forked from bartvdbraak/blender
287 lines
7.8 KiB
C
287 lines
7.8 KiB
C
/*
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* Copyright 2011-2013 Blender Foundation
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "kernel/kernel_jitter.h"
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#include "util/util_hash.h"
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CCL_NAMESPACE_BEGIN
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/* Pseudo random numbers, uncomment this for debugging correlations. Only run
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* this single threaded on a CPU for repeatable resutls. */
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//#define __DEBUG_CORRELATION__
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/* High Dimensional Sobol.
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*
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* Multidimensional sobol with generator matrices. Dimension 0 and 1 are equal
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* to classic Van der Corput and Sobol sequences. */
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#ifdef __SOBOL__
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/* Skip initial numbers that for some dimensions have clear patterns that
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* don't cover the entire sample space. Ideally we would have a better
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* progressive pattern that doesn't suffer from this problem, because even
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* with this offset some dimensions are quite poor.
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*/
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#define SOBOL_SKIP 64
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ccl_device uint sobol_dimension(KernelGlobals *kg, int index, int dimension)
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{
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uint result = 0;
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uint i = index + SOBOL_SKIP;
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for(uint j = 0; i; i >>= 1, j++) {
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if(i & 1) {
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result ^= kernel_tex_fetch(__sobol_directions, 32*dimension + j);
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}
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}
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return result;
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}
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#endif /* __SOBOL__ */
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ccl_device_forceinline float path_rng_1D(KernelGlobals *kg,
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uint rng_hash,
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int sample, int num_samples,
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int dimension)
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{
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#ifdef __DEBUG_CORRELATION__
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return (float)drand48();
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#endif
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#ifdef __CMJ__
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# ifdef __SOBOL__
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if(kernel_data.integrator.sampling_pattern == SAMPLING_PATTERN_CMJ)
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# endif
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{
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/* Correlated multi-jitter. */
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int p = rng_hash + dimension;
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return cmj_sample_1D(sample, num_samples, p);
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}
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#endif
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#ifdef __SOBOL__
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/* Sobol sequence value using direction vectors. */
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uint result = sobol_dimension(kg, sample, dimension);
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float r = (float)result * (1.0f/(float)0xFFFFFFFF);
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/* Cranly-Patterson rotation using rng seed */
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float shift;
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/* Hash rng with dimension to solve correlation issues.
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* See T38710, T50116.
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*/
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uint tmp_rng = cmj_hash_simple(dimension, rng_hash);
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shift = tmp_rng * (1.0f/(float)0xFFFFFFFF);
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return r + shift - floorf(r + shift);
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#endif
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}
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ccl_device_forceinline void path_rng_2D(KernelGlobals *kg,
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uint rng_hash,
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int sample, int num_samples,
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int dimension,
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float *fx, float *fy)
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{
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#ifdef __DEBUG_CORRELATION__
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*fx = (float)drand48();
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*fy = (float)drand48();
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return;
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#endif
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#ifdef __CMJ__
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# ifdef __SOBOL__
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if(kernel_data.integrator.sampling_pattern == SAMPLING_PATTERN_CMJ)
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# endif
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{
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/* Correlated multi-jitter. */
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int p = rng_hash + dimension;
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cmj_sample_2D(sample, num_samples, p, fx, fy);
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return;
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}
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#endif
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#ifdef __SOBOL__
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/* Sobol. */
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*fx = path_rng_1D(kg, rng_hash, sample, num_samples, dimension);
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*fy = path_rng_1D(kg, rng_hash, sample, num_samples, dimension + 1);
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#endif
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}
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ccl_device_inline void path_rng_init(KernelGlobals *kg,
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int sample, int num_samples,
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uint *rng_hash,
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int x, int y,
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float *fx, float *fy)
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{
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/* load state */
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*rng_hash = hash_int_2d(x, y);
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*rng_hash ^= kernel_data.integrator.seed;
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#ifdef __DEBUG_CORRELATION__
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srand48(*rng_hash + sample);
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#endif
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if(sample == 0) {
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*fx = 0.5f;
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*fy = 0.5f;
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}
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else {
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path_rng_2D(kg, *rng_hash, sample, num_samples, PRNG_FILTER_U, fx, fy);
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}
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}
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/* Linear Congruential Generator */
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ccl_device uint lcg_step_uint(uint *rng)
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{
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/* implicit mod 2^32 */
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*rng = (1103515245*(*rng) + 12345);
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return *rng;
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}
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ccl_device float lcg_step_float(uint *rng)
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{
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/* implicit mod 2^32 */
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*rng = (1103515245*(*rng) + 12345);
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return (float)*rng * (1.0f/(float)0xFFFFFFFF);
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}
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ccl_device uint lcg_init(uint seed)
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{
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uint rng = seed;
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lcg_step_uint(&rng);
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return rng;
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}
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/* Path Tracing Utility Functions
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*
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* For each random number in each step of the path we must have a unique
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* dimension to avoid using the same sequence twice.
