sp_validation.cosmo_val.cosebis

COSEBIs diagnostic: complete orthogonal E/B integrals.

Mixin providing COSEBIs calculation and plotting for the CosmologyValidation class.

class CosebisMixin[source]

Bases: object

calculate_cosebis(version, min_sep_int=0.5, max_sep_int=500, nbins_int=1000, npatch=None, nmodes=10, cov_path=None, scale_cuts=None, evaluate_all_scale_cuts=False, min_sep=None, max_sep=None, nbins=None)[source]

Calculate COSEBIs from a finely-binned correlation function.

COSEBIs fundamentally require fine binning for accurate transformations. This function computes a single, finely-binned correlation function using integration binning parameters and can evaluate either a single scale cut (full range) or multiple scale cuts systematically.

Parameters:

  • version (str) – The catalog version to compute the COSEBIs for.

  • min_sep_int (float, optional) – Minimum separation for integration binning (fine binning for COSEBIs). Defaults to 0.5 arcmin.

  • max_sep_int (float, optional) – Maximum separation for integration binning (fine binning for COSEBIs). Defaults to 500 arcmin.

  • nbins_int (int, optional) – Number of bins for integration binning (fine binning for COSEBIs). Defaults to 1000.

  • npatch (int, optional) – Number of patches for the jackknife resampling. Defaults to self.npatch.

  • nmodes (int, optional) – Number of COSEBIs modes to compute. Defaults to 10.

  • cov_path (str, optional) – Path to theoretical covariance matrix. When provided, enables analytic covariance calculation.

  • scale_cuts (list of tuples, optional) – Explicit list of (min_theta, max_theta) scale cuts to evaluate. Overrides evaluate_all_scale_cuts when provided.

  • evaluate_all_scale_cuts (bool, optional) – If True, evaluates COSEBIs for all possible scale cut combinations using the reporting binning parameters. Ignored when scale_cuts is provided. Defaults to False.

  • min_sep (float, optional) – Minimum separation for reporting binning (only used when evaluate_all_scale_cuts=True). Defaults to self.treecorr_config[“min_sep”].

  • max_sep (float, optional) – Maximum separation for reporting binning (only used when evaluate_all_scale_cuts=True). Defaults to self.treecorr_config[“max_sep”].

  • nbins (int, optional) – Number of bins for reporting binning (only used when evaluate_all_scale_cuts=True). Defaults to self.treecorr_config[“nbins”].

Returns:

When a single scale cut: Dictionary containing COSEBIs results with E/B modes, covariances, and statistics. When multiple scale cuts: Dictionary with scale cut tuples as keys and results dictionaries as values.

Return type:

dict

plot_cosebis(version=None, output_dir=None, min_sep_int=0.5, max_sep_int=500, nbins_int=1000, npatch=None, nmodes=10, cov_path=None, scale_cuts=None, evaluate_all_scale_cuts=False, min_sep=None, max_sep=None, nbins=None, fiducial_scale_cut=None, results=None)[source]

Generate comprehensive COSEBIs analysis plots for a single version.

Creates two types of plots: 1. COSEBIs E/B mode correlation functions 2. COSEBIs covariance matrix

Parameters:

  • version (str, optional) – Version string to process. Defaults to first version in self.versions.

  • output_dir (str, optional) – Output directory for plots. Defaults to self.cc[‘paths’][‘output’].

  • min_sep_int (float, float, int) – Integration binning parameters for correlation function (default: 0.5, 500, 1000)

  • max_sep_int (float, float, int) – Integration binning parameters for correlation function (default: 0.5, 500, 1000)

  • nbins_int (float, float, int) – Integration binning parameters for correlation function (default: 0.5, 500, 1000)

  • npatch (int, optional) – Number of patches for jackknife covariance. Defaults to instance value.

  • nmodes (int) – Number of COSEBIs modes to compute (default: 10)

  • cov_path (str, optional) – Path to theoretical covariance matrix. When provided, analytic covariance is used.

  • scale_cuts (list of tuples, optional) – Explicit list of (min_theta, max_theta) scale cuts to evaluate. Overrides evaluate_all_scale_cuts when provided.

  • evaluate_all_scale_cuts (bool) – Whether to evaluate all scale cuts from reporting binning grid (default: False). Ignored when scale_cuts is provided.

  • min_sep (float, float, int, optional) – Reporting binning parameters. Only used when evaluate_all_scale_cuts=True.

  • max_sep (float, float, int, optional) – Reporting binning parameters. Only used when evaluate_all_scale_cuts=True.

  • nbins (float, float, int, optional) – Reporting binning parameters. Only used when evaluate_all_scale_cuts=True.

  • fiducial_scale_cut (tuple, optional) – (min_scale, max_scale) reference scale cut for plotting

  • results (dict, optional) – Precalculated results to avoid recomputation. If None (default), results will be calculated using calculate_cosebis.