class_docstr: Class for the manifold of Hermitian positive definite (HPD) matrices.
  
  Parameters
  ----------
  n : int
      Integer representing the shape of the matrices: n x n.
docstr: Sample in HPD(n) from the log-uniform distribution.
  
  Parameters
  ----------
  n_samples : int
      Number of samples.
      Optional, default: 1.
  bound : float
      Bound of the interval in which to sample in the tangent space.
      Optional, default: 1.
  
  Returns
  -------
  samples : array-like, shape=[..., n, n]
      Points sampled in HPD(n).
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code: def random_point(self, n_samples=1, bound=0.1):
      """Sample in HPD(n) from the log-uniform distribution.
  
      Parameters
      ----------
      n_samples : int
          Number of samples.
          Optional, default: 1.
      bound : float
          Bound of the interval in which to sample in the tangent space.
          Optional, default: 1.
  
      Returns
      -------
      samples : array-like, shape=[..., n, n]
          Points sampled in HPD(n).
      """
      n = self.n
      size = (n_samples, n, n) if n_samples != 1 else (n, n)
      eye = gs.eye(n, dtype=gs.get_default_cdtype())
      samples = gs.stack([eye for i_sample in range(n_samples)], axis=0)
      samples = gs.reshape(samples, size)
      samples += bound * gs.random.rand(
          *size, dtype=gs.get_default_cdtype()
      )
      samples = self.projection(samples)
      return samples
  
imports: import math
  import geomstats.backend
  from geomstats.geometry.base import ComplexVectorSpaceOpenSet
  from geomstats.geometry.complex_matrices import ComplexMatrices, ComplexMatricesMetric
  from geomstats.geometry.complex_riemannian_metric import ComplexRiemannianMetric
  from geomstats.geometry.general_linear import GeneralLinear
  from geomstats.geometry.hermitian_matrices import HermitianMatrices, expmh, powermh
  from geomstats.geometry.matrices import Matrices
  from geomstats.geometry.pullback_metric import PullbackDiffeoMetric
  from geomstats.geometry.spd_matrices import SymMatrixLog, logmh
  from geomstats.integrator import integrate
  from geomstats.vectorization import repeat_out
label_desc: Use image node_id 5 for calling the HPDMatrices obj's underlying member method code with example usage: obj.random_point(n_samples, bound) and returns: samples