From e7b2aad2c0ddaf08f0d787b996a0456480bc54df 2014-03-28 18:29:25
From: Thomas A Caswell <tcaswell@bnl.gov>
Date: 2014-03-28 18:29:25
Subject: [PATCH] DOC : fixed minor error in using topological sort

`topological_sort` is a function in `nx` not an instance method
of a directed graph.

---

diff --git a/docs/source/parallel/dag_dependencies.rst b/docs/source/parallel/dag_dependencies.rst
index 719913c..9d03b28 100644
--- a/docs/source/parallel/dag_dependencies.rst
+++ b/docs/source/parallel/dag_dependencies.rst
@@ -58,9 +58,9 @@ The code to generate the simple DAG:
 .. sourcecode:: python
 
     import networkx as nx
-    
+
     G = nx.DiGraph()
-    
+
     # add 5 nodes, labeled 0-4:
     map(G.add_node, range(5))
     # 1,2 depend on 0:
@@ -71,7 +71,7 @@ The code to generate the simple DAG:
     G.add_edge(2,3)
     # 4 depends on 1
     G.add_edge(1,4)
-    
+
     # now draw the graph:
     pos = { 0 : (0,0), 1 : (1,1), 2 : (-1,1),
             3 : (0,2), 4 : (2,2)}
@@ -96,11 +96,11 @@ Now, we need to build our dict of jobs corresponding to the nodes on the graph:
 .. sourcecode:: ipython
 
     In [3]: jobs = {}
-    
+
     # in reality, each job would presumably be different
     # randomwait is just a function that sleeps for a random interval
     In [4]: for node in G:
-       ...:     jobs[node] = randomwait 
+       ...:     jobs[node] = randomwait
 
 Once we have a dict of jobs matching the nodes on the graph, we can start submitting jobs,
 and linking up the dependencies. Since we don't know a job's msg_id until it is submitted,
@@ -114,10 +114,10 @@ on which it depends:
 
     In [5]: rc = Client()
     In [5]: view = rc.load_balanced_view()
-    
+
     In [6]: results = {}
-    
-    In [7]: for node in G.topological_sort():
+
+    In [7]: for node in nx.topological_sort(G):
        ...:    # get list of AsyncResult objects from nodes
        ...:    # leading into this one as dependencies
        ...:    deps = [ results[n] for n in G.predecessors(node) ]
@@ -152,18 +152,18 @@ will be at the top, and quick, small tasks will be at the bottom.
 .. sourcecode:: ipython
 
     In [10]: from matplotlib.dates import date2num
-    
+
     In [11]: from matplotlib.cm import gist_rainbow
-    
+
     In [12]: pos = {}; colors = {}
-    
+
     In [12]: for node in G:
        ....:    md = results[node].metadata
        ....:    start = date2num(md.started)
        ....:    runtime = date2num(md.completed) - start
        ....:    pos[node] = (start, runtime)
        ....:    colors[node] = md.engine_id
-    
+
     In [13]: nx.draw(G, pos, node_list=colors.keys(), node_color=colors.values(),
        ....:    cmap=gist_rainbow)