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Python SparseGraph.degreeDistribution方法代码示例

本文整理汇总了Python中apgl.graph.SparseGraph.SparseGraph.degreeDistribution方法的典型用法代码示例。如果您正苦于以下问题:Python SparseGraph.degreeDistribution方法的具体用法?Python SparseGraph.degreeDistribution怎么用?Python SparseGraph.degreeDistribution使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在apgl.graph.SparseGraph.SparseGraph的用法示例。


在下文中一共展示了SparseGraph.degreeDistribution方法的3个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: testDegreeDistribution

# 需要导入模块: from apgl.graph.SparseGraph import SparseGraph [as 别名]
# 或者: from apgl.graph.SparseGraph.SparseGraph import degreeDistribution [as 别名]
    def testDegreeDistribution(self):
        #We want to see how the degree distribution changes with kronecker powers


        numVertices = 3
        numFeatures = 0

        vList = VertexList(numVertices, numFeatures)
        initialGraph = SparseGraph(vList)
        initialGraph.addEdge(0, 1)
        initialGraph.addEdge(1, 2)

        for i in range(numVertices):
            initialGraph.addEdge(i, i)

        logging.debug((initialGraph.outDegreeSequence()))
        logging.debug((initialGraph.degreeDistribution()))

        k = 2
        generator = StochasticKroneckerGenerator(initialGraph, k)
        graph = generator.generateGraph()

        logging.debug((graph.outDegreeSequence()))
        logging.debug((graph.degreeDistribution()))

        k = 3
        generator = StochasticKroneckerGenerator(initialGraph, k)
        graph = generator.generateGraph()

        logging.debug((graph.degreeDistribution()))
开发者ID:charanpald,项目名称:APGL,代码行数:32,代码来源:StochasticKroneckerGeneratorTest.py

示例2: testGraphDisplay

# 需要导入模块: from apgl.graph.SparseGraph import SparseGraph [as 别名]
# 或者: from apgl.graph.SparseGraph.SparseGraph import degreeDistribution [as 别名]
    def testGraphDisplay(self):
        try:
            import networkx
            import matplotlib
        except ImportError as error:
            logging.debug(error)
            return 

        #Show
        numFeatures = 1
        numVertices = 20

        vList = VertexList(numVertices, numFeatures)
        graph = SparseGraph(vList)

        ell = 2
        m = 2
        generator = BarabasiAlbertGenerator(ell, m)

        graph = generator.generate(graph)

        logging.debug((graph.degreeDistribution()))

        nxGraph = graph.toNetworkXGraph()
        nodePositions = networkx.spring_layout(nxGraph)
        nodesAndEdges = networkx.draw_networkx(nxGraph, pos=nodePositions)
开发者ID:awj223,项目名称:Insight-Data-Engineering-Code-Challenge,代码行数:28,代码来源:BarabasiAlbertGeneratorTest.py

示例3: testDegreeDistribution

# 需要导入模块: from apgl.graph.SparseGraph import SparseGraph [as 别名]
# 或者: from apgl.graph.SparseGraph.SparseGraph import degreeDistribution [as 别名]
    def testDegreeDistribution(self):
        numFeatures = 0
        numVertices = 100

        vList = VertexList(numVertices, numFeatures)
        graph = SparseGraph(vList)

        alpha = 10.0
        p = 0.01
        dim = 2
        generator = GeometricRandomGenerator(graph)
        graph = generator.generateGraph(alpha, p, dim)

        logging.debug((graph.degreeDistribution()))
开发者ID:malcolmreynolds,项目名称:APGL,代码行数:16,代码来源:GeometricRandomGeneratorTest.py


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