fix

backend/app/services/zones.py

@@ -0,0 +1,75 @@
+import numpy as np
+
+from backend.app.models.activity import DataPoint
+
+# Coggan 7-zone power model (% of FTP)
+POWER_ZONES = [
+    {"zone": 1, "name": "Active Recovery", "min_pct": 0, "max_pct": 55},
+    {"zone": 2, "name": "Endurance", "min_pct": 55, "max_pct": 75},
+    {"zone": 3, "name": "Tempo", "min_pct": 75, "max_pct": 90},
+    {"zone": 4, "name": "Threshold", "min_pct": 90, "max_pct": 105},
+    {"zone": 5, "name": "VO2max", "min_pct": 105, "max_pct": 120},
+    {"zone": 6, "name": "Anaerobic", "min_pct": 120, "max_pct": 150},
+    {"zone": 7, "name": "Neuromuscular", "min_pct": 150, "max_pct": 10000},
+]
+
+# 5-zone HR model (% of LTHR)
+HR_ZONES = [
+    {"zone": 1, "name": "Recovery", "min_pct": 0, "max_pct": 81},
+    {"zone": 2, "name": "Aerobic", "min_pct": 81, "max_pct": 90},
+    {"zone": 3, "name": "Tempo", "min_pct": 90, "max_pct": 95},
+    {"zone": 4, "name": "Threshold", "min_pct": 95, "max_pct": 100},
+    {"zone": 5, "name": "Anaerobic", "min_pct": 100, "max_pct": 10000},
+]
+
+
+def calculate_power_zones(
+    data_points: list[DataPoint],
+    ftp: float,
+) -> list[dict]:
+    """Calculate time-in-zone distribution for power."""
+    powers = np.array([dp.power for dp in data_points if dp.power is not None], dtype=float)
+    if len(powers) == 0 or ftp <= 0:
+        return []
+
+    total = len(powers)
+    result = []
+    for z in POWER_ZONES:
+        low = ftp * z["min_pct"] / 100
+        high = ftp * z["max_pct"] / 100
+        seconds = int(np.sum((powers >= low) & (powers < high)))
+        result.append({
+            "zone": z["zone"],
+            "name": z["name"],
+            "min_watts": round(low),
+            "max_watts": round(high) if z["max_pct"] < 10000 else None,
+            "seconds": seconds,
+            "percentage": round(seconds / total * 100, 1) if total > 0 else 0,
+        })
+    return result
+
+
+def calculate_hr_zones(
+    data_points: list[DataPoint],
+    lthr: int,
+) -> list[dict]:
+    """Calculate time-in-zone distribution for heart rate."""
+    hrs = np.array([dp.heart_rate for dp in data_points if dp.heart_rate is not None], dtype=float)
+    if len(hrs) == 0 or lthr <= 0:
+        return []
+
+    total = len(hrs)
+    result = []
+    for z in HR_ZONES:
+        low = lthr * z["min_pct"] / 100
+        high = lthr * z["max_pct"] / 100
+        seconds = int(np.sum((hrs >= low) & (hrs < high)))
+        result.append({
+            "zone": z["zone"],
+            "name": z["name"],
+            "min_bpm": round(low),
+            "max_bpm": round(high) if z["max_pct"] < 10000 else None,
+            "seconds": seconds,
+            "percentage": round(seconds / total * 100, 1) if total > 0 else 0,
+        })
+    return result