Create salvage_lookup.py

salvage_lookup.py

@@ -0,0 +1,81 @@
+# salvage_lookup.py
+from typing import Dict, Tuple, Optional
+from salvage_table_data import SALVAGE_TABLE
+
+def _interp(x: float, x0: float, x1: float, y0: float, y1: float) -> float:
+    if x0 == x1:
+        return y0
+    # linear interpolation (also used for gentle extrapolation)
+    return y0 + (y1 - y0) * ((x - x0) / (x1 - x0))
+
+def _interp_age(col: Dict[int, float], age: float) -> float:
+    """Interpolate salvage over age (1..20). Extrapolate softly outside."""
+    if not col:
+        return 0.20  # safety
+    ages = sorted(col.keys())  # [1..20]
+    if age <= ages[0]:
+        # extrapolate with slope of first segment
+        a0, a1 = ages[0], ages[1]
+        return _interp(age, a0, a1, col[a0], col[a1])
+    if age >= ages[-1]:
+        a0, a1 = ages[-2], ages[-1]
+        return _interp(age, a0, a1, col[a0], col[a1])
+    # bracket
+    for i in range(len(ages) - 1):
+        a0, a1 = ages[i], ages[i+1]
+        if a0 <= age <= a1:
+            return _interp(age, a0, a1, col[a0], col[a1])
+    return list(col.values())[-1]
+
+def _bands_for(machine_class: str):
+    # tractors have {200,400,600}; combines/forage {100,300,500}
+    keys = sorted(SALVAGE_TABLE[machine_class].keys())
+    return keys
+
+def get_salvage_fraction(machine_class: str, annual_hours: float, age_years: float) -> Optional[float]:
+    """
+    Bilinear interpolation across annual hours band and age.
+    Returns salvage as a fraction of new list price (e.g., 0.31).
+    """
+    if machine_class not in SALVAGE_TABLE:
+        return None
+    table = SALVAGE_TABLE[machine_class]
+    bands = _bands_for(machine_class)
+
+    # choose bracketing hour bands (soft extrapolation at ends)
+    if annual_hours <= bands[0]:
+        lo, hi = bands[0], bands[1] if len(bands) > 1 else bands[0]
+    elif annual_hours >= bands[-1]:
+        lo, hi = bands[-2], bands[-1] if len(bands) > 1 else bands[0]
+    else:
+        lo, hi = None, None
+        for i in range(len(bands) - 1):
+            if bands[i] <= annual_hours <= bands[i+1]:
+                lo, hi = bands[i], bands[i+1]
+                break
+        if lo is None:  # fallback
+            lo, hi = bands[0], bands[-1]
+
+    # age-interp in each column
+    s_lo = _interp_age(table[lo], age_years)
+    s_hi = _interp_age(table[hi], age_years)
+
+    # hour-interp across bands
+    salv = _interp(annual_hours, lo, hi, s_lo, s_hi)
+    # clamp to [0.05, 0.95] to avoid silly results
+    return max(0.05, min(0.95, salv))
+
+def classify_machine_for_salvage(machine_name: str, hp: Optional[float]) -> Optional[str]:
+    m = (machine_name or "").lower()
+    if "combine" in m or "forage" in m:
+        return "combine/forage harvester"
+    if "tractor" in m:
+        # map by hp
+        if hp is None:
+            return "80-149 hp tractor"  # a reasonable default middle class
+        if hp < 80:
+            return "30-79 hp tractor"
+        if hp < 150:
+            return "80-149 hp tractor"
+        return "150+ hp tractor"
+    return None