def run_graph(dot):
""" Runs graphviz to see if the syntax is good. """
graph = AGraph()
graph = graph.from_string(dot)
extension = 'png'
graph.draw(path='output.png', prog='dot', format=extension)
sys.exit(0)
def run_graph(dot):
""" Runs graphviz to see if the syntax is good. """
graph = AGraph()
graph = graph.from_string(dot)
extension = 'png'
graph.draw(path='output.png', prog='dot', format=extension)
sys.exit(0)
def processLines(self):
if len(self.lines) == 0:
return
self.identifier = self.lines[0][2:]
s = '\n'.join(self.lines)
A = AGraph()
G = A.from_string(s)
self.processGraph(G)
def processLines(self):
if len(self.lines) == 0:
return
self.identifier = self.lines[0][2:]
s = '\n'.join(self.lines)
A = AGraph()
G = A.from_string(s)
self.processGraph(G)
def consensus_network_image(self, net, outfile, cm, node_positions):
def colorize_edge(weight):
colors = "9876543210"
breakpoints = [.1, .2, .3, .4, .5, .6, .7, .8, .9]
return "#" + str(colors[bisect(breakpoints, weight)]) * 6
def node(n, position):
s = "\t\"%s\"" % n.name
if position:
x, y = position
s += " [pos=\"%d,%d\"]" % (x, y)
return s + ";"
nodes = net.nodes
positions = node_positions
dotstr = "\n".join(
["digraph G {"] +
[node(n, pos) for n,pos in zip(nodes, positions)] +
["\t\"%s\" -> \"%s\" [color=\"%s\"];" % \
(nodes[src].name, nodes[dest].name, colorize_edge(cm[src][dest])) \
for src,dest in net.edges
] +
["}"]
)
fd, fname = tempfile.mkstemp()
open(fname, 'w').write(dotstr)
# needless repitition of network.as_gml() here:
A = AGraph()
net = A.from_string(string=dotstr)
G = nx.from_agraph(net)
nx.write_gml(G, outfile.replace(".png", ".gml"))
os.system("dot -n1 -Tpng -o%s %s" % (outfile, fname))
os.system("dot -n1 -Tsvg -o%s %s" %
(outfile.replace(".png", ".svg"), fname))
os.remove(fname)
def as_gml(self, filename):
dstr = self.as_dotstring()
A = AGraph()
net = A.from_string(string=dstr)
G = nx.from_agraph(net)
nx.write_gml(G, filename)
def consensus_network(self, filename, threshold, write_gml=False):
"""
**Purpose**
Draw a consensus network for a specified threshold
**Arguments**
filename (Required)
filename to save the png and svg to.
threshold (Required)
threshold value 0..1.0 for the consensus network
write_gml (Optional, default=False)
write the GML file for loadinging into e.g. Cytoscape
"""
assert self.result, "bayes.consensus_network: Bayes network not learnt yet"
assert filename, "You must specify a filename"
assert threshold, "You must specify a threshold"
assert threshold <= 1.0, "threshold is >= 1.0!"
assert threshold >= 0.0, "threshold is <= 0.0!"
#print [n.score for n in list(reversed(self.result.networks))]
this_posterior = posterior.from_sorted_scored_networks(self.result.nodes, list(reversed(self.result.networks)))
net_this_threshold = this_posterior.consensus_network(threshold)
cm = this_posterior.consensus_matrix # A method/property...
top = this_posterior[0] # posterior object
top.layout()
nodes = net_this_threshold.nodes
A = AGraph()
net = A.from_string(string=net_this_threshold.as_dotstring()) # Load their Network into a AGraph and NX.
G = nx.from_agraph(net)
edge_cols = [colorize_edge(cm[src][dest]) for src, dest in net_this_threshold.edges]
#pos = nx.graphviz_layout(G, 'dot')
#fig = plot.figure()
#ax = fig.add_subplot(111)
#nx.draw_graphviz(G, 'dot', with_labels=True, edge_color=edge_cols, linewidths=0)
#fig.tight_layout()
#fig.savefig(filename.replace(".png", ".pgv.png"))
dotstr = "\n".join(
["digraph G {"] +
[node(n, pos) for n, pos in zip(nodes, top.node_positions)] +
["\t\"%s\" -> \"%s\" [color=\"%s\"];" % (nodes[src].name, nodes[dest].name, colorize_edge(cm[src][dest])) for src,dest in net_this_threshold.edges] +
["}"])
fd, fname = tempfile.mkstemp()
open(fname, 'w').write(dotstr)
if write_gml:
nx.write_gml(G, filename.replace(".png", ".gml"))
# Better done through pygraphviz gives different results...
os.system("dot -n1 -Tpng -o%s %s" % (filename, fname))
os.system("dot -n1 -Tsvg -o%s %s" % (filename.replace(".png", ".svg"), fname))
os.remove(fname)
config.log.info("bayes.consensus_network: Saved '%s'" % filename)