Replace DFATOOL_RMT_FUNCTION_LEAVES=0 with DFATOOL_RMT_SUBMODEL=static

2 files changed, 6 insertions, 5 deletions

diff --git a/lib/functions.py b/lib/functions.py
index 07f1823..c6ea283 100644
--- a/lib/functions.py
+++ b/lib/functions.py
@@ -1844,7 +1844,7 @@ class analytic:
                 repr_str="β₀ + β₁ * safe_sqrt(x)",
             )
 
-        if os.getenv("DFATOOL_SUBMODEL", "uls") == "fol":
+        if os.getenv("DFATOOL_RMT_SUBMODEL", "uls") == "fol":
             functions = {"linear": functions["linear"]}
 
         return functions
diff --git a/lib/parameters.py b/lib/parameters.py
index bafc2a5..acc77d4 100644
--- a/lib/parameters.py
+++ b/lib/parameters.py
@@ -598,7 +598,7 @@ class ModelAttribute:
 
         # There must be at least 3 distinct data values (≠ None) if an analytic model
         # is to be fitted. For 2 (or fewer) values, decision trees are better.
-        # Exceptions such as DFATOOL_SUBMODEL=fol (2 values sufficient)
+        # Exceptions such as DFATOOL_RMT_SUBMODEL=fol (2 values sufficient)
         # can be handled via DFATOOL_ULS_MIN_DISTINCT_VALUES
         self.min_values_for_analytic_model = int(
             os.getenv("DFATOOL_ULS_MIN_DISTINCT_VALUES", "3")
@@ -1031,9 +1031,10 @@ class ModelAttribute:
         """
 
         if with_function_leaves is None:
-            with_function_leaves = bool(
-                int(os.getenv("DFATOOL_RMT_FUNCTION_LEAVES", "1"))
-            )
+            if os.getenv("DFATOOL_RMT_SUBMODEL", "uls") == "static":
+                with_function_leaves = False
+            else:
+                with_function_leaves = True
         if with_nonbinary_nodes is None:
             with_nonbinary_nodes = bool(
                 int(os.getenv("DFATOOL_RMT_NONBINARY_NODES", "1"))