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Merge pull request #5462 from tacaswell/dag_docfix...
Thomas Kluyver -
r16044:e641df57 merge
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@@ -58,9 +58,9 b' The code to generate the simple DAG:'
58 .. sourcecode:: python
58 .. sourcecode:: python
59
59
60 import networkx as nx
60 import networkx as nx
61
61
62 G = nx.DiGraph()
62 G = nx.DiGraph()
63
63
64 # add 5 nodes, labeled 0-4:
64 # add 5 nodes, labeled 0-4:
65 map(G.add_node, range(5))
65 map(G.add_node, range(5))
66 # 1,2 depend on 0:
66 # 1,2 depend on 0:
@@ -71,7 +71,7 b' The code to generate the simple DAG:'
71 G.add_edge(2,3)
71 G.add_edge(2,3)
72 # 4 depends on 1
72 # 4 depends on 1
73 G.add_edge(1,4)
73 G.add_edge(1,4)
74
74
75 # now draw the graph:
75 # now draw the graph:
76 pos = { 0 : (0,0), 1 : (1,1), 2 : (-1,1),
76 pos = { 0 : (0,0), 1 : (1,1), 2 : (-1,1),
77 3 : (0,2), 4 : (2,2)}
77 3 : (0,2), 4 : (2,2)}
@@ -96,11 +96,11 b' Now, we need to build our dict of jobs corresponding to the nodes on the graph:'
96 .. sourcecode:: ipython
96 .. sourcecode:: ipython
97
97
98 In [3]: jobs = {}
98 In [3]: jobs = {}
99
99
100 # in reality, each job would presumably be different
100 # in reality, each job would presumably be different
101 # randomwait is just a function that sleeps for a random interval
101 # randomwait is just a function that sleeps for a random interval
102 In [4]: for node in G:
102 In [4]: for node in G:
103 ...: jobs[node] = randomwait
103 ...: jobs[node] = randomwait
104
104
105 Once we have a dict of jobs matching the nodes on the graph, we can start submitting jobs,
105 Once we have a dict of jobs matching the nodes on the graph, we can start submitting jobs,
106 and linking up the dependencies. Since we don't know a job's msg_id until it is submitted,
106 and linking up the dependencies. Since we don't know a job's msg_id until it is submitted,
@@ -114,10 +114,10 b' on which it depends:'
114
114
115 In [5]: rc = Client()
115 In [5]: rc = Client()
116 In [5]: view = rc.load_balanced_view()
116 In [5]: view = rc.load_balanced_view()
117
117
118 In [6]: results = {}
118 In [6]: results = {}
119
119
120 In [7]: for node in G.topological_sort():
120 In [7]: for node in nx.topological_sort(G):
121 ...: # get list of AsyncResult objects from nodes
121 ...: # get list of AsyncResult objects from nodes
122 ...: # leading into this one as dependencies
122 ...: # leading into this one as dependencies
123 ...: deps = [ results[n] for n in G.predecessors(node) ]
123 ...: deps = [ results[n] for n in G.predecessors(node) ]
@@ -152,18 +152,18 b' will be at the top, and quick, small tasks will be at the bottom.'
152 .. sourcecode:: ipython
152 .. sourcecode:: ipython
153
153
154 In [10]: from matplotlib.dates import date2num
154 In [10]: from matplotlib.dates import date2num
155
155
156 In [11]: from matplotlib.cm import gist_rainbow
156 In [11]: from matplotlib.cm import gist_rainbow
157
157
158 In [12]: pos = {}; colors = {}
158 In [12]: pos = {}; colors = {}
159
159
160 In [12]: for node in G:
160 In [12]: for node in G:
161 ....: md = results[node].metadata
161 ....: md = results[node].metadata
162 ....: start = date2num(md.started)
162 ....: start = date2num(md.started)
163 ....: runtime = date2num(md.completed) - start
163 ....: runtime = date2num(md.completed) - start
164 ....: pos[node] = (start, runtime)
164 ....: pos[node] = (start, runtime)
165 ....: colors[node] = md.engine_id
165 ....: colors[node] = md.engine_id
166
166
167 In [13]: nx.draw(G, pos, node_list=colors.keys(), node_color=colors.values(),
167 In [13]: nx.draw(G, pos, node_list=colors.keys(), node_color=colors.values(),
168 ....: cmap=gist_rainbow)
168 ....: cmap=gist_rainbow)
169
169
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