analyze-config, to_json: use paramNames in exported json nodes

4 files changed, 36 insertions, 34 deletions

diff --git a/lib/automata.py b/lib/automata.py
index 5989a50..37fc821 100755
--- a/lib/automata.py
+++ b/lib/automata.py
@@ -274,11 +274,11 @@ class State:
                         new_suffix.extend(suffix)
                         yield new_suffix
 
-    def to_json(self) -> dict:
+    def to_json(self, **kwargs) -> dict:
         """Return JSON encoding of this state object."""
         ret = {"name": self.name, "power": None}
         if self.power is not None:
-            ret["power"] = self.power.to_json()
+            ret["power"] = self.power.to_json(**kwargs)
         return ret
 
     def to_dot(self) -> str:
@@ -432,7 +432,7 @@ class Transition:
                 ret[v] = args[k]
         return ret
 
-    def to_json(self) -> dict:
+    def to_json(self, **kwargs) -> dict:
         """Return JSON encoding of this transition object."""
         ret = {
             "name": self.name,
@@ -449,11 +449,11 @@ class Transition:
             "timeout": None,
         }
         if self.duration is not None:
-            ret["duration"] = self.duration.to_json()
+            ret["duration"] = self.duration.to_json(**kwargs)
         if self.energy is not None:
-            ret["energy"] = self.energy.to_json()
+            ret["energy"] = self.energy.to_json(**kwargs)
         if self.timeout is not None:
-            ret["timeout"] = self.timeout.to_json()
+            ret["timeout"] = self.timeout.to_json(**kwargs)
         return ret
 
     def to_dot(self) -> str:
@@ -785,7 +785,7 @@ class PTA:
 
         return pta
 
-    def to_json(self) -> dict:
+    def to_json(self, **kwargs) -> dict:
         """
         Return JSON encoding of this PTA.
 
@@ -795,9 +795,9 @@ class PTA:
             "parameters": self.parameters,
             "initial_param_values": self.initial_param_values,
             "state": dict(
-                [[state.name, state.to_json()] for state in self.state.values()]
+                [[state.name, state.to_json(**kwargs)] for state in self.state.values()]
             ),
-            "transitions": [trans.to_json() for trans in self.transitions],
+            "transitions": [trans.to_json(**kwargs) for trans in self.transitions],
             "accepting_states": self.accepting_states,
         }
         return ret
diff --git a/lib/functions.py b/lib/functions.py
index 81f6ab5..78dfab8 100644
--- a/lib/functions.py
+++ b/lib/functions.py
@@ -194,7 +194,7 @@ class ModelFunction:
     def webconf_function_map(self):
         return list()
 
-    def to_json(self):
+    def to_json(self, **kwargs):
         """Convert model to JSON."""
         ret = {
             "value": self.value,
@@ -264,8 +264,8 @@ class StaticFunction(ModelFunction):
         """
         return self.value
 
-    def to_json(self):
-        ret = super().to_json()
+    def to_json(self, **kwargs):
+        ret = super().to_json(**kwargs)
         ret.update({"type": "static", "value": self.value})
         return ret
 
@@ -309,16 +309,18 @@ class SplitFunction(ModelFunction):
             ret.extend(child.webconf_function_map())
         return ret
 
-    def to_json(self):
-        ret = super().to_json()
-        ret.update(
-            {
-                "type": "split",
-                "paramIndex": self.param_index,
-                # TODO zusätzlich paramName
-                "child": dict([[k, v.to_json()] for k, v in self.child.items()]),
-            }
-        )
+    def to_json(self, **kwargs):
+        ret = super().to_json(**kwargs)
+        with_param_name = kwargs.get("with_param_name", False)
+        param_names = kwargs.get("param_names", list())
+        update = {
+            "type": "split",
+            "paramIndex": self.param_index,
+            "child": dict([[k, v.to_json(**kwargs)] for k, v in self.child.items()]),
+        }
+        if with_param_name and param_names:
+            update["paramName"] = param_names[self.param_index]
+        ret.update(update)
         return ret
 
     @classmethod
@@ -368,14 +370,14 @@ class SubstateFunction(ModelFunction):
 
         return cumulative_energy / total_duration
 
-    def to_json(self):
-        ret = super().to_json()
+    def to_json(self, **kwargs):
+        ret = super().to_json(**kwargs)
         ret.update(
             {
                 "type": "substate",
                 "sequence": self.sequence_by_count,
-                "countModel": self.count_model.to_json(),
-                "subModel": self.sub_model.to_json(),
+                "countModel": self.count_model.to_json(**kwargs),
+                "subModel": self.sub_model.to_json(**kwargs),
             }
         )
         return ret
@@ -594,8 +596,8 @@ class AnalyticFunction(ModelFunction):
         js_buf = "(param, args) => " + js_buf.replace("np.", "Math.")
         return [(f'"{self.model_function}"', js_buf)]
 
-    def to_json(self):
-        ret = super().to_json()
+    def to_json(self, **kwargs):
+        ret = super().to_json(**kwargs)
         ret.update(
             {
                 "type": "analytic",
diff --git a/lib/model.py b/lib/model.py
index 8cbb012..1e6bb28 100644
--- a/lib/model.py
+++ b/lib/model.py
@@ -358,7 +358,7 @@ class AnalyticModel:
                 )
         return ret
 
-    def to_json(self) -> dict:
+    def to_json(self, **kwargs) -> dict:
         """
         Return JSON encoding of this AnalyticModel.
         """
@@ -369,7 +369,7 @@ class AnalyticModel:
 
         for name in self.names:
             for attr_name, attr in self.attr_by_name[name].items():
-                ret["name"][name][attr_name] = attr.to_json()
+                ret["name"][name][attr_name] = attr.to_json(**kwargs)
 
         return ret
 
@@ -796,7 +796,7 @@ class PTAModel(AnalyticModel):
 
         self.submodel_by_name[name] = PTAModel(by_name, self.parameters, dict())
 
-    def to_json(self):
+    def to_json(self, **kwargs):
         static_model = self.get_static()
         static_quality = self.assess(static_model)
         param_model, param_info = self.get_fitted()
@@ -820,7 +820,7 @@ class PTAModel(AnalyticModel):
         pta.update(
             param_info, static_error=static_quality, function_error=analytic_quality
         )
-        return pta.to_json()
+        return pta.to_json(**kwargs)
 
     def to_dot(self) -> str:
         param_model, param_info = self.get_fitted()
diff --git a/lib/parameters.py b/lib/parameters.py
index d5339c5..1f6f8e3 100644
--- a/lib/parameters.py
+++ b/lib/parameters.py
@@ -525,11 +525,11 @@ class ModelAttribute:
         mean = np.mean(self.data)
         return f"ModelAttribute<{self.name}, {self.attr}, mean={mean}>"
 
-    def to_json(self):
+    def to_json(self, **kwargs):
         ret = {
             "paramNames": self.param_names,
             "argCount": self.arg_count,
-            "modelFunction": self.model_function.to_json(),
+            "modelFunction": self.model_function.to_json(**kwargs),
         }
         return ret