Update doctests

src/graph_tool/__init__.py

@@ -1828,9 +1828,9 @@ class Graph(object):
         --------
         >>> g = gt.random_graph(6, lambda: 1, directed=False)
         >>> g.get_edges()
-        array([[0, 4, 0],
-               [2, 1, 2],
-               [5, 3, 1]], dtype=uint64)
+        array([[2, 1, 2],
+               [3, 4, 0],
+               [5, 0, 1]], dtype=uint64)
         """
         edges = libcore.get_edge_list(self.__graph)
         E = edges.shape[0] // 3

src/graph_tool/clustering/__init__.py

@@ -121,7 +121,7 @@ def local_clustering(g, prop=None, undirected=True):
     >>> g = gt.random_graph(1000, lambda: (5,5))
     >>> clust = gt.local_clustering(g)
     >>> print(gt.vertex_average(g, clust))
-    (0.006177777777777778, 0.00036966184079941211)
+    (0.008177777777777779, 0.00042080229075093...)
 
     References
     ----------
@@ -182,7 +182,7 @@ def global_clustering(g):
 
     >>> g = gt.random_graph(1000, lambda: (5,5))
     >>> print(gt.global_clustering(g))
-    (0.006177777777777778, 0.0003700318726720...)
+    (0.008177777777777779, 0.0004212235142651...)
 
     References
     ----------
@@ -263,11 +263,11 @@ def extended_clustering(g, props=None, max_depth=3, undirected=False):
     >>> for i in range(0, 5):
     ...    print(gt.vertex_average(g, clusts[i]))
     ...
-    (0.00421, 0.00041685103920811...)
-    (0.027226666666666666, 0.00100735228307788...)
-    (0.11549166666666667, 0.00208139908541773...)
-    (0.4128066666666666, 0.00294792212319872...)
-    (0.4205716666666667, 0.00315646574114149...)
+    (0.0050483333333333335, 0.0004393940240073...)
+    (0.024593787878787878, 0.0009963004021144...)
+    (0.11238924242424242, 0.001909615401971...)
+    (0.40252272727272725, 0.003113987400030...)
+    (0.43629378787878786, 0.003144159256565...)
 
     References
     ----------
@@ -349,10 +349,9 @@ def motifs(g, k, p=1.0, motif_list=None, return_maps=False):
     >>> g = gt.random_graph(1000, lambda: (5,5))
     >>> motifs, counts = gt.motifs(gt.GraphView(g, directed=False), 4)
     >>> print(len(motifs))
-    13
+    18
     >>> print(counts)
-    [115408, 388542, 1031, 1182, 2662, 2138, 833, 28, 16, 5, 5, 3, 4]
-
+    [115557, 390005, 627, 700, 1681, 2815, 820, 12, 27, 44, 15, 7, 12, 4, 6, 1, 2, 1]
 
     References
     ----------
@@ -523,7 +522,7 @@ def motif_significance(g, k, n_shuffles=100, p=1.0, motif_list=None,
     >>> print(len(motifs))
     11
     >>> print(zscores)
-    [0.04162670293683441, 0.046769781223679897, 0.55888261369689918, 0.82906624302416043, -0.41384527710386287, -0.42070845824900477, -1.3262411347517733, 1.82, -0.13, -0.37, -0.22]
+    [0.22728646681107012, 0.21409572051644973, 0.0070220407889021114, 0.58721419671233477, -0.37770179603294357, -0.34847335047837341, 0.88618118013255021, -0.08, -0.2, -0.38, -0.2]
     """
 
     s_ms, counts = motifs(g, k, p, motif_list)

src/graph_tool/stats/__init__.py

@@ -231,7 +231,7 @@ def vertex_average(g, deg):
     >>> from numpy.random import poisson
     >>> g = gt.random_graph(1000, lambda: (poisson(5), poisson(5)))
     >>> print(gt.vertex_average(g, "in"))
-    (4.975, 0.068675869124460318)
+    (4.96, 0.067988234276233406)
     """
 
     if isinstance(deg, PropertyMap) and "string" in deg.value_type():
@@ -293,7 +293,7 @@ def edge_average(g, eprop):
     >>> eprop = g.new_edge_property("double")
     >>> eprop.get_array()[:] = random(g.num_edges())
     >>> print(gt.edge_average(g, eprop))
-    (0.4989741369720412, 0.004101065927783254)
+    (0.49888156584192045, 0.0040967399234187541)
     """
 
     if "string" in eprop.value_type():
@@ -426,10 +426,10 @@ def distance_histogram(g, weight=None, bins=[0, 1], samples=None,
     >>> g = gt.random_graph(100, lambda: (3, 3))
     >>> hist = gt.distance_histogram(g)
     >>> print(hist)
-    [array([    0.,   300.,   865.,  2214.,  3857.,  2480.,   184.]), array([0, 1, 2, 3, 4, 5, 6, 7], dtype=uint...)]
+    [array([    0.,   300.,   880.,  2269.,  3974.,  2358.,   119.]), array([0, 1, 2, 3, 4, 5, 6, 7], dtype=uint64)]
     >>> hist = gt.distance_histogram(g, samples=10)
     >>> print(hist)
-    [array([   0.,   30.,   88.,  226.,  391.,  240.,   15.]), array([0, 1, 2, 3, 4, 5, 6, 7], dtype=uint...)]
+    [array([   0.,   30.,   87.,  223.,  394.,  239.,   17.]), array([0, 1, 2, 3, 4, 5, 6, 7], dtype=uint64)]
     """
 
     if samples is not None: