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diff --git a/modules/noise/tests/test_fastnoise_lite.h b/modules/noise/tests/test_fastnoise_lite.h new file mode 100644 index 0000000000..0a435c6a5c --- /dev/null +++ b/modules/noise/tests/test_fastnoise_lite.h @@ -0,0 +1,637 @@ +/**************************************************************************/ +/* test_fastnoise_lite.h */ +/**************************************************************************/ +/* This file is part of: */ +/* GODOT ENGINE */ +/* https://godotengine.org */ +/**************************************************************************/ +/* Copyright (c) 2014-present Godot Engine contributors (see AUTHORS.md). */ +/* Copyright (c) 2007-2014 Juan Linietsky, Ariel Manzur. */ +/* */ +/* Permission is hereby granted, free of charge, to any person obtaining */ +/* a copy of this software and associated documentation files (the */ +/* "Software"), to deal in the Software without restriction, including */ +/* without limitation the rights to use, copy, modify, merge, publish, */ +/* distribute, sublicense, and/or sell copies of the Software, and to */ +/* permit persons to whom the Software is furnished to do so, subject to */ +/* the following conditions: */ +/* */ +/* The above copyright notice and this permission notice shall be */ +/* included in all copies or substantial portions of the Software. */ +/* */ +/* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, */ +/* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF */ +/* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. */ +/* IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY */ +/* CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, */ +/* TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE */ +/* SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */ +/**************************************************************************/ + +#ifndef TEST_FASTNOISE_LITE_H +#define TEST_FASTNOISE_LITE_H + +#include "tests/test_macros.h" + +#include "modules/noise/fastnoise_lite.h" + +namespace TestFastNoiseLite { + +// Uitility functions for finding differences in noise generation + +bool all_equal_approx(const Vector<real_t> &p_values_1, const Vector<real_t> &p_values_2) { + ERR_FAIL_COND_V_MSG(p_values_1.size() != p_values_2.size(), false, "Arrays must be the same size. This is a error in the test code."); + + for (int i = 0; i < p_values_1.size(); i++) { + if (!Math::is_equal_approx(p_values_1[i], p_values_2[i])) { + return false; + } + } + return true; +} + +Vector<Pair<size_t, size_t>> find_approx_equal_vec_pairs(std::initializer_list<Vector<real_t>> inputs) { + Vector<Vector<real_t>> p_array = Vector<Vector<real_t>>(inputs); + + Vector<Pair<size_t, size_t>> result; + for (int i = 0; i < p_array.size(); i++) { + for (int j = i + 1; j < p_array.size(); j++) { + if (all_equal_approx(p_array[i], p_array[j])) { + result.push_back(Pair<size_t, size_t>(i, j)); + } + } + } + return result; +} + +#define CHECK_ARGS_APPROX_PAIRWISE_DISTINCT_VECS(...) \ + { \ + Vector<Pair<size_t, size_t>> equal_pairs = find_approx_equal_vec_pairs({ __VA_ARGS__ }); \ + for (Pair<size_t, size_t> p : equal_pairs) { \ + MESSAGE("Argument with index ", p.first, " is approximately equal to argument with index ", p.second); \ + } \ + CHECK_MESSAGE(equal_pairs.size() == 0, "All arguments should be pairwise distinct."); \ + } + +Vector<real_t> get_noise_samples_1d(const FastNoiseLite &p_noise, size_t p_count = 32) { + Vector<real_t> result; + result.resize(p_count); + for (size_t i = 0; i < p_count; i++) { + result.write[i] = p_noise.get_noise_1d(i); + } + return result; +} + +Vector<real_t> get_noise_samples_2d(const FastNoiseLite &p_noise, size_t p_count = 32) { + Vector<real_t> result; + result.resize(p_count); + for (size_t i = 0; i < p_count; i++) { + result.write[i] = p_noise.get_noise_2d(i, i); + } + return result; +} + +Vector<real_t> get_noise_samples_3d(const FastNoiseLite &p_noise, size_t p_count = 32) { + Vector<real_t> result; + result.resize(p_count); + for (size_t i = 0; i < p_count; i++) { + result.write[i] = p_noise.get_noise_3d(i, i, i); + } + return