preston_pressure_kernel — DRIVE polish op

• Data kinds: scalar × scalar × scalar → image2d

• Call: import fullseye as fs; fs.ledger.preston_pressure_kernel(force: 'float', radius: 'float', res: 'float', kind: 'str' = 'flat', estar=None, normalize: 'bool' = False) -> 'np.ndarray' (to call the implementation directly, import polish; polish.preston_pressure_kernel(force: 'float', radius: 'float', res: 'float', kind: 'str' = 'flat', estar=None, normalize: 'bool' = False) -> 'np.ndarray'; from the registry, opsdrive.get("preston_pressure_kernel"))

Usage

Window of the pressure [Pa] under the tool, sampled at pixel centers (odd × odd; the center pixel is the tool center). Flat: uniform F/(πa²) inside the circle; Hertz: p0 √(1 − r²/a²) (radius = sphere radius R, requires estar). With normalize=True it is scaled so that Σ p · res² = F (removes the error of the pixel-counted circle area, so that FFT convolution preserves volume). Raises ValueError: force, radius or pixel not positive, unknown kind, Hertz without estar, contact radius smaller than 1 pixel.

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)

• poc_polish_wipe_measure — py -3.11 examples/poc_polish_wipe_measure.py

Ops the type connects to (they accept image2d as input)

flow_from_depth_motion · ttc_truth · ttc_from_flow · foe_from_flow · perlin2 · fbm_height · fbm_gradient · radial_periodogram

Same category (polish)

preston_removal_map · preston_track_profile · wipe_band_width · raster_wipe_area · coat_image · coat_thickness_from_image · wipe_coverage · band_width_profile


*Provenance: polish.py — DRIVE 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.