fix: remove locality-only fallback — mac is always required for payment()

The payment() join on (mac, locality) is the only correct path.
Locality alone is not unique in GPCI and produces wrong results.
Remove the conditional fallback, require mac in both DataFrames.

Update all test fixtures and inline test DataFrames to include mac.

src/pfs/calcs/payment.py

@@ -24,21 +24,21 @@ def payment(
     ``Payment = (Work_RVU × Work_GPCI + PE_RVU × PE_GPCI
                 + MP_RVU × MP_GPCI) × Conversion_Factor``
 
-    The join uses ``(mac, locality)`` when both DataFrames have a
+    Joins on ``(mac, locality)`` — both columns are required.
-    ``mac`` column, falling back to ``locality`` alone for backward
+    Locality alone is not unique in the GPCI table (109 rows map to
-    compatibility.  Using the MAC-aware join is critical for accuracy —
+    47 locality codes).  Different MACs apply different GPCI values
-    different Medicare Administrative Contractors apply different GPCI
+    to the same locality number, so joining without MAC produces
-    values to the same locality number.
+    wrong results.
 
     Parameters
     ----------
     rvu : DataFrame
         RVU data with columns: ``hcpcs``, ``work_rvu``,
         ``non_fac_pe_rvu`` or ``fac_pe_rvu``, ``mp_rvu``,
-        ``conv_factor``, ``locality``, and optionally ``mac``.
+        ``conv_factor``, ``mac``, ``locality``.
     gpci : DataFrame
-        GPCI data with columns: ``locality``, ``work_gpci``,
+        GPCI data with columns: ``mac``, ``locality``, ``work_gpci``,
-        ``pe_gpci``, ``mp_gpci``, and optionally ``mac``.
+        ``pe_gpci``, ``mp_gpci``.
     facility : bool
         If True, use facility PE RVUs; otherwise non-facility.
 
@@ -49,15 +49,9 @@ def payment(
     """
     pe_col = "fac_pe_rvu" if facility else "non_fac_pe_rvu"
 
-    # MAC-aware join produces exact CMS carrier file parity (0.00 diff
+    # MAC + locality is the correct join — locality alone is not unique
-    # across 889k rows).  Fall back to locality-only for simple usage.
+    # in the GPCI table and produces wrong results.
-    join_on = (
+    joined = rvu.join(gpci, on=["mac", "locality"], how="left")
-        ["mac", "locality"]
-        if ("mac" in rvu.columns and "mac" in gpci.columns)
-        else ["locality"]
-    )
-
-    joined = rvu.join(gpci, on=join_on, how="left")
 
     return joined.with_columns(
         (

tests/conftest.py

@@ -526,6 +526,7 @@ def rvu_df() -> pl.DataFrame:
             "fac_pe_rvu": [0.41, 0.63, 0.95],
             "mp_rvu": [0.07, 0.11, 0.16],
             "conv_factor": [32.7442, 32.7442, 32.7442],
+            "mac": ["10212", "10212", "10212"],
             "locality": ["0201", "0201", "0201"],
         }
     )
@@ -536,6 +537,7 @@ def gpci_df() -> pl.DataFrame:
     """GPCI data for PFS payment calculation tests."""
     return pl.DataFrame(
         {
+            "mac": ["10212"],
             "locality": ["0201"],
             "work_gpci": [1.0],
             "pe_gpci": [0.998],

tests/pfs/test_payment.py

@@ -133,11 +133,13 @@ class TestPayment:
                 "fac_pe_rvu": [0.41],
                 "mp_rvu": [0.07],
                 "conv_factor": [32.7442],
+                "mac": ["10212"],
                 "locality": ["9999"],  # no match in gpci
             }
         )
         gpci = pl.DataFrame(
             {
+                "mac": ["10212"],
                 "locality": ["0201"],
                 "work_gpci": [1.0],
                 "pe_gpci": [0.998],
@@ -158,11 +160,13 @@ class TestPayment:
                 "fac_pe_rvu": [0.41, 0.41],
                 "mp_rvu": [0.07, 0.07],
                 "conv_factor": [32.7442, 32.7442],
+                "mac": ["10212", "10212"],
                 "locality": ["0201", "0101"],
             }
         )
         gpci = pl.DataFrame(
             {
+                "mac": ["10212", "10212"],
                 "locality": ["0201", "0101"],
                 "work_gpci": [1.0, 1.05],
                 "pe_gpci": [0.998, 1.10],
@@ -188,12 +192,14 @@ class TestPayment:
                 "fac_pe_rvu": [0.41],
                 "mp_rvu": [0.07],
                 "conv_factor": [32.7442],
+                "mac": ["10212"],
                 "locality": ["0201"],
             }
         )
         rvu_double = rvu_base.with_columns(pl.col("conv_factor") * 2)
         gpci = pl.DataFrame(
             {
+                "mac": ["10212"],
                 "locality": ["0201"],
                 "work_gpci": [1.0],
                 "pe_gpci": [0.998],
@@ -215,11 +221,13 @@ class TestPayment:
                 "fac_pe_rvu": [0.0],
                 "mp_rvu": [0.0],
                 "conv_factor": [32.7442],
+                "mac": ["10212"],
                 "locality": ["0201"],
             }
         )
         gpci = pl.DataFrame(
             {
+                "mac": ["10212"],
                 "locality": ["0201"],
                 "work_gpci": [1.0],
                 "pe_gpci": [0.998],
@@ -238,11 +246,13 @@ class TestPayment:
                 "fac_pe_rvu": pl.Series([], dtype=pl.Float64),
                 "mp_rvu": pl.Series([], dtype=pl.Float64),
                 "conv_factor": pl.Series([], dtype=pl.Float64),
+                "mac": pl.Series([], dtype=pl.Utf8),
                 "locality": pl.Series([], dtype=pl.Utf8),
             }
         )
         gpci = pl.DataFrame(
             {
+                "mac": ["10212"],
                 "locality": ["0201"],
                 "work_gpci": [1.0],
                 "pe_gpci": [0.998],