Add Chromium-only Blender WebEngine parity work

blender-5.2.0/intern/cycles/kernel/sample/mapping.h

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+/* SPDX-FileCopyrightText: 2009-2010 Sony Pictures Imageworks Inc., et al. All Rights Reserved.
+ * SPDX-FileCopyrightText: 2011-2022 Blender Foundation
+ *
+ * SPDX-License-Identifier: BSD-3-Clause
+ *
+ * Adapted code from Open Shading Language. */
+
+#pragma once
+
+#include "util/math.h"
+#include "util/projection.h"
+
+#ifndef __KERNEL_GPU__
+#  include <climits>
+#endif
+
+CCL_NAMESPACE_BEGIN
+
+/* Distribute 2D uniform random samples on [0, 1] over unit disk [-1, 1], with concentric mapping
+ * to better preserve stratification for some RNG sequences. */
+ccl_device float2 sample_uniform_disk(const float2 rand)
+{
+  float phi;
+  float r;
+  const float a = 2.0f * rand.x - 1.0f;
+  const float b = 2.0f * rand.y - 1.0f;
+
+  if (a == 0.0f && b == 0.0f) {
+    return zero_float2();
+  }
+
+  if (a * a > b * b) {
+    r = a;
+    phi = M_PI_4_F * (b / a);
+  }
+  else {
+    r = b;
+    phi = M_PI_2_F - M_PI_4_F * (a / b);
+  }
+
+  return polar_to_cartesian(r, phi);
+}
+
+/* return an orthogonal tangent and bitangent given a normal and tangent that
+ * may not be exactly orthogonal */
+ccl_device void make_orthonormals_tangent(const float3 N,
+                                          const float3 T,
+                                          ccl_private float3 *a,
+                                          ccl_private float3 *b)
+{
+  *b = normalize(cross(N, T));
+  *a = cross(*b, N);
+}
+
+ccl_device void make_orthonormals_safe_tangent(const float3 N,
+                                               const float3 T,
+                                               ccl_private float3 *a,
+                                               ccl_private float3 *b)
+{
+  *b = safe_normalize(cross(N, T));
+  if (len_squared(*b) < 0.99f) {
+    /* Normalization failed, so fall back to basic orthonormals. */
+    make_orthonormals(N, a, b);
+  }
+  else {
+    *a = cross(*b, N);
+  }
+}
+
+/* sample direction with cosine weighted distributed in hemisphere */
+ccl_device_inline void sample_cos_hemisphere(const float3 N,
+                                             const float2 rand_in,
+                                             ccl_private float3 *wo,
+                                             ccl_private float *pdf)
+{
+  const float2 rand = sample_uniform_disk(rand_in);
+  const float costheta = safe_sqrtf(1.0f - len_squared(rand));
+
+  float3 T;
+  float3 B;
+  make_orthonormals(N, &T, &B);
+  *wo = rand.x * T + rand.y * B + costheta * N;
+  *pdf = costheta * M_1_PI_F;
+}
+
+ccl_device_inline float pdf_cos_hemisphere(const float3 N, const float3 D)
+{
+  const float cos_theta = dot(N, D);
+  return cos_theta > 0 ? cos_theta * M_1_PI_F : 0.0f;
+}
+
+/* sample direction uniformly distributed in hemisphere */
+ccl_device_inline void sample_uniform_hemisphere(const float3 N,
+                                                 const float2 rand,
+                                                 ccl_private float3 *wo,
+                                                 ccl_private float *pdf)
+{
+  float2 xy = sample_uniform_disk(rand);
+  const float z = 1.0f - len_squared(xy);
+
+  xy *= safe_sqrtf(z + 1.0f);
+
+  float3 T;
+  float3 B;
+  make_orthonormals(N, &T, &B);
+
+  *wo = xy.x * T + xy.y * B + z * N;
+  *pdf = M_1_2PI_F;
+}
+
+ccl_device_inline float pdf_uniform_cone(const float3 N, const float3 D, const float angle)
+{
+  const float z = precise_angle(N, D);
+  if (z < angle) {
+    return M_1_2PI_F / one_minus_cos(angle);
+  }
+  return 0.0f;
+}
+
+/* Uniformly sample a direction in a cone of given angle around `N`. Use concentric mapping to
+ * better preserve stratification. Return the angle between `N` and the sampled direction as
+ * `cos_theta`.
+ * Pass `1 - cos(angle)` as argument instead of `angle` to alleviate precision issues at small
+ * angles (see sphere light for reference). */
+ccl_device_inline float3 sample_uniform_cone(const float3 N,
+                                             const float one_minus_cos_angle,
+                                             const float2 rand,
+                                             ccl_private float *cos_theta,
+                                             ccl_private float *pdf)
+{
+  if (one_minus_cos_angle > 0) {
+    /* Remap radius to get a uniform distribution w.r.t. solid angle on the cone.
+     * The logic to derive this mapping is as follows:
+     *
+     * Sampling a cone is comparable to sampling the hemisphere, we just restrict theta. Therefore,
+     * the same trick of first sampling the unit disk and the projecting the result up towards the
+     * hemisphere by calculating the appropriate z coordinate still works.
