""" Unit tests of Graph Element. """ from unittest import SkipTest import numpy as np import pandas as pd from holoviews.core.data import Dataset from holoviews.element.chart import Points from holoviews.element.comparison import ComparisonTestCase from holoviews.element.graphs import Chord, Graph, Nodes, TriMesh from holoviews.element.sankey import Sankey from holoviews.element.util import circular_layout, connect_edges, connect_edges_pd class GraphTests(ComparisonTestCase): def setUp(self): N = 8 self.nodes = circular_layout(np.arange(N)) self.source = np.arange(N, dtype=np.int32) self.target = np.zeros(N, dtype=np.int32) self.edge_info = np.arange(N) self.graph = Graph(((self.source, self.target),)) def test_basic_constructor(self): graph = Graph(((self.source, self.target),)) nodes = Nodes(self.nodes) self.assertEqual(graph.nodes, nodes) def test_constructor_with_nodes(self): graph = Graph(((self.source, self.target), self.nodes)) nodes = Nodes(self.nodes) self.assertEqual(graph.nodes, nodes) def test_graph_edge_segments(self): segments = connect_edges(self.graph) paths = [] nodes = np.column_stack(self.nodes) for start, end in zip(nodes[self.source], nodes[self.target]): paths.append(np.array([start[:2], end[:2]])) self.assertEqual(segments, paths) def test_graph_node_info_no_index(self): node_info = Dataset(np.arange(8), vdims=['Label']) graph = Graph(((self.source, self.target), node_info)) self.assertEqual(graph.nodes.dimension_values(3), node_info.dimension_values(0)) def test_graph_node_info_no_index_mismatch(self): node_info = Dataset(np.arange(6), vdims=['Label']) with self.assertRaises(ValueError): Graph(((self.source, self.target), node_info)) def test_graph_node_info_merge_on_index(self): node_info = Dataset((np.arange(8), np.arange(1,9)), 'index', 'label') graph = Graph(((self.source, self.target), node_info)) self.assertEqual(graph.nodes.dimension_values(3), node_info.dimension_values(1)) def test_graph_node_info_merge_on_index_partial(self): node_info = Dataset((np.arange(5), np.arange(1,6)), 'index', 'label') graph = Graph(((self.source, self.target), node_info)) expected = np.array([1., 2., 3., 4., 5., np.nan, np.nan, np.nan]) self.assertEqual(graph.nodes.dimension_values(3), expected) def test_graph_edge_segments_pd(self): segments = connect_edges_pd(self.graph) paths = [] nodes = np.column_stack(self.nodes) for start, end in zip(nodes[self.source], nodes[self.target]): paths.append(np.array([start[:2], end[:2]])) self.assertEqual(segments, paths) def test_constructor_with_nodes_and_paths(self): paths = Graph(((self.source, self.target), self.nodes)).edgepaths graph = Graph(((self.source, self.target), self.nodes, paths.data)) self.assertEqual(graph._edgepaths, paths) def test_constructor_with_nodes_and_paths_dimension_mismatch(self): paths = Graph(((self.source, self.target), self.nodes)).edgepaths exception = 'Ensure that the first two key dimensions on Nodes and EdgePaths match: x != x2' with self.assertRaisesRegex(ValueError, exception): Graph(((self.source, self.target), self.nodes, paths.redim(x='x2'))) def test_graph_clone_static_plot_id(self): self.assertEqual(self.graph.clone()._plot_id, self.graph._plot_id) def test_select_by_node_in_edges_selection_mode(self): graph = Graph(((self.source, self.target),)) selection = Graph(([(1, 0), (2, 0)], list(zip(*self.nodes))[0:3])) self.assertEqual(graph.select(index=(1, 3)), selection) def test_select_by_node_in_nodes_selection_mode(self): graph = Graph(((self.source, self.source+1), self.nodes)) selection = Graph(([(1, 2)], list(zip(*self.nodes))[1:3])) self.assertEqual(graph.select(index=(1, 3), selection_mode='nodes'), selection) def test_select_by_source(self): graph = Graph(((self.source, self.target),)) selection = Graph(([(0,0), (1, 0)], list(zip(*self.nodes))[:2])) self.assertEqual(graph.select(start=(0, 2)), selection) def