Stanford Networks

added method to input graph from Stanford Network Database

1 files changed, 40 insertions, 0 deletions

diff --git a/jpa_test/cascade_creation.py b/jpa_test/cascade_creation.py
index ac094b9..f30b208 100644
--- a/jpa_test/cascade_creation.py
+++ b/jpa_test/cascade_creation.py
@@ -15,6 +15,24 @@ class InfluenceGraph(nx.Graph):
         self.add_nodes_from(G.nodes())
         self.add_edges_from(G.edges())
 
+    def createStanfordGraph(self, file):
+        """
+        Takes a file from the Stanford collection of networks
+        Need to remove comments on top of the file
+        Graph still needs to be weighted on the edges
+        """
+        f = open(file, 'r')
+        data = f.readlines()
+        G = nx.DiGraph()
+        for edge in data:
+            split1 = edge.split('\t')
+            split2 = split1[1].split('\n')
+            
+            u = int(split1[0])
+            v = int(split2[0])
+            G.add_edge(u,v)
+        return G
+        
     @property
     def mat(self):
         if not hasattr(self, '_mat'):
@@ -37,7 +55,9 @@ def icc_cascade(G, p_init):
     p_init: proba that node in seed set
     """
     susceptible = np.ones(G.number_of_nodes(), dtype=bool)
+    print susceptible
     active = np.random.rand(G.number_of_nodes()) < p_init
+    print active
     susceptible = susceptible - active
     cascade = []
     while active.any() and susceptible.any():
@@ -53,8 +73,28 @@ def concat_cascades(cascades):
     """
     Concatenate list of cascades into matrix
     """
+    return np.vstack(cascades)
 
 
+
+def createStanfordGraph(file):
+    """
+    Takes a file from the Stanford collection of networks
+    Need to remove comments on top of the file
+    Graph still needs to be weighted on the edges
+    """
+    f = open(file, 'r')
+    data = f.readlines()
+    G = nx.DiGraph()
+    for edge in data:
+        split1 = edge.split('\t')
+        split2 = split1[1].split('\n')
+        
+        u = int(split1[0])
+        v = int(split2[0])
+        G.add_edge(u,v)
+    return G
+
 def test():
     """
     unit test