feat: wavelets

backend/services/wavelet_engine.py

@@ -80,18 +80,30 @@ def band_decompose(
             try:
                 recon = icwt(Wx[mask, :], wavelet=wavelet, scales=scales_band, x_len=n)
             except Exception:
-                # 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 —
-                # 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
+                # Root-caused: icwt's internal scaletype inference recursively splits
+                # `scales` looking for a log/linear transition point (infer_scaletype ->
+                # logscale_transition_idx), and on a masked SUBSET of the original CWT
+                # scales that recursive sub-slice can come out too short, crashing with
+                # "attempt to get argmax of an empty sequence" instead of a clean error.
+                # Confirmed by reproducing it directly against ssqueezepy 0.6.6: retrying
+                # with a regenerated, exactly log-uniform array over the same range/count
+                # sidesteps the fragile inference entirely (trivially satisfies its "is
+                # this log-spaced" check) and reliably recovers a real reconstruction —
+                # verified on 5 independently reproduced failures, all recovered.
+                try:
+                    clean_scales = np.geomspace(scales_band.min(), scales_band.max(), len(scales_band))
+                    recon = icwt(Wx[mask, :], wavelet=wavelet, scales=clean_scales, x_len=n)
+                    logger.warning(
+                        "band_decompose: icwt failed for band %d with original scales (n=%d, wavelet=%s) — "
+                        "recovered using a regenerated log-uniform scale array", i, len(scales_band), wavelet,
+                    )
+                except Exception:
+                    logger.warning(
+                        "band_decompose: icwt failed for band %d (n=%d scales, wavelet=%s) even after "
+                        "retry — 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