class_docstr: Returns the adjacency matrix for a cluster network via .create().
  
  The graph can be made fully connected using chaining assumption when
  chain_blocks=True (default).
  
  Parameters
  -----------
  low : float (0, 1) (default=0.3)
      Lower bound for np.random.RandomState.uniform cluster values.
  
  high : float (0, 1) > low (default=0.7)
      Upper bound for np.random.RandomState.uniform vluster values.
  
  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: Build a new graph.
  
  Doc for ".create(n_features, alpha)"
  
  Parameters
  -----------
  n_features : int
  
  [alpha] : float (0,1)
      Unused.
  
  Each graph will have a minimum of
  
      (n_blocks * n_block_features**2 - n_blocks) / 2
  
  edges and exactly this amount if chain_blocks=False.
  
  Returns
  -----------
  (n_features, n_features) matrices: covariance, precision, adjacency
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code: def prototype_adjacency(self, n_block_features, alpha=None):
      """Build a new graph.
  
      Doc for ".create(n_features, alpha)"
  
      Parameters
      -----------
      n_features : int
  
      [alpha] : float (0,1)
          Unused.
  
      Each graph will have a minimum of
  
          (n_blocks * n_block_features**2 - n_blocks) / 2
  
      edges and exactly this amount if chain_blocks=False.
  
      Returns
      -----------
      (n_features, n_features) matrices: covariance, precision, adjacency
      """
      return -np.ones(
          (n_block_features, n_block_features)
      ) * 0.5 + self.prng.uniform(
          low=self.low,
          high=self.high,
          size=(n_block_features, n_block_features),
      )
  
imports: from __future__ import absolute_import
  import numpy
  from .graphs import Graph
label_desc: Use image node_id 2 for calling the ClusterGraph obj's underlying member method code with example usage: obj.prototype_adjacency(n_block_features, alpha) and returns: unknown