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lowest_common_ancestors algorithm
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| # Copyright (c) 2024, NVIDIA CORPORATION. | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
|
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| import cupy as cp | ||
| import networkx as nx | ||
| import numpy as np | ||
| import pylibcugraph as plc | ||
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| from nx_cugraph.convert import _to_directed_graph | ||
| from nx_cugraph.utils import ( | ||
| _groupby, | ||
| index_dtype, | ||
| networkx_algorithm, | ||
| not_implemented_for, | ||
| ) | ||
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| __all__ = ["lowest_common_ancestor"] | ||
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| @not_implemented_for("undirected") | ||
| @networkx_algorithm(is_incomplete=True, version_added="24.12", _plc="bfs") | ||
| def lowest_common_ancestor(G, node1, node2, default=None): | ||
| """May not always raise NetworkXError for graphs that are not DAGs.""" | ||
| G = _to_directed_graph(G) | ||
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| # if not nxcg.is_directed_acyclic_graph(G): # TODO | ||
| # raise nx.NetworkXError("LCA only defined on directed acyclic graphs.") | ||
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| if G._N == 0: | ||
| raise nx.NetworkXPointlessConcept("LCA meaningless on null graphs.") | ||
| if node1 not in G: | ||
| raise nx.NodeNotFound( | ||
| f"Node(s) { {node1} } from pair {(node1, node2)} not in G." | ||
| ) | ||
| if node2 not in G: | ||
| raise nx.NodeNotFound( | ||
| f"Node(s) { {node2} } from pair {(node1, node2)} not in G." | ||
| ) | ||
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| # Ancestor BFS from node1 | ||
| node1_index = node1 if G.key_to_id is None else G.key_to_id[node1] | ||
| node2_index = node2 if G.key_to_id is None else G.key_to_id[node2] | ||
| if node1_index == node2_index: # Handle trivial case | ||
| return node1 | ||
| plc_graph = G._get_plc_graph(switch_indices=True) | ||
| distances1, predecessors1, node_ids1 = plc.bfs( | ||
| handle=plc.ResourceHandle(), | ||
| graph=plc_graph, | ||
| sources=cp.array([node1_index], index_dtype), | ||
| direction_optimizing=False, # True for undirected only | ||
| depth_limit=-1, | ||
| compute_predecessors=False, | ||
| do_expensive_check=False, | ||
| ) | ||
| mask1 = distances1 != np.iinfo(distances1.dtype).max | ||
| node_ids1 = node_ids1[mask1] | ||
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| # Ancestor BFS from node2 | ||
| distances2, predecessors2, node_ids2 = plc.bfs( | ||
| handle=plc.ResourceHandle(), | ||
| graph=plc_graph, | ||
| sources=cp.array([node2_index], index_dtype), | ||
| direction_optimizing=False, # True for undirected only | ||
| depth_limit=-1, | ||
| compute_predecessors=False, | ||
| do_expensive_check=False, | ||
| ) | ||
| mask2 = distances2 != np.iinfo(distances2.dtype).max | ||
| node_ids2 = node_ids2[mask2] | ||
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| # Find all common ancestors | ||
| common_ids = cp.intersect1d(node_ids1, node_ids2, assume_unique=True) | ||
| if common_ids.size == 0: | ||
| return default | ||
| if common_ids.size == 1: | ||
| # Only one; it must be the lowest common ancestor | ||
| node_index = common_ids[0].tolist() | ||
| return node_index if G.key_to_id is None else G.id_to_key[node_index] | ||
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| # Find nodes from `common_ids` that have no predecessors from `common_ids`. | ||
| # TODO: create utility functions for getting neighbors, predecessors, | ||
| # and successors of nodes, which may simplify this code. | ||
| mask = cp.isin(G.src_indices, common_ids) & (G.src_indices != G.dst_indices) | ||
| groups = _groupby(G.src_indices[mask], G.dst_indices[mask]) | ||
| # Walk along successors until we reach a lowest common ancestor | ||
| stack = sorted(groups, reverse=True) # Sort for consistency | ||
| seen = set() | ||
| while stack: | ||
| node_index = stack.pop() | ||
| if node_index in seen: | ||
| continue | ||
| seen.add(node_index) | ||
| successors = groups[node_index] | ||
| lower_ancestors = successors[cp.isin(successors, common_ids)] | ||
| if lower_ancestors.size == 0: | ||
| return node_index if G.key_to_id is None else G.id_to_key[node_index] | ||
| stack.extend(sorted(lower_ancestors.tolist(), reverse=True)) | ||
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| raise nx.NetworkXError("LCA only defined on directed acyclic graphs.") |