evaluate E = P*t model. Seems slightly better in some cases

TODO: Fix send duration model generation for cc1200, should improve eval

2 files changed, 19 insertions, 0 deletions

diff --git a/lib/loader.py b/lib/loader.py
index 43d591b..577336a 100644
--- a/lib/loader.py
+++ b/lib/loader.py
@@ -1181,6 +1181,9 @@ def _add_trace_data_to_aggregate(aggregate, key, element):
                 "power",
                 "rel_power_prev",
                 "rel_power_next",
+                "energy",
+                "rel_energy_prev",
+                "rel_energy_next",
             ]
             # Uncomment this line if you also want to analyze mean transition power
             # aggregate[key]['attributes'].append('power')
diff --git a/lib/model.py b/lib/model.py
index 781a29c..9070ece 100644
--- a/lib/model.py
+++ b/lib/model.py
@@ -1132,6 +1132,22 @@ class PTAModel:
                 )
                 measures = regression_measures(predicted_data, elem[key])
                 detailed_results[name][key] = measures
+            if elem["isa"] == "transition":
+                predicted_data = np.array(
+                    list(
+                        map(
+                            lambda i: model_function(
+                                name, "power", param=elem["param"][i]
+                            )
+                            * model_function(name, "duration", param=elem["param"][i]),
+                            range(len(elem["power"])),
+                        )
+                    )
+                )
+                measures = regression_measures(
+                    predicted_data, elem["power"] * elem["duration"]
+                )
+                detailed_results[name]["energy_Pt"] = measures
 
         return {"by_name": detailed_results}