--show-quality=table: customizable --error-metric; default smape, fallback mae

3 files changed, 12 insertions, 4 deletions

diff --git a/bin/analyze-archive.py b/bin/analyze-archive.py
index 535979c..ebd16ce 100755
--- a/bin/analyze-archive.py
+++ b/bin/analyze-archive.py
@@ -768,6 +768,7 @@ if __name__ == "__main__":
             static=static_quality,
             model_info=param_info,
             xv_method=xv_method,
+            error_metric=args.error_metric,
         )
         if args.with_substates:
             for submodel in model.submodel_by_name.values():
@@ -782,6 +783,7 @@ if __name__ == "__main__":
                     model=sub_analytic_quality,
                     static=sub_static_quality,
                     model_info=sub_param_info,
+                    error_metric=args.error_metric,
                 )
 
     if "overall" in show_quality or "all" in show_quality:
diff --git a/bin/analyze-kconfig.py b/bin/analyze-kconfig.py
index 8fcb623..f2c6f8f 100755
--- a/bin/analyze-kconfig.py
+++ b/bin/analyze-kconfig.py
@@ -504,15 +504,18 @@ def main():
 
     if "table" in args.show_quality or "all" in args.show_quality:
         if xv_method is not None:
-            print(f"Model error after cross validation ({xv_method}, {xv_count}):")
+            print(
+                f"Model error ({args.error_metric}) after cross validation ({xv_method}, {xv_count}):"
+            )
         else:
-            print("Model error on training data:")
+            print(f"Model error ({args.error_metric}) on training data:")
         dfatool.cli.model_quality_table(
             lut=lut_quality,
             model=analytic_quality,
             static=static_quality,
             model_info=param_info,
             xv_method=xv_method,
+            error_metric=args.error_metric,
         )
 
     if not args.show_quality:
diff --git a/bin/analyze-log.py b/bin/analyze-log.py
index 7d6f5bc..e3cd7aa 100755
--- a/bin/analyze-log.py
+++ b/bin/analyze-log.py
@@ -278,15 +278,18 @@ def main():
 
     if "table" in args.show_quality or "all" in args.show_quality:
         if xv_method is not None:
-            print(f"Model error after cross validation ({xv_method}, {xv_count}):")
+            print(
+                f"Model error ({args.error_metric}) after cross validation ({xv_method}, {xv_count}):"
+            )
         else:
-            print("Model error on training data:")
+            print(f"Model error ({args.error_metric}) on training data:")
         dfatool.cli.model_quality_table(
             lut=lut_quality,
             model=analytic_quality,
             static=static_quality,
             model_info=param_info,
             xv_method=xv_method,
+            error_metric=args.error_metric,
         )
 
     if args.export_model: