imaging_sim op• Data kinds: table → image2d
• Call: import fullseye as fs; fs.ledger.psf_from_opd(system, field=None, size=None, wavelength_um=None, pixel_pitch_um=None, oversample=4) (to call the implementation directly, import lensimage; lensimage.psf_from_opd(system, field=None, size=None, wavelength_um=None, pixel_pitch_um=None, oversample=4); from the registry, opsoptics.get("psf_from_opd"))
Diffraction PSF of the real, aberrated pupil (image2d, sums to 1).
The pupil function P = mask · exp(i·2π·W) comes from raytrace.opd_samples (*W* in waves on a size × size grid over the exit pupil; size=None picks a grid that keeps the phase below 0.4 waves per sample, up to MAX_PUPIL_SAMPLES; an explicit *size* that aliases is refused). The PSF is |FFT(P)|² on a zero-padded grid whose sample spacing is λ·F#·(size−1)/M ≈ λ·F#/oversample with the working f-number F# = 1/(2·NA_image) from raytrace.paraxial_trace. With *pixel_pitch_um* the fine PSF is area-integrated onto detector pixels of that pitch (each fine sample is binned into the pixel it falls in; the pitch must not be finer than the sample spacing).
Ground truth (tests/test_lensimage.py): an unaberrated pupil (the singlet stopped to a 1 mm semi-aperture) gives the Airy pattern — first dark ring at 1.22·λ·F# within 3 %, 83.8 % ± 1 % of the energy inside it; the f/4 singlet (11 waves of spherical aberration) has a Strehl ratio below 0.05 (peak versus the unaberrated peak of the same pupil).
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.
• mv_cables — Cables (standards, speed, power delivery, robot cables)
• mv_cameras — Industrial camera makers (sensor mapping, line scan / TDI)
• mv_frame_grabbers — Frame grabber boards (not optics, but they decide whether you can capture at all)
• mv_image_sensors — Industrial image sensors (mainly current products)
• mv_standards — Camera interface standards and the bodies behind them
• virtual_machine_vision — Virtual machine vision — enumerating the parameters and an object model
• 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.
• lens_defect_dataset_demo — py -3.11 examples/lens_defect_dataset_demo.py
image2d as input)fraunhofer_pattern · pupil_psf · pupil_blur · psf_to_mtf · edge_spread · veiling_glare_index · emva_pair_statistics · emva_defect_pixels
imaging_sim)distortion_map · render_through_lens · defect_dataset · calibration_views
*Provenance: lensimage.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.