Add matched training signals, daily recovery and performance analysis

app/stats_sources.py

@@ -12,7 +12,12 @@ def expand(history, q, catalog):
         (spec["name"], expression_tree(spec["expression"], catalog)[0]) for spec in q["derived"]
     ]
     for activity in history:
-        for index, unit in enumerate((activity.analysis_summary or {}).get(q["source"], [])):
+        source = q["source"]
+        units = (activity.analysis_summary or {}).get(source, [])
+        if source == "efforts":
+            units = [{"distance": e["distance"], "duration": e["seconds"],
+                      "effort_time": e["seconds"]} for e in activity.best_efforts or []]
+        for index, unit in enumerate(units):
             if (
                 not isinstance(unit, dict)
                 or not valid(unit.get("distance"))
@@ -23,6 +28,8 @@ def expand(history, q, catalog):
                 continue
             row = copy(activity)
             row.activity_id = activity.id
+            row.parent_title = activity.title
+            row.recording = unit
             row.id = activity.id * 1000000 + index
             row.title = (
                 f"{activity.title} · {'lap' if q['source'] == 'laps' else 'segment'} {index + 1}"
@@ -42,12 +49,16 @@ def expand(history, q, catalog):
                 pace=row.duration_s * 1000 / row.distance_m,
                 speed=row.distance_m / row.duration_s * 3.6,
                 heart_rate=row.avg_hr,
+                matched_minutes=row.duration_s / 60,
+                matched_windows=1,
                 elevation=row.elevation_m,
                 elevation_per_km=row.elevation_m / (row.distance_m / 1000)
                 if valid(row.elevation_m)
                 else None,
             )
-            for key in ("gap", "pace_variability", "heart_rate_drift", "sensor_coverage"):
+            for key in catalog:
+                if key in {"distance", "duration", "pace", "count", "speed", "heart_rate", "elevation", "elevation_per_km", "matched_minutes", "matched_windows"}:
+                    continue
                 row.values[key] = unit.get(key)
             row.analysis_summary = row.values
             row.previous = None