From 0ce1e079344a79717c60394c2a1932436e45936b Mon Sep 17 00:00:00 2001
From: Isaac Virshup <ivirshup@gmail.com>
Date: Thu, 11 Feb 2021 18:34:23 +1100
Subject: [PATCH 1/2] Fix gen_clustree

---
 constclust/clustree.py |  4 ++--
 tests/test_clustree.py | 39 +++++++++++++++++++++++++++++++++++++++
 2 files changed, 41 insertions(+), 2 deletions(-)
 create mode 100644 tests/test_clustree.py

diff --git a/constclust/clustree.py b/constclust/clustree.py
index 99f9309..e8c338c 100644
--- a/constclust/clustree.py
+++ b/constclust/clustree.py
@@ -74,8 +74,8 @@ def gen_clustree(cluster_df):
         current_nodes = grouped[level]
         next_nodes = grouped[level + 1]
         for current_node, next_node in product(current_nodes, next_nodes):
-            current_contents = g.node[current_node]["contents"]
-            next_contents = g.node[next_node]["contents"]
+            current_contents = g.nodes[current_node]["contents"]
+            next_contents = g.nodes[next_node]["contents"]
             intersect = np.intersect1d(
                 current_contents, next_contents, assume_unique=True
             )
diff --git a/tests/test_clustree.py b/tests/test_clustree.py
new file mode 100644
index 0000000..6a034d0
--- /dev/null
+++ b/tests/test_clustree.py
@@ -0,0 +1,39 @@
+import numpy as np
+import pandas as pd
+import networkx as nx
+
+from constclust.clustree import gen_clustree
+
+import pytest
+
+
+@pytest.mark.parametrize(
+    "clusterings,expected",
+    [
+        (
+            pd.DataFrame(
+                {
+                    "a": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                    "b": [1, 1, 1, 1, 1, 0, 0, 0, 0, 0],
+                    "c": [0, 0, 0, 1, 1, 2, 2, 2, 2, 2],
+                }
+            ),
+            nx.DiGraph({0: [1, 2], 1: [3, 4], 2: [6]}),
+        ),
+        (
+            pd.DataFrame(
+                {
+                    "a": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                    "b": [1, 1, 1, 1, 1, 0, 0, 0, 0, 0],
+                    "c": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                }
+            ),
+            nx.DiGraph({0: [1, 2], 1: [3], 2: [3]}),
+        ),
+    ],
+    ids=["tree", "diamond"],
+)
+def test_clustree_generation_isomorphic(clusterings, expected):
+    result = gen_clustree(clusterings)
+
+    assert nx.is_isomorphic(expected, result)

From 3db3e3a0d5b53a4b2c97eaad5262b6d471dafef5 Mon Sep 17 00:00:00 2001
From: Isaac Virshup <ivirshup@gmail.com>
Date: Thu, 11 Feb 2021 18:49:01 +1100
Subject: [PATCH 2/2] Add weights to test

---
 tests/test_clustree.py | 24 ++++++++++++++++++++----
 1 file changed, 20 insertions(+), 4 deletions(-)

diff --git a/tests/test_clustree.py b/tests/test_clustree.py
index 6a034d0..fd65e07 100644
--- a/tests/test_clustree.py
+++ b/tests/test_clustree.py
@@ -18,7 +18,13 @@
                     "c": [0, 0, 0, 1, 1, 2, 2, 2, 2, 2],
                 }
             ),
-            nx.DiGraph({0: [1, 2], 1: [3, 4], 2: [6]}),
+            nx.DiGraph(
+                {
+                    0: {1: {"weight": 0.5}, 2: {"weight": 0.5}},
+                    1: {3: {"weight": 0.6}, 4: {"weight": 0.4}},
+                    2: {6: {"weight": 1.0}},
+                }
+            ),
         ),
         (
             pd.DataFrame(
@@ -28,12 +34,22 @@
                     "c": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
                 }
             ),
-            nx.DiGraph({0: [1, 2], 1: [3], 2: [3]}),
+            nx.DiGraph(
+                {
+                    0: {1: {"weight": 0.5}, 2: {"weight": 0.5}},
+                    1: {3: {"weight": 0.5}},
+                    2: {3: {"weight": 0.5}},
+                }
+            ),
         ),
     ],
     ids=["tree", "diamond"],
 )
-def test_clustree_generation_isomorphic(clusterings, expected):
+def test_clustree_weights(clusterings, expected):
+    import networkx.algorithms.isomorphism as iso
+
     result = gen_clustree(clusterings)
 
-    assert nx.is_isomorphic(expected, result)
+    assert nx.is_isomorphic(
+        expected, result, edge_match=iso.numerical_edge_match("weight", default=1)
+    )