proper kconfig-webconf export

3 files changed, 32 insertions, 0 deletions

diff --git a/lib/functions.py b/lib/functions.py
index 33ecaca..81f6ab5 100644
--- a/lib/functions.py
+++ b/lib/functions.py
@@ -191,6 +191,9 @@ class ModelFunction:
             return self.function_error["mae"]
         return self.value_error["mae"]
 
+    def webconf_function_map(self):
+        return list()
+
     def to_json(self):
         """Convert model to JSON."""
         ret = {
@@ -300,6 +303,12 @@ class SplitFunction(ModelFunction):
         param_value = param_list[self.param_index]
         return self.child[param_value].eval(param_list)
 
+    def webconf_function_map(self):
+        ret = list()
+        for child in self.child.values():
+            ret.extend(child.webconf_function_map())
+        return ret
+
     def to_json(self):
         ret = super().to_json()
         ret.update(
@@ -572,6 +581,19 @@ class AnalyticFunction(ModelFunction):
         """
         return self._function(self.model_args, param_list)
 
+    def webconf_function_map(self):
+        js_buf = self.model_function
+        for i in range(len(self.model_args)):
+            js_buf = js_buf.replace(f"regression_arg({i})", str(self.model_args[i]))
+        for parameter_name in self._parameter_names:
+            js_buf = js_buf.replace(
+                f"parameter({parameter_name})", f"""param["{parameter_name}"]"""
+            )
+        for arg_num in range(self._num_args):
+            js_buf = js_buf.replace(f"function_arg({arg_num})", f"args[{arg_num}]")
+        js_buf = "(param, args) => " + js_buf.replace("np.", "Math.")
+        return [(f'"{self.model_function}"', js_buf)]
+
     def to_json(self):
         ret = super().to_json()
         ret.update(
diff --git a/lib/model.py b/lib/model.py
index 4585dfe..8cbb012 100644
--- a/lib/model.py
+++ b/lib/model.py
@@ -373,6 +373,13 @@ class AnalyticModel:
 
         return ret
 
+    def webconf_function_map(self) -> list:
+        ret = list()
+        for name in self.names:
+            for attr_model in self.attr_by_name[name].values():
+                ret.extend(attr_model.webconf_function_map())
+        return ret
+
     def predict(self, trace, with_fitted=True, wth_lut=False):
         pass
         # TODO trace= ( (name, duration), (name, duration), ...)
diff --git a/lib/parameters.py b/lib/parameters.py
index a8a8451..d5339c5 100644
--- a/lib/parameters.py
+++ b/lib/parameters.py
@@ -537,6 +537,9 @@ class ModelAttribute:
         ret = {"mean": (self.mean, unit), "median": (self.median, unit)}
         return ret
 
+    def webconf_function_map(self):
+        return self.model_function.webconf_function_map()
+
     @staticmethod
     def from_json(cls, name, attr, data):
         param_names = data["paramNames"]