class_docstr: Fisher Geodesic Discriminant analysis.
  
  Project data in Tangent space, apply a FLDA to reduce dimention, and
  project filtered data back in the manifold.
  For a complete description of the algorithm, see [1]_.
  
  Parameters
  ----------
  metric : string | dict, default='riemann'
      The type of metric used for reference matrix estimation (see
      `mean_covariance` for the list of supported metric) and for tangent
      space map (see `tangent_space` for the list of supported metric).
      The metric could be a dict with two keys, `mean` and `map` in
      order to pass different metrics for the reference matrix estimation
      and the tangent space mapping.
  tsupdate : bool, default=False
      Activate tangent space update for covariante shift correction between
      training and test, as described in [2]_. This is not compatible with
      online implementation. Performance are better when the number of
      matrices for prediction is higher.
  
  See Also
  --------
  FgMDM
  TangentSpace
  
  References
  ----------
  .. [1] `Riemannian geometry applied to BCI classification
      <https://hal.archives-ouvertes.fr/hal-00602700/>`_
      A. Barachant, S. Bonnet, M. Congedo and C. Jutten. 9th International
      Conference Latent Variable Analysis and Signal Separation
      (LVA/ICA 2010), LNCS vol. 6365, 2010, p. 629-636.
  .. [2] `Classification of covariance matrices using a Riemannian-based
      kernel for BCI applications
      <https://hal.archives-ouvertes.fr/hal-00820475/>`_
      A. Barachant, S. Bonnet, M. Congedo and C. Jutten. Neurocomputing,
      Elsevier, 2013, 112, pp.172-178.
docstr: Init.
docstr_tok: ["Init","."]
code: def __init__(self, metric="riemann", tsupdate=False):
      """Init."""
      self.metric = metric
      self.tsupdate = tsupdate
  
imports: import numpy
  from sklearn.base import BaseEstimator, TransformerMixin
  from .utils.utils import check_version
  from .utils.mean import mean_covariance
  from .utils.tangentspace import tangent_space, untangent_space
label_desc: Use image node_id 1 to create a new FGDA object from inherited base classes: BaseEstimator, TransformerMixin with example: obj = FGDA(metric, tsupdate)