complex op• 데이터 종류: cpoints × cpoints → table
• 호출: import fullseye as fs; fs.ledger.cplx_laurent_coeffs(z, fz, kmin=-1, kmax=4)(구현을 직접 호출하려면 import mathops; mathops.cplx_laurent_coeffs(z, fz, kmin=-1, kmax=4), 원장에서 가져오려면 opsmath.get("cplx_laurent_coeffs"))
균일하게 표본화한 원 위의 로랑(및 테일러) 계수 —— 유수 포함.
> 아래 상세 설명은 원문입니다 —— 요약과 제목은 번역되어 있습니다.
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.
mathops 의 모든 연산자는 입력을 검증한 뒤에 계산합니다(조용히 통과시키지 않습니다):
• complex 입력은 ValueError —— float64 로의 강제 변환은 허수부를 조용히 버립니다(numpy 는 ComplexWarning 만 내고 「그럴듯하게 틀린」 실수를 돌려줍니다). .real/.imag/abs() 를 명시하거나 복소수를 다루는 complexops 를 쓰세요.
• masked 요소가 있는 masked array 는 ValueError —— 마스크를 벗겨 아래 원값을 쓰는 암묵 변환을 거부합니다. 채울지 버릴지를 명시하세요.
• NaN/Inf 는 모든 입력에서 ValueError(개수를 명시하고 거부 —— 결과 전체로 전파되므로).
• 형상은 엄격: 1-D 와 2-D 를 암묵적으로 승격·브로드캐스트하지 않습니다(vector 슬롯에 matrix, matrix 슬롯에 vector 는 ValueError. reshape 를 명시하세요).
• 크기 상한: 행렬을 받는 연산자와 stat_histogram 의 bins 는 mathops.MAX_ELEMENTS(2^26 ≈ 6700 만 요소)를 넘으면 ValueError.
• 샘플 데이터 카탈로그(DL URL / 라이선스) —— 2-D 는 skimage.data(BSD/public)+ 합성, 3-D 는 실데이터 소스(Stanford/PDS 등)의 DL URL.
• 연산자의 내력·참고문헌 —— 이 연산자 족의 바탕이 된 연구/기법의 출처.
• 알고리즘의 정전(저자·연도)과 용도는 위의 패밀리 사용 가이드에 적혀 있습니다.
• math_complex — py -3.11 examples/math_complex.py
table 를 입력으로 받는 것)dynsys_poincare_section · dwt_inverse · chebyshev_eval_nd
complex)cplx_contour_circle · cplx_poly_eval · cplx_contour_integral · cplx_winding_number · cplx_cauchy_value · cplx_argument_principle · cplx_joukowski · cplx_mobius
*Provenance: mathops.py — MATH 연산자 레지스트리. 이 op 노트는 tools/opdocs.py md 가 자동 생성합니다(직접 편집하지 마세요).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.