derivate_funct_1d — ONED function op

• 数据种类:signal → signal

• 调用: import fullseye as fs; fs.ledger.derivate_funct_1d(y)(要直接调用实现,import funct1d; funct1d.derivate_funct_1d(y);从台账取用则 ops1d.get("derivate_funct_1d"))

用法

> 该算子的说明尚无译文,以下照原文给出。

First derivative by central differences (HALCON `derivate_funct_1d`).

Units are y per sample (the x-grid is the index): for a physical signal

sampled every `dt seconds, divide the result by dt`. Interior points

use the second-order central difference; the two boundary points use one-sided

differences (`numpy.gradient`).

:param y: 1-D function, at least 2 samples (a derivative needs a neighbour).

:returns: float64 array of the same length.

:raises ValueError: non-1-D / NaN / Inf input, or fewer than 2 samples.

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_tree_ring_dendro — py -3.11 examples/poc_tree_ring_dendro.py

• poc_veiling_glare — py -3.11 examples/poc_veiling_glare.py

• signal_funct1d — py -3.11 examples/signal_funct1d.py

类型可衔接的下一个算子(可接受 signal 作为输入)

create_funct_1d_array · create_funct_1d_pairs · smooth_funct_1d_gauss · smooth_funct_1d_mean · integrate_funct_1d · zero_crossings_funct_1d · local_min_max_funct_1d · abs_funct_1d

同类别(function)

create_funct_1d_array · create_funct_1d_pairs · smooth_funct_1d_gauss · smooth_funct_1d_mean · integrate_funct_1d · zero_crossings_funct_1d · local_min_max_funct_1d · abs_funct_1d

*Provenance: funct1d.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.