custom indel

RNAmigos/rna_ged.py

@@ -102,7 +102,7 @@ def edge_edit_cost_custom(u,v, g1, g2, node, sub_matrix, indel_cost=4, sub_cost=
             cost = indel_cost
         else:
             cost = 0
-        return cost + edge_edit_cost(u,v,g1,g2,node.parent)
+        return cost + edge_edit_cost_custom(u,v,g1,g2,node.parent, sub_mat)
 def edge_edit_cost(u,v, g1, g2, node, indel_cost=4, sub_cost=1, ss_break_cost=2):
     """
     Recursively search for edge substitution.
@@ -173,7 +173,7 @@ def node_cost(op, G1, G2):
         else:
             return 0
 
-def cost(op, G1, G2, parent, loop_cost=True, skeleton=False, sub_matrix=None):
+def cost(op, G1, G2, parent, loop_cost=True, skeleton=False, sub_matrix=None, indel=4):
     """
     Returns the cost of an operation.
     TODO: add edge edit cost here.
@@ -188,7 +188,7 @@ def cost(op, G1, G2, parent, loop_cost=True, skeleton=False, sub_matrix=None):
     if loop_cost:
         return edge_edit_cost(u,v,G1,G2,parent) + node_cost(op, G1, G2)
     elif sub_matrix:
-        return edge_edit_cost_custom(u,v,G1,G2, parent, sub_matrix)
+        return edge_edit_cost_custom(u,v,G1,G2, parent, sub_matrix, indel=indel)
     else:
         return edge_edit_cost(u,v,G1,G2, parent)
 
@@ -273,7 +273,8 @@ def local_heuristic(op, parent, g1, g2):
     diff = 2 * (abs(len(unmapped_nei_v) - len(unmapped_nei_u)))
     return diff
 
-def ged(graphs, with_heuristic=False, timeout=30, halt=None, source_only=False, sub_matrix=None):
+def ged(graphs, with_heuristic=False, timeout=30, halt=None, source_only=False, 
+            sub_matrix=None, indel=4):
     """
     Compute GED of two graphs.
     """
@@ -296,14 +297,14 @@ def ged(graphs, with_heuristic=False, timeout=30, halt=None, source_only=False,
 
     for n in g2_nodes:
         op = (g1_nodes[0], n)
-        c = cost(op, g1, g2, None, sub_matrix=sub_matrix)
+        c = cost(op, g1, g2, None, sub_matrix=sub_matrix, indel=indel)
         h=0
         if with_heuristic:
             h = heuristic(op,None, g1, g2)
         heappush(open, (c+h, count, OpNode(op, c, root)))
         count += 1
     del_op = (g1_nodes[0], 'NILL')
-    c = cost(del_op, g1, g2, None, sub_matrix=sub_matrix)
+    c = cost(del_op, g1, g2, None, sub_matrix=sub_matrix, indel=indel)
     h = 0
     if with_heuristic:
         h = heuristic(op,None, g1, g2)
@@ -329,14 +330,14 @@ def ged(graphs, with_heuristic=False, timeout=30, halt=None, source_only=False,
             ops = [(g1_nodes[p_min.depth], u) for u in g2.nodes if
                 u not in p_min.target_map]
             for op in ops:
-                c = cost(op, g1, g2, p_min, sub_matrix=sub_matrix) + cum_cost
+                c = cost(op, g1, g2, p_min, sub_matrix=sub_matrix, indel=indel) + cum_cost
                 h=0
                 if with_heuristic:
                     h = heuristic(op,p_min, g1, g2)
                 heappush(open, (c+h , count, OpNode(op,c,p_min)))
                 count += 1
             del_op = (g1_nodes[p_min.depth], 'NILL')
-            c = cost(del_op, g1, g2, p_min, sub_matrix=sub_matrix) + cum_cost
+            c = cost(del_op, g1, g2, p_min, sub_matrix=sub_matrix, indel=indel) + cum_cost
             h=0
             if with_heuristic:
                 h = heuristic(op,p_min, g1, g2)
@@ -351,7 +352,7 @@ def ged(graphs, with_heuristic=False, timeout=30, halt=None, source_only=False,
                 cur_node = p_min
                 return (p_min, graphs, time.time() - start)
             for op in ops:
-                c = cost(op, g1, g2, p_min, sub_matrix=sub_matrix) + cum_cost
+                c = cost(op, g1, g2, p_min, sub_matrix=sub_matrix, indel=indel) + cum_cost
                 h=0
                 if with_heuristic:
                     h = heuristic(op,p_min, g1, g2)