routine commit

1 files changed, 13 insertions, 3 deletions

diff --git a/src/cascade_creation.py b/src/cascade_creation.py
index 1c365b9..a71fce7 100644
--- a/src/cascade_creation.py
+++ b/src/cascade_creation.py
@@ -9,9 +9,11 @@ class InfluenceGraph(nx.DiGraph):
     """
     networkX graph with mat and logmat attributes
     """
-    def __init__(self, max_proba=None, min_proba=None, *args, **kwargs):
+    def __init__(self, max_proba=None, min_proba=None,sparse_edges=False,
+                 *args, **kwargs):
         self.max_proba = max_proba
         self.min_proba = min_proba
+        self.sparse_edges=sparse_edges
         super(InfluenceGraph, self).__init__(*args, **kwargs)
 
     def erdos_init(self, n, p):
@@ -61,8 +63,16 @@ class InfluenceGraph(nx.DiGraph):
     @property
     def mat(self):
         if not hasattr(self, '_mat'):
-            self._mat = self.max_proba * np.random.rand(len(self), len(self)
+            if self.min_proba is None or self.max_proba is None:
+                print("You forgot to initialize the min and max proba")
+                self._mat = np.zeros((self.number_of_nodes(), self.number_of_nodes()))
+            else:
+                self._mat = self.max_proba * np.random.rand(len(self), len(self)
                         ) * np.asarray(nx.adjacency_matrix(self).todense().T)
+        if self.sparse_edges:
+            #Adding sparse non-edges to the graph!
+            self._mat += .1 * np.random.rand(len(self), len(self)
+                            ) * np.random.binomial(1, p=.33, size=(len(self), len(self)))
         return self._mat
 
     @property
@@ -175,7 +185,7 @@ def add_edges_from_proba_vector(G, p_node, node, floor_cstt):
     floor_parent = np.nonzero(p_node*(p_node > floor_cstt))
     for parent in floor_parent[0]:
         G.add_edge(parent, node)
-    #TODO: update G's mat matrix
+    G.mat[node] = p_node.T
     return G