def test_kappy_influence_json_to_graph():
with open(
path.join(path.dirname(path.abspath(__file__)),
'kappy_influence.json'), 'r') as f:
imap = json.load(f)
graph = im_json_to_graph(imap)
assert graph is not None, 'No graph produced.'
n_nodes = len(graph.nodes())
n_edges = len(graph.edges())
assert n_nodes == 13, \
'Wrong number (%d vs. %d) of nodes on the graph.' % (n_nodes, 13)
assert n_edges == 6, \
"Wrong number (%d vs. %d) of edges on graph." % (n_edges, 4)
def make_influence_map(pysb_model):
"""Return a Kappa influence map."""
kappa = kappy.KappaStd()
model_str = export(pysb_model, 'kappa')
kappa.add_model_string(model_str)
kappa.project_parse()
imap = kappa.analyses_influence_map()
im = im_json_to_graph(imap)
for param in pysb_model.parameters:
try:
im.remove_node(param.name)
except:
pass
return im
def make_influence_map(pysb_model):
"""Return a Kappa influence map."""
kappa = kappy.KappaStd()
model_str = export(pysb_model, 'kappa')
kappa.add_model_string(model_str)
kappa.project_parse()
imap = kappa.analyses_influence_map()
im = im_json_to_graph(imap)
for param in pysb_model.parameters:
try:
im.remove_node(param.name)
except:
pass
return im
def generate_im(self, model):
"""Return a graph representing the influence map generated by Kappa
Parameters
----------
model : pysb.Model
The PySB model whose influence map is to be generated
Returns
-------
graph : networkx.MultiDiGraph
A MultiDiGraph representing the influence map
"""
kappa = kappy.KappaStd()
model_str = export.export(model, 'kappa')
kappa.add_model_string(model_str)
kappa.project_parse()
imap = kappa.analyses_influence_map()
graph = im_json_to_graph(imap)
return graph