Brecht Van Lommel
fd25e883e2
Remove prefix of filenames that is the same as the folder name. This used to help when #includes were using individual files, but now they are always relative to the cycles root directory and so the prefixes are redundant. For patches and branches, git merge and rebase should be able to detect the renames and move over code to the right file.
117 lines
4.3 KiB
C++
117 lines
4.3 KiB
C++
/*
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* Copyright 2011-2021 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 "testing/testing.h"
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#include "integrator/adaptive_sampling.h"
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#include "util/vector.h"
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CCL_NAMESPACE_BEGIN
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TEST(AdaptiveSampling, schedule_samples)
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{
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AdaptiveSampling adaptive_sampling;
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adaptive_sampling.use = true;
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adaptive_sampling.min_samples = 0;
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adaptive_sampling.adaptive_step = 4;
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for (int sample = 2; sample < 32; ++sample) {
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for (int num_samples = 8; num_samples < 32; ++num_samples) {
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const int num_samples_aligned = adaptive_sampling.align_samples(sample, num_samples);
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/* NOTE: `sample + num_samples_aligned` is the number of samples after rendering, so need
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* to convert this to the 0-based index of the last sample. */
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EXPECT_TRUE(adaptive_sampling.need_filter(sample + num_samples_aligned - 1));
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}
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}
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}
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TEST(AdaptiveSampling, align_samples)
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{
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AdaptiveSampling adaptive_sampling;
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adaptive_sampling.use = true;
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adaptive_sampling.min_samples = 11 /* rounded of sqrt(128) */;
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adaptive_sampling.adaptive_step = 4;
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/* Filtering will happen at the following samples:
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* 15, 19, 23, 27, 31, 35, 39, 43 */
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/* Requested sample and number of samples will result in number of samples lower than
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* `min_samples`. */
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EXPECT_EQ(adaptive_sampling.align_samples(0, 4), 4);
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EXPECT_EQ(adaptive_sampling.align_samples(0, 7), 7);
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/* Request number of samples higher than the minimum samples before filter, but prior to the
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* first sample at which filtering will happen. */
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EXPECT_EQ(adaptive_sampling.align_samples(0, 15), 15);
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/* When rendering many samples from the very beginning, limit number of samples by the first
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* sample at which filtering is to happen. */
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EXPECT_EQ(adaptive_sampling.align_samples(0, 16), 16);
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EXPECT_EQ(adaptive_sampling.align_samples(0, 17), 16);
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EXPECT_EQ(adaptive_sampling.align_samples(0, 20), 16);
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EXPECT_EQ(adaptive_sampling.align_samples(0, 60), 16);
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/* Similar to above, but start sample is not 0. */
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EXPECT_EQ(adaptive_sampling.align_samples(9, 8), 7);
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EXPECT_EQ(adaptive_sampling.align_samples(9, 20), 7);
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EXPECT_EQ(adaptive_sampling.align_samples(9, 60), 7);
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/* Start sample is past the minimum required samples, but prior to the first filter sample. */
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EXPECT_EQ(adaptive_sampling.align_samples(12, 6), 4);
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EXPECT_EQ(adaptive_sampling.align_samples(12, 20), 4);
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EXPECT_EQ(adaptive_sampling.align_samples(12, 60), 4);
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/* Start sample is the sample which is to be filtered. */
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EXPECT_EQ(adaptive_sampling.align_samples(15, 4), 1);
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EXPECT_EQ(adaptive_sampling.align_samples(15, 6), 1);
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EXPECT_EQ(adaptive_sampling.align_samples(15, 10), 1);
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EXPECT_EQ(adaptive_sampling.align_samples(58, 2), 2);
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/* Start sample is past the sample which is to be filtered. */
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EXPECT_EQ(adaptive_sampling.align_samples(16, 3), 3);
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EXPECT_EQ(adaptive_sampling.align_samples(16, 4), 4);
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EXPECT_EQ(adaptive_sampling.align_samples(16, 5), 4);
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EXPECT_EQ(adaptive_sampling.align_samples(16, 10), 4);
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/* Should never exceed requested number of samples. */
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EXPECT_EQ(adaptive_sampling.align_samples(15, 2), 1);
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EXPECT_EQ(adaptive_sampling.align_samples(16, 2), 2);
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EXPECT_EQ(adaptive_sampling.align_samples(17, 2), 2);
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EXPECT_EQ(adaptive_sampling.align_samples(18, 2), 2);
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}
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TEST(AdaptiveSampling, need_filter)
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{
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AdaptiveSampling adaptive_sampling;
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adaptive_sampling.use = true;
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adaptive_sampling.min_samples = 11 /* rounded of sqrt(128) */;
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adaptive_sampling.adaptive_step = 4;
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const vector<int> expected_samples_to_filter = {
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{15, 19, 23, 27, 31, 35, 39, 43, 47, 51, 55, 59}};
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vector<int> actual_samples_to_filter;
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for (int sample = 0; sample < 60; ++sample) {
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if (adaptive_sampling.need_filter(sample)) {
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actual_samples_to_filter.push_back(sample);
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}
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}
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EXPECT_EQ(actual_samples_to_filter, expected_samples_to_filter);
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}
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CCL_NAMESPACE_END
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