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/* SPDX-License-Identifier: Apache-2.0
* Copyright 2011-2022 Blender Foundation */
#include "kernel/sample/util.h"
#include "util/hash.h"
#pragma once
CCL_NAMESPACE_BEGIN
ccl_device float pmj_sample_1D(KernelGlobals kg,
uint sample,
const uint rng_hash,
const uint dimension)
{
uint seed = rng_hash;
/* Use the same sample sequence seed for all pixels when using
* scrambling distance. */
if (kernel_data.integrator.scrambling_distance < 1.0f) {
seed = kernel_data.integrator.seed;
}
/* Shuffle the pattern order and sample index to better decorrelate
* dimensions and make the most of the finite patterns we have.
* The funky sample mask stuff is to ensure that we only shuffle
* *within* the current sample pattern, which is necessary to avoid
* early repeat pattern use. */
const uint pattern_i = hash_shuffle_uint(dimension, NUM_PMJ_PATTERNS, seed);
/* NUM_PMJ_SAMPLES should be a power of two, so this results in a mask. */
const uint sample_mask = NUM_PMJ_SAMPLES - 1;
const uint sample_shuffled = nested_uniform_scramble(sample,
hash_wang_seeded_uint(dimension, seed));
sample = (sample & ~sample_mask) | (sample_shuffled & sample_mask);
/* Fetch the sample. */
const uint index = ((pattern_i * NUM_PMJ_SAMPLES) + sample) %
(NUM_PMJ_SAMPLES * NUM_PMJ_PATTERNS);
float x = kernel_data_fetch(sample_pattern_lut, index * 2);
/* Do limited Cranley-Patterson rotation when using scrambling distance. */
if (kernel_data.integrator.scrambling_distance < 1.0f) {
const float jitter_x = hash_wang_seeded_float(dimension, rng_hash) *
kernel_data.integrator.scrambling_distance;
x += jitter_x;
x -= floorf(x);
}
return x;
}
ccl_device float2 pmj_sample_2D(KernelGlobals kg,
uint sample,
const uint rng_hash,
const uint dimension)
{
uint seed = rng_hash;
/* Use the same sample sequence seed for all pixels when using
* scrambling distance. */
if (kernel_data.integrator.scrambling_distance < 1.0f) {
seed = kernel_data.integrator.seed;
}
/* Shuffle the pattern order and sample index to better decorrelate
* dimensions and make the most of the finite patterns we have.
* The funky sample mask stuff is to ensure that we only shuffle
* *within* the current sample pattern, which is necessary to avoid
* early repeat pattern use. */
const uint pattern_i = hash_shuffle_uint(dimension, NUM_PMJ_PATTERNS, seed);
/* NUM_PMJ_SAMPLES should be a power of two, so this results in a mask. */
const uint sample_mask = NUM_PMJ_SAMPLES - 1;
const uint sample_shuffled = nested_uniform_scramble(sample,
hash_wang_seeded_uint(dimension, seed));
sample = (sample & ~sample_mask) | (sample_shuffled & sample_mask);
/* Fetch the sample. */
const uint index = ((pattern_i * NUM_PMJ_SAMPLES) + sample) %
(NUM_PMJ_SAMPLES * NUM_PMJ_PATTERNS);
float x = kernel_data_fetch(sample_pattern_lut, index * 2);
float y = kernel_data_fetch(sample_pattern_lut, index * 2 + 1);
/* Do limited Cranley-Patterson rotation when using scrambling distance. */
if (kernel_data.integrator.scrambling_distance < 1.0f) {
const float jitter_x = hash_wang_seeded_float(dimension, rng_hash) *
kernel_data.integrator.scrambling_distance;
const float jitter_y = hash_wang_seeded_float(dimension, rng_hash ^ 0xca0e1151) *
kernel_data.integrator.scrambling_distance;
x += jitter_x;
y += jitter_y;
x -= floorf(x);
y -= floorf(y);
}
return make_float2(x, y);
}
CCL_NAMESPACE_END
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