result; +} + +// The following test suite is rather for testing the wrapper code than the actual noise generation. + +TEST_CASE("[FastNoiseLite] Getter and setter") { + FastNoiseLite noise; + + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_SIMPLEX_SMOOTH); + CHECK(noise.get_noise_type() == FastNoiseLite::NoiseType::TYPE_SIMPLEX_SMOOTH); + + noise.set_seed(123); + CHECK(noise.get_seed() == 123); + + noise.set_frequency(0.123); + CHECK(noise.get_frequency() == doctest::Approx(0.123)); + + noise.set_offset(Vector3(1, 2, 3)); + CHECK(noise.get_offset() == Vector3(1, 2, 3)); + + noise.set_fractal_type(FastNoiseLite::FractalType::FRACTAL_PING_PONG); + CHECK(noise.get_fractal_type() == FastNoiseLite::FractalType::FRACTAL_PING_PONG); + + noise.set_fractal_octaves(2); + CHECK(noise.get_fractal_octaves() == 2); + + noise.set_fractal_lacunarity(1.123); + CHECK(noise.get_fractal_lacunarity() == doctest::Approx(1.123)); + + noise.set_fractal_gain(0.123); + CHECK(noise.get_fractal_gain() == doctest::Approx(0.123)); + + noise.set_fractal_weighted_strength(0.123); + CHECK(noise.get_fractal_weighted_strength() == doctest::Approx(0.123)); + + noise.set_fractal_ping_pong_strength(0.123); + CHECK(noise.get_fractal_ping_pong_strength() == doctest::Approx(0.123)); + + noise.set_cellular_distance_function(FastNoiseLite::CellularDistanceFunction::DISTANCE_MANHATTAN); + CHECK(noise.get_cellular_distance_function() == FastNoiseLite::CellularDistanceFunction::DISTANCE_MANHATTAN); + + noise.set_cellular_return_type(FastNoiseLite::CellularReturnType::RETURN_DISTANCE2_SUB); + CHECK(noise.get_cellular_return_type() == FastNoiseLite::CellularReturnType::RETURN_DISTANCE2_SUB); + + noise.set_cellular_jitter(0.123); + CHECK(noise.get_cellular_jitter() == doctest::Approx(0.123)); + + noise.set_domain_warp_enabled(true); + CHECK(noise.is_domain_warp_enabled() == true); + noise.set_domain_warp_enabled(false); + CHECK(noise.is_domain_warp_enabled() == false); + + noise.set_domain_warp_type(FastNoiseLite::DomainWarpType::DOMAIN_WARP_SIMPLEX_REDUCED); + CHECK(noise.get_domain_warp_type() == FastNoiseLite::DomainWarpType::DOMAIN_WARP_SIMPLEX_REDUCED); + + noise.set_domain_warp_amplitude(0.123); + CHECK(noise.get_domain_warp_amplitude() == doctest::Approx(0.123)); + + noise.set_domain_warp_frequency(0.123); + CHECK(noise.get_domain_warp_frequency() == doctest::Approx(0.123)); + + noise.set_domain_warp_fractal_type(FastNoiseLite::DomainWarpFractalType::DOMAIN_WARP_FRACTAL_INDEPENDENT); + CHECK(noise.get_domain_warp_fractal_type() == FastNoiseLite::DomainWarpFractalType::DOMAIN_WARP_FRACTAL_INDEPENDENT); + + noise.set_domain_warp_fractal_octaves(2); + CHECK(noise.get_domain_warp_fractal_octaves() == 2); + + noise.set_domain_warp_fractal_lacunarity(1.123); + CHECK(noise.get_domain_warp_fractal_lacunarity() == doctest::Approx(1.123)); + + noise.set_domain_warp_fractal_gain(0.123); + CHECK(noise.get_domain_warp_fractal_gain() == doctest::Approx(0.123)); +} + +TEST_CASE("[FastNoiseLite] Basic noise generation") { + FastNoiseLite noise; + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_SIMPLEX); + noise.set_fractal_type(FastNoiseLite::FractalType::FRACTAL_NONE); + noise.set_seed(123); + noise.set_offset(Vector3(10, 10, 10)); + + // 1D noise will be checked just in the cases where there's the possibility of + // finding a bug/regression in the wrapper function. + // (since it uses FastNoise's 2D noise generator with the Y coordinate set to 0). + + SUBCASE("Determinacy of noise generation (all noise types)") { + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_SIMPLEX); + CHECK(noise.get_noise_2d(0, 0) == doctest::Approx(noise.get_noise_2d(0, 0))); + CHECK(noise.get_noise_3d(0, 0, 0) == doctest::Approx(noise.get_noise_3d(0, 0, 0))); + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_SIMPLEX_SMOOTH); + CHECK(noise.get_noise_2d(0, 0) == doctest::Approx(noise.get_noise_2d(0, 0))); + CHECK(noise.get_noise_3d(0, 0, 0) == doctest::Approx(noise.get_noise_3d(0, 0, 0))); + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_CELLULAR); + CHECK(noise.get_noise_2d(0, 0) == doctest::Approx(noise.get_noise_2d(0, 