class_docstr: Class for product of Riemannian metrics.
class_docstr_tok: ["Class","for","product","of","Riemannian","metrics","."]
docstr: Compute the matrix of the inner-product.
  
  Matrix of the inner-product defined by the Riemmanian metric
  at point base_point of the manifold.
  
  Parameters
  ----------
  base_point : array-like, shape=[..., self.shape]
      Point on the manifold at which to compute the inner-product matrix.
      Optional, default: None.
  
  Returns
  -------
  matrix : array-like, shape as described below
      Matrix of the inner-product at the base point.
      The matrix is in block diagonal form with a block for each factor.
      Each block is the same size as the metric_matrix for that factor.
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code: def metric_matrix(self, base_point=None):
      """Compute the matrix of the inner-product.
  
      Matrix of the inner-product defined by the Riemmanian metric
      at point base_point of the manifold.
  
      Parameters
      ----------
      base_point : array-like, shape=[..., self.shape]
          Point on the manifold at which to compute the inner-product matrix.
          Optional, default: None.
  
      Returns
      -------
      matrix : array-like, shape as described below
          Matrix of the inner-product at the base point.
          The matrix is in block diagonal form with a block for each factor.
          Each block is the same size as the metric_matrix for that factor.
      """
      factor_matrices = self._iterate_over_factors(
          "metric_matrix", {"base_point": base_point}
      )
      return _block_diagonal(factor_matrices)
  
imports: import math
  import geomstats.backend
  import geomstats.errors
  from geomstats.geometry.complex_manifold import ComplexManifold
  from geomstats.geometry.complex_riemannian_metric import ComplexRiemannianMetric
  from geomstats.geometry.manifold import Manifold
  from geomstats.geometry.riemannian_metric import RiemannianMetric
  from geomstats.vectorization import get_batch_shape
label_desc: Use image node_id 4 for calling the ProductRiemannianMetric obj's underlying member method code with example usage: obj.metric_matrix(base_point) and returns: _block_diagonal