cluster_abundance_intp_bin_d2n
Computes the integrated differential abundance over the specified observed mass and redshift bins.
nc_cluster_abundance_intp_bin_d2n_bias
Computes the bias-weighted integrated differential abundance over the specified bins.
nc_cluster_abundance_intp_d2n
Computes the interpolated differential abundance $d^2N/dzd\ln M$ at the given mass and redshift.
nc_cluster_abundance_intp_d2n_bias
Computes the bias-weighted differential abundance for the given observed mass and redshift.
nc_cluster_abundance_lnM_p_d2n
This function computes $ \int_{\ln M^{obs} - 7\sigma_{\ln M}}^{\ln M^{obs} + 7\sigma_{\ln M}} d\ln M \, \frac{d^2N}{dzdlnM} * P(\ln M^{obs}|\ln M) $. The integral limits were determined requiring a precision to five decimal places.
nc_cluster_abundance_n
This function computes the total number of clusters within specific redshift
and mass intervals, which are defined in clusterz and clusterm, respectively,
and over a sky area.
nc_cluster_abundance_prepare_if_needed
Prepares the cluster abundance object if the cosmology or cluster models have changed.
This function checks if any of the models have been updated and calls nc_cluster_abundance_prepare()
if necessary.
nc_cluster_abundance_prepare_inv_dNdlnM_z
This function prepares a spline where the x array corresponds to the value of $\int_{\ln M_0} ^{\ln M_1} d^2N/dzd\ln M dM/ \int_lnMi^lnMf dN/dz dM$ given a redshift $z$ and the y array contains the values of logarithms base e of the mass. It is used to generate a sample of $\ln M$ values.
nc_cluster_abundance_true_n
This function computes the total number of “true” clusters, i.e., halos within redshift and mass intervals, and over a sky area.
nc_cluster_abundance_z_p_d2n
This function computes $ \int_{z_{phot} - 10\sigma_{phot}}^{z_{phot} + 10\sigma_{phot}} dz \, \frac{d^2N}{dzdlnM} * P(z^{photo}|z) $. The integral limits were determined requiring a precision to five decimal places.
nc_cluster_abundance_z_p_lnM_p_d2n
This function computes $ \int_0^\infty dz \int_{-\infty}^\infty d\ln M \frac{d^2N(\ln M, z)}{dzd\ln M} * P(z^{phot}|z) * P(\ln M^{obs}|\ln M, z) $. We studied the convergence of this integral to optimize this function. We verified that it converges to 5 decimal places at the redshift interval $ [z^{phot} - 10\sigma^{phot}, z^{phot} + 10\sigma^{phot}] $ and the mass interval $ [\ln M^{obs} - 7\sigma_{\ln M}, \ln M^{obs} + 7\sigma_{\ln M}] $.
Properties
NumCosmo.ClusterAbundance:mean-bias
The mean halo bias function used to compute the bias-weighted cluster abundance. This is used in clustering analyses to relate the spatial distribution of clusters to the underlying matter distribution.
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.