tjpcov.covariance_cluster_counts_ssc#

Module Contents#

Classes#

ClusterCountsSSC

Implementation of the SSC cluster covariance term.
class tjpcov.covariance_cluster_counts_ssc.ClusterCountsSSC(config)[source]#

Bases: tjpcov.covariance_cluster_counts.CovarianceClusterCounts

Implementation of the SSC cluster covariance term.

Calculates the sample variance contribution to the autocorrelation of cluster counts (NxN) following N. Ferreira 2019.

Class to calculate the SSC covariance of cluster counts

Parameters:

config (dict or str) – If dict, it returns the configuration dictionary directly. If string, it asumes a YAML file and parses it.

cov_type = 'SSC'[source]#
_get_covariance_block_for_sacc(tracer_comb1, tracer_comb2, **kwargs)[source]#

Compute a single covariance entry ‘clusters_redshift_richness’

Parameters:

  • tracer_comb1 (tuple of str) – e.g. (‘survey’, ‘bin_z_0’, ‘bin_richness_1’)

  • tracer_comb2 (tuple of str) – e.g. (‘survey’, ‘bin_z_0’, ‘bin_richness_0’)

Returns:

Covariance for a single block

Return type:

float

_get_covariance_cluster_counts(tracer_comb1, tracer_comb2)[source]#

Compute a single covariance entry ‘clusters_redshift_richness’

Parameters:

  • tracer_comb1 (tuple of str) – e.g. (‘survey’, ‘bin_z_0’, ‘bin_richness_1’)

  • tracer_comb2 (tuple of str) – e.g. (‘survey’, ‘bin_z_0’, ‘bin_richness_0’)

Returns:

Covariance for a single block

Return type:

array_like

get_covariance_block(tracer_comb1, tracer_comb2, **kwargs)[source]#

Compute a single covariance entry ‘clusters_redshift_richness’

Parameters:

  • tracer_comb1 (tuple of str) – e.g. (‘clusters_0_0’,)

  • tracer_comb2 (tuple of str) – e.g. (‘clusters_0_1’,)

Returns:

Covariance for a single block

Return type:

array_like