diff options
Diffstat (limited to 'bin/analyze-kconfig.py')
| -rwxr-xr-x | bin/analyze-kconfig.py | 22 |
1 files changed, 7 insertions, 15 deletions
diff --git a/bin/analyze-kconfig.py b/bin/analyze-kconfig.py index 0900255..7eb63c8 100755 --- a/bin/analyze-kconfig.py +++ b/bin/analyze-kconfig.py @@ -418,6 +418,7 @@ def main(): static_model = model.get_static() try: lut_model = model.get_param_lut() + lut_quality = model.assess(lut_model) except RuntimeError as e: if args.force_tree: # this is to be expected @@ -425,6 +426,7 @@ def main(): else: logging.warning(f"Skipping LUT model: {e}") lut_model = None + lut_quality = None if args.export_csv: for name in model.names: @@ -444,24 +446,12 @@ def main(): static_quality, _ = xv.montecarlo( lambda m: m.get_static(), xv_count, static=True ) - if lut_model: - lut_quality, _ = xv.montecarlo( - lambda m: m.get_param_lut(fallback=True), xv_count, static=True - ) - else: - lut_quality = None 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, static=True) - if lut_model: - lut_quality, _ = xv.kfold( - lambda m: m.get_param_lut(fallback=True), xv_count, static=True - ) - 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 @@ -521,9 +511,11 @@ def main(): else: print("Model error on training data:") dfatool.cli.model_quality_table( - ["static", "parameterized", "LUT"], - [static_quality, analytic_quality, lut_quality], - [None, param_info, None], + lut=lut_quality, + model=analytic_quality, + static=static_quality, + model_info=param_info, + xv_method=xv_method, ) if not args.show_quality: |