feat: cockpit

backend/services/wavelet_signals.py

@@ -231,7 +231,33 @@ def _technical_desk_wavelet_config() -> Dict:
     return (desk.get("config") or {}).get("signals") or {}
 
 
-def scan_watchlist_wavelet_signals() -> List[Dict]:
+def _fetch_close_series(ticker: str, saxo_symbol: Optional[str]):
+    """Saxo-first when this watchlist instrument has a saxo_quote_symbol link, yfinance
+    otherwise or as a silent fallback on any Saxo failure — same pattern as
+    routers/wavelet.py's _fetch_history, duplicated locally rather than importing across a
+    router boundary. Needed because several Watchlist instruments (BRENT, COPPER...) have no
+    real yfinance ticker at all — get_historical(ticker, ...) always failed for them, which
+    silently dropped them out of the per-cycle scan entirely (one bad ticker just gets
+    skipped, see the try/except around the caller) — that's why the Wavelets Signal card
+    only ever showed the yfinance-recognized subset of the Watchlist."""
+    if saxo_symbol:
+        try:
+            from services.database import get_saxo_catalog_by_symbol
+            from services.saxo_client import get_price_history
+            entry = get_saxo_catalog_by_symbol(saxo_symbol)
+            asset_type = entry["asset_type"] if entry else "FxSpot"
+            bars = get_price_history(saxo_symbol, asset_type, days=400)
+            return [b["close"] for b in bars], [b["date"] for b in bars]
+        except Exception as e:
+            import logging
+            logging.getLogger(__name__).warning(f"[wavelet_signals] Saxo fetch failed for '{saxo_symbol}', falling back to yfinance: {e}")
+
+    from services.data_fetcher import get_historical
+    hist = get_historical(ticker, period="1y", interval="1d")
+    return [h["close"] for h in hist], [h["date"] for h in hist]
+
+
+def scan_watchlist_wavelet_signals(run_id: Optional[str] = None) -> List[Dict]:
     """Compute a causal (no-look-ahead) band decomposition for each watchlist
     instrument. Every (ticker, band) gets a row every cycle — current slope/
     value/energy state always, plus signal_kind/direction/params_json when one
@@ -239,9 +265,13 @@ def scan_watchlist_wavelet_signals() -> List[Dict]:
     wins, evaluated extremum -> level_threshold -> trend_flatten ->
     acceleration -> band_cross -> energy_threshold). ridge_shift is evaluated
     once per ticker (not per band — the ridge is a single track for the whole
-    decomposition) and stored as an extra band_label="ridge" row."""
-    from services.database import get_instruments_watchlist
-    from services.data_fetcher import get_historical
+    decomposition) and stored as an extra band_label="ridge" row.
+
+    Also caches the full (untruncated) decomposition per ticker in
+    wavelet_decomposition_cache — Instrument Analysis's Wavelet tab reads that instead of
+    running its own live decomposition on open, so it always agrees with the Watchlist
+    Signal card and never needs a click just to show the current state."""
+    from services.database import get_instruments_watchlist, save_wavelet_decomposition_cache
     from services.wavelet_engine import rolling_causal_bands, rolling_causal_bands_ssq
 
     sig_cfg = _technical_desk_wavelet_config()
@@ -267,11 +297,9 @@ def scan_watchlist_wavelet_signals() -> List[Dict]:
     for item in get_instruments_watchlist():
         ticker = item["ticker"]
         try:
-            hist = get_historical(ticker, period="1y", interval="1d")
-            if len(hist) < lookback + 32:
+            values, dates = _fetch_close_series(ticker, item.get("saxo_quote_symbol"))
+            if len(values) < lookback + 32:
                 continue
-            values = [h["close"] for h in hist]
-            dates = [h["date"] for h in hist]
             start_idx = max(lookback, len(values) - 60)
             decomposed = decomposer(
                 values, dates,
@@ -280,6 +308,7 @@ def scan_watchlist_wavelet_signals() -> List[Dict]:
             )
             if not decomposed["dates"]:
                 continue
+            save_wavelet_decomposition_cache(ticker, run_id, method, wavelet, num_levels, lookback, decomposed)
             price_at_signal = decomposed["original"][-1]
             bands = decomposed["bands"]
 
@@ -378,6 +407,6 @@ def scan_watchlist_wavelet_signals() -> List[Dict]:
 
 def compute_and_save_wavelet_signals(run_id: str) -> List[Dict]:
     from services.database import save_wavelet_signals
-    results = scan_watchlist_wavelet_signals()
+    results = scan_watchlist_wavelet_signals(run_id)
     save_wavelet_signals(run_id, results)
     return results