passed test except hubo case

OpenJij · May 15, 2021 · b1ce296 · b1ce296
1 parent 34fa3e9
commit b1ce296
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Showing 23 changed files with 127 additions and 1,531 deletions.
diff --git a/benchmark/benchmark2.py b/benchmark/benchmark2.py
@@ -21,7 +21,7 @@
 NUM_CALL_UPDATER = 1000
 
 
-bqm = oj.BinaryQuadraticModel(h, J, var_type='SPIN')
+bqm = oj.BinaryQuadraticModel(h, J, vartype='SPIN')
 
 graph = bqm.get_cxxjij_ising_graph(sparse=False)
 

diff --git a/examples/python/example_sa.py b/examples/python/example_sa.py
@@ -33,7 +33,7 @@ class SASampler(BaseSampler):
         energy_bias (float):
             Energy bias.
 
-        var_type (str):
+        vartype (str):
             Type of variables: 'SPIN' or 'BINARY' which mean {-1, 1} or {0, 1}.
 
         indices (int):
@@ -144,8 +144,8 @@ def sample_ising(self, h, J,
 
         """
 
-        var_type = openjij.SPIN
-        model = openjij.BinaryQuadraticModel(h=h, J=J, var_type=var_type)
+        vartype = openjij.SPIN
+        model = openjij.BinaryQuadraticModel(h=h, J=J, vartype=vartype)
         return self.sampling(model,
                              initial_state=initial_state, updater=updater,
                              reinitilize_state=reinitilize_state,
@@ -194,8 +194,8 @@ def sample_qubo(self, Q,
 
         """
 
-        var_type = openjij.BINARY
-        model = openjij.BinaryQuadraticModel(Q=Q, var_type=var_type)
+        vartype = openjij.BINARY
+        model = openjij.BinaryQuadraticModel(Q=Q, vartype=vartype)
         return self.sampling(model,
                              initial_state=initial_state, updater=updater,
                              reinitilize_state=reinitilize_state,
@@ -218,7 +218,7 @@ def sampling(self, model,
 
             def _generate_init_state(): return ising_graph.gen_spin()
         else:
-            if model.var_type == openjij.SPIN:
+            if model.vartype == openjij.SPIN:
                 _init_state = np.array(initial_state)
             else:  # BINARY
                 _init_state = (2*np.array(initial_state)-1).astype(np.int)
@@ -276,7 +276,7 @@ def exec_sampling():
                     need_to_convert_from_spin=True))
         sampling_time = exec_sampling()
         response = openjij.Response(
-            var_type=model.var_type, indices=self.indices)
+            vartype=model.vartype, indices=self.indices)
         response.update_ising_states_energies(states, energies)
 
         response.info['sampling_time'] = sampling_time * \

diff --git a/examples/python/optimizaiton.py b/examples/python/optimizaiton.py
@@ -40,7 +40,7 @@ class SQASampler(BaseSampler):
         energy_bias (float):
             Energy bias.
 
-        var_type (str):
+        vartype (str):
             Type of variables: 'SPIN' or 'BINARY' which mean {-1, 1} or {0, 1}.
 
         indices (int):
@@ -147,8 +147,8 @@ def sample_ising(self, h, J,
 
         """
 
-        var_type = openjij.SPIN
-        bqm = openjij.BinaryQuadraticModel(h=h, J=J, var_type=var_type)
+        vartype = openjij.SPIN
+        bqm = openjij.BinaryQuadraticModel(h=h, J=J, vartype=vartype)
         return self.sampling(bqm,
                              initial_state=initial_state, updater=updater,
                              reinitilize_state=reinitilize_state,
@@ -185,8 +185,8 @@ def sample_qubo(self, Q,
 
         """
 
-        var_type = openjij.BINARY
-        bqm = openjij.BinaryQuadraticModel(Q=Q, var_type=var_type)
+        vartype = openjij.BINARY
+        bqm = openjij.BinaryQuadraticModel(Q=Q, vartype=vartype)
         return self.sampling(bqm,
                              initial_state=initial_state, updater=updater,
                              reinitilize_state=reinitilize_state,
@@ -210,7 +210,7 @@ def sampling(self, model,
             def _generate_init_state(): return [ising_graph.gen_spin()
                                                 for _ in range(self.trotter)]
         else:
-            if model.var_type == openjij.SPIN:
+            if model.vartype == openjij.SPIN:
                 trotter_init_state = [np.array(initial_state)
                                       for _ in range(self.trotter)]
             else:  # BINARY
@@ -268,7 +268,7 @@ def exec_sampling():
 
         sampling_time = exec_sampling()
         response = openjij.Response(
-            var_type=model.var_type, indices=self.indices)
+            vartype=model.vartype, indices=self.indices)
         response.update_trotter_ising_states_energies(q_states, q_energies)
 
         response.info['sampling_time'] = sampling_time * \
@@ -302,7 +302,7 @@ def reverse_annealing():
     sqa = oj.SASampler(schedule=reverse_schedule, iteration=20)
     res = sqa.sample_qubo(qubo, initial_state=initial_state)
     print(res.min_samples)
-    model = oj.BinaryQuadraticModel(Q=qubo, var_type='BINARY')
+    model = oj.BinaryQuadraticModel(Q=qubo, vartype='BINARY')
     print(model.calc_energy(res.min_samples['min_states'][0]))
 
     print('RQA')

diff --git a/openjij/__init__.py b/openjij/__init__.py
@@ -1,8 +1,7 @@
 
 from .__version import __version__
-from .variable_type import SPIN, BINARY, Vartype, cast_var_type
+from .variable_type import SPIN, BINARY, Vartype, cast_vartype
 from .sampler import Response
 from .sampler import SASampler, SQASampler, CSQASampler
-from .sampler import GPUChimeraSQASampler, GPUChimeraSASampler, CMOSAnnealer
-from .model import BinaryQuadraticModel, BinaryPolynomialModel, KingGraph, ChimeraModel
+from .model import BinaryQuadraticModel, BinaryPolynomialModel
 from .utils import solver_benchmark, convert_response
diff --git a/openjij/model/__init__.py b/openjij/model/__init__.py
@@ -1,3 +1 @@
 from .model import *
-from .king_graph import *
-from .chimera_model import *