Make initialization of eigenvector() and pagerank() optional

src/graph/centrality/graph_eigenvector.hh

@@ -43,22 +43,10 @@ struct get_eigenvector
 
         CentralityMap c_temp(vertex_index, num_vertices(g));
 
-        // init centrality
-        int i, N = num_vertices(g), V = HardNumVertices()(g);
-        #pragma omp parallel for default(shared) private(i)     \
-                schedule(dynamic)
-        for (i = 0; i < N; ++i)
-        {
-            typename graph_traits<Graph>::vertex_descriptor v = vertex(i, g);
-            if (v == graph_traits<Graph>::null_vertex())
-                continue;
-            c[v] = 1.0 / V;
-        }
-
         t_type norm = 0;
-
         t_type delta = epsilon + 1;
         size_t iter = 0;
+        int i, N = num_vertices(g);
         while (delta >= epsilon)
         {
             norm = 0;

src/graph/centrality/graph_pagerank.hh

@@ -40,7 +40,7 @@ struct get_pagerank
         RankMap r_temp(vertex_index, num_vertices(g));
         RankMap deg(vertex_index, num_vertices(g));
 
-        // init ranks
+        // init degs
         int i, N = num_vertices(g);
         #pragma omp parallel for default(shared) private(i)     \
                 schedule(dynamic)
@@ -49,10 +49,8 @@ struct get_pagerank
             typename graph_traits<Graph>::vertex_descriptor v = vertex(i, g);
             if (v == graph_traits<Graph>::null_vertex())
                 continue;
-            put(rank, v, get(pers, v));
-
-            typename graph_traits<Graph>::out_edge_iterator e, e_end;
             put(deg, v, 0);
+            typename graph_traits<Graph>::out_edge_iterator e, e_end;
             for (tie(e, e_end) = out_edges(v, g); e!= e_end; ++e)
                 put(deg, v, get(deg, v) + get(weight, *e));
         }

src/graph_tool/centrality/__init__.py

@@ -73,7 +73,8 @@ def pagerank(g, damping=0.85, pers=None, weight=None, prop=None, epsilon=1e-6,
     weight : :class:`~graph_tool.PropertyMap`, optional (default: None)
         Edge weights. If omitted, a constant value of 1 will be used.
     prop : :class:`~graph_tool.PropertyMap`, optional (default: None)
-        Vertex property map to store the PageRank values.
+        Vertex property map to store the PageRank values. If supplied, it will
+        be used uninitialized.
     epsilon : float, optional (default: 1e-6)
         Convergence condition. The iteration will stop if the total delta of all
         vertices are below this value.
@@ -198,6 +199,8 @@ def pagerank(g, damping=0.85, pers=None, weight=None, prop=None, epsilon=1e-6,
         max_iter = 0
     if prop == None:
         prop = g.new_vertex_property("double")
+        N = len(prop.a)
+        prop.a = pers.a[:N] if pers is not None else 1. / g.num_vertices()
     ic = libgraph_tool_centrality.\
             get_pagerank(g._Graph__graph, _prop("v", g, prop),
                          _prop("v", g, pers), _prop("e", g, weight),
@@ -375,7 +378,8 @@ def eigenvector(g, weight=None, vprop=None, epsilon=1e-6, max_iter=None):
     weight : :class:`~graph_tool.PropertyMap` (optional, default: ``None``)
         Edge property map with the edge weights.
     vprop : :class:`~graph_tool.PropertyMap`, optional (default: ``None``)
-        Vertex property map where the values of eigenvector must be stored.
+        Vertex property map where the values of eigenvector must be stored. If
+        provided, it will be used uninitialized.
     epsilon : float, optional (default: ``1e-6``)
         Convergence condition. The iteration will stop if the total delta of all
         vertices are below this value.
@@ -460,8 +464,9 @@ def eigenvector(g, weight=None, vprop=None, epsilon=1e-6, max_iter=None):
 
     """
 
-    if vprop == None:
+    if vprop is None:
         vprop = g.new_vertex_property("double")
+        vprop.a = 1. / g.num_vertices()
     if max_iter is None:
         max_iter = 0
     ee = libgraph_tool_centrality.\