test_select_by_target(self): graph = Graph(((self.source, self.target),)) selection = Graph(([(0,0), (1, 0)], list(zip(*self.nodes))[:2])) self.assertEqual(graph.select(start=(0, 2)), selection) def test_select_by_source_and_target(self): graph = Graph(((self.source, self.source+1), self.nodes)) selection = Graph(([(0,1)], list(zip(*self.nodes))[:2])) self.assertEqual(graph.select(start=(0, 3), end=1), selection) def test_select_by_edge_data(self): graph = Graph(((self.target, self.source, self.edge_info),), vdims=['info']) selection = Graph(([(0, 0, 0), (0, 1, 1)], list(zip(*self.nodes))[:2]), vdims=['info']) self.assertEqual(graph.select(info=(0, 2)), selection) def test_graph_node_range(self): graph = Graph(((self.target, self.source),)) self.assertEqual(graph.range('x'), (-1, 1)) self.assertEqual(graph.range('y'), (-1, 1)) def test_graph_redim_nodes(self): graph = Graph(((self.target, self.source),)) redimmed = graph.redim(x='x2', y='y2') self.assertEqual(redimmed.nodes, graph.nodes.redim(x='x2', y='y2')) self.assertEqual(redimmed.edgepaths, graph.edgepaths.redim(x='x2', y='y2')) class FromNetworkXTests(ComparisonTestCase): def setUp(self): try: import networkx as nx # noqa except ImportError: raise SkipTest('Test requires networkx to be installed') def test_from_networkx_with_node_attrs(self): import networkx as nx G = nx.karate_club_graph() graph = Graph.from_networkx(G, nx.circular_layout) clubs = np.array([ 'Mr. Hi', 'Mr. Hi', 'Mr. Hi', 'Mr. Hi', 'Mr. Hi', 'Mr. Hi', 'Mr. Hi', 'Mr. Hi', 'Mr. Hi', 'Officer', 'Mr. Hi', 'Mr. Hi', 'Mr. Hi', 'Mr. Hi', 'Officer', 'Officer', 'Mr. Hi', 'Mr. Hi', 'Officer', 'Mr. Hi', 'Officer', 'Mr. Hi', 'Officer', 'Officer', 'Officer', 'Officer', 'Officer', 'Officer', 'Officer', 'Officer', 'Officer', 'Officer', 'Officer', 'Officer']) self.assertEqual(graph.nodes.dimension_values('club'), clubs) def test_from_networkx_with_invalid_node_attrs(self): import networkx as nx FG = nx.Graph() FG.add_node(1, test=[]) FG.add_node(2, test=[]) FG.add_edge(1, 2) graph = Graph.from_networkx(FG, nx.circular_layout) self.assertEqual(graph.nodes.vdims, []) self.assertEqual(graph.nodes.dimension_values(2), np.array([1, 2])) self.assertEqual(graph.array(), np.array([(1, 2)])) def test_from_networkx_with_edge_attrs(self): import networkx as nx FG = nx.Graph() FG.add_weighted_edges_from([(1,2,0.125), (1,3,0.75), (2,4,1.2), (3,4,0.375)]) graph = Graph.from_networkx(FG, nx.circular_layout) self.assertEqual(graph.dimension_values('weight'), np.array([0.125, 0.75, 1.2, 0.375])) def test_from_networkx_with_invalid_edge_attrs(self): import networkx as nx FG = nx.Graph() FG.add_weighted_edges_from([(1,2,[]), (1,3,[]), (2,4,[]), (3,4,[])]) graph = Graph.from_networkx(FG, nx.circular_layout) self.assertEqual(graph.vdims, []) def test_from_networkx_only_nodes(self): import networkx as nx G = nx.Graph() G.add_nodes_from([1, 2, 3]) graph = Graph.from_networkx(G, nx.circular_layout) self.assertEqual(graph.nodes.dimension_values(2), np.array([1, 2, 3])) def test_from_networkx_custom_nodes(self): import networkx as nx FG = nx.Graph() FG.add_weighted_edges_from([(1,2,0.125), (1,3,0.75), (2,4,1.2), (3,4,0.375)]) nodes = Dataset([(1, 'A'), (2, 'B'), (3, 'A'), (4, 'B')], 'index', 'some_attribute') graph = Graph.from_networkx(FG, nx.circular_layout, nodes=nodes) self.assertEqual(graph.nodes.dimension_values('some_attribute'), np.array(['A', 'B', 'A', 'B'])) def test_from_networkx_dictionary_positions(self): import networkx as nx G = nx.Graph() G.add_nodes_from([1, 2, 3]) positions = nx.circular_layout(G) graph = Graph.from_networkx(G, positions) self.assertEqual(graph.nodes.dimension_values(2), np.array([1, 2, 3])) class ChordTests(ComparisonTestCase): def setUp(self): self.simplices = [(0, 1, 2), (1, 2, 3), (2, 3, 4)] def test_chord_constructor_no_vdims(self): chord = Chord(self.simplices) nodes = np.array([[0.8660254037844387, 0.49999999999999994, 0], [-0.4999999999999998, 0.8660254037844388, 1], [-0.5000000000000004, -0.8660254037844384, 2], [0.8660254037844379, -0.5000000000000012, 3]]) self.assertEqual(chord.nodes, Nodes(nodes)) self.assertEqual(chord.array(), np.array([s[:2] for s in self.simplices])) def test_chord_constructor_with_vdims(self): chord = Chord(self.simplices, vdims=['z']) nodes = np.array( [[0.9396926207859084, 0.3420201433256687, 0], [6.123233995736766e-17, 1.0, 1], [-0.8660254037844388, -0.4999999999999998, 2], [0.7660444431189779, -0.6427876096865396, 3]] ) self.assertEqual(chord.nodes, Nodes(nodes)) self.assertEqual(chord.array(), np.array(self.simplices)) def test_chord_constructor_self_reference(self): chord = Chord([('A', 'B', 2), ('B', 'A', 3), ('A', 'A', 2)]) nodes = pd.DataFrame( [[-0.5, 0.866025, "A"], [0.5, -0.866025, "B"]], columns=["x", "y", "index"] ) self.assertEqual(chord.nodes, Nodes(nodes)) class TriMeshTests(ComparisonTestCase): def setUp(self): self.nodes = [(0, 0, 0), (0.5, 1, 1), (1., 0, 2), (1.5, 1, 4)] self.simplices = [(0, 1, 2), (1, 2, 3)] def test_trimesh_constructor(self): nodes = [n[:2] for n in self.nodes] trimesh = TriMesh((self.simplices, nodes)) self.assertEqual(trimesh.array(), np.array(self.simplices)) self.assertEqual(trimesh.nodes.array([0, 1]), np.array(nodes)) self.assertEqual(trimesh.nodes.dimension_values(2), np.arange(4)) def test_trimesh_empty(self): trimesh = TriMesh([]) self.assertEqual(trimesh.array(), np.empty((0, 3))) self.assertEqual(trimesh.nodes.array(), np.empty((0, 3))) def test_trimesh_empty_clone(self): trimesh = TriMesh([]).clone() self.assertEqual(trimesh.array(), np.empty((0, 3))) self.assertEqual(trimesh.nodes.array(), np.empty((0, 3))) def test_trimesh_constructor_tuple_nodes(self): nodes = tuple(zip(*self.nodes))[:2] trimesh = TriMesh((self.simplices, nodes)) self.assertEqual(trimesh.array(), np.array(self.simplices)) self.assertEqual(trimesh.nodes.array([0, 1]), np.array(nodes).T) self.assertEqual(trimesh.nodes.dimension_values(2), np.arange(4)) def test_trimesh_constructor_df_nodes(self): nodes_df = pd.DataFrame(self.nodes, columns=['x', 'y', 'z']) trimesh = TriMesh((self.simplices, nodes_df)) nodes = Nodes([(0, 0, 0, 0), (0.5, 1, 1, 1), (1., 0, 2, 2), (1.5, 1, 3, 4)], vdims='z') self.assertEqual(trimesh.array(), np.array(self.simplices)) self.assertEqual(trimesh.nodes, nodes) def test_trimesh_constructor_point_nodes(self): nodes = [n[:2] for n in self.nodes] trimesh = TriMesh((self.simplices, Points(self.nodes))) self.assertEqual(trimesh.array(), np.array(self.simplices)) self.assertEqual(trimesh.nodes.array([0, 1]), np.array(nodes)) self.assertEqual(trimesh.nodes.dimension_values(2), np.arange(4)) def test_trimesh_edgepaths(self): trimesh = TriMesh((self.simplices, self.nodes)) paths = [np.array([(0, 0), (0.5, 1), (1, 0), (0, 0), (np.nan, np.nan), (0.5, 1), (1, 0), (1.5, 1), (0.5, 1)])] for p1, p2 in zip(trimesh.edgepaths.split(datatype='array'), paths): self.assertEqual(p1, p2) def test_trimesh_select(self): trimesh = TriMesh((self.simplices, self.nodes)).select(x=(0.1, None)) self.assertEqual(trimesh.array(), np.array(self.simplices[1:])) class TestSankey(ComparisonTestCase): def test_single_edge_sankey(self): sankey = Sankey([('A', 'B', 1)]) links = list(sankey._sankey['links']) self.assertEqual(len(links), 1) del links[0]['source']['sourceLinks'] del links[0]['target']['targetLinks'] link = { 'index': 0, 'source': { 'index': 'A', 'values': (), 'targetLinks': [], 'value': 1, 'depth': 0, 'height': 1, 'column': 0, 'x0': 0, 'x1': 15, 'y0': 0.0, 'y1': 500.0}, 'target': { 'index': 'B', 'values': (), 'sourceLinks': [], 'value': 1, 'depth': 1, 'height': 0, 'column': 1, 'x0': 985.0, 'x1': 1000.0, 'y0': 0.0, 'y1': 500.0}, 'value': 1, 'width': 500.0, 'y0': 250.0, 'y1': 250.0 } self.assertEqual(links[0], link)