code: def get_normalised_laplacian(A):
      """Returns the (Symmetric) Normalised Graph Laplacian from an adjacency matrix A."""
      assert is_valid_adj_mat(A)
      with np.errstate(divide="ignore"):
          D_sqrt_inv = 1.0 / np.sqrt(A.sum(axis=0))
          D_sqrt_inv[D_sqrt_inv == np.inf] = 0
      L = (
          np.eye(A.shape[0])
          - (A * D_sqrt_inv) * D_sqrt_inv[:, np.newaxis]
      )
      return L
  
file_path: dragonfly/dragonfly/utils/graph_utils.py
imports: from copy import deepcopy
  import numpy
  from scipy.linalg import eigh
  from .general_utils import get_nonzero_indices_in_vector
label_desc: Use image node_id 4 for calling a global function with example usage: get_normalised_laplacian(A) and returns: L