wavefront_stats — OPTICS imaging op

Data kinds: tabletable

Call: import optics; optics.wavefront_stats(coeffs, radial=128, angular=192) (or opsoptics.get("wavefront_stats"))

Usage

Wavefront error statistics from a Zernike expansion: RMS, PV and Strehl.

*coeffs* is exactly the dict :func:match3d.fit_zernike returns —

`{(n, m): coefficient}`, coefficients in waves — and this op re-uses

`match3d`'s own basis builder, so the two cannot drift apart in

normalisation or in the `(n, m) convention. Fit with fit_zernike`,

characterise here.

The wavefront is reconstructed on a polar grid (*radial* x *angular*) over

the unit pupil and reduced with the area element `rho d(rho) d(theta)`

— an unweighted mean over a uniform-in-rho grid over-counts the centre and

is a real, silent, ~10% error.

Returns a dict: `rms_waves` (piston removed — piston is not an

aberration) · `pv_waves peak-to-valley over the pupil · strehl` the

Marechal estimate `exp(-(2*pi*rms)^2) · marechal_valid` whether

`rms_waves <= MARECHAL_RMS_LIMIT` (0.1), because past that the estimate is

optimistic and reporting the number without the caveat is the dishonest

option · `terms and n_max` of the expansion.

Ground truth it reproduces (measured at the defaults): pure defocus

`{(2, 0): 0.1} — for which Z = 2*rho^2 - 1` has an exact pupil RMS of

`1/sqrt(3) — gives rms_waves = 0.0577422` against the exact

`0.0577350`, a relative error of 1.2e-4 from the discrete quadrature

(3.1e-5 at `radial=256), and pv_waves = 0.2` exactly; the Strehl is

0.8766676 against the exact 0.8766962. Pure astigmatism `{(2, 2): 0.1}`

(exact RMS `1/sqrt(6)`) gives 0.0408280 against 0.0408248. Piston alone

(`{(0, 0): c}) gives rms 0 and Strehl 1 for any c`, and RMS scales

exactly linearly in the coefficients (doubling them doubles the RMS to

machine precision).

Raises `ValueError`: *coeffs* is not a dict, is empty, holds more than

:data:MAX_ZERNIKE_TERMS terms, has a key that is not an `(n, m)` int

pair or is not a valid Zernike index (`n >= 0, |m| <= n, n-|m|`

even), or a non-finite coefficient; a radial order above

:data:MAX_ZERNIKE_ORDER (40 — the shared basis builder's factorial

recurrence breaks its own `|Z| <= 1 bound at n = 46`, measured, and

the same bound is re-checked at runtime); *radial* / *angular* outside

`[8, MAX_GRID]`.

The radial quadrature is discrete, so its error grows with the order being

integrated: measured, the relative RMS error tracks `(n_max/radial)^2`

within a factor 2 — 1.2e-4 at `n_max=2, 1.7e-3 at n_max=6` and 4.3e-2

at `n_max=20, all at the default radial=128`. Below

`radial >= 16*n_max a RuntimeWarning` says so rather than letting a

12%-wrong Strehl look authoritative. Raising *radial* fixes it at

`O(1/radial^2)`, but note the basis is built for *all* orders up to

`n_max, so the working set grows as n_max^2 * radial * angular` and is

capped by :data:MAX_ZERNIKE_BASIS.

Marechal is a small-aberration approximation and the RMS is over the *fitted*

expansion, so it says nothing about wavefront structure finer than `n_max`

— and `fit_zernike` itself discloses ~10% inter-mode crosstalk at its

default sampling. Both limits compound; treat the Strehl as an indicator,

not a measurement.

Family-wide input contract (fail-closed)

Every optics op validates its input before computing (nothing slips through silently):

Units are baked into the argument name_mm / _um / _deg / _mrad. Confusing mm with µm does not crash; it yields a plausible-looking wrong answer, so the name prevents it. Nothing here guesses the unit from the magnitude.

• **Strings raise ValueError** — float('50') succeeds, so an unparsed configuration value would slip through as a length (measured: thin_lens('50', '200') returned a plausible 66.667 mm). bool is refused too, as the implicit promotion True == 1.

• **complex / masked arrays raise ValueError (real-valued slots only; silently dropping the imaginary part or peeling off the mask is refused). NaN/Inf raises ValueError on every input.**

Division by zero and its relatives are refused by name: focal length 0, radius of curvature 0, refractive index <= 0, a fully opaque aperture (all zeros, so the normalisation is 0/0), a PSF whose sum is <= 0, a Stokes vector with S0 = 0, and an object sitting at the front focal point (the image is at infinity).

Only two ops return a non-finite value, and both state it as a contract: depth_of_field returns far_mm = inf beyond the hyperfocal distance (that is what the hyperfocal distance means), and gaussian_beam returns wavefront_radius_mm = inf at the waist (the radius of curvature of a plane wavefront). Both also return a finite companion (far_is_infinite / curvature_per_mm). **Any other silent NaN/Inf is detected internally and raises ValueError** — "float64 overflowed" and "the answer is infinite" are different claims, so the first is never returned wearing the face of the second.

Size caps: generated grids are capped by optics.MAX_GRID (4096); supplied fields/PSFs/apertures by optics.MAX_FIELD_ELEMENTS (2^24); ABCD element chains by optics.MAX_SYSTEM_ELEMENTS (1024); Zernike by MAX_ZERNIKE_TERMS (512) / MAX_ZERNIKE_ORDER (40) / MAX_ZERNIKE_BASIS (2^25). This closes, fail-closed, the paths where a small argument triggers a huge internal allocation (measured: n_max=40 × 4096² needs 108 GB).

Physically impossible states are refused too: a Stokes vector with degree of polarisation > 1, negative transmittance, negative intensity, and invalid Zernike indices such as n-|m| odd.

Detailed usage guide

optics_imaging family guide

Background guides (the physics and conventions behind this op)

measurement_uncertainty — 計測の不確かさと校正の知識 — 「測れている」を主張するために

mv_cameras — 産業用カメラメーカー(センサとの紐付け・ラインスキャン / TDI)

virtual_machine_vision — 仮想マシンビジョン — パラメータの洗い出しとオブジェクト模型

References (sample data, literature)

• 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.

Runnable examples (verified samples that actually call this op)

optics_imagingpy -3.11 examples/optics_imaging.py

Ops the type connects to (they accept table as input)

abcd_matrix · paraxial_trace · seidel_coefficients · spot_stats · tolerance_analysis · wavefront_from_opd · spot_diagram · ray_fan

Same category (imaging)

psf_to_mtf · mtf_diffraction


*Provenance: optics.py — OPTICS 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.