Likelihood

class asteca.Likelihood(my_cluster: Cluster, lkl_name: str = 'plr', bin_method: str = 'knuth')

Bases: object

Define a Likelihood object.

This object is used to assess how similar your observed cluster is, stored in a asteca.Cluster object, compared to a given synthetic cluster, generated by the asteca.Synthetic.generate() method.

Parameters:

• my_cluster (Cluster) – asteca.Cluster object with the loaded data for the observed cluster

• lkl_name (str) – Currently only the Poisson likelihood ratio (plr) defined in Tremmel et al. (2013) is accepted, defaults to plr

• bin_method (str) – Bin method used to split the color-magnitude diagram into cells (Hess diagram); one of: knuth, blocks, scott, freedman or fixed. See Choosing Histogram Bins in astropy documentation for details on the knuth, blocks, scott, freedman methods. The method fixed uses (15, 10) bins in magnitude and color(s) respectively. Defaults to knuth

Raises:

ValueError – If any of the attributes is not recognized as a valid option

Methods Summary

get(synth_clust)

Evaluate the selected likelihood function.

Methods Documentation

get(synth_clust: ndarray) → float

Evaluate the selected likelihood function.

Parameters:

synth_clust (np.ndarray) – Array containing the synthetic cluster data. The shape of this array is assumed to be be: [magnitude, color1, (color2)], where magnitude and color are arrays with the synthetic magnitude and color photometric data (color2 is the optional second color defined) If the array contains any extra columns beyond these they will be ignored.

Raises:

ValueError – If the likelihood function is not recognized

Returns:

Likelihood value

Return type:

float