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*
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* For branches in the path we must be careful not to reuse the same number
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* in a sequence and offset accordingly.
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*/
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ccl_device_inline float path_state_rng_1D(KernelGlobals *kg,
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const ccl_addr_space PathState *state,
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int dimension)
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{
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return path_rng_1D(kg,
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state->rng_hash,
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state->sample, state->num_samples,
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state->rng_offset + dimension);
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}
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ccl_device_inline void path_state_rng_2D(KernelGlobals *kg,
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const ccl_addr_space PathState *state,
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int dimension,
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float *fx, float *fy)
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{
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path_rng_2D(kg,
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state->rng_hash,
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state->sample, state->num_samples,
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state->rng_offset + dimension,
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fx, fy);
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}
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ccl_device_inline float path_branched_rng_1D(
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KernelGlobals *kg,
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uint rng_hash,
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const ccl_addr_space PathState *state,
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int branch,
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int num_branches,
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int dimension)
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{
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return path_rng_1D(kg,
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rng_hash,
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state->sample * num_branches + branch,
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state->num_samples * num_branches,
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state->rng_offset + dimension);
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}
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ccl_device_inline void path_branched_rng_2D(
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KernelGlobals *kg,
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uint rng_hash,
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const ccl_addr_space PathState *state,
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int branch,
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int num_branches,
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int dimension,
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float *fx, float *fy)
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{
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path_rng_2D(kg,
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rng_hash,
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state->sample * num_branches + branch,
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state->num_samples * num_branches,
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state->rng_offset + dimension,
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fx, fy);
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}
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/* Utitility functions to get light termination value,
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* since it might not be needed in many cases.
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*/
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ccl_device_inline float path_state_rng_light_termination(
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KernelGlobals *kg,
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const ccl_addr_space PathState *state)
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{
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if(kernel_data.integrator.light_inv_rr_threshold > 0.0f) {
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return path_state_rng_1D(kg, state, PRNG_LIGHT_TERMINATE);
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}
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return 0.0f;
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}
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ccl_device_inline float path_branched_rng_light_termination(
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KernelGlobals *kg,
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uint rng_hash,
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const ccl_addr_space PathState *state,
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int branch,
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int num_branches)
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{
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if(kernel_data.integrator.light_inv_rr_threshold > 0.0f) {
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return path_branched_rng_1D(kg,
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rng_hash,
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state,
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branch,
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num_branches,
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PRNG_LIGHT_TERMINATE);
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}
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return 0.0f;
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}
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ccl_device_inline uint lcg_state_init(PathState *state,
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uint scramble)
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{
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return lcg_init(state->rng_hash + state->rng_offset + state->sample*scramble);
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}
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ccl_device_inline uint lcg_state_init_addrspace(ccl_addr_space PathState *state,
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uint scramble)
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{
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return lcg_init(state->rng_hash + state->rng_offset + state->sample*scramble);
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}
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ccl_device float lcg_step_float_addrspace(ccl_addr_space uint *rng)
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{
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/* Implicit mod 2^32 */
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*rng = (1103515245*(*rng) + 12345);
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return (float)*rng * (1.0f/(float)0xFFFFFFFF);
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}
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CCL_NAMESPACE_END
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