Simplfy results normalization

Author: gsvgit

cfpq_add_context/add_contexts.py

@@ -76,7 +76,7 @@ def to_label_decomposed_graph(graph, automata_size, initial_graph_size):
     entrypoints << graph.reduce_columnwise(op.lor)
     #mask_v(op.lor) << Vector.from_coo(list(set(range(0,graph.nrows)).difference(entrypoints.to_coo(values=False)[0])), values=True, dtype = BOOL)
 
-    mask_v(op.lor) << Vector.from_coo([i * automata_size for i in range(0, initial_graph_size)], values=True, dtype = BOOL, size= graph.ncols)
+    mask_v("any") << Vector.from_coo([i * automata_size for i in range(0, initial_graph_size)], values=True, dtype = BOOL, size = graph.ncols)
 
     load_i = Matrix(UINT64, graph.ncols, graph.nrows, name = "load_i_after_intersection")
     load_i << graph.select(graphblas.select.select_load).apply(graphblas.unary.decode_load)
@@ -201,11 +201,12 @@ def normalize(solver_result, initial_graph_nvertices):
 
     normalization_start = time.perf_counter()
 
-    c = solver_result.ncols // initial_graph_nvertices
-    start_vertices = set([i * c for i in range(0,initial_graph_nvertices)])
+    atm_size = solver_result.ncols // initial_graph_nvertices
+    # start_vertices = set([i * atm_size for i in range(0,initial_graph_nvertices)])
     edges = solver_result.to_edgelist()
     edges = zip(edges[0], edges[1])
-    new_edges = set([(_edg[0] // c, _edg[1] // c) for (_edg, _lbl) in edges if _edg[0] in start_vertices])
+    #new_edges = set([(_edg[0] // atm_size, _edg[1] // atm_size) for (_edg, _lbl) in edges if _edg[0] in start_vertices])
+    new_edges = set([(_edg[0] // atm_size, _edg[1] // atm_size) for (_edg, _lbl) in edges])
     result = Matrix.from_edgelist(new_edges, values=True, dtype=BOOL, nrows = initial_graph_nvertices,
                                              ncols=initial_graph_nvertices, name = "normalized_solver_result")
     normalization_end = time.perf_counter()