class_docstr: This minibatch iterator iterates over nodes for supervised learning.
  
  G -- networkx graph
  id2idx -- dict mapping node ids to integer values indexing feature tensor
  placeholders -- standard tensorflow placeholders object for feeding
  label_map -- map from node ids to class values (integer or list)
  num_classes -- number of output classes
  batch_size -- size of the minibatches
  max_degree -- maximum size of the downsampled adjacency lists
class_docstr_tok: ["This","minibatch","iterator","iterates","over","nodes","for","supervised","learning",".","G","--","networkx","graph","id2idx","--","dict","mapping","node","ids","to","integer","values","indexing","feature","tensor","placeholders","--","standard","tensorflow","placeholders","object","for","feeding","label_map","--","map","from","node","ids","to","class","values","(","integer","or","list",")","num_classes","--","number","of","output","classes","batch_size","--","size","of","the","minibatches","max_degree","--","maximum","size","of","the","downsampled","adjacency","lists"]
code: def construct_test_adj(self):
      adj = len(self.id2idx) * np.ones(
          (len(self.id2idx) + 1, self.max_degree)
      )
      for nodeid in self.G.nodes():
          neighbors = np.array(
              [
                  self.id2idx[neighbor]
                  for neighbor in self.G.neighbors(nodeid)
              ]
          )
          if len(neighbors) == 0:
              continue
          if len(neighbors) > self.max_degree:
              neighbors = np.random.choice(
                  neighbors, self.max_degree, replace=False
              )
          elif len(neighbors) < self.max_degree:
              neighbors = np.random.choice(
                  neighbors, self.max_degree, replace=True
              )
          adj[self.id2idx[nodeid], :] = neighbors
      return adj
  
imports: from __future__ import division
  from __future__ import print_function
  import numpy
label_desc: Use image node_id 4 for calling the NodeMinibatchIterator obj's underlying member method code with example usage: obj.construct_test_adj() and returns: adj