diff options
Diffstat (limited to 'bin/analyze-kconfig.py')
| -rwxr-xr-x | bin/analyze-kconfig.py | 15 |
1 files changed, 8 insertions, 7 deletions
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) |