optiland.rays.ray_aiming.cached

Cached Ray Aiming Module

This module implements a caching wrapper for ray aiming algorithms. It stores previous results to speed up repetitive calculations, especially during optimization or tolerance analysis where system changes might be small.

Kramer Harrison, 2025

Classes

CachedRayAimer(optic, wrapped_aimer[, ...])

Cached ray aiming strategy.

class CachedRayAimer(optic: Optic, wrapped_aimer: BaseRayAimer, max_cache_size: int = 128, **kwargs: Any)[source]

Cached ray aiming strategy.

This class wraps another ray aimer and caches its results. It checks if the inputs and the optical system state have changed. If they match a cached entry, the result is returned immediately. If the system has changed but inputs match, the previous result is used as a starting guess.

optic

The optical system being traced.

Type:: Optic

wrapped_aimer

The actual aiming strategy being cached.

Type:: BaseRayAimer

max_cache_size

Maximum number of entries in the cache.

Type:: int

aim_rays(fields: tuple, wavelengths: Any, pupil_coords: tuple, initial_guess: tuple | None = None) → tuple[source]

Calculate ray starting coordinates, using cache if available.

Parameters:

fields (tuple) – Field coordinates.
wavelengths (Any) – Wavelengths.
pupil_coords (tuple) – Pupil coordinates.
initial_guess (tuple | None, optional) – Explicit starting guess.

Returns:

Ray parameters (x, y, z, L, M, N).

Return type:

tuple

clear_cache() → None[source]: Clear the internal cache.