class_docstr: Class for generating a graph object from a dataset.
  
  Prepare Graph object from a dataset file.
  
  Parameters
  ----------
  graph_matrix_path : string
      Path to graph adjacency matrix.
  labels_path : string
      Path to labels of the nodes of the graph.
  
  Attributes
  ----------
  edges : dict
      Dictionary with node number as key
      and edge connected node numbers as values.
  n_nodes : int
      Number of nodes in the graph.
  labels : dict
      Dictionary with node number as key and the true label number as values.
class_docstr_tok: ["Class","for","generating","a","graph","object","from","a","dataset",".","Prepare","Graph","object","from","a","dataset","file",".","Parameters","--","--","--","--","--","graph_matrix_path",":","string","Path","to","graph","adjacency","matrix",".","labels_path",":","string","Path","to","labels","of","the","nodes","of","the","graph",".","Attributes","--","--","--","--","--","edges",":","dict","Dictionary","with","node","number","as","key","and","edge","connected","node","numbers","as","values",".","n_nodes",":","int","Number","of","nodes","in","the","graph",".","labels",":","dict","Dictionary","with","node","number","as","key","and","the","true","label","number","as","values","."]
docstr: Generate a single random walk.
docstr_tok: ["Generate","a","single","random","walk","."]
code: def _walk(self, index, walk_length):
      """Generate a single random walk."""
      count_index = index
      path = [index]
      for _ in range(walk_length):
          count_index = self.edges[count_index][
              random.randint(0, len(self.edges[count_index]) - 1)
          ]
          path.append(count_index)
      return gs.array(path, dtype=gs.int32)
  
file_path: geomstats/geomstats/datasets/prepare_graph_data.py
imports: import logging
  import random
  import geomstats.backend
  from geomstats.geometry.poincare_ball import PoincareBall
label_desc: Use image node_id 3 for calling the Graph obj's underlying member method code with example usage: obj._walk(index, walk_length) and returns: gs