class_docstr: Abstract class for Matrix Distribution.
class_docstr_tok: ["Abstract","class","for","Matrix","Distribution","."]
docstr: Internal sample method
  
  Returns dictionary mapping RandomSymbol to realization value.
code: def sample(self, size=(), library="scipy", seed=None):
      """
      Internal sample method
  
      Returns dictionary mapping RandomSymbol to realization value.
      """
  
      libraries = ["scipy", "numpy", "pymc3", "pymc"]
      if library not in libraries:
          raise NotImplementedError(
              "Sampling from %s is not supported yet." % str(library)
          )
      if not import_module(library):
          raise ValueError("Failed to import %s" % library)
  
      samps = _get_sample_class_matrixrv[library](self, size, seed)
  
      if samps is not None:
          return samps
      raise NotImplementedError(
          "Sampling for %s is not currently implemented from %s"
          % (self.__class__.__name__, library)
      )
  
imports: from math import prod
  from sympy.core.basic import Basic
  from sympy.core.numbers import pi
  from sympy.core.singleton import S
  from sympy.functions.elementary.exponential import exp
  from sympy.functions.special.gamma_functions import multigamma
  from sympy.core.sympify import sympify, _sympify
  from sympy.matrices import ImmutableMatrix, Inverse, Trace, Determinant, MatrixSymbol, MatrixBase, Transpose, MatrixSet, matrix2numpy
  from sympy.stats.rv import _value_check, RandomMatrixSymbol, NamedArgsMixin, PSpace, _symbol_converter, MatrixDomain, Distribution
  from sympy.external import import_module
label_desc: Use image node_id 4 for calling the MatrixDistribution obj's underlying member method code with example usage: obj.sample(size, library, seed) and returns: samps