shape_from_polarization op• Data kinds: normalmap → polsweep
• Call: import fullseye as fs; fs.ledger.sfp_render(normals, refractive_index=1.5, specular_radiance=1.0, diffuse_radiance=0.0, angles_deg=(0.0, 45.0, 90.0, 135.0), mask=None) (to call the implementation directly, import sfpolar; sfpolar.sfp_render(normals, refractive_index=1.5, specular_radiance=1.0, diffuse_radiance=0.0, angles_deg=(0.0, 45.0, 90.0, 135.0), mask=None); from the registry, opsoptics.get("sfp_render"))
Render the images a 4-direction polarisation camera records of a dielectric surface with the given normal map (the forward model of shape from polarisation).
Each pixel is I(t) = (S0/2) (1 + rho cos 2(t - psi)) with rho from sfp_dolp_model and psi the normal's azimuth (diffuse) or the azimuth plus 90 degrees (specular). Orthographic camera looking down -z; angles in the module's convention (x toward y).
The pixel is the Stokes sum of a specular part (unpolarised environment light reflected once off the surface, radiance *specular_radiance*) and a diffuse part (light scattered inside the body and refracted out, radiance *diffuse_radiance*). The defaults (1, 0) give a pure specular surface (black gloss, glass); (0, 1) a pure diffuse one. Anything in between is a mixed pixel: the two polarisations are 90 degrees apart and partly cancel, which is exactly why such a pixel misleads either single model. Both radiances are scalars or (H, W) maps, >= 0, not both zero. Pixels outside *mask* are black.
Returns (N, H, W) float64 — the polsweep sort, in the order of *angles_deg* (default 0/45/90/135, optics.polarization_demosaic's order), ready for sfp_normals and the specularity polarisation ops.
Raises ValueError: *normals* not a finite (H, W, 3) field of unit normals facing the camera; index not > 1; negative, non-finite or all-zero radiance; fewer than 3 or non-finite angles.
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.
• 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.
• poc_shape_from_polarization — py -3.11 examples/poc_shape_from_polarization.py
polsweep as input)shape_from_polarization)sfp_dolp_model · dolp_to_zenith · aolp_to_azimuth · sfp_normals · sfp_disambiguate · sfp_estimate_index · sfp_height
*Provenance: sfpolar.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.