class_docstr: Class for the pseudo-Riemannian Minkowski metric.
  
  The metric is flat: the inner product is independent of the base point.
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docstr: Compute the inner product matrix, independent of the base point.
  
  Parameters
  ----------
  base_point : array-like, shape=[..., dim]
      Base point.
  
  Returns
  -------
  inner_prod_mat : array-like, shape=[..., dim, dim]
      Inner-product matrix.
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code: def metric_matrix(self, base_point=None):
      """Compute the inner product matrix, independent of the base point.
  
      Parameters
      ----------
      base_point : array-like, shape=[..., dim]
          Base point.
  
      Returns
      -------
      inner_prod_mat : array-like, shape=[..., dim, dim]
          Inner-product matrix.
      """
      q, p = self.signature
      diagonal = gs.array([-1.0] * p + [1.0] * q)
      mat = from_vector_to_diagonal_matrix(diagonal)
      if base_point is not None and base_point.ndim > 1:
          mat = gs.broadcast_to(mat, base_point.shape + (p + q,))
      return mat
  
file_path: geomstats/geomstats/geometry/minkowski.py
imports: import math
  import geomstats.backend
  from geomstats.algebra_utils import from_vector_to_diagonal_matrix
  from geomstats.geometry.euclidean import Euclidean
  from geomstats.geometry.riemannian_metric import RiemannianMetric
  from geomstats.vectorization import repeat_out
label_desc: Use image node_id 2 for calling the MinkowskiMetric obj's underlying member method code with example usage: obj.metric_matrix(base_point) and returns: mat