0))); + CHECK(noise.get_noise_3d(0, 0, 0) == doctest::Approx(noise.get_noise_3d(0, 0, 0))); + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_PERLIN); + CHECK(noise.get_noise_2d(0, 0) == doctest::Approx(noise.get_noise_2d(0, 0))); + CHECK(noise.get_noise_3d(0, 0, 0) == doctest::Approx(noise.get_noise_3d(0, 0, 0))); + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_VALUE); + CHECK(noise.get_noise_2d(0, 0) == doctest::Approx(noise.get_noise_2d(0, 0))); + CHECK(noise.get_noise_3d(0, 0, 0) == doctest::Approx(noise.get_noise_3d(0, 0, 0))); + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_VALUE_CUBIC); + CHECK(noise.get_noise_2d(0, 0) == doctest::Approx(noise.get_noise_2d(0, 0))); + CHECK(noise.get_noise_3d(0, 0, 0) == doctest::Approx(noise.get_noise_3d(0, 0, 0))); + } + + SUBCASE("Different seeds should produce different noise") { + noise.set_seed(456); + Vector<real_t> noise_seed_1_1d = get_noise_samples_1d(noise); + Vector<real_t> noise_seed_1_2d = get_noise_samples_2d(noise); + Vector<real_t> noise_seed_1_3d = get_noise_samples_3d(noise); + noise.set_seed(123); + Vector<real_t> noise_seed_2_1d = get_noise_samples_1d(noise); + Vector<real_t> noise_seed_2_2d = get_noise_samples_2d(noise); + Vector<real_t> noise_seed_2_3d = get_noise_samples_3d(noise); + + CHECK_FALSE(all_equal_approx(noise_seed_1_1d, noise_seed_2_1d)); + CHECK_FALSE(all_equal_approx(noise_seed_1_2d, noise_seed_2_2d)); + CHECK_FALSE(all_equal_approx(noise_seed_1_3d, noise_seed_2_3d)); + } + + SUBCASE("Different frequencies should produce different noise") { + noise.set_frequency(0.1); + Vector<real_t> noise_frequency_1_1d = get_noise_samples_1d(noise); + Vector<real_t> noise_frequency_1_2d = get_noise_samples_2d(noise); + Vector<real_t> noise_frequency_1_3d = get_noise_samples_3d(noise); + noise.set_frequency(1.0); + Vector<real_t> noise_frequency_2_1d = get_noise_samples_1d(noise); + Vector<real_t> noise_frequency_2_2d = get_noise_samples_2d(noise); + Vector<real_t> noise_frequency_2_3d = get_noise_samples_3d(noise); + + CHECK_FALSE(all_equal_approx(noise_frequency_1_1d, noise_frequency_2_1d)); + CHECK_FALSE(all_equal_approx(noise_frequency_1_2d, noise_frequency_2_2d)); + CHECK_FALSE(all_equal_approx(noise_frequency_1_3d, noise_frequency_2_3d)); + } + + SUBCASE("Noise should be offset by the offset parameter") { + noise.set_offset(Vector3(1, 2, 3)); + Vector<real_t> noise_offset_1_1d = get_noise_samples_1d(noise); + Vector<real_t> noise_offset_1_2d = get_noise_samples_2d(noise); + Vector<real_t> noise_offset_1_3d = get_noise_samples_3d(noise); + noise.set_offset(Vector3(4, 5, 6)); + Vector<real_t> noise_offset_2_1d = get_noise_samples_1d(noise); + Vector<real_t> noise_offset_2_2d = get_noise_samples_2d(noise); + Vector<real_t> noise_offset_2_3d = get_noise_samples_3d(noise); + + CHECK_FALSE(all_equal_approx(noise_offset_1_1d, noise_offset_2_1d)); + CHECK_FALSE(all_equal_approx(noise_offset_1_2d, noise_offset_2_2d)); + CHECK_FALSE(all_equal_approx(noise_offset_1_3d, noise_offset_2_3d)); + } + + SUBCASE("Different noise types should produce different noise") { + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_SIMPLEX); + Vector<real_t> noise_type_simplex_2d = get_noise_samples_2d(noise); + Vector<real_t> noise_type_simplex_3d = get_noise_samples_3d(noise); + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_SIMPLEX_SMOOTH); + Vector<real_t> noise_type_simplex_smooth_2d = get_noise_samples_2d(noise); + Vector<real_t> noise_type_simplex_smooth_3d = get_noise_samples_3d(noise); + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_CELLULAR); + Vector<real_t> noise_type_cellular_2d = get_noise_samples_2d(noise); + Vector<real_t> noise_type_cellular_3d = get_noise_samples_3d(noise); + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_PERLIN); + Vector<real_t> noise_type_perlin_2d = get_noise_samples_2d(noise); + Vector<real_t> noise_type_perlin_3d = get_noise_samples_3d(noise); + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_VALUE); + Vector<real_t> noise_type_value_2d = get_noise_samples_2d(noise); + Vector<real_t> noise_type_value_3d = get_noise_samples_3d(noise); + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_VALUE_CUBIC); + Vector<real_t> noise_type_value_cubic_2d = get_noise_samples_2d(noise); + Vector<real_t> noise_type_value_cubic_3d = get_noise_samples_3d(noise); + + CHECK_ARGS_APPROX_PAIRWISE_DISTINCT_VECS(noise_type_simplex_2d, + noise_type_simplex_smooth_2d, + noise_type_cellular_2d, + noise_type_perlin_2d, + noise_type_value_2d, + noise_type_value_cubic_2d); + + CHECK_ARGS_APPROX_PAIRWISE_DISTINCT_VECS(noise_type_simplex_3d, + noise_type_simplex_smooth_3d, + noise_type_cellular_3d, + noise_type_perlin_3d, + noise_type_value_3d, + noise_type_value_cubic_3d); + } +} + +TEST_CASE("[FastNoiseLite] Fractal noise") { + FastNoiseLite noise; + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_SIMPLEX); + noise.set_offset(Vector3(10, 10, 10)); + noise.set_frequency(0.01); + noise.set_fractal_type(FastNoiseLite::FractalType::FRACTAL_FBM); + noise.set_fractal_octaves(4); + noise.set_fractal_lacunarity(2.0); + noise.set_fractal_gain(0.5); + noise.set_fractal_weighted_strength(0.5); + noise.set_fractal_ping_pong_strength(2.0); + + SUBCASE("Different fractal types should produce different results") { + noise.set_fractal_type(FastNoiseLite::FractalType::FRACTAL_NONE); + Vector<real_t> fractal_type_none_2d = get_noise_samples_2d(noise); + Vector<real_t> fractal_type_none_3d = get_noise_samples_3d(noise); + noise.set_fractal_type(FastNoiseLite::FractalType::FRACTAL_FBM); + Vector<real_t> fractal_type_fbm_2d = get_noise_samples_2d(noise); + Vector<real_t> fractal_type_fbm_3d = get_noise_samples_3d(noise); + noise.set_fractal_type(FastNoiseLite::FractalType::FRACTAL_RIDGED); + Vector<real_t> fractal_type_ridged_2d = get_noise_samples_2d(noise); + Vector<real_t> fractal_type_ridged_3d = get_noise_samples_3d(noise); + noise.set_fractal_type(FastNoiseLite::FractalType::FRACTAL_PING_PONG); + Vector<real_t> fractal_type_ping_pong_2d = get_noise_samples_2d(noise); + Vector<real_t> fractal_type_ping_pong_3d = get_noise_samples_3d(noise); + + CHECK_ARGS_APPROX_PAIRWISE_DISTINCT_VECS(fractal_type_none_2d, + fractal_type_fbm_2d, + fractal_type_ridged_2d, + fractal_type_ping_pong_2d); + + CHECK_ARGS_APPROX_PAIRWISE_DISTINCT_VECS(fractal_type_none_3d, + fractal_type_fbm_3d, + fractal_type_ridged_3d, + fractal_type_ping_pong_3d); + } + + SUBCASE("Different octaves should produce different results") { + noise.set_fractal_octaves(1.0); + Vector<real_t> fractal_octaves_1_2d = get_noise_samples_2d(noise); + Vector<real_t> fractal_octaves_1_3d = get_noise_samples_3d(noise); + noise.set_fractal_octaves(8.0); + Vector<real_t> fractal_octaves_2_2d = get_noise_samples_2d(noise); + Vector<real_t> fractal_octaves_2_3d = get_noise_samples_3d(noise); + + CHECK_FALSE(all_equal_approx(fractal_octaves_1_2d, fractal_octaves_2_2d)); + CHECK_FALSE(all_equal_approx(fractal_octaves_1_3d, fractal_octaves_2_3d)); + } + + SUBCASE("Different lacunarity should produce different results") { + noise.set_fractal_lacunarity(1.0); + Vector<real_t> fractal_lacunarity_1_2d = get_noise_samples_2d(noise); + Vector<real_t> fractal_lacunarity_1_3d = get_noise_samples_3d(noise); + noise.set_fractal_lacunarity(2.0); + Vector<real_t> fractal_lacunarity_2_2d = get_noise_samples_2d(noise); + Vector<real_t> fractal_lacunarity_2_3d = get_noise_samples_3d(noise); + + CHECK_FALSE(all_equal_approx(fractal_lacunarity_1_2d, fractal_lacunarity_2_2d)); + CHECK_FALSE(all_equal_approx(fractal_lacunarity_1_3d, fractal_lacunarity_2_3d)); + } + + SUBCASE("Different gain should produce different results") { + noise.set_fractal_gain(0.5); + Vector<real_t> fractal_gain_1_2d = get_noise_samples_2d(noise); + Vector<real_t> fractal_gain_1_3d = get_noise_samples_3d(noise); + noise.set_fractal_gain(0.75); + Vector<real_t> fractal_gain_2_2d = get_noise_samples_2d(noise); + Vector<real_t> fractal_gain_2_3d = get_noise_samples_3d(noise); + + CHECK_FALSE(all_equal_approx(fractal_gain_1_2d, fractal_gain_2_2d)); + CHECK_FALSE(all_equal_approx(fractal_gain_1_3d, fractal_gain_2_3d)); + } + + SUBCASE("Different weights should produce different results") { + noise.set_fractal_weighted_strength(0.5); + Vector<real_t> fractal_weighted_strength_1_2d = get_noise_samples_2d(noise); + Vector<real_t> fractal_weighted_strength_1_3d = get_noise_samples_3d(noise); + noise.set_fractal_weighted_strength(0.75); + Vector<real_t> fractal_weighted_strength_2_2d = get_noise_samples_2d(noise); + Vector<real_t> fractal_weighted_strength_2_3d = get_noise_samples_3d(noise); + + CHECK_FALSE(all_equal_approx(fractal_weighted_strength_1_2d, fractal_weighted_strength_2_2d)); + CHECK_FALSE(all_equal_approx(fractal_weighted_strength_1_3d, fractal_weighted_strength_2_3d)); + } + + SUBCASE("Different ping pong strength should produce different results") { + noise.set_fractal_type(FastNoiseLite::FractalType::FRACTAL_PING_PONG); + noise.set_fractal_ping_pong_strength(0.5); + Vector<real_t> fractal_ping_pong_strength_1_2d = get_noise_samples_2d(noise); + Vector<real_t> fractal_ping_pong_strength_1_3d = get_noise_samples_3d(noise); + noise.set_fractal_ping_pong_strength(0.75); + Vector<real_t> fractal_ping_pong_strength_2_2d = get_noise_samples_2d(noise); + Vector<real_t> fractal_ping_pong_strength_2_3d = get_noise_samples_3d(noise); + + CHECK_FALSE(all_equal_approx(fractal_ping_pong_strength_1_2d, fractal_ping_pong_strength_2_2d)); + CHECK_FALSE(all_equal_approx(fractal_ping_pong_strength_1_3d, fractal_ping_pong_strength_2_3d)); + } +} + +TEST_CASE("[FastNoiseLite] Cellular noise") { + FastNoiseLite noise; + noise.set_fractal_type(FastNoiseLite::FractalType::FRACTAL_NONE); + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_CELLULAR); + noise.set_cellular_distance_function(FastNoiseLite::CellularDistanceFunction::DISTANCE_EUCLIDEAN); + noise.set_cellular_return_type(FastNoiseLite::CellularReturnType::RETURN_DISTANCE); + noise.set_frequency(1.0); + + SUBCASE("Different distance functions should produce different results") { + noise.set_cellular_distance_function(FastNoiseLite::CellularDistanceFunction::DISTANCE_EUCLIDEAN); + Vector<real_t> cellular_distance_function_euclidean_2d = get_noise_samples_2d(noise); + Vector<real_t> cellular_distance_function_euclidean_3d = get_noise_samples_3d(noise); + noise.set_cellular_distance_function(FastNoiseLite::CellularDistanceFunction::DISTANCE_EUCLIDEAN_SQUARED); + Vector<real_t> cellular_distance_function_euclidean_squared_2d = get_noise_samples_2d(noise); + Vector<real_t> cellular_distance_function_euclidean_squared_3d = get_noise_samples_3d(noise); + noise.set_cellular_distance_function(FastNoiseLite::CellularDistanceFunction::DISTANCE_MANHATTAN); + Vector<real_t> cellular_distance_function_manhattan_2d = get_noise_samples_2d(noise); + Vector<real_t> cellular_distance_function_manhattan_3d = get_noise_samples_3d(noise); + noise.set_cellular_distance_function(FastNoiseLite::CellularDistanceFunction::DISTANCE_HYBRID); + Vector<real_t> cellular_distance_function_hybrid_2d = get_noise_samples_2d(noise); + Vector<real_t> cellular_distance_function_hybrid_3d = get_noise_samples_3d(noise); + + CHECK_ARGS_APPROX_PAIRWISE_DISTINCT_VECS(cellular_distance_function_euclidean_2d, + cellular_distance_function_euclidean_squared_2d, + cellular_distance_function_manhattan_2d, + cellular_distance_function_hybrid_2d); + + CHECK_ARGS_APPROX_PAIRWISE_DISTINCT_VECS(cellular_distance_function_euclidean_3d, + cellular_distance_function_euclidean_squared_3d, + cellular_distance_function_manhattan_3d, + cellular_distance_function_hybrid_3d); + } + + SUBCASE("Different return function types should produce different results") { + noise.set_cellular_return_type(FastNoiseLite::CellularReturnType::RETURN_CELL_VALUE); + Vector<real_t> cellular_return_type_cell_value_2d = get_noise_samples_2d(noise); + Vector<real_t> cellular_return_type_cell_value_3d = get_noise_samples_3d(noise); + noise.set_cellular_return_type(FastNoiseLite::CellularReturnType::RETURN_DISTANCE); + Vector<real_t> cellular_return_type_distance_2d = get_noise_samples_2d(noise); + Vector<real_t> cellular_return_type_distance_3d = get_noise_samples_3d(noise); + noise.set_cellular_return_type(FastNoiseLite::CellularReturnType::RETURN_DISTANCE2); + Vector<real_t> cellular_return_type_distance2_2d = get_noise_samples_2d(noise); + Vector<real_t> cellular_return_type_distance2_3d = get_noise_samples_3d(noise); + noise.set_cellular_return_type(FastNoiseLite::CellularReturnType::RETURN_DISTANCE2_ADD); + Vector<real_t> cellular_return_type_distance2_add_2d = get_noise_samples_2d(noise); + Vector<real_t> cellular_return_type_distance2_add_3d = get_noise_samples_3d(noise); + noise.set_cellular_return_type(FastNoiseLite::CellularReturnType::RETURN_DISTANCE2_SUB); + Vector<real_t> cellular_return_type_distance2_sub_2d = get_noise_samples_2d(noise); + Vector<real_t> cellular_return_type_distance2_sub_3d = get_noise_samples_3d(noise); + noise.set_cellular_return_type(FastNoiseLite::CellularReturnType::RETURN_DISTANCE2_MUL); + Vector<real_t> cellular_return_type_distance2_mul_2d = get_noise_samples_2d(noise); + Vector<real_t> cellular_return_type_distance2_mul_3d = get_noise_samples_3d(noise); + noise.set_cellular_return_type(FastNoiseLite::CellularReturnType::RETURN_DISTANCE2_DIV); + Vector<real_t> cellular_return_type_distance2_div_2d = get_noise_samples_2d(noise); + Vector<real_t> cellular_return_type_distance2_div_3d = get_noise_samples_3d(noise); + + CHECK_ARGS_APPROX_PAIRWISE_DISTINCT_VECS(cellular_return_type_cell_value_2d, + cellular_return_type_distance_2d, + cellular_return_type_distance2_2d, + cellular_return_type_distance2_add_2d, + cellular_return_type_distance2_sub_2d, + cellular_return_type_distance2_mul_2d, + cellular_return_type_distance2_div_2d); + + CHECK_ARGS_APPROX_PAIRWISE_DISTINCT_VECS(cellular_return_type_cell_value_3d, + cellular_return_type_distance_3d, + cellular_return_type_distance2_3d, + cellular_return_type_distance2_add_3d, + cellular_return_type_distance2_sub_3d, + cellular_return_type_distance2_mul_3d, + cellular_return_type_distance2_div_3d); + } + + SUBCASE("Different cellular jitter should produce different results") { + noise.set_cellular_jitter(0.0); + Vector<real_t> cellular_jitter_1_2d = get_noise_samples_2d(noise); + Vector<real_t> cellular_jitter_1_3d = get_noise_samples_3d(noise); + noise.set_cellular_jitter(0.5); + Vector<real_t> cellular_jitter_2_2d = get_noise_samples_2d(noise); + Vector<real_t> cellular_jitter_2_3d = get_noise_samples_3d(noise); + + CHECK_FALSE(all_equal_approx(cellular_jitter_1_2d, cellular_jitter_2_2d)); + CHECK_FALSE(all_equal_approx(cellular_jitter_1_3d, cellular_jitter_2_3d)); + } +} + +TEST_CASE("[FastNoiseLite] Domain warp") { + FastNoiseLite noise; + noise.set_frequency(1.0); + noise.set_domain_warp_amplitude(200.0); + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_SIMPLEX); + noise.set_domain_warp_enabled(true); + + SUBCASE("Different domain warp types should produce different results") { + noise.set_domain_warp_type(FastNoiseLite::DomainWarpType::DOMAIN_WARP_SIMPLEX); + Vector<real_t> domain_warp_type_simplex_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_type_simplex_3d = get_noise_samples_3d(noise); + noise.set_domain_warp_type(FastNoiseLite::DomainWarpType::DOMAIN_WARP_SIMPLEX_REDUCED); + Vector<real_t> domain_warp_type_simplex_reduced_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_type_simplex_reduced_3d = get_noise_samples_3d(noise); + noise.set_domain_warp_type(FastNoiseLite::DomainWarpType::DOMAIN_WARP_BASIC_GRID); + Vector<real_t> domain_warp_type_basic_grid_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_type_basic_grid_3d = get_noise_samples_3d(noise); + + CHECK_ARGS_APPROX_PAIRWISE_DISTINCT_VECS(domain_warp_type_simplex_2d, + domain_warp_type_simplex_reduced_2d, + domain_warp_type_basic_grid_2d); + + CHECK_ARGS_APPROX_PAIRWISE_DISTINCT_VECS(domain_warp_type_simplex_3d, + domain_warp_type_simplex_reduced_3d, + domain_warp_type_basic_grid_3d); + } + + SUBCASE("Different domain warp amplitude should produce different results") { + noise.set_domain_warp_amplitude(0.0); + Vector<real_t> domain_warp_amplitude_1_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_amplitude_1_3d = get_noise_samples_3d(noise); + noise.set_domain_warp_amplitude(100.0); + Vector<real_t> domain_warp_amplitude_2_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_amplitude_2_3d = get_noise_samples_3d(noise); + + CHECK_FALSE(all_equal_approx(domain_warp_amplitude_1_2d, domain_warp_amplitude_2_2d)); + CHECK_FALSE(all_equal_approx(domain_warp_amplitude_1_3d, domain_warp_amplitude_2_3d)); + } + + SUBCASE("Different domain warp frequency should produce different results") { + noise.set_domain_warp_frequency(0.1); + Vector<real_t> domain_warp_frequency_1_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_frequency_1_3d = get_noise_samples_3d(noise); + noise.set_domain_warp_frequency(2.0); + Vector<real_t> domain_warp_frequency_2_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_frequency_2_3d = get_noise_samples_3d(noise); + + CHECK_FALSE(all_equal_approx(domain_warp_frequency_1_2d, domain_warp_frequency_2_2d)); + CHECK_FALSE(all_equal_approx(domain_warp_frequency_1_3d, domain_warp_frequency_2_3d)); + } + + SUBCASE("Different domain warp fractal type should produce different results") { + noise.set_domain_warp_fractal_type(FastNoiseLite::DomainWarpFractalType::DOMAIN_WARP_FRACTAL_NONE); + Vector<real_t> domain_warp_fractal_type_none_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_fractal_type_none_3d = get_noise_samples_3d(noise); + noise.set_domain_warp_fractal_type(FastNoiseLite::DomainWarpFractalType::DOMAIN_WARP_FRACTAL_PROGRESSIVE); + Vector<real_t> domain_warp_fractal_type_progressive_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_fractal_type_progressive_3d = get_noise_samples_3d(noise); + noise.set_domain_warp_fractal_type(FastNoiseLite::DomainWarpFractalType::DOMAIN_WARP_FRACTAL_INDEPENDENT); + Vector<real_t> domain_warp_fractal_type_independent_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_fractal_type_independent_3d = get_noise_samples_3d(noise); + + CHECK_ARGS_APPROX_PAIRWISE_DISTINCT_VECS(domain_warp_fractal_type_none_2d, + domain_warp_fractal_type_progressive_2d, + domain_warp_fractal_type_independent_2d); + + CHECK_ARGS_APPROX_PAIRWISE_DISTINCT_VECS(domain_warp_fractal_type_none_3d, + domain_warp_fractal_type_progressive_3d, + domain_warp_fractal_type_independent_3d); + } + + SUBCASE("Different domain warp fractal octaves should produce different results") { + noise.set_domain_warp_fractal_octaves(1); + Vector<real_t> domain_warp_fractal_octaves_1_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_fractal_octaves_1_3d = get_noise_samples_3d(noise); + noise.set_domain_warp_fractal_octaves(6); + Vector<real_t> domain_warp_fractal_octaves_2_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_fractal_octaves_2_3d = get_noise_samples_3d(noise); + + CHECK_FALSE(all_equal_approx(domain_warp_fractal_octaves_1_2d, domain_warp_fractal_octaves_2_2d)); + CHECK_FALSE(all_equal_approx(domain_warp_fractal_octaves_1_3d, domain_warp_fractal_octaves_2_3d)); + } + + SUBCASE("Different domain warp fractal lacunarity should produce different results") { + noise.set_domain_warp_fractal_lacunarity(0.5); + Vector<real_t> domain_warp_fractal_lacunarity_1_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_fractal_lacunarity_1_3d = get_noise_samples_3d(noise); + noise.set_domain_warp_fractal_lacunarity(5.0); + Vector<real_t> domain_warp_fractal_lacunarity_2_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_fractal_lacunarity_2_3d = get_noise_samples_3d(noise); + + CHECK_FALSE(all_equal_approx(domain_warp_fractal_lacunarity_1_2d, domain_warp_fractal_lacunarity_2_2d)); + CHECK_FALSE(all_equal_approx(domain_warp_fractal_lacunarity_1_3d, domain_warp_fractal_lacunarity_2_3d)); + } + + SUBCASE("Different domain warp fractal gain should produce different results") { + noise.set_domain_warp_fractal_gain(0.1); + Vector<real_t> domain_warp_fractal_gain_1_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_fractal_gain_1_3d = get_noise_samples_3d(noise); + noise.set_domain_warp_fractal_gain(0.9); + Vector<real_t> domain_warp_fractal_gain_2_2d = get_noise_samples_2d(noise); + Vector<real_t> domain_warp_fractal_gain_2_3d = get_noise_samples_3d(noise); + + CHECK_FALSE(all_equal_approx(domain_warp_fractal_gain_1_2d, domain_warp_fractal_gain_2_2d)); + CHECK_FALSE(all_equal_approx(domain_warp_fractal_gain_1_3d, domain_warp_fractal_gain_2_3d)); + } +} + +// Raw image data for the reference images used in the