code: def _to_diagonally_dominant(mat):
      """Make matrix unweighted diagonally dominant using the Laplacian."""
      mat += np.diag(np.sum(mat != 0, axis=1) + 0.01)
      return mat
  
file_path: skggm/inverse_covariance/profiling/graphs.py
imports: import numpy
  import scipy
label_desc: Use image node_id 3 for calling a global function with example usage: _to_diagonally_dominant(mat) and returns: mat