Implement personalized pagerank by date uniformity

date_selection.py

+import math
 from collections import Counter
 
 import igraph
@@ -37,13 +38,35 @@ def rank_dates_by_wilson(articles, start_date, end_date, num_dates):
     g = igraph.Graph.TupleList(edges, directed=True, edge_attrs='weight')
     vertex_names = g.vs['name']
 
-    # rank vertices by pagerank score
-    pagerank_scores = g.pagerank(directed=True, weights=g.es['weight'])
-    ranked_dates = util.rank(vertex_names, scores=pagerank_scores)
+    # rank the dates with personalized pagerank
+    # (do this multiple times with different "vertex weights", depending on alpha,
+    # and return the result that is most uniform)
+    best_uniformity = math.inf
+    best_ranked_dates = []
+    candidate_alphas = [0.01 * x for x in range(1, 100)]
+    for alpha in candidate_alphas:
 
-    print(date_uniformity(ranked_dates[:num_dates]))
+        # calculate vertex "weights" for personalized pagerank
+        vertex_weights = []
+        start = min(vertex_names)
+        for date in vertex_names:
+            diff_to_start = util.days_between(start, date)
+            try:
+                vertex_weights.append(alpha ** -diff_to_start)
+            except OverflowError:
+                vertex_weights.append(math.inf)
 
-    return ranked_dates
+        # rank vertices with personalized pagerank
+        pagerank_scores = g.personalized_pagerank(directed=True, weights=g.es['weight'], reset=vertex_weights)
+        ranked_dates = util.rank(vertex_names, scores=pagerank_scores)
+
+        # if this result is the most uniform yet, save it
+        uniformity = date_uniformity(ranked_dates[:num_dates])
+        if uniformity < best_uniformity:
+            best_uniformity = uniformity
+            best_ranked_dates = ranked_dates
+
+    return best_ranked_dates
 
 
 def date_uniformity(dates):