How to use test_multi_graphs method in yandex-tank

Best Python code snippet using yandex-tank

test_weaire_thorpe.py

Source:test_weaire_thorpe.py

...22    #ax.scatter(*WT_g.vertices.positions.T, color = 'g')23    edge_labels = np.where(np.arange(WT_g.edges.indices.shape[0]) < g.edges.indices.shape[0], 0, 1)24    edge_arrows = np.where(np.arange(WT_g.edges.indices.shape[0]) < g.edges.indices.shape[0], 0, 1)25    plot_lattice(WT_g, edge_arrows = edge_arrows, ax = ax, edge_labels = edge_labels)26def test_multi_graphs():27    """The following graph has vertices with edges that link the same vertex together,28     this checks that clockwise edges about handles them correctly as part of the Weaire-Thorpe process"""29    g = Lattice(30        vertices = np.array([[0.5,0.7], [0.5,0.3]]),31        edge_indices = np.array([[0,1],[0,0],[0,1],[1,1]]),32        edge_crossing = np.array([[0,0],[1,0],[1,0],[1,0]]),33    )34    ordered_edge_indices = clockwise_edges_about(vertex_i = 0, g=g)35    solveable, edge_labels = edge_color(g, n_colors = 3, fixed = enumerate(ordered_edge_indices))36    WT_g = vertices_to_triangles(g, edge_labels)37    edge_labels = np.where(np.arange(WT_g.edges.indices.shape[0]) < g.edges.indices.shape[0], 0, 1)38    internal_edges = np.where(np.arange(WT_g.edges.indices.shape[0]) < g.edges.indices.shape[0], 0, 1)39    fig, axes = plt.subplots(ncols = 2)40    plot_lattice(g, edge_arrows = True, ax = axes[0])#, edge_labels = edge_labels)...

test_spark.py

Source:test_spark.py

...32        short_spark = ''.join(sparkline.get_sparkline('data', spark_len=4))33        assert (short_spark == expected_short)34        long_spark = ''.join(sparkline.get_sparkline('data'))35        assert (long_spark == expected_long)36    def test_multi_graphs(self):37        expected_continous = '__ââââââââââââââ'38        expected_spotty = '_ â â â â â â â '39        continous_vals = range(1, 17)40        sparkline = Sparkline(len(continous_vals))41        start = int(time.time()) - len(continous_vals)42        for val in continous_vals:43            sparkline.add(start + val, 'continous', val)44            if val % 2 == 1:45                sparkline.add(start + val, 'spotty', val)46        continous = ''.join(sparkline.get_sparkline('continous'))47        spotty = ''.join(sparkline.get_sparkline('spotty'))48        assert (continous == expected_continous)...

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