sensitivity random path fix

deconvolution/main/d2_random_path_evaluation.py

@@ -139,18 +139,38 @@ def evaluate_accuracy_paths(path_len,max_paths_per_node=5):
 # ---- sensitivity evaluation
 
 """ given an ordered list of molecules, determine if the graph contains a path of central nodse which have these molecules.
-it does that by testing all possible combinations of d-graphs having those molecules in their central nodes """
+it does that creating a multipartite graph with a source and a sink
+"""
 def is_there_path(graph,molecules_to_nodes,sought_path):
-    possible_central_nodes = []
-    for mol in sought_path:
+    MPG = nx.Graph() # a multipartite graph
+    
+    # construct all levels of the multipartite graph
+    possible_central_nodes = [] 
+    for i,mol in enumerate(sought_path):
         possible_central_nodes += [molecules_to_nodes[mol]]
-    #print(possible_central_nodes)
-    for mols in itertools.product(*possible_central_nodes):
-        if nx.is_connected(graph.subgraph(mols)):
-            #print("found connected path",mols)
-            return True
-    #print("found no connected paths",sought_path)
-    return False
+        for node in possible_central_nodes:
+            MPG.add_node("%d-%s" % (i,node))
+    
+    # construct edges between levels
+    for i in range(len(sought_path)-1):
+        pcn_i = molecules_to_nodes[sought_path[i]]
+        pcn_ip1 = molecules_to_nodes[sought_path[i+1]]
+        for node_i,node_j in itertools.product(pcn_i,pcn_ip1):
+            #print(node_i,node_j)
+            if graph.has_edge(node_i,node_j):
+                MPG.add_edge("%d-%s" %(i,node_i),"%d-%s" % (i+1,node_j))
+
+    # add source/sink
+    MPG.add_node("source")
+    MPG.add_node("sink")
+    pcn_0 = molecules_to_nodes[sought_path[0]]
+    for node in pcn_0:
+        MPG.add_edge("source","0-%s" % node)
+    pcn_end = molecules_to_nodes[sought_path[-1]]
+    for node in pcn_end:
+        MPG.add_edge("%d-%s" % (len(sought_path)-1, node), "sink")
+
+    return nx.has_path(MPG,"source","sink")
 
 def evaluate_sensitivity_paths(path_len,overlap_length=7000):
     all_molecules = set()
@@ -183,9 +203,14 @@ def main():
     p = Pool(12)
     #p.map(evaluate_accuracy_paths, [1,2,4,6,8,10,15,20,50,100,200,500])
     p.map(evaluate_accuracy_paths, [2,4,10,100])
-    p.join()
-    #p.map(evaluate_sensitivity_paths, [1,2,3,4])
+    p.map(evaluate_sensitivity_paths, [2,4,10,100])
     #evaluate_accuracy_paths(100)
+    #evaluate_sensitivity_paths(1)
+    #evaluate_sensitivity_paths(3)
+    #evaluate_sensitivity_paths(10)
+    
+    p.close()        
+    p.join()
 
 if __name__ == "__main__":
     main()