Source code for graphscope.analytical.app.pagerank

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright 2020 Alibaba Group Holding Limited. All Rights Reserved.
#
# 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.
#


from graphscope.framework.app import AppAssets
from graphscope.framework.app import not_compatible_for
from graphscope.framework.app import project_to_simple

__all__ = ["pagerank", "pagerank_nx"]


[docs]@project_to_simple @not_compatible_for("arrow_property", "dynamic_property") def pagerank(graph, delta=0.85, max_round=10): """Evalute PageRank on a graph. Args: graph (:class:`graphscope.Graph`): A simple graph. delta (float, optional): Dumping factor. Defaults to 0.85. max_round (int, optional): Maximum number of rounds. Defaults to 10. Returns: :class:`graphscope.framework.context.VertexDataContextDAGNode`: A context with each vertex assigned with the pagerank value, evaluated in eager mode. Examples: .. code:: python >>> import graphscope >>> from graphscope.dataset import load_p2p_network >>> sess = graphscope.session(cluster_type="hosts", mode="eager") >>> g = load_p2p_network(sess) >>> # project to a simple graph (if needed) >>> pg = g.project(vertices={"host": ["id"]}, edges={"connect": ["dist"]}) >>> c = graphscope.pagerank(pg, delta=0.85, max_round=10) >>> sess.close() """ delta = float(delta) max_round = int(max_round) return AppAssets(algo="pagerank", context="vertex_data")(graph, delta, max_round)
@project_to_simple @not_compatible_for("arrow_property", "dynamic_property") def pagerank_nx(graph, alpha=0.85, max_iter=100, tol=1e-06): """Evaluate pagerank on a graph using algorithm exactly follows the implemented in NetworkX library. Args: graph (:class:`graphscope.Graph`): A simple graph. alpha (float, optional): Dumping factor. Defaults to 0.85. max_iter (int, optional): Maximum number of iteration. Defaults to 100. tol (float, optional): Error tolerance used to check convergence in power method solver. Returns: :class:`graphscope.framework.context.VertexDataContextDAGNode`: A context with each vertex assigned with the pagerank value, evaluated in eager mode. Examples: .. code:: python >>> import graphscope >>> from graphscope.dataset import load_p2p_network >>> sess = graphscope.session(cluster_type="hosts", mode="eager") >>> g = load_p2p_network(sess) >>> # project to a simple graph (if needed) >>> pg = g.project(vertices={"host": ["id"]}, edges={"connect": ["dist"]}) >>> c = graphscope.pagerank_nx(pg, alpha=0.85, max_iter=10, tol=1e-06) >>> sess.close() """ alpha = float(alpha) max_iter = int(max_iter) return AppAssets(algo="pagerank_nx", context="vertex_data")( graph, alpha, max_iter, tol )