def importGraph(self): # This method is called to import a new graph. # An empty graph to populate is accessible through the "graph" class attribute # (see documentation of class tlp.Graph). # The parameters provided by the user are stored in a Tulip DataSet # and can be accessed through the "dataSet" class attribute # (see documentation of class tlp.DataSet). # The method must return a boolean indicating if the # graph has been successfully imported. if not tulipnx.checkNetworkX(self.pluginProgress): return False graph = self.graph n = self.dataSet["n"] m = self.dataSet["m"] p = self.dataSet["p"] bp_graph = tulipnx.bipartite_random_graph(n, m, p) tulipnx.nxGraphToTlpGraph(bp_graph, graph) return True
def importGraph(self):
# This method is called to import a new graph.
# An empty graph to populate is accessible through the "graph" class attribute
# (see documentation of class tlp.Graph).
# The parameters provided by the user are stored in a Tulip DataSet
# and can be accessed through the "dataSet" class attribute
# (see documentation of class tlp.DataSet).
# The method must return a boolean indicating if the
# graph has been successfully imported.
if not tulipnx.checkNetworkX(self.pluginProgress):
return False
graph = self.graph
graphMLFile = self.dataSet["file::filename"]
nx_graph = None
try:
nx_graph = tulipnx.nx.read_graphml(graphMLFile)
except:
pass
if nx_graph:
tulipnx.nxGraphToTlpGraph(nx_graph, graph)
return True
else:
if self.pluginProgress:
self.pluginProgress.setError("An error occurred when trying to import the GraphML file")
return False