code: def adjacency_matrix_to_graph(adjacency_matrix, labels=None):
      """
      Convert a given graph adjacency matrix to DOT format.
  
      :param adjacency_matrix: A numpy array representing the graph adjacency matrix.
      :param labels: List of labels.
      :returns: Graph in DOT format.
      """
      # Only consider edges have absolute edge weight > 0.01
      idx = np.abs(adjacency_matrix) > 0.01
      dirs = np.where(idx)
      import graphviz
  
      d = graphviz.Digraph(engine="dot")
      names = (
          labels
          if labels
          else [f"x{i}" for i in range(len(adjacency_matrix))]
      )
      for name in names:
          d.node(name)
      for to, from_, coef in zip(
          dirs[0], dirs[1], adjacency_matrix[idx]
      ):
          d.edge(names[from_], names[to], label=str(coef))
      return d
  
imports: import re
  from queue import LifoQueue
  import networkx
  import numpy
  from networkx.algorithms.dag import is_directed_acyclic_graph
  from networkx.algorithms.shortest_paths.generic import shortest_path
  from dowhy.utils.ordered_set import OrderedSet
label_desc: Use image node_id 2 for calling a global function with example usage: adjacency_matrix_to_graph(adjacency_matrix, labels) and returns: d