class_docstr: Breadth First sampler that generates the composite of a number of sampled paths from a starting node.
  It can be used to extract a random sub-graph starting from a set of initial nodes.
class_docstr_tok: ["Breadth","First","sampler","that","generates","the","composite","of","a","number","of","sampled","paths","from","a","starting","node",".","It","can","be","used","to","extract","a","random","sub-graph","starting","from","a","set","of","initial","nodes","."]
code: def __init__(self, graph, graph_schema=None, seed=None):
      super().__init__(graph, graph_schema, seed)
      if not graph.is_directed():
          self._raise_error("Graph must be directed")
  
imports: import numpy
  import warnings
  from collections import defaultdict, deque
  from scipy import stats
  from scipy.special import softmax
  from ..core.schema import GraphSchema
  from ..core.graph import StellarGraph
  from ..core.utils import is_real_iterable
  from ..core.validation import require_integer_in_range, comma_sep
  from ..random import random_state
  from abc import ABC, abstractmethod
label_desc: Use image node_id 1 to create a new DirectedBreadthFirstNeighbours object from inherited base classes: GraphWalk with example: obj = DirectedBreadthFirstNeighbours(graph, graph_schema, seed)