refactor --show-model=param into lib/cli.py

4 files changed, 35 insertions, 65 deletions

diff --git a/bin/analyze-archive.py b/bin/analyze-archive.py
index ffc0d67..c91150d 100755
--- a/bin/analyze-archive.py
+++ b/bin/analyze-archive.py
@@ -679,35 +679,15 @@ if __name__ == "__main__":
         for state in model.states:
             for attribute in model.attributes(state):
                 info = param_info(state, attribute)
-                if type(info) is df.AnalyticFunction:
-                    dfatool.cli.print_analyticinfo(f"{state:10s} {attribute:15s}", info)
-                elif type(info) is df.CARTFunction:
-                    dfatool.cli.print_cartinfo(
-                        f"{state:10s} {attribute:15s}", info, model.parameters
-                    )
-                elif type(info) is df.SplitFunction:
-                    dfatool.cli.print_splitinfo(
-                        model.parameters, info, f"{state:10s} {attribute:15s}"
-                    )
-                elif type(info) is df.StaticFunction:
-                    dfatool.cli.print_staticinfo(f"{state:10s} {attribute:15s}", info)
-                elif type(info) is df.SubstateFunction:
-                    print(f"{state:10s} {attribute:15s}: Substate (TODO)")
+                dfatool.cli.print_model(
+                    f"{state:10s} {attribute:15s}", info, model.parameters
+                )
         for trans in model.transitions:
             for attribute in model.attributes(trans):
                 info = param_info(trans, attribute)
-                if type(info) is df.AnalyticFunction:
-                    dfatool.cli.print_analyticinfo(f"{trans:10s} {attribute:15s}", info)
-                elif type(info) is df.CARTFunction:
-                    dfatool.cli.print_cartinfo(
-                        f"{trans:10s} {attribute:15s}", info, model.parameters
-                    )
-                elif type(info) is df.SplitFunction:
-                    dfatool.cli.print_splitinfo(
-                        model.parameters, info, f"{trans:10s} {attribute:15s}"
-                    )
-                elif type(info) is df.SubstateFunction:
-                    print(f"{state:10s} {attribute:15s}: Substate (TODO)")
+                dfatool.cli.print_model(
+                    f"{trans:10s} {attribute:15s}", info, model.parameters
+                )
         if args.with_substates:
             for submodel in model.submodel_by_name.values():
                 sub_param_model, sub_param_info = submodel.get_fitted()
diff --git a/bin/analyze-kconfig.py b/bin/analyze-kconfig.py
index baf3cc7..098d6ba 100755
--- a/bin/analyze-kconfig.py
+++ b/bin/analyze-kconfig.py
@@ -528,20 +528,9 @@ def main():
         for name in model.names:
             for attribute in model.attributes(name):
                 info = param_info(name, attribute)
-                if type(info) is df.AnalyticFunction:
-                    dfatool.cli.print_analyticinfo(f"{name:20s} {attribute:15s}", info)
-                elif type(info) is df.CARTFunction:
-                    dfatool.cli.print_cartinfo(
-                        f"{name:20s} {attribute:15s}", info, model.parameters
-                    )
-                elif type(info) is df.FOLFunction:
-                    dfatool.cli.print_analyticinfo(f"{name:20s} {attribute:15s}", info)
-                elif type(info) is df.SplitFunction:
-                    dfatool.cli.print_splitinfo(
-                        model.parameters, info, f"{name:20s} {attribute:15s}"
-                    )
-                elif type(info) is df.StaticFunction:
-                    dfatool.cli.print_staticinfo(f"{name:10s} {attribute:15s}", info)
+                dfatool.cli.print_model(
+                    f"{name:20s} {attribute:15s}", info, model.parameters
+                )
 
