code: def test_walk_generation_many_root_nodes(self):
      g = create_test_graph()
      biasedrw = BiasedRandomWalk(g)
  
      nodes = ["0", 2]
      n = 1
      length = 1
      seed = None
      p = 1.0
      q = 0.3
  
      subgraphs = biasedrw.run(
          nodes=nodes, n=n, p=p, q=q, length=length, seed=seed
      )
      assert len(subgraphs) == n * len(nodes)
      for i, subgraph in enumerate(subgraphs):
          assert len(subgraph) == length  # should be 1
          assert subgraph[0] == nodes[i]  # should equal the root node
  
      length = 2
      subgraphs = biasedrw.run(
          nodes=nodes, n=n, p=p, q=q, length=length, seed=seed
      )
      assert len(subgraphs) == n * len(nodes)
      for subgraph in subgraphs:
          assert len(subgraph) <= length
  
      n = 2
      length = 2
      subgraphs = biasedrw.run(
          nodes=nodes, n=n, p=p, q=q, length=length, seed=seed
      )
      assert len(subgraphs) == n * len(nodes)
      for subgraph in subgraphs:
          assert len(subgraph) <= length
  
      length = 3
      subgraphs = biasedrw.run(
          nodes=nodes, n=n, p=p, q=q, length=length, seed=seed
      )
      assert len(subgraphs) == n * len(nodes)
      for subgraph in subgraphs:
          assert len(subgraph) <= length
  
      n = 5
      length = 10
      subgraphs = biasedrw.run(
          nodes=nodes, n=n, p=p, q=q, length=length, seed=seed
      )
      assert len(subgraphs) == n * len(nodes)
      for subgraph in subgraphs:
          assert len(subgraph) <= length
  
imports: import numpy
  import pandas
  import pytest
  import networkx
  from stellargraph.data.explorer import BiasedRandomWalk
  from stellargraph.core.graph import StellarGraph
  from ..test_utils.graphs import create_test_graph, example_graph_random
label_desc: Use image node_id 3 for calling the TestBiasedRandomWalk obj's underlying member method code with example usage: obj.test_walk_generation_many_root_nodes() without return types