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// 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;
}
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