Excessive API calls bugfix - #2
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Two bugs fixed: 1. Forecaster was making zones×slots API calls (up to 720+) per run. Each predict_for_zone() call triggered a separate load_recent_observations() and weather.get_at() → most timed out → only 1-2 zones got forecasts. Fix: pre-fetch recent_hourly once per zone in forecaster.run(), pass it through predict() → predict_for_zone() so the thread pool does pure math. Also cache zone→camera map in weather module (one get_zones call per process). 2. Forecasts beyond ~25h were always identical (static) because load_recent_observations(zone, future_ts, 25h) returns empty — all lag/MA features were constant FALLBACK=0.5 regardless of hour. Fix: store per-zone per-hour historical averages in zone_meta.json at training time; use them as lag/MA fallback so 3am and 4pm get meaningfully different feature vectors.
When recent data exists but is sparse (e.g. 1-2 readings in 25h window), all get_lag() calls were resolving to the same last-known value, making every prediction slot produce identical feature vectors and therefore identical forecasts. Fix: when no observation exists at the exact lag timestamp, use the per-zone per-hour historical average instead of the last known reading. Same logic applied to MA windows when the window is empty. Result: 3am and 4pm now get meaningfully different lag/MA values.
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