sensorchar op• Data kinds: image2d × image2d → table
• Call: import fullseye as fs; fs.ledger.emva_noise_whiteness(y0, y1, y2=None, z_limit=5.0) (to call the implementation directly, import sensorchar; sensorchar.emva_noise_whiteness(y0, y1, y2=None, z_limit=5.0); from the registry, opsoptics.get("emva_noise_whiteness"))
Is the temporal noise independent between pixels (assumption 3 of Linear section 1.2) and between consecutive images (assumption 3 of Linear and General)?
> The detailed description below is the original text — the summary and the headings are translated.
★規格は前提を書く(「前処理がこの条件を壊すなら Release 4 Linear は使えない。典型は debayer・雑音除去・輪郭強調」)が、確かめ方の数は定義していない。ここの数はこの族の検査で、規格の数ではない。同じ露光の 2 枚の差 d = y0 − y1(固定パターンが消え、時間雑音だけが残る)の隣の画素との相関 ρ_h = ⟨d[m][n] d[m][n+1]⟩/⟨d²⟩、ρ_v(縦)、斜め ρ_d(2 方向の平均)。白い雑音では 0 で、標準偏差は約 1/√n なので z = ρ √n を返す。2 × 2 にまとめた和の分散比 VR = var(和)/(4 var(d)) = 1 + ρ_h + ρ_v + ρ_d は、平滑化(雑音除去)で 1 を越え、輪郭強調で 1 を割る。*y2*(3 枚目、y1 の次の画像)を渡すと、var(y0 − y2)/var(y0 − y1) − 1 = 1 枚おきの画像の相関 ρ_t を返す(1 次の再帰の時間フィルタ y_t = α x_t + (1 − α) y_{t−1} なら ρ_t = 1 − α。独立なら 0、z は √n/√3 で割る近似)。
返り値 {"rho_h", "rho_v", "rho_d", "z_h", "z_v", "z_d", "variance_ratio_2x2", "rho_t", "z_t", "white", "z_limit", "n"} (white は |z| がすべて *z_limit* 未満)。
Raises ValueError: 2-D でない / 形が違う / 4 × 4 未満 / 差がすべて 0(雑音が無い)/ z_limit が正でない。
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_emva1288_in_camera_processing — py -3.11 examples/poc_emva1288_in_camera_processing.py
table as input)abcd_matrix · wavefront_stats · sfr_from_edge · paraxial_trace · seidel_coefficients · spot_stats · tolerance_analysis · wavefront_from_opd
sensorchar)emva_pair_statistics · emva_photon_transfer · emva_quantum_efficiency · emva_linearity_error · emva_snr_curve · emva_sensitivity_threshold · emva_dynamic_range · emva_dark_current
*Provenance: sensorchar.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.