Source code for graphscope.analytical.app.eigenvector_centrality
#!/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.#fromgraphscope.framework.appimportAppAssetsfromgraphscope.framework.appimportnot_compatible_forfromgraphscope.framework.appimportproject_to_simple__all__=["eigenvector_centrality"]
[docs]@project_to_simple@not_compatible_for("arrow_property","dynamic_property")defeigenvector_centrality(graph,tolerance=1e-06,max_round=100,weight=None):"""Compute the eigenvector centrality for the `graph`. See more about eigenvector centrality here: https://networkx.org/documentation/networkx-1.10/reference/generated/networkx.algorithms.centrality.eigenvector_centrality.html Args: graph (:class:`graphscope.Graph`): A simple graph. tolerance (float, optional): Defaults to 1e-06. max_round (int, optional): Defaults to 100. weight (str, optional): The edge data key corresponding to the edge weight. Note that property under multiple labels should have the consistent index. Defaults to None. Returns: :class:`graphscope.framework.context.VertexDataContextDAGNode`: A context with each vertex assigned with a gv-centrality, 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.eigenvector_centrality(pg, tolerance=1e-06, max_round=10) >>> sess.close() """tolerance=float(tolerance)max_round=int(max_round)returnAppAssets(algo="eigenvector_centrality",context="vertex_data")(graph,tolerance,max_round)