Do not run XV on LUT model; it's not helpful.

--show-quality=table now always compares LUT (training data) to model
(training or XV) and static (training or XV)

3 files changed, 22 insertions, 33 deletions

diff --git a/bin/analyze-archive.py b/bin/analyze-archive.py
index d939c44..64792fd 100755
--- a/bin/analyze-archive.py
+++ b/bin/analyze-archive.py
@@ -626,15 +626,7 @@ if __name__ == "__main__":
     if len(show_models):
         print("--- LUT ---")
     lut_model = model.get_param_lut()
-
-    if xv_method == "montecarlo":
-        lut_quality, _ = xv.montecarlo(
-            lambda m: m.get_param_lut(fallback=True), xv_count
-        )
-    elif xv_method == "kfold":
-        lut_quality, _ = xv.kfold(lambda m: m.get_param_lut(fallback=True), xv_count)
-    else:
-        lut_quality = model.assess(lut_model)
+    lut_quality = model.assess(lut_model)
 
     if len(show_models):
         print("--- param model ---")
@@ -772,9 +764,11 @@ if __name__ == "__main__":
 
     if "table" in show_quality or "all" in show_quality:
         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 args.with_substates:
             for submodel in model.submodel_by_name.values():
@@ -785,9 +779,10 @@ if __name__ == "__main__":
                 sub_param_model, sub_param_info = submodel.get_fitted()
                 sub_analytic_quality = submodel.assess(sub_param_model)
                 dfatool.cli.model_quality_table(
-                    ["static", "parameterized", "LUT"],
-                    [sub_static_quality, sub_analytic_quality, sub_lut_quality],
-                    [None, sub_param_info, None],
+                    lut=sub_lut_quality,
+                    model=sub_analytic_quality,
+                    static=sub_static_quality,
+                    model_info=sub_param_info,
                 )
 
     if "overall" in show_quality or "all" in show_quality:
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:
diff --git a/bin/analyze-log.py b/bin/analyze-log.py
index 4a74116..4f5e420 100755
--- a/bin/analyze-log.py
+++ b/bin/analyze-log.py
@@ -284,9 +284,11 @@ 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 args.export_model: