Source code for graphscope.analytical.app.lpa

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
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# Copyright 2020 Alibaba Group Holding Limited. All Rights Reserved.
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# 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
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#     http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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from graphscope.framework.app import AppAssets
from graphscope.framework.app import not_compatible_for
from graphscope.framework.app import project_to_simple

__all__ = ["lpa", "cdlp", "lpa_u2i"]


[docs]@project_to_simple @not_compatible_for("arrow_property", "dynamic_property") def lpa(graph, max_round=10): """Evaluate Community Detection with Label Propagation. Args: graph (:class:`graphscope.Graph`): A simple graph. max_round (int, optional): Maximum rounds. Defaults to 10. Returns: :class:`graphscope.framework.context.VertexDataContextDAGNode`: A context with each vertex assigned with a community ID, will be 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.lpa(pg, max_round=10) >>> sess.close() """ max_round = int(max_round) return AppAssets(algo="cdlp", context="vertex_data")(graph, max_round)
@not_compatible_for( "dynamic_property", "arrow_projected", "dynamic_projected", "arrow_flattened" ) def lpa_u2i(graph, max_round=10): """Evaluate (multi-) label propagation on a property graph. Args: graph (:class:`graphscope.Graph`): A property graph. max_round (int, optional): Maximum number of rounds. Defaults to 10. Returns: :class:`graphscope.framework.context.LabeledVertexPropertyContextDAGNode`: A context with each vertex, following an array of propagated labels, evaluated in eager mode. Examples: .. code:: python import graphscope as gs g = gs.g() # Load some data r = gs.lpa(g) s.close() """ max_round = int(max_round) return AppAssets(algo="lpau2i", context="labeled_vertex_property")(graph, max_round) cdlp = lpa