From 4154848fd356f13c77e054b769e7bf4b11a20f73 Mon Sep 17 00:00:00 2001 From: OpenSquared Date: Sun, 19 Jul 2026 12:55:45 +0200 Subject: [PATCH] feat: wavelets --- backend/services/wavelet_engine.py | 45 +++++++++++++++++++++- frontend/src/pages/InstrumentDashboard.tsx | 8 +++- 2 files changed, 50 insertions(+), 3 deletions(-) diff --git a/backend/services/wavelet_engine.py b/backend/services/wavelet_engine.py index 467a166..b885c59 100644 --- a/backend/services/wavelet_engine.py +++ b/backend/services/wavelet_engine.py @@ -4,12 +4,15 @@ c:\\DataS\\InstrumentSimulator\\backend\\app\\wavelet.py (project "Macro Causal No project-specific dependencies — pure numpy/ssqueezepy, safe to call from any service. """ +import logging import warnings import numpy as np from ssqueezepy import cwt, icwt from ssqueezepy.utils.cwt_utils import center_frequency +logger = logging.getLogger(__name__) + MIN_SCALES_PER_BAND = 4 # Fixed period (days) lower-bounds for bands 0..5, independent of the analysis @@ -72,6 +75,7 @@ def band_decompose( mask = (log_scales >= lo) & (log_scales <= hi if i == num_levels - 1 else log_scales < hi) scales_band = scales[mask] + reconstruction_failed = False if len(scales_band) >= MIN_SCALES_PER_BAND: try: recon = icwt(Wx[mask, :], wavelet=wavelet, scales=scales_band, x_len=n) @@ -79,14 +83,26 @@ def band_decompose( # ssqueezepy's internal scale-type inference (log vs linear spacing # detection) can raise on some narrow slices depending on how many # scales land in this bucket for this specific series length. - # Treat as a negligible band instead of failing the whole request. + # Treat as a negligible band instead of failing the whole request — + # but log it (previously silently swallowed) and flag it, since a flat + # zero band otherwise looks identical to "genuinely no energy here". + logger.warning( + "band_decompose: icwt failed for band %d (n=%d scales, wavelet=%s) — " + "falling back to a zero band", i, len(scales_band), wavelet, exc_info=True, + ) recon = np.zeros(n) + reconstruction_failed = True scale_lo, scale_hi = float(scales_band.min()), float(scales_band.max()) else: # Too few scales in this bucket for a stable reconstruction; report a # flat zero band (its content ends up folded into the residual) so the # band list always stays num_levels long. + logger.warning( + "band_decompose: only %d scale(s) in band %d (< %d minimum) — falling back to a zero band", + len(scales_band), i, MIN_SCALES_PER_BAND, + ) recon = np.zeros(n) + reconstruction_failed = True scale_lo, scale_hi = float(np.exp(lo)), float(np.exp(hi)) freq_at_scale_hi = center_frequency(wavelet, scale=scale_hi, N=n) @@ -105,6 +121,7 @@ def band_decompose( "period_low_days": period_low_days, "period_high_days": period_high_days, "series": [round(float(v), 6) for v in recon], + "reconstruction_failed": reconstruction_failed, } ) @@ -148,6 +165,7 @@ def windowed_band_decompose( all_residual: list[float] = [] band_series: list[list[float]] = [[] for _ in range(num_levels)] band_meta: list[dict | None] = [None] * num_levels + band_failed: list[bool] = [False] * num_levels chunk_count = 0 start = 0 @@ -164,6 +182,10 @@ def windowed_band_decompose( for band in chunk["bands"]: band_series[band["index"]].extend(band["series"]) band_meta[band["index"]] = band + # OR across chunks: if any slice couldn't reconstruct this band, flag the + # whole concatenated series as unreliable rather than losing that signal + # when a later chunk happens to succeed and overwrites band_meta. + band_failed[band["index"]] = band_failed[band["index"]] or band.get("reconstruction_failed", False) start = end bands = [] @@ -176,6 +198,7 @@ def windowed_band_decompose( "period_low_days": meta["period_low_days"], "period_high_days": meta["period_high_days"], "series": band_series[i], + "reconstruction_failed": band_failed[i], } ) @@ -216,6 +239,7 @@ def rolling_causal_bands( out_original: list[float] = [] band_series: list[list[float]] = [[] for _ in range(num_levels)] band_labels = [f"bande {i + 1}" for i in range(num_levels)] + band_failed = [False] * num_levels last_tip: list[float] | None = None recomputations = 0 @@ -229,6 +253,8 @@ def rolling_causal_bands( result = band_decompose(window_values, window_dates, num_levels, wavelet) last_tip = [band["series"][-1] for band in result["bands"]] band_labels = [band["label"] for band in result["bands"]] + for i, band in enumerate(result["bands"]): + band_failed[i] = band_failed[i] or band.get("reconstruction_failed", False) recomputations += 1 out_dates.append(dates[t]) out_original.append(values[t]) @@ -242,6 +268,7 @@ def rolling_causal_bands( "period_low_days": None, "period_high_days": None, "series": band_series[i], + "reconstruction_failed": band_failed[i], } for i in range(num_levels) ] @@ -324,6 +351,7 @@ def band_decompose_ssq( hi_period = period_edges[i + 1] if i + 1 < len(period_edges) else float(periods.max()) mask = (periods >= lo_period) & (periods <= hi_period if i == num_levels - 1 else periods < hi_period) + reconstruction_failed = False if mask.any(): try: Tx_band = np.zeros_like(Tx) @@ -333,12 +361,20 @@ def band_decompose_ssq( recon = np.real(issq_cwt(Tx_band, wavelet=wavelet)) except Exception: # Defensive, mirroring band_decompose: never let one band's edge - # case fail the whole request. + # case fail the whole request — but log it and flag it (see + # band_decompose's identical fix for why this used to be silent). + logger.warning( + "band_decompose_ssq: issq_cwt failed for band %d (wavelet=%s) — " + "falling back to a zero band", i, wavelet, exc_info=True, + ) recon = np.zeros(n) + reconstruction_failed = True energy = np.sum(np.abs(Tx[mask, :]) ** 2, axis=0) else: + logger.warning("band_decompose_ssq: no frequencies fall in band %d — falling back to a zero band", i) recon = np.zeros(n) energy = np.zeros(n) + reconstruction_failed = True period_low_days = round(float(lo_period), 1) period_high_days = round(float(hi_period), 1) @@ -350,6 +386,7 @@ def band_decompose_ssq( "period_high_days": period_high_days, "series": [round(float(v), 6) for v in recon], "energy": [round(float(v), 8) for v in energy], + "reconstruction_failed": reconstruction_failed, } ) @@ -397,6 +434,7 @@ def rolling_causal_bands_ssq( energy_series: list[list[float]] = [[] for _ in range(num_levels)] ridge_series: list[float | None] = [] band_labels = [f"bande {i + 1}" for i in range(num_levels)] + band_failed = [False] * num_levels last_tip: list[float] | None = None last_energy_tip: list[float] | None = None last_ridge_tip: float | None = None @@ -414,6 +452,8 @@ def rolling_causal_bands_ssq( last_energy_tip = [band["energy"][-1] for band in result["bands"]] last_ridge_tip = result["ridge_period_days"][-1] band_labels = [band["label"] for band in result["bands"]] + for i, band in enumerate(result["bands"]): + band_failed[i] = band_failed[i] or band.get("reconstruction_failed", False) recomputations += 1 out_dates.append(dates[t]) out_original.append(values[t]) @@ -430,6 +470,7 @@ def rolling_causal_bands_ssq( "period_high_days": None, "series": band_series[i], "energy": energy_series[i], + "reconstruction_failed": band_failed[i], } for i in range(num_levels) ] diff --git a/frontend/src/pages/InstrumentDashboard.tsx b/frontend/src/pages/InstrumentDashboard.tsx index 0691aa5..405dfc3 100644 --- a/frontend/src/pages/InstrumentDashboard.tsx +++ b/frontend/src/pages/InstrumentDashboard.tsx @@ -1719,7 +1719,7 @@ export default function InstrumentDashboard({ instrumentIdProp, isVisible }: { i const WAVELET_SLOPE_LAG = 5 const waveletEnergy = useMemo(() => { - const bands: { label: string; series: number[] }[] = waveletData?.bands ?? [] + const bands: { label: string; series: number[]; reconstruction_failed?: boolean }[] = waveletData?.bands ?? [] const n = bands[0]?.series?.length ?? 0 if (!bands.length || n === 0) return null @@ -2184,6 +2184,9 @@ export default function InstrumentDashboard({ instrumentIdProp, isVisible }: { i })} /> {b.label} + {b.reconstruction_failed && ( + ⚠ + )} ))} @@ -2272,6 +2275,9 @@ export default function InstrumentDashboard({ instrumentIdProp, isVisible }: { i
{b.label} {isSlow && (lente)} + {b.reconstruction_failed && ( + ⚠ + )}