content: """Example for generating an arbitrary DAG as a dependency map.
  
  This demo uses networkx to generate the graph.
  
  Authors
  -------
  * MinRK
  """
  import networkx as nx
  from random import randint, random
  from IPython import parallel
  
  def randomwait():
      import time
      from random import random
      time.sleep(random())
      return time.time()
  
  
  def random_dag(nodes, edges):
      """Generate a random Directed Acyclic Graph (DAG) with a given number of nodes and edges."""
      G = nx.DiGraph()
      for i in range(nodes):
          G.add_node(i)
      while edges > 0:
          a = randint(0,nodes-1)
          b=a
          while b==a:
              b = randint(0,nodes-1)
          G.add_edge(a,b)
          if nx.is_directed_acyclic_graph(G):
              edges -= 1
          else:
              # we closed a loop!
              G.remove_edge(a,b)
      return G
  
  def add_children(G, parent, level, n=2):
      """Add children recursively to a binary tree."""
      if level == 0:
          return
      for i in range(n):
          child = parent+str(i)
          G.add_node(child)
          G.add_edge(parent,child)
          add_children(G, child, level-1, n)
  
  def make_bintree(levels):
      """Make a symmetrical binary tree with @levels"""
      G = nx.DiGraph()
      root = '0'
      G.add_node(root)
      add_children(G, root, levels, 2)
      return G
  
  def submit_jobs(view, G, jobs):
      """Submit jobs via client where G describes the time dependencies."""
      results = {}
      for node in nx.topological_sort(G):
          with view.temp_flags(after=[ results[n] for n in G.predecessors(node) ]):
              results[node] = view.apply(jobs[node])
      return results
  
  def validate_tree(G, results):
      """Validate that jobs executed after their dependencies."""
      for node in G:
          started = results[node].metadata.started
          for parent in G.predecessors(node):
              finished = results[parent].metadata.completed
              assert started > finished, "%s should have happened after %s"%(node, parent)
  
  def main(nodes, edges):
      """Generate a random graph, submit jobs, then validate that the
      dependency order was enforced.
      Finally, plot the graph, with time on the x-axis, and
      in-degree on the y (just for spread).  All arrows must
      point at least slightly to the right if the graph is valid.
      """
      from matplotlib import pyplot as plt
      from matplotlib.dates import date2num
      from matplotlib.cm import gist_rainbow
      print("building DAG")
      G = random_dag(nodes, edges)
      jobs = {}
      pos = {}
      colors = {}
      for node in G:
          jobs[node] = randomwait
      
      client = parallel.Client()
      view = client.load_balanced_view()
      print("submitting %i tasks with %i dependencies"%(nodes,edges))
      results = submit_jobs(view, G, jobs)
      print("waiting for results")
      view.wait()
      print("done")
      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
      validate_tree(G, results)
      nx.draw(G, pos, node_list=colors.keys(), node_color=colors.values(), cmap=gist_rainbow,
              with_labels=False)
      x,y = zip(*pos.values())
      xmin,ymin = map(min, (x,y))
      xmax,ymax = map(max, (x,y))
      xscale = xmax-xmin
      yscale = ymax-ymin
      plt.xlim(xmin-xscale*.1,xmax+xscale*.1)
      plt.ylim(ymin-yscale*.1,ymax+yscale*.1)
      return G,results
  
  if __name__ == '__main__':
      from matplotlib import pyplot as plt
      # main(5,10)
      main(32,96)
      plt.show()
      
  