How to use the pydot.graph_from_dot_file function in pydot

###### Visualizing a Single Decision Tree #########
    # Import tools needed for visualization
    from sklearn.tree import export_graphviz
    import pydot
    # Pull out one tree from the forest
    tree = rf.estimators_[5]
    # Import tools needed for visualization
    from sklearn.tree import export_graphviz

    # Pull out one tree from the forest
    tree = rf.estimators_[5]
    # Export the image to a dot file
    export_graphviz(tree, out_file='tree.dot', feature_names=feature_list, rounded=True, precision=1)
    # Use dot file to create a graph
    (graph,) = pydot.graph_from_dot_file('tree.dot')
    # Write graph to a png file
    graph.write_png('tree.png')


    # Limit depth of tree to 3 levels
    rf_small = RandomForestRegressor(n_estimators=10, max_depth=3)
    rf_small.fit(train_features, train_labels)
    # Extract the small tree
    tree_small = rf_small.estimators_[5]
    # Save the tree as a png image
    export_graphviz(tree_small, out_file='small_tree.dot', feature_names=feature_list, rounded=True, precision=1)
    (graph,) = pydot.graph_from_dot_file('small_tree.dot')
    graph.write_png('small_tree.png')


    ######## Variable Importances  ############

# Export the image to a dot file
    export_graphviz(tree, out_file='tree.dot', feature_names=feature_list, rounded=True, precision=1)
    # Use dot file to create a graph
    (graph,) = pydot.graph_from_dot_file('tree.dot')
    # Write graph to a png file
    graph.write_png('tree.png')


    # Limit depth of tree to 3 levels
    rf_small = RandomForestRegressor(n_estimators=10, max_depth=3)
    rf_small.fit(train_features, train_labels)
    # Extract the small tree
    tree_small = rf_small.estimators_[5]
    # Save the tree as a png image
    export_graphviz(tree_small, out_file='small_tree.dot', feature_names=feature_list, rounded=True, precision=1)
    (graph,) = pydot.graph_from_dot_file('small_tree.dot')
    graph.write_png('small_tree.png')


    ######## Variable Importances  ############
    # Get numerical feature importances
    importances = list(rf.feature_importances_)
    # List of tuples with variable and importance
    feature_importances = [(feature, round(importance, 2)) for feature, importance in zip(feature_list, importances)]
    # Sort the feature importances by most important first
    feature_importances = sorted(feature_importances, key=lambda x: x[1], reverse=True)
    # Print out the feature and importances
    [print('Variable: {:20} Importance: {}'.format(*pair)) for pair in feature_importances]

    ######## Visualizations ################
    import matplotlib.pyplot as plt
    # Set the style

def main(args=None):
  parser = argparse.ArgumentParser(description='Attack Tree to CAIRIS Model converter')
  parser.add_argument('dotFile',help='attack tree model to import (Dot format)')
  parser.add_argument('--context',dest='contextName',help='attack context')
  parser.add_argument('--author',dest='originatorName',help='author/s')
  parser.add_argument('--out',dest='outFile',help='output file (CAIRIS format)')
  args = parser.parse_args()
  dotInstance = pydot.graph_from_dot_file(args.dotFile)
  xmlBuf = dotToObstacleModel(dotInstance[0],args.contextName,args.originatorName)
  f = open(args.outFile,'w')
  f.write(xmlBuf)
  f.close()

def OnPopupItemGraph(self, event):

		for row in self.ReportGrid.GetSelectedRows():
			label = self.ReportGrid.GetCellValue(row,0)
			id = self.ReportGrid.GetCellValue(row,1)

			### plot the graph
			### TODO link with properties frame
			for fct in ('extTransition','intTransition', 'outputFnc', 'timeAdvance'):
				filename = "%s(%s)_%s.dot"%(label,str(id),fct)
				path = os.path.join(tempfile.gettempdir(), filename)

				### if path exist
				if os.path.exists(path):
					graph = pydot.graph_from_dot_file(path)
					filename_png = os.path.join(tempfile.gettempdir(),"%s(%s)_%s.png"%(label,str(id),fct))
					graph.write_png(filename_png, prog='dot')

					pylab.figure()
					img = pylab.imread(filename_png)
					pylab.imshow(img)

					fig = pylab.gcf()
					fig.canvas.set_window_title(filename)

					pylab.axis('off')
					pylab.show()

def loadWorkflowFromDotFile( dotfile, workflowcls = None ):
	"""Create a graph from the given dotfile and create a workflow from it.
	The workflow will be fully intiialized with connected process instances.
	The all compatible plugs will automatically be connected for all processes
	connected in the dot file
	
	:param workflowcls: if not None, a dgengine.Graph compatible class to be used
		for workflow creation. Defaults to automation.workflow.Workflow.
	:return: List of initialized workflow classes - as they can be nested, the
		creation of one workflow can actually create several of them"""
	import pydot
	import processes
	from workflow import Workflow
	wflclass = workflowcls or Workflow
	dotgraph = pydot.graph_from_dot_file( dotfile )

	if not dotgraph:
		raise AssertionError( "Returned graph from file %r was None" % dotfile )


