Fixed ChimeraModel() fails due to missing positional argument 'sparse' …

…#381  (#433)

## Changes

added sparse arguement where its needed 
## Related issue

- ChimeraModel() fails due to missing positional argument 'sparse' #381 

## Sample code
```
from openjij.model.chimera_model import ChimeraModel
Q={(0, 4): -1, (4, 12): -1}
chimera_model = ChimeraModel(quadratic =Q, unit_num_L=2)
chimera_model.validate_chimera(chimera_model)
```

## Misc
Added dimod types Vartype, SPIN and BINARY as well

openjij/model/chimera_model.py

@@ -12,12 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from __future__ import annotations
-
-from dimod import SPIN
 
+from __future__ import annotations
+from dimod import SPIN, BINARY, Vartype
 import openjij.cxxjij as cj
-
 from openjij.model.model import make_BinaryQuadraticModel
 
 
@@ -28,7 +26,7 @@ def make_ChimeraModel(linear, quadratic):
         generated ChimeraModel class
     """
 
-    class ChimeraModel(make_BinaryQuadraticModel(linear, quadratic)):
+    class ChimeraModel(make_BinaryQuadraticModel(linear, quadratic,sparse=True)):
         """Binary quadnratic model dealing with chimera graph This model deal
 
         with chimera graph. ChimeraModel provide methods to verify whether a
@@ -43,14 +41,14 @@ class ChimeraModel(make_BinaryQuadraticModel(linear, quadratic)):
         """
 
         def __init__(
-                self,
-            linear=None,
-            quadratic=None,
-            offset=0.0,
-            vartype=SPIN,
-            unit_num_L=None,
-            model=None,
-        ):
+                    self,
+                    linear: dict = {},
+                    quadratic: dict = {},
+                    offset: float = 0.0,
+                    vartype: Vartype = SPIN,
+                    unit_num_L: int = 2,
+                    model = None,
+                ):
             if model:
                 super().__init__(
                     model.linear, model.quadratic, model.offset, model.vartype
@@ -316,11 +314,11 @@ def make_ChimeraModel_from_JSON(obj):
 
 
 def ChimeraModel(
-        linear: dict = None,
-        quadratic: dict = None,
+        linear: dict = {},
+        quadratic: dict = {},
         offset: float = 0.0,
         vartype = SPIN,
-        unit_num_L: int = None,
+        unit_num_L: int = 2,
         model = None,
         ):
     """Generate ChimeraModel object
@@ -366,4 +364,4 @@ def ChimeraModel(
 
 ChimeraModel.from_serializable = lambda obj: make_ChimeraModel_from_JSON(
     obj
-).from_serializable(obj)
+).from_serializable(obj)

openjij/sampler/csqa_sampler.py

@@ -31,24 +31,24 @@ class CSQASampler(SQASampler):
     """
 
     def __init__(
-        self, beta=5.0, gamma=1.0, num_sweeps=1000, schedule=None, num_reads=1
+    self, beta=5.0, gamma=1.0, num_sweeps=1000, schedule=None, num_reads=1
     ):
 
         self._default_params = {
-            "beta": beta,
-            "gamma": gamma,
-            "num_sweeps": num_sweeps,
-            "schedule": schedule,
-            "num_reads": num_reads,
-        }
+        "beta": beta,
+        "gamma": gamma,
+        "num_sweeps": num_sweeps,
+        "schedule": schedule,
+        "num_reads": num_reads,
+    }
 
         self._params = {
-            "beta": beta,
-            "gamma": gamma,
-            "num_sweeps": num_sweeps,
-            "schedule": schedule,
-            "num_reads": num_reads,
-        }
+        "beta": beta,
+        "gamma": gamma,
+        "num_sweeps": num_sweeps,
+        "schedule": schedule,
+        "num_reads": num_reads,
+    }
 
     def _get_result(self, system, model):
         info = {}
@@ -62,11 +62,11 @@ def sample_ising(
         self,
         h,
         J,
-        beta=None,
-        gamma=None,
-        num_sweeps=None,
+        beta:float=5.0,
+        gamma:float = 1.0,
+        num_sweeps: int=1000,
         schedule=None,
-        num_reads=None,
+        num_reads:int=1,
         initial_state=None,
         updater=None,
         reinitialize_state=True,
@@ -145,7 +145,7 @@ def init_generator():
 
         # choose updater -------------------------------------------
         sqa_system = cxxjij.system.make_continuous_time_ising(
-            init_generator(), ising_graph, self.gamma
+            init_generator(), ising_graph[0], self._params["gamma"]
         )
         _updater_name = updater.lower().replace("_", "").replace(" ", "")
         if _updater_name == "swendsenwang":

openjij/utils/benchmark.py

@@ -192,12 +192,12 @@ def se_success_probability(
             sampled_states = response.samples()
             se_suc_prob = np.std(
                 [1 if dict(state) in solutions else 0 for state in sampled_states]
-            )
+            )/np.sqrt(len(sampled_states))
         else:
             sampled_states = response.states
             se_suc_prob = np.std(
                 [1 if list(state) in solutions else 0 for state in sampled_states]
-            )
+            )/np.sqrt(len(sampled_states))
 
     return se_suc_prob