1 files changed, 26 insertions, 6 deletions
diff --git a/lib/model.py b/lib/model.py
index 0026249..dbe05aa 100644
--- a/lib/model.py
+++ b/lib/model.py
@@ -20,6 +20,7 @@ from .utils import (
     by_name_to_by_param,
     by_param_to_by_name,
     regression_measures,
+    param_eq_or_none,
 )
 
 logger = logging.getLogger(__name__)
@@ -85,6 +86,7 @@ class AnalyticModel:
         compute_stats=True,
         force_tree=False,
         max_std=None,
+        by_param=None,
         from_json=None,
     ):
         """
@@ -154,9 +156,18 @@ class AnalyticModel:
             for name, name_data in from_json["name"].items():
                 self.attr_by_name[name] = dict()
                 for attr, attr_data in name_data.items():
-                    self.attr_by_name[name][attr] = ModelAttribute.from_json(
-                        name, attr, attr_data
-                    )
+                    if by_param:
+                        self.attr_by_name[name][attr] = ModelAttribute.from_json(
+                            name,
+                            attr,
+                            attr_data,
+                            data_values=by_name[name][attr],
+                            param_values=by_name[name]["param"],
+                        )
+                    else:
+                        self.attr_by_name[name][attr] = ModelAttribute.from_json(
+                            name, attr, attr_data
+                        )
             self.fit_done = True
             return
 
@@ -255,7 +266,7 @@ class AnalyticModel:
 
         return static_model_getter
 
-    def get_param_lut(self, use_mean=False, fallback=False):
+    def get_param_lut(self, use_mean=False, fallback=False, allow_none=False):
         """
         Get parameter-look-up-table model function: name, attribute, parameter values -> model value.
 
@@ -285,7 +296,16 @@ class AnalyticModel:
                 try:
                     return lut_model[name][key][param]
                 except KeyError:
-                    if fallback:
+                    if allow_none:
+                        keys = filter(
+                            lambda p: param_eq_or_none(param, p),
+                            lut_model[name][key].keys(),
+                        )
+                        values = list(map(lambda p: lut_model[name][key][p], keys))
+                        if not values:
+                            raise
+                        return np.mean(values)
+                    elif fallback:
                         return static_model[name][key]
                     raise
             params = kwargs["params"]
@@ -684,7 +704,7 @@ class AnalyticModel:
             for (nk, pk), v in data["byParam"]:
                 by_param[(nk, tuple(pk))] = v
             by_name = by_param_to_by_name(by_param)
-            return cls(by_name, data["parameters"], from_json=data)
+            return cls(by_name, data["parameters"], by_param=by_param, from_json=data)
         else:
             assert data["parameters"] == parameters
             return cls(by_name, parameters, from_json=data)