Added option to Edge weight the graph when splitting

Including this line of code will split the graph using edge weighting

G.graph['edge_weight_attr'] = 'weight'

python/examples/metis-block-graph/block_to_graph_test.py

@@ -42,8 +42,8 @@ def view_pydot(pdot):
 
 import metis
 G = read_data()['Graph']
-G.graph['node_weight_attr'] = ['weights']
-
+G.graph['node_weight_attr'] = ['weight']
+G.graph['edge_weight_attr'] = 'weight'
 (edgecuts, parts) = metis.part_graph(G, 2,tpwgts=[0.5,0.5])
 
 colors = ['red','blue','green','magenta']

python/examples/metis-block-graph/block_to_graph_test_large.py

@@ -15,12 +15,13 @@ def view_pydot(pdot):
 face_matches =  glennht_to_con('kenji_diced_1.p3d_conn')
 max_block_index = [(f['block1']['block_index'], f['block2']['block_index']) for f in face_matches]
 max_block_index = np.max(np.array(max_block_index).flatten())
-block_sizes = [(np.random.randint(33,101), np.random.randint(33,101), np.random.randint(33,101)) for _ in range(max_block_index)]
+block_sizes = [(np.random.randint(33,101)*np.random.randint(33,101)*np.random.randint(33,101)) for _ in range(max_block_index)]
 G = block_connectivity_to_graph(face_matches,block_sizes)
 
 #%% Split the Graph
 import metis
 G.graph['node_weight_attr'] = ['weight']
+G.graph['edge_weight_attr'] = 'weight'
 nparts = 3
 (edgecuts, parts) = metis.part_graph(G, nparts,tpwgts=[0.3,0.3,0.4])
 nodes_per_part = list()
@@ -29,7 +30,7 @@ def view_pydot(pdot):
     indexes = [p for p, e in enumerate(parts) if e == i]
     nodes = 0 
     for idx in indexes:  
-        nodes += block_sizes[idx-1][0]*block_sizes[idx-1][1]*block_sizes[idx-1][2]
+        nodes += block_sizes[idx-1]
     nodes_per_part.append(nodes)
 
 #%% Plotting