Covariance

class gammapy.modeling.Covariance(parameters, data=None)

Bases: object

Parameter covariance class

Parameters

parametersParameters

Parameter list

datandarray

Covariance data array

Attributes Summary

correlation	Correlation matrix (numpy.ndarray).
data	Covariance data (ndarray)
scipy_mvn
shape	Covariance shape

Methods Summary

from_factor_matrix(parameters, matrix)	Set covariance from factor covariance matrix.
from_stack(covar_list)	Stack sub-covariance matrices from list
get_subcovariance(self, parameters)	Get sub-covariance matrix
plot_correlation(self[, ax])	Plot correlation matrix.
set_subcovariance(self, covar)	Set sub-covariance matrix

Attributes Documentation

correlation

Correlation matrix (numpy.ndarray).

Correlation \(C\) is related to covariance \(\Sigma\) via:

\[C_{ij} = \frac{ \Sigma_{ij} }{ \sqrt{\Sigma_{ii} \Sigma_{jj}} }\]

data

Covariance data (ndarray)

scipy_mvn

shape

Covariance shape

Methods Documentation

classmethod from_factor_matrix(parameters, matrix)

Set covariance from factor covariance matrix.

Used in the optimizer interface.

classmethod from_stack(covar_list)

Stack sub-covariance matrices from list

Parameters

covar_listlist of Covariance

List of sub-covariances

Returns

covarCovariance

Stacked covariance

get_subcovariance(self, parameters)

Get sub-covariance matrix

Parameters

parametersParameters

Sub list of parameters.

Returns

covariancendarray

Sub-covariance.

plot_correlation(self, ax=None, **kwargs)

Plot correlation matrix.

Parameters

axAxes, optional

Axis to plot on.

**kwargsdict

Keyword arguments passed to plot_heatmap

Returns

axAxes, optional

Axis

set_subcovariance(self, covar)

Set sub-covariance matrix

Parameters

parametersParameters

Sub list of parameters.