示例#1
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    def setUp(self):
        super(TestBokehGraphPlot, self).setUp()

        N = 8
        self.nodes = circular_layout(np.arange(N, dtype=np.int32))
        self.source = np.arange(N, dtype=np.int32)
        self.target = np.zeros(N, dtype=np.int32)
        self.weights = np.random.rand(N)
        self.graph = Graph(((self.source, self.target),))
        self.node_info = Dataset(['Output']+['Input']*(N-1), vdims=['Label'])
        self.node_info2 = Dataset(self.weights, vdims='Weight')
        self.graph2 = Graph(((self.source, self.target), self.node_info))
        self.graph3 = Graph(((self.source, self.target), self.node_info2))
        self.graph4 = Graph(((self.source, self.target, self.weights),), vdims='Weight')
示例#2
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    def setUp(self):
        super(TestMplGraphPlot, self).setUp()

        N = 8
        self.nodes = circular_layout(np.arange(N, dtype=np.int32))
        self.source = np.arange(N, dtype=np.int32)
        self.target = np.zeros(N, dtype=np.int32)
        self.weights = np.random.rand(N)
        self.graph = Graph(((self.source, self.target),))
        self.node_info = Dataset(['Output']+['Input']*(N-1), vdims=['Label'])
        self.node_info2 = Dataset(self.weights, vdims='Weight')
        self.graph2 = Graph(((self.source, self.target), self.node_info))
        self.graph3 = Graph(((self.source, self.target), self.node_info2))
        self.graph4 = Graph(((self.source, self.target, self.weights),), vdims='Weight')
示例#3
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    def setUp(self):
        if not mpl_renderer:
            raise SkipTest('Matplotlib tests require matplotlib to be available')
        self.previous_backend = Store.current_backend
        Store.current_backend = 'matplotlib'
        self.default_comm = mpl_renderer.comms['default']
        mpl_renderer.comms['default'] = (comms.Comm, '')

        N = 8
        self.nodes = circular_layout(np.arange(N))
        self.source = np.arange(N)
        self.target = np.zeros(N)
        self.graph = Graph(((self.source, self.target),))
        self.node_info = Dataset(['Output']+['Input']*(N-1), vdims=['Label'])
        self.graph2 = Graph(((self.source, self.target), self.node_info))
示例#4
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    def setUp(self):
        if not bokeh_renderer:
            raise SkipTest("Bokeh required to test plot instantiation")
        elif bokeh_version < str('0.12.9'):
            raise SkipTest("Bokeh >= 0.12.9 required to test graphs")
        self.previous_backend = Store.current_backend
        Store.current_backend = 'bokeh'
        self.default_comm = bokeh_renderer.comms['default']

        N = 8
        self.nodes = circular_layout(np.arange(N))
        self.source = np.arange(N)
        self.target = np.zeros(N)
        self.graph = Graph(((self.source, self.target),))
        self.node_info = Dataset(['Output']+['Input']*(N-1), vdims=['Label'])
        self.graph2 = Graph(((self.source, self.target), self.node_info))
示例#5
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    def setUp(self):
        if not mpl_renderer:
            raise SkipTest(
                'Matplotlib tests require matplotlib to be available')
        self.previous_backend = Store.current_backend
        Store.current_backend = 'matplotlib'
        self.default_comm = mpl_renderer.comms['default']
        mpl_renderer.comms['default'] = (comms.Comm, '')

        N = 8
        self.nodes = circular_layout(np.arange(N))
        self.source = np.arange(N)
        self.target = np.zeros(N)
        self.graph = Graph(((self.source, self.target), ))
        self.node_info = Dataset(['Output'] + ['Input'] * (N - 1),
                                 vdims=['Label'])
        self.graph2 = Graph(((self.source, self.target), self.node_info))
示例#6
0
    def setUp(self):
        if not bokeh_renderer:
            raise SkipTest("Bokeh required to test plot instantiation")
        self.previous_backend = Store.current_backend
        Store.current_backend = 'bokeh'
        self.default_comm = bokeh_renderer.comms['default']

        N = 8
        self.nodes = circular_layout(np.arange(N, dtype=np.int32))
        self.source = np.arange(N, dtype=np.int32)
        self.target = np.zeros(N, dtype=np.int32)
        self.weights = np.random.rand(N)
        self.graph = Graph(((self.source, self.target), ))
        self.node_info = Dataset(['Output'] + ['Input'] * (N - 1),
                                 vdims=['Label'])
        self.node_info2 = Dataset(self.weights, vdims='Weight')
        self.graph2 = Graph(((self.source, self.target), self.node_info))
        self.graph3 = Graph(((self.source, self.target), self.node_info2))
        self.graph4 = Graph(((self.source, self.target, self.weights), ),
                            vdims='Weight')