class_docstr: Estimation of covariance matrix.
  
  Perform a simple covariance matrix estimation for each given input.
  
  Parameters
  ----------
  estimator : string, default='scm'
      Covariance matrix estimator, see
      :func:`pyriemann.utils.covariance.covariances`.
  **kwds : dict
      Any further parameters are passed directly to the covariance estimator.
  
  See Also
  --------
  ERPCovariances
  XdawnCovariances
  CospCovariances
  HankelCovariances
docstr: Init.
docstr_tok: ["Init","."]
code: def __init__(self, estimator="scm", **kwds):
      """Init."""
      self.estimator = estimator
      self.kwds = kwds
  
imports: import numpy
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.covariance import shrunk_covariance
  from sklearn.metrics.pairwise import pairwise_kernels
  from .spatialfilters import Xdawn
  from .utils.covariance import covariances, covariances_EP, cospectrum, coherence, block_covariances
label_desc: Use image node_id 1 to create a new Covariances object from inherited base classes: BaseEstimator, TransformerMixin with example: obj = Covariances(estimator)