Merge pull request #36 from arcondello/bugfix_8_variable_constraint

Bugfix: 8 variable constraint

dwavebinarycsp/compilers/stitcher.py

@@ -131,6 +131,13 @@ def aux_factory():
     for const in csp.constraints:
         configurations = const.configurations
 
+        if len(const.variables) > max_graph_size:
+            msg = ("The given csp contains a constraint {const} with {num_var} variables. "
+                   "This cannot be mapped to a graph with {max_graph_size} nodes. "
+                   "Consider checking whether your constraint is irreducible."
+                   "").format(const=const, num_var=len(const.variables), max_graph_size=max_graph_size)
+            raise ImpossibleBQM(msg)
+
         pmodel = None
 
         if len(const) == 0:
@@ -149,7 +156,7 @@ def aux_factory():
         # if configurations in penalty_models:
         #     raise NotImplementedError
 
-        for G in iter_complete_graphs(const.variables, max_graph_size, aux):
+        for G in iter_complete_graphs(const.variables, max_graph_size + 1, aux):
 
             # construct a specification
             spec = pm.Specification(

requirements.txt

@@ -1,6 +1,6 @@
 penaltymodel[all]==0.14.0
 networkx==2.0
-dimod==0.6.7
+dimod==0.6.8
 six==1.11.0
 
 coverage

tests/test_int_stitcher.py

@@ -95,7 +95,7 @@ def test_csp_one_xor(self):
                     # if classical gap is less than 2
                     self.assertTrue(csp.check(sample))
 
-    def test_csp_one_xor(self):
+    def test_csp_one_xor_impossible(self):
 
         csp = dwavebinarycsp.ConstraintSatisfactionProblem(dwavebinarycsp.BINARY)
 
@@ -105,3 +105,35 @@ def test_csp_one_xor(self):
 
         with self.assertRaises(pm.ImpossiblePenaltyModel):
             bqm = dwavebinarycsp.stitch(csp, max_graph_size=3)
+
+    def test_eight_variable_constraint_smoketest(self):
+
+        csp = dwavebinarycsp.ConstraintSatisfactionProblem(dwavebinarycsp.BINARY)
+
+        variables = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']
+
+        # this is reducible but for our purposes here that's fine
+        def f(a, b, c, d, e, f, g, h):
+            if a and b:
+                return False
+            if c and d:
+                return False
+            if e and f:
+                return False
+            return not (g and h)
+
+        csp.add_constraint(f, variables)
+
+        bqm = dwavebinarycsp.stitch(csp)
+
+        resp = dimod.ExactSolver().sample(bqm)
+
+        ground_energy = min(resp.data_vectors['energy'])
+
+        for sample, energy in resp.data(['sample', 'energy']):
+            if energy == ground_energy:
+                self.assertTrue(csp.check(sample))
+            else:
+                if abs(energy - ground_energy) < 2:
+                    # if classical gap is less than 2
+                    self.assertTrue(csp.check(sample))

tests/test_stitcher.py

@@ -25,7 +25,7 @@
 from dwavebinarycsp.compilers import stitcher
 
 
-class TestStitch(unittest.TestCase):
+class TestIterCompleteGraph(unittest.TestCase):
     def test_iter_complete_graph_simple(self):
 
         graphs = list(stitcher.iter_complete_graphs(4, 6))
@@ -76,6 +76,19 @@ def factory():
 
         self.assertEqual(set(G2), {'a', 'b', 'aux0', 'aux1'})
 
+    def test_start_8_stop_8(self):
+        variables = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']
+
+        # should produce at least one graph
+        G, = stitcher.iter_complete_graphs(variables, 9)
+
+        G0 = nx.complete_graph(variables)
+
+        self.assertEqual(G.nodes, G0.nodes)
+        self.assertEqual(G.edges, G0.edges)
+
+
+class TestStitch(unittest.TestCase):
     def test__bqm_from_1sat(self):
         const = dwavebinarycsp.Constraint.from_configurations([(0,)], ['a'], dwavebinarycsp.BINARY)
 
@@ -192,6 +205,17 @@ def test_stitch_max_graph_size_is_1(self):
         with self.assertRaises(dwavebinarycsp.exceptions.ImpossibleBQM):
             bqm = dwavebinarycsp.stitch(csp, max_graph_size=1)
 
+    def test_stitch_constraint_too_large(self):
+        csp = dwavebinarycsp.ConstraintSatisfactionProblem(dwavebinarycsp.BINARY)
+
+        def f(*args):
+            return all(args)
+
+        csp.add_constraint(f, list('abcdefghijk'))  # 11 variables
+
+        with self.assertRaises(dwavebinarycsp.exceptions.ImpossibleBQM):
+            bqm = dwavebinarycsp.stitch(csp, max_graph_size=8)
+
 
 def powerset(iterable):
     "powerset([1,2,3]) --> () (1,) (2,) (3,) (1,2) (1,3) (2,3) (1,2,3)"