code: def vectorspace_dimensionality(ary):
      """Computes the hyper-volume spanned by a vector set
  
      Parameters
      ----------
      ary : array-like, shape=[num_vectors, num_vectors]
          An orthogonal set of vectors (arranged as columns in a matrix)
  
      Returns
      ----------
      dimensions : int
          An integer indicating the "dimensionality" hyper-volume spanned by
          the vector set
  
      Examples
      -----------
      For usage examples, please see
      https://rasbt.github.io/mlxtend/user_guide/math/vectorspace_dimensionality/
  
      """
      # Note that since the vectors of
      # an orthonormal vectoset have unit length or are zero,
      # the sum of the individual
      # norms equals the dimensionality of that vector space
      return int(
          np.sum(
              np.linalg.norm(
                  vectorspace_orthonormalization(ary), axis=0
              )
          )
      )
  
label_desc: Use image node_id 2 for calling a global function with example usage: vectorspace_dimensionality(ary) and returns: int