Use the actual scalar param key in the borrowing-constraint benchmark test.

`consumption_dollars_floor` is a DAG function output; the scalar key
in `params` is `consumption_equiv_floor`. Looking up the function name
raised `KeyError` before the constraint check ran.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

Author: hmgaudecker

tests/test_benchmark.py

@@ -72,8 +72,8 @@ def test_benchmark_simulate_obeys_borrowing_constraint() -> None:
 
     df = result.to_dataframe(additional_targets=["cash_on_hand", "equivalence_scale"])
     alive = df.loc[df["regime_name"] != "dead"].copy()
-    consumption_dollars_floor = float(params["consumption_dollars_floor"])
-    floor = consumption_dollars_floor * alive["equivalence_scale"].to_numpy()
+    consumption_equiv_floor = float(params["consumption_equiv_floor"])
+    floor = consumption_equiv_floor * alive["equivalence_scale"].to_numpy()
     rhs = np.maximum(alive["cash_on_hand"].to_numpy(), floor)
     slack = rhs - alive["consumption_dollars"].to_numpy()
     assert (slack >= 0).all(), (