GED readme

README.md

@@ -17,3 +17,35 @@ Data used for training, models and binding pocket visualizations available [here
 * Networkx 2.1+
 * BioPython
 
+
+## Installing
+
+## Sample Usage
+
+## Building Pocket Graph Dataset
+
+## Pocket Graph Drawing
+
+## Computing GED
+
+For a pair of graphs.
+
+```python
+>>> from RNAmigos import ged
+>>> G = nx.read_gpickle('../Data/sample_graphs/3ds7_GNG_P.nxpickle')
+>>> H = nx.read_gpickle('../Data/sample_graphs/3skt_GNG_L.nxpickle')
+>>> graphs = (G, H) #graphs currently need to be pased as single argument for multiprocessing.
+>>> aln, (G, H), time = ged(graphs)
+>>> aln.cost # get distance
+16
+>>> aln.source_map #get node mapping
+{('B', 8): ('A', 7), ('B', 9): ('A', 8), ('B', 59): ('A', 61), ('B', 7): ('A', 6), ('B', 10): ('A', 9), ('B', 37): ('A', 38), ('B', 60): ('A', 62), ('B', 31): ('A', 32), 'NILL': ('A', 37)}
+```
+
+## Graph Embedding
+
+
+## Fingerprint Prediction
+
+
+

RNAmigos/ged.py

@@ -94,7 +94,7 @@ def edge_edit_cost(u,v, g1, g2, node, indel_cost=4, sub_cost=1, ss_break_cost=2)
                 cost = sub_cost
                 if 'B53' in (l1, l2):
                     cost = sys.maxsize
-                if l1 == 'CWW' != l2 'CWW':
+                if 'CWW' in (l1, l2): 
                     cost = ss_break_cost
         elif e1 not in g1.edges and e2 in g2.edges:
             #edge insert+ion