code: def test_from_networkx_homogeneous_features(feature_type, dtype):
      features = [[0, 1, 2], [3, 4, 5]]
  
      def node(i, **kwargs):
          feat = {"f": features[i]} if feature_type == "nodes" else {}
          return i, feat
  
      a_nodes = [node(0), node(1)]
      if feature_type == "nodes":
          node_features = "f"
      elif feature_type == "dataframe no types":
          node_features = pd.DataFrame(features)
      elif feature_type == "dataframe types":
          node_features = {"a": pd.DataFrame(features)}
      elif feature_type == "iterable no types":
          node_features = enumerate(features)
      elif feature_type == "iterable types":
          node_features = {"a": enumerate(features)}
  
      expected_nodes = {"a": pd.DataFrame(features, dtype=dtype)}
  
      g = nx.MultiDiGraph()
      g.add_nodes_from(a_nodes)
      nodes, edges = from_networkx_for_testing(g, node_features, dtype)
      assert_dataframe_dict_equal(nodes, expected_nodes)
      assert edges == {}
  
imports: import networkx
  import numpy
  import pandas
  import pytest
  from stellargraph.core.convert import ColumnarConverter, convert_nodes, convert_edges, from_networkx
  from stellargraph.core.indexed_array import IndexedArray
label_desc: Use image node_id 24 for calling a global function with example usage: test_from_networkx_homogeneous_features(feature_type, dtype) and returns: i,  feat