parameters: (matrix)
return_statement: return numpy.linalg.inv(matrix)
docstring: Return inverse of square transformation matrix.
  
      >>> M0 = random_rotation_matrix()
      >>> M1 = inverse_matrix(M0.T)
      >>> numpy.allclose(M1, numpy.linalg.inv(M0.T))
      True
      >>> for size in range(1, 7):
      ...     M0 = numpy.random.rand(size, size)
      ...     M1 = inverse_matrix(M0)
      ...     if not numpy.allclose(M1, numpy.linalg.inv(M0)): print size
docstring_summary: Return inverse of square transformation matrix.
docstring_tokens: Return inverse of square transformation matrix .
function: def inverse_matrix(matrix):
      """Return inverse of square transformation matrix.
  
      >>> M0 = random_rotation_matrix()
      >>> M1 = inverse_matrix(M0.T)
      >>> numpy.allclose(M1, numpy.linalg.inv(M0.T))
      True
      >>> for size in range(1, 7):
      ...     M0 = numpy.random.rand(size, size)
      ...     M1 = inverse_matrix(M0)
      ...     if not numpy.allclose(M1, numpy.linalg.inv(M0)): print size
  
      """
      return numpy.linalg.inv(matrix)
function_tokens: def inverse_matrix ( matrix ) : return numpy . linalg . inv ( matrix )