class_docstr: Manifold of lower triangular matrices with >0 diagonal.
  
  This manifold is also called the cholesky space.
  
  Parameters
  ----------
  n : int
      Integer representing the shape of the matrices: n x n.
  
  References
  ----------
  .. [TP2019] Z Lin. "Riemannian Geometry of Symmetric
      Positive Definite Matrices Via Cholesky Decomposition"
      SIAM journal on Matrix Analysis and Applications , 2019.
      https://arxiv.org/abs/1908.09326
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docstr: Sample in PLT.
  
  Parameters
  ----------
  n_samples : int
      Number of samples.
      Optional, default: 1.
  bound : float
      Side of hypercube support of the uniform distribution.
      Optional, default: 1.0
  
  Returns
  -------
  point : array-like, shape=[..., *point_shape]
     Sample.
docstr_tok: ["Sample","in","PLT",".","Parameters","--","--","--","--","--","n_samples",":","int","Number","of","samples",".","Optional",",","default",":","1.","bound",":","float","Side","of","hypercube","support","of","the","uniform","distribution",".","Optional",",","default",":","1.0","Returns","--","--","--","-","point",":","array-like",",","shape=","[","...",",","*","point_shape","]","Sample","."]
code: def random_point(self, n_samples=1, bound=1.0):
      """Sample in PLT.
  
      Parameters
      ----------
      n_samples : int
          Number of samples.
          Optional, default: 1.
      bound : float
          Side of hypercube support of the uniform distribution.
          Optional, default: 1.0
  
      Returns
      -------
      point : array-like, shape=[..., *point_shape]
         Sample.
      """
      batch_shape = (n_samples,) if n_samples > 1 else ()
      shape = batch_shape + (self.dim - self.n,)
  
      lower_part = bound * (gs.random.rand(*shape) - 0.5) * 2
  
      diag_shape = batch_shape + (self.n,)
      diagonal = bound * gs.random.rand(*diag_shape) + gs.atol
  
      return gs.mat_from_diag_triu_tril(
          diagonal, gs.array([0.0]), lower_part
      )
  
imports: import geomstats.backend
  from geomstats.geometry.base import DiffeomorphicManifold, VectorSpaceOpenSet
  from geomstats.geometry.diffeo import Diffeo
  from geomstats.geometry.invariant_metric import _InvariantMetricMatrix
  from geomstats.geometry.lie_group import MatrixLieGroup
  from geomstats.geometry.lower_triangular_matrices import LowerTriangularMatrices
  from geomstats.geometry.matrices import Matrices
  from geomstats.geometry.open_hemisphere import OpenHemisphere, OpenHemispheresProduct
  from geomstats.geometry.pullback_metric import PullbackDiffeoMetric
  from geomstats.geometry.riemannian_metric import RiemannianMetric
label_desc: Use image node_id 3 for calling the PositiveLowerTriangularMatrices obj's underlying member method code with example usage: obj.random_point(n_samples, bound) and returns: gs