// Common functions for Signed Distance Field (SDF) raymarching with object ID. // // Required user-defined functions: // - dfWithID(vec3f) -> RayMarchResult // // Requires constants from raymarching.wgsl: // TOLERANCE, MAX_RAY_LENGTH, MAX_RAY_MARCHES, NORM_OFF #include "render/raymarching" // ============================================================================ // Two-Pass Raymarching Support // ============================================================================ // Design note: RayMarchResult is passed/returned by value (not pointer). // At 12 bytes (3×f32), return value optimization makes this efficient. // See doc/CODING_STYLE.md for rationale. struct RayMarchResult { distance: f32, // Distance to surface (MAX_RAY_LENGTH if miss) distance_max: f32, // Total distance marched (for fog/AO) object_id: f32, // Object identifier (0.0 = background) } // Raymarch with object ID tracking. fn rayMarchWithID(ro: vec3f, rd: vec3f, init: RayMarchResult) -> RayMarchResult { var t = init.distance; var result = init; for (var i = 0; i < MAX_RAY_MARCHES; i++) { if (t > MAX_RAY_LENGTH) { result.distance = MAX_RAY_LENGTH; result.distance_max = MAX_RAY_LENGTH; break; } let sample = dfWithID(ro + rd * t); if (sample.distance < TOLERANCE) { result.distance = t; result.distance_max = t; result.object_id = sample.object_id; break; } t += sample.distance; } return result; } // Reconstruct world position from stored result. fn reconstructPosition(ray: Ray, result: RayMarchResult) -> vec3f { return ray.origin + ray.direction * result.distance; } // Normal calculation using dfWithID. fn normalWithID(pos: vec3f) -> vec3f { let eps = vec2f(NORM_OFF, 0.0); var nor: vec3f; nor.x = dfWithID(pos + eps.xyy).distance - dfWithID(pos - eps.xyy).distance; nor.y = dfWithID(pos + eps.yxy).distance - dfWithID(pos - eps.yxy).distance; nor.z = dfWithID(pos + eps.yyx).distance - dfWithID(pos - eps.yyx).distance; return normalize(nor); } // Shadow using stored intersection distance. fn shadowWithStoredDistance(lp: vec3f, ld: vec3f, stored_dist: f32) -> f32 { let ds = 1.0 - 0.4; var t = 0.01; var nd = 1e6; let soff = 0.05; let smul = 1.5; let MAX_SHD_MARCHES = 20; for (var i = 0; i < MAX_SHD_MARCHES; i++) { let p = lp + ld * t; let d = dfWithID(p).distance; if (d < TOLERANCE || t >= stored_dist) { let sd = 1.0 - exp(-smul * max(t / stored_dist - soff, 0.0)); return select(mix(sd, 1.0, smoothstep(0.0, 0.025, nd)), sd, t >= stored_dist); } nd = min(nd, d); t += ds * d; } let sd = 1.0 - exp(-smul * max(t / stored_dist - soff, 0.0)); return sd; }