     if "table" in args.show_quality or "all" in args.show_quality:
         if xv_method is not None:
diff --git a/bin/analyze-log.py b/bin/analyze-log.py
index b1dc6ba..9c24641 100755
--- a/bin/analyze-log.py
+++ b/bin/analyze-log.py
@@ -227,18 +227,9 @@ def main():
         for name in sorted(model.names):
             for attribute in sorted(model.attributes(name)):
                 info = param_info(name, attribute)
-                if type(info) is df.AnalyticFunction:
-                    dfatool.cli.print_analyticinfo(f"{name:10s} {attribute:15s}", info)
-                elif type(info) is df.CARTFunction:
-                    dfatool.cli.print_cartinfo(
-                        f"{name:10s} {attribute:15s}", info, model.parameters
-                    )
-                elif type(info) is df.SplitFunction:
-                    dfatool.cli.print_splitinfo(
-                        model.parameters, info, f"{name:10s} {attribute:15s}"
-                    )
-                elif type(info) is df.StaticFunction:
-                    dfatool.cli.print_staticinfo(f"{state:10s} {attribute:15s}", info)
+                dfatool.cli.print_model(
+                    f"{name:10s} {attribute:15s}", info, model.parameters
+                )
 
     if "table" in args.show_quality or "all" in args.show_quality:
         if xv_method is not None:
diff --git a/lib/cli.py b/lib/cli.py
index 5accc1f..0ebe42d 100644
--- a/lib/cli.py
+++ b/lib/cli.py
@@ -1,11 +1,6 @@
 #!/usr/bin/env python3
 
-from dfatool.functions import (
-    SplitFunction,
-    AnalyticFunction,
-    StaticFunction,
-    FOLFunction,
-)
+import dfatool.functions as df
 import dfatool.plotter
 import logging
 import numpy as np
@@ -115,21 +110,36 @@ def _print_cartinfo(prefix, model, feature_names):
 
 
 def print_splitinfo(param_names, info, prefix=""):
-    if type(info) is SplitFunction:
+    if type(info) is df.SplitFunction:
         for k, v in info.child.items():
             if info.param_index < len(param_names):
                 param_name = param_names[info.param_index]
             else:
                 param_name = f"arg{info.param_index - len(param_names)}"
             print_splitinfo(param_names, v, f"{prefix} {param_name}={k}")
-    elif type(info) is AnalyticFunction:
+    elif type(info) is df.AnalyticFunction:
         print_analyticinfo(prefix, info)
-    elif type(info) is StaticFunction:
+    elif type(info) is df.StaticFunction:
         print(f"{prefix}: {info.value}")
     else:
         print(f"{prefix}: UNKNOWN")
 
 
+def print_model(prefix, info, feature_names):
+    if type(info) is df.StaticFunction:
+        print_staticinfo(prefix, info)
+    elif type(info) is df.AnalyticFunction:
+        print_analyticinfo(prefix, info)
+    elif type(info) is df.FOLFunction:
+        print_analyticinfo(prefix, info)
+    elif type(info) is df.CARTFunction:
+        print_cartinfo(prefix, info, feature_names)
+    elif type(info) is df.SplitFunction:
+        print_splitinfo(feature_names, info, prefix)
+    else:
+        print(f"{prefix}: {type(info)} UNIMPLEMENTED")
+
+
 def print_model_size(model):
     for name in model.names:
         for attribute in model.attributes(name):
@@ -196,13 +206,13 @@ def model_quality_table(
                     info is None
                     or (
                         key != "energy_Pt"
-                        and type(info(key, attr)) is not StaticFunction
+                        and type(info(key, attr)) is not df.StaticFunction
                     )
                     or (
                         key == "energy_Pt"
                         and (
-                            type(info(key, "power")) is not StaticFunction
-                            or type(info(key, "duration")) is not StaticFunction
+                            type(info(key, "power")) is not df.StaticFunction
+                            or type(info(key, "duration")) is not df.StaticFunction
                         )
                     )
                 ):
@@ -210,7 +220,7 @@ def model_quality_table(
                     buf += format_quality_measures(result, error_metric=error_metric)
                 else:
                     buf += f"""{"----":>7s} """
-            if type(model_info(key, attr)) is not StaticFunction:
+            if type(model_info(key, attr)) is not df.StaticFunction:
                 if model[key][attr]["mae"] > static[key][attr]["mae"]:
                     buf += "  :-("
                 elif (