class_docstr: Bures-Wasserstein metric for fixed rank PSD matrices.
class_docstr_tok: ["Bures-Wasserstein","metric","for","fixed","rank","PSD","matrices","."]
code: def __init__(self, space, total_space=None):
      if total_space is None:
          k = space.rank if hasattr(space, "rank") else space.n
          total_space = FullRankMatrices(space.n, k, equip=False)
          total_space.equip_with_metric(MatricesMetric)
  
      super().__init__(
          space=space, fiber_bundle=BuresWassersteinBundle(total_space)
      )
  
imports: import geomstats.backend
  from geomstats.geometry.fiber_bundle import FiberBundle
  from geomstats.geometry.full_rank_matrices import FullRankMatrices
  from geomstats.geometry.general_linear import GeneralLinear
  from geomstats.geometry.manifold import Manifold
  from geomstats.geometry.matrices import Matrices, MatricesMetric
  from geomstats.geometry.quotient_metric import QuotientMetric
  from geomstats.geometry.spd_matrices import SPDEuclideanMetric, SPDMatrices
  from geomstats.geometry.special_orthogonal import SpecialOrthogonal
  from geomstats.geometry.symmetric_matrices import SymmetricMatrices
label_desc: Use image node_id 1 to create a new PSDBuresWassersteinMetric object from inherited base classes: QuotientMetric with example: obj = PSDBuresWassersteinMetric(space, total_space)