signal op• Data kinds: signal → signal
• Call: import fullseye as fs; fs.ledger.local_std(x, window=9) (to call the implementation directly, import dsp; dsp.local_std(x, window=9); from the registry, ops1d.get("local_std"))
Rolling standard deviation with a stated error bound.
The 1-D counterpart of the image operator local_std (HALCON's deviation_image): the variance is taken after subtracting the mean (E[x^2] - E[x]^2 loses its significant digits on a signal that sits far from zero), unbiased by n/(n-1), and the residual bias of the square root removed by c4(n), so the estimate of sigma itself is unbiased.
*window* is the number of samples in the sliding window, rounded up to the next odd number so the window can be centred (10 becomes 11). The error bound below is computed from the window actually used, so the number quoted stays true. The 2-D side does the same thing — _k(a) snaps the knob to 3/5/7/9 — and the typed bridge that exposes this op as tb_local_std scales the knob continuously, so an even value arrives whenever the knob lands between two odd ones. The relative standard error of each estimate is 1/sqrt(2(n-1)) — 35 % for a 5-sample window, 11 % for 41. Quote it next to any noise figure:
a rolling sigma over 9 samples is +- 25 %, which is wider than most of the changes people try to read off it.
Returns an array the same length as *x* (the ends are reflected).
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
• gallery2d_texture_freq — py -3.11 examples/gallery2d_texture_freq.py
signal as input)create_funct_1d_array · create_funct_1d_pairs · smooth_funct_1d_gauss · smooth_funct_1d_mean · derivate_funct_1d · integrate_funct_1d · zero_crossings_funct_1d · local_min_max_funct_1d
signal)lowpass · highpass · bandpass · envelope · rms · quantize · companding_mu_law · resample
*Provenance: dsp.py — ONED operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.