regression tests. +// Generated with the following code: +// for (int y = 0; y < img->get_data().size(); y++) { +// printf("0x%x,", img->get_data()[y]); +// } + +const Vector<uint8_t> ref_img_1_data = { 0xff, 0xe6, 0xd2, 0xc2, 0xb7, 0xb4, 0xb4, 0xb7, 0xc2, 0xd2, 0xe6, 0xe6, 0xcb, 0xb4, 0xa1, 0x94, 0x90, 0x90, 0x94, 0xa1, 0xb4, 0xcb, 0xd2, 0xb4, 0x99, 0x82, 0x72, 0x6c, 0x6c, 0x72, 0x82, 0x99, 0xb4, 0xc2, 0xa1, 0x82, 0x65, 0x50, 0x48, 0x48, 0x50, 0x65, 0x82, 0xa1, 0xb7, 0x94, 0x72, 0x50, 0x32, 0x24, 0x24, 0x32, 0x50, 0x72, 0x94, 0xb4, 0x90, 0x6c, 0x48, 0x24, 0x0, 0x0, 0x24, 0x48, 0x6c, 0x90, 0xb4, 0x90, 0x6c, 0x48, 0x24, 0x0, 0x0, 0x24, 0x48, 0x6c, 0x90, 0xb7, 0x94, 0x72, 0x50, 0x32, 0x24, 0x24, 0x33, 0x50, 0x72, 0x94, 0xc2, 0xa1, 0x82, 0x65, 0x50, 0x48, 0x48, 0x50, 0x66, 0x82, 0xa1, 0xd2, 0xb4, 0x99, 0x82, 0x72, 0x6c, 0x6c, 0x72, 0x82, 0x99, 0xb4, 0xe6, 0xcb, 0xb4, 0xa1, 0x94, 0x90, 0x90, 0x94, 0xa1, 0xb4, 0xcc }; +const Vector<uint8_t> ref_img_2_data = { 0xff, 0xe6, 0xd2, 0xc2, 0xb7, 0xb4, 0xb4, 0xb7, 0xc2, 0xd2, 0xe6, 0xe6, 0xcb, 0xb4, 0xa1, 0x94, 0x90, 0x90, 0x94, 0xa1, 0xb4, 0xcb, 0xd2, 0xb4, 0x99, 0x82, 0x72, 0x6c, 0x6c, 0x72, 0x82, 0x99, 0xb4, 0xc2, 0xa1, 0x82, 0x65, 0x50, 0x48, 0x48, 0x50, 0x65, 0x82, 0xa1, 0xb7, 0x94, 0x72, 0x50, 0x32, 0x24, 0x24, 0x32, 0x50, 0x72, 0x94, 0xb4, 0x90, 0x6c, 0x48, 0x24, 0x0, 0x0, 0x24, 0x48, 0x6c, 0x90, 0xb4, 0x90, 0x6c, 0x48, 0x24, 0x0, 0x0, 0x24, 0x48, 0x6c, 0x90, 0xb7, 0x94, 0x72, 0x50, 0x32, 0x24, 0x24, 0x33, 0x50, 0x72, 0x94, 0xc2, 0xa1, 0x82, 0x65, 0x50, 0x48, 0x48, 0x50, 0x66, 0x82, 0xa1, 0xd2, 0xb4, 0x99, 0x82, 0x72, 0x6c, 0x6c, 0x72, 0x82, 0x99, 0xb4, 0xe6, 0xcb, 0xb4, 0xa1, 0x94, 0x90, 0x90, 0x94, 0xa1, 0xb4, 0xcc }; +const Vector<uint8_t> ref_img_3_data = { 0xff, 0xe6, 0xd2, 0xc2, 0xb7, 0xb4, 0xb4, 0xb7, 0xc2, 0xd2, 0xe6, 0xe6, 0xcb, 0xb4, 0xa1, 0x94, 0x90, 0x90, 0x94, 0xa1, 0xb4, 0xcb, 0xd2, 0xb4, 0x99, 0x82, 0x72, 0x6c, 0x6c, 0x72, 0x82, 0x99, 0xb4, 0xc2, 0xa1, 0x82, 0x65, 0x50, 0x48, 0x48, 0x50, 0x65, 0x82, 0xa1, 0xb7, 0x94, 0x72, 0x50, 0x32, 0x24, 0x24, 0x32, 0x50, 0x72, 0x94, 0xb4, 0x90, 0x6c, 0x48, 0x24, 0x0, 0x0, 0x24, 0x48, 0x6c, 0x90, 0xb4, 0x90, 0x6c, 0x48, 0x24, 0x0, 0x0, 0x24, 0x48, 0x6c, 0x90, 0xb7, 0x94, 0x72, 0x50, 0x32, 0x24, 0x24, 0x33, 0x50, 0x72, 0x94, 0xc2, 0xa1, 0x82, 0x65, 0x50, 0x48, 0x48, 0x50, 0x66, 0x82, 0xa1, 0xd2, 0xb4, 0x99, 0x82, 0x72, 0x6c, 0x6c, 0x72, 0x82, 0x99, 0xb4, 0xe6, 0xcb, 0xb4, 0xa1, 0x94, 0x90, 0x90, 0x94, 0xa1, 0xb4, 0xcc }; + +// Utiliy function to compare two images pixel by pixel (for easy debugging of regressions) +void compare_image_with_reference(const Ref<Image> &p_img, const Ref<Image> &p_reference_img) { + for (int y = 0; y < p_img->get_height(); y++) { + for (int x = 0; x < p_img->get_width(); x++) { + CHECK(p_img->get_pixel(x, y) == p_reference_img->get_pixel(x, y)); + } + } +} + +TEST_CASE("[FastNoiseLite] Generating seamless 2D images (11x11px) and compare to reference images") { + FastNoiseLite noise; + noise.set_noise_type(FastNoiseLite::NoiseType::TYPE_CELLULAR); + noise.set_fractal_type(FastNoiseLite::FractalType::FRACTAL_NONE); + noise.set_cellular_distance_function(FastNoiseLite::CellularDistanceFunction::DISTANCE_EUCLIDEAN); + noise.set_frequency(0.1); + noise.set_cellular_jitter(0.0); + + SUBCASE("Blend skirt 0.0") { + Ref<Image> img = noise.get_seamless_image(11, 11, false, false, 0.0); + + Ref<Image> ref_img_1 = memnew(Image); + ref_img_1->set_data(11, 11, false, Image::FORMAT_L8, ref_img_1_data); + + compare_image_with_reference(img, ref_img_1); + } + + SUBCASE("Blend skirt 0.1") { + Ref<Image> img = noise.get_seamless_image(11, 11, false, false, 0.1); + + Ref<Image> ref_img_2 = memnew(Image); + ref_img_2->set_data(11, 11, false, Image::FORMAT_L8, ref_img_2_data); + + compare_image_with_reference(img, ref_img_2); + } + + SUBCASE("Blend skirt 1.0") { + Ref<Image> img = noise.get_seamless_image(11, 11, false, false, 0.1); + + Ref<Image> ref_img_3 = memnew(Image); + ref_img_3->set_data(11, 11, false, Image::FORMAT_L8, ref_img_3_data); + + compare_image_with_reference(img, ref_img_3); + } +} + +} //namespace TestFastNoiseLite + +#endif // TEST_FASTNOISE_LITE_H |