diff env/lib/python3.9/site-packages/networkx/algorithms/tests/test_voronoi.py @ 0:4f3585e2f14b draft default tip

"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/env/lib/python3.9/site-packages/networkx/algorithms/tests/test_voronoi.py	Mon Mar 22 18:12:50 2021 +0000
@@ -0,0 +1,103 @@
+import networkx as nx
+from networkx.utils import pairwise
+
+
+class TestVoronoiCells:
+    """Unit tests for the Voronoi cells function."""
+
+    def test_isolates(self):
+        """Tests that a graph with isolated nodes has all isolates in
+        one block of the partition.
+
+        """
+        G = nx.empty_graph(5)
+        cells = nx.voronoi_cells(G, {0, 2, 4})
+        expected = {0: {0}, 2: {2}, 4: {4}, "unreachable": {1, 3}}
+        assert expected == cells
+
+    def test_undirected_unweighted(self):
+        G = nx.cycle_graph(6)
+        cells = nx.voronoi_cells(G, {0, 3})
+        expected = {0: {0, 1, 5}, 3: {2, 3, 4}}
+        assert expected == cells
+
+    def test_directed_unweighted(self):
+        # This is the singly-linked directed cycle graph on six nodes.
+        G = nx.DiGraph(pairwise(range(6), cyclic=True))
+        cells = nx.voronoi_cells(G, {0, 3})
+        expected = {0: {0, 1, 2}, 3: {3, 4, 5}}
+        assert expected == cells
+
+    def test_directed_inward(self):
+        """Tests that reversing the graph gives the "inward" Voronoi
+        partition.
+
+        """
+        # This is the singly-linked reverse directed cycle graph on six nodes.
+        G = nx.DiGraph(pairwise(range(6), cyclic=True))
+        G = G.reverse(copy=False)
+        cells = nx.voronoi_cells(G, {0, 3})
+        expected = {0: {0, 4, 5}, 3: {1, 2, 3}}
+        assert expected == cells
+
+    def test_undirected_weighted(self):
+        edges = [(0, 1, 10), (1, 2, 1), (2, 3, 1)]
+        G = nx.Graph()
+        G.add_weighted_edges_from(edges)
+        cells = nx.voronoi_cells(G, {0, 3})
+        expected = {0: {0}, 3: {1, 2, 3}}
+        assert expected == cells
+
+    def test_directed_weighted(self):
+        edges = [(0, 1, 10), (1, 2, 1), (2, 3, 1), (3, 2, 1), (2, 1, 1)]
+        G = nx.DiGraph()
+        G.add_weighted_edges_from(edges)
+        cells = nx.voronoi_cells(G, {0, 3})
+        expected = {0: {0}, 3: {1, 2, 3}}
+        assert expected == cells
+
+    def test_multigraph_unweighted(self):
+        """Tests that the Voronoi cells for a multigraph are the same as
+        for a simple graph.
+
+        """
+        edges = [(0, 1), (1, 2), (2, 3)]
+        G = nx.MultiGraph(2 * edges)
+        H = nx.Graph(G)
+        G_cells = nx.voronoi_cells(G, {0, 3})
+        H_cells = nx.voronoi_cells(H, {0, 3})
+        assert G_cells == H_cells
+
+    def test_multidigraph_unweighted(self):
+        # This is the twice-singly-linked directed cycle graph on six nodes.
+        edges = list(pairwise(range(6), cyclic=True))
+        G = nx.MultiDiGraph(2 * edges)
+        H = nx.DiGraph(G)
+        G_cells = nx.voronoi_cells(G, {0, 3})
+        H_cells = nx.voronoi_cells(H, {0, 3})
+        assert G_cells == H_cells
+
+    def test_multigraph_weighted(self):
+        edges = [(0, 1, 10), (0, 1, 10), (1, 2, 1), (1, 2, 100), (2, 3, 1), (2, 3, 100)]
+        G = nx.MultiGraph()
+        G.add_weighted_edges_from(edges)
+        cells = nx.voronoi_cells(G, {0, 3})
+        expected = {0: {0}, 3: {1, 2, 3}}
+        assert expected == cells
+
+    def test_multidigraph_weighted(self):
+        edges = [
+            (0, 1, 10),
+            (0, 1, 10),
+            (1, 2, 1),
+            (2, 3, 1),
+            (3, 2, 10),
+            (3, 2, 1),
+            (2, 1, 10),
+            (2, 1, 1),
+        ]
+        G = nx.MultiDiGraph()
+        G.add_weighted_edges_from(edges)
+        cells = nx.voronoi_cells(G, {0, 3})
+        expected = {0: {0}, 3: {1, 2, 3}}
+        assert expected == cells