class_docstr: Base class that returns the adjacency matrix for a network via
  the .create() method.
  
  Parameters
  -----------
  n_blocks : int (default=2)
      Number of blocks.  Returned matrix will be square with
      shape n_block_features * n_blocks.
  
  chain_blocks : bool (default=True)
      Apply random lattice structure to chain blocks together.
  
  seed : int
      Seed for np.random.RandomState seed. (default=1)
docstr: Override this method with a custom base graph.
docstr_tok: ["Override","this","method","with","a","custom","base","graph","."]
code: def prototype_adjacency(self, n_block_features, alpha):
      """Override this method with a custom base graph."""
      pass
  
file_path: skggm/inverse_covariance/profiling/graphs.py
imports: import numpy
  import scipy
label_desc: Use image node_id 4 for calling the Graph obj's underlying member method code with example usage: obj.prototype_adjacency(n_block_features, alpha) without return types