"""
The :mod:`sklearn.covariance` module includes methods and algorithms to
robustly estimate the covariance of features given a set of points. The
precision matrix defined as the inverse of the covariance is also estimated.
Covariance estimation is closely related to the theory of Gaussian Graphical
Models.
"""

from ._empirical_covariance import (empirical_covariance,
                                    EmpiricalCovariance,
                                    log_likelihood)
from ._shrunk_covariance import (shrunk_covariance, ShrunkCovariance,
                                  ledoit_wolf, ledoit_wolf_shrinkage,
                                  LedoitWolf, oas, OAS)
from ._robust_covariance import fast_mcd, MinCovDet
from ._graph_lasso import graphical_lasso, GraphicalLasso, GraphicalLassoCV
from ._elliptic_envelope import EllipticEnvelope


__all__ = ['EllipticEnvelope',
           'EmpiricalCovariance',
           'GraphicalLasso',
           'GraphicalLassoCV',
           'LedoitWolf',
           'MinCovDet',
           'OAS',
           'ShrunkCovariance',
           'empirical_covariance',
           'fast_mcd',
           'graphical_lasso',
           'ledoit_wolf',
           'ledoit_wolf_shrinkage',
           'log_likelihood',
           'oas',
           'shrunk_covariance']