only export model xv results for --export-xv

2 files changed, 10 insertions, 8 deletions

diff --git a/bin/analyze-archive.py b/bin/analyze-archive.py
index a5706de..a725833 100755
--- a/bin/analyze-archive.py
+++ b/bin/analyze-archive.py
@@ -646,7 +646,6 @@ if __name__ == "__main__":
             PTAModel, by_name, parameters, arg_count, force_tree=args.force_tree
         )
         xv.parameter_aware = args.parameter_aware_cross_validation
-        xv.export_filename = args.export_xv
     else:
         xv_method = None
 
@@ -901,10 +900,12 @@ if __name__ == "__main__":
                 )
 
     if xv_method == "montecarlo":
+        xv.export_filename = args.export_xv
         analytic_quality, xv_analytic_models = xv.montecarlo(
             lambda m: m.get_fitted()[0], xv_count
         )
     elif xv_method == "kfold":
+        xv.export_filename = args.export_xv
         analytic_quality, xv_analytic_models = xv.kfold(
             lambda m: m.get_fitted()[0], xv_count
         )
diff --git a/bin/analyze-kconfig.py b/bin/analyze-kconfig.py
index 0bf6ff8..1d03839 100755
--- a/bin/analyze-kconfig.py
+++ b/bin/analyze-kconfig.py
@@ -214,7 +214,6 @@ def main():
             max_std=max_std,
         )
         xv.parameter_aware = args.parameter_aware_cross_validation
-        xv.export_filename = args.export_xv
     else:
         xv_method = None
 
@@ -235,26 +234,28 @@ def main():
 
     if xv_method == "montecarlo":
         static_quality, _ = xv.montecarlo(lambda m: m.get_static(), 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
             )
         else:
             lut_quality = None
-    elif xv_method == "kfold":
-        static_quality, _ = xv.kfold(lambda m: m.get_static(), xv_count)
-        analytic_quality, xv_analytic_models = xv.kfold(
+        xv.export_filename = args.export_xv
+        analytic_quality, xv_analytic_models = xv.montecarlo(
             lambda m: m.get_fitted()[0], xv_count
         )
+    elif xv_method == "kfold":
+        static_quality, _ = xv.kfold(lambda m: m.get_static(), xv_count)
         if lut_model:
             lut_quality, _ = xv.kfold(
                 lambda m: m.get_param_lut(fallback=True), xv_count
             )
         else:
             lut_quality = None
+        xv.export_filename = args.export_xv
+        analytic_quality, xv_analytic_models = xv.kfold(
+            lambda m: m.get_fitted()[0], xv_count
+        )
     else:
         static_quality = model.assess(static_model)
         analytic_quality = model.assess(param_model)