store decision tree attributes of xv models in dataref export

2 files changed, 30 insertions, 6 deletions

diff --git a/bin/analyze-archive.py b/bin/analyze-archive.py
index 0a2845c..5f6be9a 100755
--- a/bin/analyze-archive.py
+++ b/bin/analyze-archive.py
@@ -935,11 +935,16 @@ if __name__ == "__main__":
                 )
 
     if xv_method == "montecarlo":
-        analytic_quality, _ = xv.montecarlo(lambda m: m.get_fitted()[0], xv_count)
+        analytic_quality, xv_analytic_models = xv.montecarlo(
+            lambda m: m.get_fitted()[0], xv_count
+        )
     elif xv_method == "kfold":
-        analytic_quality, _ = xv.kfold(lambda m: m.get_fitted()[0], xv_count)
+        analytic_quality, xv_analytic_models = xv.kfold(
+            lambda m: m.get_fitted()[0], xv_count
+        )
     else:
         analytic_quality = model.assess(param_model)
+        xv_analytic_models = None
 
     if "tex" in show_models or "tex" in show_quality:
         print_text_model_data(
@@ -1053,7 +1058,14 @@ if __name__ == "__main__":
 
     if args.export_dref:
         dref = raw_data.to_dref()
-        dref.update(model.to_dref(static_quality, lut_quality, analytic_quality))
+        dref.update(
+            model.to_dref(
+                static_quality,
+                lut_quality,
+                analytic_quality,
+                xv_models=xv_analytic_models,
+            )
+        )
         dref["constructor duration"] = (constructor_duration, r"\second")
         dref["regression duration"] = (fit_duration, r"\second")
         with open(args.export_dref, "w") as f:
diff --git a/bin/analyze-kconfig.py b/bin/analyze-kconfig.py
index 048c8c9..684d6b3 100755
--- a/bin/analyze-kconfig.py
+++ b/bin/analyze-kconfig.py
@@ -238,7 +238,9 @@ def main():
 
     if xv_method == "montecarlo":
         static_quality, _ = xv.montecarlo(lambda m: m.get_static(), xv_count)
-        analytic_quality, _ = xv.montecarlo(lambda m: m.get_fitted()[0], xv_count)
+        analytic_quality, xv_analytic_models = xv.montecarlo(
+            lambda m: m.get_fitted()[0], xv_count
+        )
         if lut_model:
             lut_quality, _ = xv.montecarlo(
                 lambda m: m.get_param_lut(fallback=True), xv_count
@@ -247,7 +249,9 @@ def main():
             lut_quality = None
     elif xv_method == "kfold":
         static_quality, _ = xv.kfold(lambda m: m.get_static(), xv_count)
-        analytic_quality, _ = xv.kfold(lambda m: m.get_fitted()[0], xv_count)
+        analytic_quality, xv_analytic_models = xv.kfold(
+            lambda m: m.get_fitted()[0], xv_count
+        )
         if lut_model:
             lut_quality, _ = xv.kfold(
                 lambda m: m.get_param_lut(fallback=True), xv_count
@@ -257,6 +261,7 @@ def main():
     else:
         static_quality = model.assess(static_model)
         analytic_quality = model.assess(param_model)
+        xv_analytic_models = none
         if lut_model:
             lut_quality = model.assess(lut_model)
         else:
@@ -324,7 +329,14 @@ def main():
         static_quality = model.assess(static_model)
 
     if args.export_dref:
-        dref.update(model.to_dref(static_quality, lut_quality, analytic_quality))
+        dref.update(
+            model.to_dref(
+                static_quality,
+                lut_quality,
+                analytic_quality,
+                xv_models=xv_analytic_models,
+            )
+        )
         dref["constructor duration"] = (constructor_duration, r"\second")
         dref["regression duration"] = (fit_duration, r"\second")
         with open(args.export_dref, "w") as f: