cplx_laurent_coeffs — MATH complex op

数据种类:cpoints × cpointstable

调用:import mathops; mathops.cplx_laurent_coeffs(z, fz, kmin=-1, kmax=4)(或 opsmath.get("cplx_laurent_coeffs"))

用法

均匀采样圆周上的 Laurent(以及 Taylor)系数 —— 含留数。

> 以下的详细说明为原文 —— 摘要与标题已翻译。

For `f holomorphic on an annulus around c`,

`f(z) = sum_k c_k (z - c)^k` with

`c_k = 1/(2*pi*i) ∮ f(zeta)/(zeta - c)^(k+1) dzeta`. On a circle of

radius `r sampled at n` equally spaced angles this becomes a discrete

Fourier sum, `c_k = (1/(n r^k)) sum_j f_j exp(-i k theta_j)` — the

trapezoidal rule in the angle, where it converges geometrically rather

than as `O(n^-2)` (Trefethen & Weideman 2014, "The exponentially

convergent trapezoidal rule").

`c_-1 **is the residue** at c (when c` is the only singularity

inside), `c_k for k >= 0` are the Taylor coefficients

`f^(k)(c)/k!, and a non-zero c_-m for m > 1` reveals a pole of

order `m. Measured on the unit circle with f = 1/(z - 0.5)`,

`n = 64: c_-1 = 1 and c_-2 = 0.5` to 1e-16 (machine precision).

Returns a dict: `k (int64 orders, kmin..kmax) · c` (complex128

coefficients) · `center · radius`. The centre is the sample mean,

which is exact for a uniformly sampled circle.

Orientation, and how it differs from the rest of the family: the sum

runs over the sample *set*, not the sample *order*, so this op always

returns the coefficients of the positively oriented circle — the standard

definition — whatever order the points arrive in. Feed a clockwise circle

and `c_-1 still comes back +` the residue, while

`cplx_contour_integral / (2*pi*i) on the same points returns -` it

(verified). Both are right; they answer different questions (the intrinsic

coefficient vs the integral along *this* traversal). Do not cross-check one

against the other without fixing the orientation first.

Honest limitation — aliasing: the discrete sum cannot distinguish

`c_k from c_{k+n}`, so a coefficient carries the alias sum

`sum_m c_{k+m n} r^{m n}`. That is negligible for a rapidly converging

series (the `0.5^64` term above) and ruinous near the annulus boundary.

Requesting more than `n` coefficients is refused for the same reason.

Raises `ValueError`: the samples are not a uniformly spaced circle

(unequal radii or unequal angular gaps beyond `1e-8` relative — this op

is *not* valid on an arbitrary contour, and silently pretending otherwise

would return numbers that mean nothing), `kmin > kmax, more than n`

coefficients requested, non-integer orders, and a coefficient that

overflowed (`r^-k` for a small radius and a large negative order).

HALCON: no operator.

该族通用的输入契约(fail-closed)

mathops 的每个算子都先校验输入再计算(不让任何东西无声通过):

• **complex 输入一律 ValueError** —— 强制转成 float64 会无声丢掉虚部(numpy 只发一个 ComplexWarning,然后返回一个「看着合理却是错的」实数)。请显式写出 .real/.imag/abs(),或改用支持复数的 complexops。

• **含被掩元素的 masked array 一律 ValueError** —— 拒绝「剥掉掩码直接使用下面原值」的隐式转换。请显式选择填充还是丢弃。

• **所有输入中的 NaN/Inf 一律 ValueError**(明确给出个数后拒绝 —— 它会污染整个结果)。

形状严格:不对 1-D 与 2-D 做隐式提升或广播(向量槽位收到矩阵、矩阵槽位收到向量都是 ValueError;请显式 reshape)。

尺寸上限:接受矩阵的算子与 stat_histogram 的 bins,超过 mathops.MAX_ELEMENTS(2^26 ≈ 6700 万个元素)即 ValueError

详细使用指南

math_metrology 族使用指南

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)

math_complexpy -3.11 examples/math_complex.py

类型可衔接的下一个算子(可接受 table 作为输入)

同类别(complex)

cplx_contour_circle · cplx_poly_eval · cplx_contour_integral · cplx_winding_number · cplx_cauchy_value · cplx_argument_principle · cplx_joukowski · cplx_mobius


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