Source code for littleballoffur.exploration_sampling.breadthfirstsearchsampler

import random
import networkx as nx
import networkit as nk
from typing import Union
from queue import Queue
from littleballoffur.sampler import Sampler


NKGraph = type(nk.graph.Graph())
NXGraph = nx.classes.graph.Graph


[docs]class BreadthFirstSearchSampler(Sampler): r"""An implementation of node sampling by breadth first search. The starting node is selected randomly and neighbors are added to the queue by shuffling them randomly. Args: number_of_nodes (int): Number of nodes. Default is 100. seed (int): Random seed. Default is 42. """ def __init__(self, number_of_nodes: int = 100, seed: int = 42): self.number_of_nodes = number_of_nodes self.seed = seed self._set_seed() def _create_seed_set(self, graph, start_node): """ Creating seed sets of nodes and edges. """ self._queue = Queue() if start_node is not None: if start_node >= 0 and start_node < self.backend.get_number_of_nodes(graph): self._queue.put(start_node) else: raise ValueError("Starting node index is out of range.") else: start_node = random.choice(range(self.backend.get_number_of_nodes(graph))) self._queue.put(start_node) self._nodes = set([start_node]) self._edges = set()
[docs] def sample( self, graph: Union[NXGraph, NKGraph], start_node: int = None ) -> Union[NXGraph, NKGraph]: """ Sampling a graph with randomized breadth first search. Arg types: * **graph** *(NetworkX or NetworKit graph)* - The graph to be sampled from. * **start_node** *(int, optional)* - The start node. Return types: * **new_graph** *(NetworkX or NetworKit graph)* - The graph of sampled nodes. """ self._deploy_backend(graph) self._check_number_of_nodes(graph) self._create_seed_set(graph, start_node) while len(self._nodes) < self.number_of_nodes: source = self._queue.get() neighbors = self.backend.get_neighbors(graph, source) random.shuffle(neighbors) for neighbor in neighbors: if neighbor not in self._nodes: self._nodes.add(neighbor) self._edges.add((source, neighbor)) self._queue.put(neighbor) if len(self._nodes) >= self.number_of_nodes: break if len(self._edges) > 0: new_graph = self.backend.graph_from_edgelist(self._edges) new_graph = self.backend.get_subgraph(new_graph, self._nodes) else: new_graph = self.backend.get_subgraph(graph, self._nodes) return new_graph