+     *
+     * However, by itself this results in cosine-weighted hemisphere sampling, so we need some kind
+     * of remapping. Cosine-weighted hemisphere and uniform cone sampling have the same conditional
+     * PDF for phi (both are constant), so we only need to think about theta, which corresponds
+     * directly to the radius.
+     *
+     * To find this mapping, we consider the simplest sampling strategies for cosine-weighted
+     * hemispheres and uniform cones. In both, phi is chosen as `2pi * random()`. For the former,
+     * `r_disk(rand) = sqrt(rand)`. This is just naive disk sampling, since the projection to the
+     * hemisphere doesn't change the radius.
+     * For the latter, `r_cone(rand) = sin_from_cos(mix(cos_angle, 1, rand))`.
+     *
+     * So, to remap, we just invert r_disk `(-> rand(r_disk) = r_disk^2)` and insert it into
+     * r_cone: `r_cone(r_disk) = r_cone(rand(r_disk)) = sin_from_cos(mix(cos_angle, 1, r_disk^2))`.
+     * In practice, we need to replace `rand` with `1 - rand` to preserve the stratification,
+     * but since it's uniform, that's fine. */
+    float2 xy = sample_uniform_disk(rand);
+    const float r2 = len_squared(xy);
+
+    /* Equivalent to `mix(cos_angle, 1.0f, 1.0f - r2)`. */
+    *cos_theta = 1.0f - r2 * one_minus_cos_angle;
+
+    /* Remap disk radius to cone radius, equivalent to `xy *= sin_theta / sqrt(r2)`. */
+    xy *= safe_sqrtf(one_minus_cos_angle * (2.0f - one_minus_cos_angle * r2));
+
+    *pdf = M_1_2PI_F / one_minus_cos_angle;
+
+    float3 T;
+    float3 B;
+    make_orthonormals(N, &T, &B);
+    return xy.x * T + xy.y * B + *cos_theta * N;
+  }
+
+  *cos_theta = 1.0f;
+  *pdf = 1.0f;
+
+  return N;
+}
+
+/* sample uniform point on the surface of a sphere */
+ccl_device float3 sample_uniform_sphere(const float2 rand)
+{
+  const float z = 1.0f - 2.0f * rand.x;
+  const float r = sin_from_cos(z);
+  const float phi = M_2PI_F * rand.y;
+
+  return make_float3(polar_to_cartesian(r, phi), z);
+}
+
+/* sample point in unit polygon with given number of corners and rotation */
+ccl_device float2 regular_polygon_sample(const float corners, float rotation, const float2 rand)
+{
+  float u = rand.x;
+  float v = rand.y;
+
+  /* sample corner number and reuse u */
+  const float corner = floorf(u * corners);
+  u = u * corners - corner;
+
+  /* uniform sampled triangle weights */
+  u = sqrtf(u);
+  v = v * u;
+  u = 1.0f - u;
+
+  /* point in triangle */
+  const float angle = M_PI_F / corners;
+  const float2 p = make_float2((u + v) * cosf(angle), (u - v) * sinf(angle));
+
+  /* rotate */
+  rotation += corner * 2.0f * angle;
+
+  const float cr = cosf(rotation);
+  const float sr = sinf(rotation);
+
+  return make_float2(cr * p.x - sr * p.y, sr * p.x + cr * p.y);
+}
+
+/* Generate random variable x following geometric distribution p(x) = r * (1 - r)^x, 0 <= p <= 1.
+ * Also compute the probability mass function pmf.
+ * The sampled order is truncated at `cut_off`. */
+ccl_device_inline int sample_geometric_distribution(const float rand,
+                                                    const float r,
+                                                    ccl_private float &pmf,
+                                                    const int cut_off = INT_MAX)
+{
+  const int n = min(int(floorf(logf(rand) / logf(1.0f - r))), cut_off);
+  pmf = (n == cut_off) ? powf(1.0f - r, n) : r * powf(1.0f - r, n);
+  return n;
+}
+
+/* Generate random variable x following exponential distribution p(x) = lambda * exp(-lambda * x),
+ * where lambda > 0 is the rate parameter. */
+ccl_device_inline float sample_exponential_distribution(const float rand, const float lambda)
+{
+  return -logf(1.0f - rand) / lambda;
+}
+
+/* Generate random variable x following bounded exponential distribution
+ * p(x) = lambda * exp(-lambda * x) / (exp(-lambda * t.min) - exp(-lambda * t.max)),
+ * where lambda > 0 is the rate parameter.
+ * The generated sample lies in (t.min, t.max). */
+ccl_device_inline float sample_exponential_distribution(const float rand,
+                                                        const float lambda,
+                                                        const Interval<float> t)
+{
+  const float attenuation = 1.0f - expf(lambda * (t.min - t.max));
+  return clamp(t.min - logf(1.0f - rand * attenuation) / lambda, t.min, t.max);
+}
+
+ccl_device_inline Spectrum pdf_exponential_distribution(const float x,
+                                                        const Spectrum lambda,
+                                                        const Interval<float> t)
+{
+  const Spectrum attenuation = exp(-lambda * t.min) - exp(-lambda * t.max);
+  return safe_divide(lambda * exp(-lambda * clamp(x, t.min, t.max)), attenuation);
+}
+
+CCL_NAMESPACE_END