point_spectrum — ONED signal op

• 数据种类:positions → table

• 调用: import fullseye as fs; fs.ledger.point_spectrum(positions, extent=None, n_freq=2048, f_max=None, method='direct', weights=None, bins_per_period=8)(要直接调用实现,import dsp; dsp.point_spectrum(positions, extent=None, n_freq=2048, f_max=None, method='direct', weights=None, bins_per_period=8);从台账取用则 ops1d.get("point_spectrum"))

用法

> 该算子的说明尚无译文,以下照原文给出。

Periodogram of event positions — defects, impacts, counts, arrivals.

spectrum needs an evenly sampled signal, but a great deal of industrial data arrives as a *list of positions*: where each defect was on the web, when each particle was counted, at what angle each dent sits. The usual workaround is to histogram the positions and FFT the histogram, which works but hides two choices — bin width and record length — that decide the answer. This operator makes both explicit and returns them.

*method* picks the estimator:

"direct"

the point-process (Bartlett) periodogram

|sum_j w_j exp(-2 pi i f x_j) - rate * integral|^2 / sum_j w_j,

evaluated at each requested frequency. No binning at all, so no bin

width to choose and no aliasing from one. The subtracted term is the

contribution a *uniform* process of the same rate would make; without it

every spectrum peaks at f -> 0 simply because events exist.

"binned"

histogram the positions, then rfft, with the bin width set so the

finest frequency asked for still gets bins_per_period samples per

cycle. Cheaper for very many events, and the result is what a

histogram-and-FFT pipeline would have produced.

The frequency resolution is a property of the record, not of the method. Two periods closer than 1/extent apart cannot be told apart by either estimator, and the returned dict says so in resolution: read it before reading a peak, not after.

A periodic train of events is a comb, not a line. Its harmonics at k/period are as tall as the fundamental, so argmax of this spectrum routinely returns period/k rather than the period. Measured on 93 events (43 spaced 471.24 apart with 1.5 of jitter, plus 50 uniformly random) over a record of 20000: the global maximum lands on 58.90 with direct (the 8th harmonic) and 52.35 with binned (the 9th), while the fundamental is present and prominent in both — direct puts 0.947 of the maximum power at 1/471.24, binned 0.379. Take the lowest frequency whose first few harmonics *all* stand, rather than the tallest line — see examples/poc_web_roll_periodicity.py, which is what this operator was added for.

Returns a dict: freq (cycles per unit of *positions*), power, resolution (1/extent), extent, n_events, method, and bin_width (None for "direct").

Fail-closed: fewer than two events raises ValueError — a periodogram of one point is not a weak measurement, it is not a measurement.

参考(示例数据、文献)

• 示例数据目录(下载 URL / 许可证) —— 2-D 用 skimage.data(BSD/公有领域)加合成图,3-D 给出真实数据源(Stanford/PDS 等)的下载 URL。

• 算子来历与参考文献 —— 该算子族所依据的研究/方法出处。

• 算法的正典(作者、年份)与用途见上面的族使用指南。

可运行的示例(实际调用该算子并已验证的样例)

• poc_web_roll_periodicity — py -3.11 examples/poc_web_roll_periodicity.py

类型可衔接的下一个算子(可接受 table 作为输入)

—

同类别(signal)

lowpass · highpass · bandpass · envelope · rms · local_std · quantize · companding_mu_law


*Provenance: dsp.py — ONED 算子登记表。本条目由 tools/opdocs.py md 自动生成(请勿手工编辑)。*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.