	# use the filename as name
	edge_lut = {}									# string -> processinst
	wfl = wflclass( name=dotfile.namebase() )


	for node in dotgraph.get_node_list():
		# can have initializers
		nodeid = node.get_name().strip( '"' )
		# ignore default node
		if nodeid == "node":
			continue

y = radius*math.sin(angle)

        file.write("  %d[pos=\"%f,%f!\",shape=circle];\n"%(i-1, x, y))

    for i in range(len(connections)):
        for j in connections[i]:
            if j not in messages[i]: file.write("%d->%d\n"%(i, j))
        for j in messages[i]:
            file.write("%d->%d[color=\"red\"];\n"%(i, j))

    file.write("labelloc=\"t\";\n")
    file.write("label=\"%s\";\n"%label)
    file.write("}\n")
    file.close()
    
    (graph,) = pydot.graph_from_dot_file("%s.dot"%filename)
    graph.write_png('%s.png'%filename)

# Create dot file by using extra/gprof2dot/gprof2dot.py
    # http://code.google.com/p/jrfonseca/wiki/Gprof2Dot
    dotFilePointer = codecs.open(dotOutputFile, 'wt', UNICODE_ENCODING)
    parser = gprof2dot.PstatsParser(profileOutputFile)
    profile = parser.parse()
    profile.prune(0.5 / 100.0, 0.1 / 100.0)
    dot = gprof2dot.DotWriter(dotFilePointer)
    dot.graph(profile, gprof2dot.TEMPERATURE_COLORMAP)
    dotFilePointer.close()

    infoMsg = "converting dot file into a graph image '%s'" % imageOutputFile
    logger.info(infoMsg)

    # Create graph image (png) by using pydot (python-pydot)
    # http://code.google.com/p/pydot/
    pydotGraph = pydot.graph_from_dot_file(dotOutputFile)

    # Reference: http://stackoverflow.com/questions/38176472/graph-write-pdfiris-pdf-attributeerror-list-object-has-no-attribute-writ
    if isinstance(pydotGraph, list):
        pydotGraph = pydotGraph[0]

    try:
        pydotGraph.write_png(imageOutputFile)
    except OSError:
        errMsg = "profiling requires graphviz installed "
        errMsg += "(Hint: 'sudo apt install graphviz')"
        logger.error(errMsg)
    else:
        infoMsg = "displaying interactive graph with xdot library"
        logger.info(infoMsg)

        # Display interactive Graphviz dot file by using extra/xdot/xdot.py

def gen_graph_from_gv(ifile, odir, oformat="png"):
    (graph,) = pydot.graph_from_dot_file(ifile)
    gen_graph_func = getattr(graph, "write_" + oformat)
    filename = os.path.basename(ifile)
    ofile = odir + "/" + os.path.splitext(filename)[0] + "." + oformat
    gen_graph_func(ofile)

def read_dot(filename):
    """ Read a graphviz dot file using pydot

    Parameters
    ----------
    filename: str
        A DOT (graphviz) filename

    Returns
    -------
    MultiGraph
        A networkx MultiGraph file
    """
    try:
        import pydot
        pydot_graph = pydot.graph_from_dot_file(filename)[0]
        return _from_pydot(pydot_graph)
    except ImportError:
        raise ImportError('Importing graphviz files requires the pydot '
                          'library')

# Create dot file by using extra/gprof2dot/gprof2dot.py
    # http://code.google.com/p/jrfonseca/wiki/Gprof2Dot
    dotFilePointer = codecs.open(dotOutputFile, 'wt', UNICODE_ENCODING)
    parser = gprof2dot.PstatsParser(profileOutputFile)
    profile = parser.parse()
    profile.prune(0.5 / 100.0, 0.1 / 100.0)
    dot = gprof2dot.DotWriter(dotFilePointer)
    dot.graph(profile, gprof2dot.TEMPERATURE_COLORMAP)
    dotFilePointer.close()

    infoMsg = "converting dot file into a graph image '%s'" % imageOutputFile
    logger.info(infoMsg)

    # Create graph image (png) by using pydot (python-pydot)
    # http://code.google.com/p/pydot/
    pydotGraph = pydot.graph_from_dot_file(dotOutputFile)
    pydotGraph.write_png(imageOutputFile)

    infoMsg = "displaying interactive graph with xdot library"
    logger.info(infoMsg)

    # Display interactive Graphviz dot file by using extra/xdot/xdot.py
    # http://code.google.com/p/jrfonseca/wiki/XDot
    win = xdot.DotWindow()
    win.connect('destroy', gtk.main_quit)
    win.set_filter("dot")
    win.open_file(dotOutputFile)
    gobject.timeout_add(1000, win.update, dotOutputFile)
    gtk.main()