diff options
Diffstat (limited to 'bin')
| -rwxr-xr-x | bin/analyze-archive.py | 2 | ||||
| -rwxr-xr-x | bin/analyze-kconfig.py | 7 | ||||
| -rwxr-xr-x | bin/analyze-log.py | 7 |
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: |