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authorHendrik Brucker <hendrik.brucker@mail.de>2023-01-06 02:46:08 +0100
committerHendrik Brucker <hendrik.brucker@mail.de>2023-01-06 02:46:08 +0100
commitffb8c74f266f585ff3b494bb9cbaf9d25b8591da (patch)
tree0c091fcb667f8579f0263cc9112f7455ce365e3e /modules/noise/tests
parent95ce236b7d6a70a06ecc13fb08d48da90ed98430 (diff)
Add tests for FastNoiseLite/NoiseTexture
+ fix some issues with seamless noise generation
Diffstat (limited to 'modules/noise/tests')
-rw-r--r--modules/noise/tests/test_fastnoise_lite.h637
-rw-r--r--modules/noise/tests/test_noise_texture_2d.h267
2 files changed, 904 insertions, 0 deletions
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
diff --git a/modules/noise/tests/test_noise_texture_2d.h b/modules/noise/tests/test_noise_texture_2d.h
new file mode 100644
index 0000000000..9e280b5d97
--- /dev/null
+++ b/modules/noise/tests/test_noise_texture_2d.h
@@ -0,0 +1,267 @@
+/**************************************************************************/
+/* test_noise_texture_2d.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_NOISE_TEXTURE_2D_H
+#define TEST_NOISE_TEXTURE_2D_H
+
+#include "tests/test_macros.h"
+
+#include "modules/noise/noise_texture_2d.h"
+
+namespace TestNoiseTexture2D {
+
+class NoiseTextureTester : public RefCounted {
+ GDCLASS(NoiseTextureTester, RefCounted);
+
+ const NoiseTexture2D *const texture;
+
+public:
+ NoiseTextureTester(const NoiseTexture2D *const p_texture) :
+ texture{ p_texture } {};
+
+ Color compute_average_color(const Ref<Image> &p_noise_image) {
+ Color r_avg_color{};
+
+ for (int i = 0; i < p_noise_image->get_width(); ++i) {
+ for (int j = 0; j < p_noise_image->get_height(); ++j) {
+ const Color pixel = p_noise_image->get_pixel(i, j);
+ r_avg_color += pixel;
+ }
+ }
+
+ int pixel_count = p_noise_image->get_width() * p_noise_image->get_height();
+ r_avg_color /= pixel_count;
+ return r_avg_color;
+ }
+
+ void check_mip_and_color_ramp() {
+ const Ref<Image> noise_image = texture->get_image();
+ CHECK(noise_image.is_valid());
+ CHECK(noise_image->get_width() == texture->get_width());
+ CHECK(noise_image->get_height() == texture->get_height());
+
+ CHECK(noise_image->get_format() == Image::FORMAT_RGBA8);
+ CHECK(noise_image->has_mipmaps());
+
+ Color avg_color = compute_average_color(noise_image);
+
+ // Check that the noise texture is modulated correctly by the color ramp (Gradient).
+ CHECK_FALSE_MESSAGE((avg_color.r + avg_color.g + avg_color.b) == doctest::Approx(0.0), "The noise texture should not be all black");
+ CHECK_FALSE_MESSAGE((avg_color.r + avg_color.g + avg_color.b) == doctest::Approx(noise_image->get_width() * noise_image->get_height() * 3.0), "The noise texture should not be all white");
+ CHECK_MESSAGE(avg_color.g == doctest::Approx(0.0), "The noise texture should not have any green when modulated correctly by the color ramp");
+ }
+
+ void check_normal_map() {
+ const Ref<Image> noise_image = texture->get_image();
+ CHECK(noise_image.is_valid());
+ CHECK(noise_image->get_width() == texture->get_width());
+ CHECK(noise_image->get_height() == texture->get_height());
+
+ CHECK(noise_image->get_format() == Image::FORMAT_RGBA8);
+ CHECK_FALSE(noise_image->has_mipmaps());
+
+ Color avg_color = compute_average_color(noise_image);
+
+ // Check for the characteristic color distribution (for tangent space) of a normal map.
+ CHECK(avg_color.r == doctest::Approx(0.5).epsilon(0.05));
+ CHECK(avg_color.g == doctest::Approx(0.5).epsilon(0.05));
+ CHECK(avg_color.b == doctest::Approx(1.0).epsilon(0.05));
+ }
+
+ void check_seamless_texture_grayscale() {
+ const Ref<Image> noise_image = texture->get_image();
+ CHECK(noise_image.is_valid());
+ CHECK(noise_image->get_width() == texture->get_width());
+ CHECK(noise_image->get_height() == texture->get_height());
+
+ CHECK(noise_image->get_format() == Image::FORMAT_L8);
+
+ Color avg_color = compute_average_color(noise_image);
+
+ // Since it's a grayscale image and every channel except the alpha channel has the
+ // same values (conversion happens in Image::get_pixel) we only need to test one channel.
+ CHECK(avg_color.r == doctest::Approx(0.5).epsilon(0.05));
+ }
+
+ void check_seamless_texture_rgba() {
+ const Ref<Image> noise_image = texture->get_image();
+ CHECK(noise_image.is_valid());
+ CHECK(noise_image->get_width() == texture->get_width());
+ CHECK(noise_image->get_height() == texture->get_height());
+
+ CHECK(noise_image->get_format() == Image::FORMAT_RGBA8);
+
+ // Check that the noise texture is modulated correctly by the color ramp (Gradient).
+ Color avg_color = compute_average_color(noise_image);
+
+ // We use a default (black to white) gradient, so the average of the red, green and blue channels should be the same.
+ CHECK(avg_color.r == doctest::Approx(0.5).epsilon(0.05));
+ CHECK(avg_color.g == doctest::Approx(0.5).epsilon(0.05));
+ CHECK(avg_color.b == doctest::Approx(0.5).epsilon(0.05));
+ }
+};
+
+TEST_CASE("[NoiseTexture][SceneTree] Getter and setter") {
+ Ref<NoiseTexture2D> noise_texture = memnew(NoiseTexture2D);
+
+ Ref<FastNoiseLite> noise = memnew(FastNoiseLite);
+ noise_texture->set_noise(noise);
+ CHECK(noise_texture->get_noise() == noise);
+ noise_texture->set_noise(nullptr);
+ CHECK(noise_texture->get_noise() == nullptr);
+
+ noise_texture->set_width(8);
+ noise_texture->set_height(4);
+ CHECK(noise_texture->get_width() == 8);
+ CHECK(noise_texture->get_height() == 4);
+
+ ERR_PRINT_OFF;
+ noise_texture->set_width(-1);
+ noise_texture->set_height(-1);
+ ERR_PRINT_ON;
+ CHECK(noise_texture->get_width() == 8);
+ CHECK(noise_texture->get_height() == 4);
+
+ noise_texture->set_invert(true);
+ CHECK(noise_texture->get_invert() == true);
+ noise_texture->set_invert(false);
+ CHECK(noise_texture->get_invert() == false);
+
+ noise_texture->set_in_3d_space(true);
+ CHECK(noise_texture->is_in_3d_space() == true);
+ noise_texture->set_in_3d_space(false);
+ CHECK(noise_texture->is_in_3d_space() == false);
+
+ noise_texture->set_generate_mipmaps(true);
+ CHECK(noise_texture->is_generating_mipmaps() == true);
+ noise_texture->set_generate_mipmaps(false);
+ CHECK(noise_texture->is_generating_mipmaps() == false);
+
+ noise_texture->set_seamless(true);
+ CHECK(noise_texture->get_seamless() == true);
+ noise_texture->set_seamless(false);
+ CHECK(noise_texture->get_seamless() == false);
+
+ noise_texture->set_seamless_blend_skirt(0.45);
+ CHECK(noise_texture->get_seamless_blend_skirt() == doctest::Approx(0.45));
+
+ ERR_PRINT_OFF;
+ noise_texture->set_seamless_blend_skirt(-1.0);
+ noise_texture->set_seamless_blend_skirt(2.0);
+ CHECK(noise_texture->get_seamless_blend_skirt() == doctest::Approx(0.45));
+ ERR_PRINT_ON;
+
+ noise_texture->set_as_normal_map(true);
+ CHECK(noise_texture->is_normal_map() == true);
+ noise_texture->set_as_normal_map(false);
+ CHECK(noise_texture->is_normal_map() == false);
+
+ noise_texture->set_bump_strength(0.168);
+ CHECK(noise_texture->get_bump_strength() == doctest::Approx(0.168));
+
+ Ref<Gradient> gradient = memnew(Gradient);
+ noise_texture->set_color_ramp(gradient);
+ CHECK(noise_texture->get_color_ramp() == gradient);
+ noise_texture->set_color_ramp(nullptr);
+ CHECK(noise_texture->get_color_ramp() == nullptr);
+}
+
+TEST_CASE("[NoiseTexture2D][SceneTree] Generating a basic noise texture with mipmaps and color ramp modulation") {
+ Ref<NoiseTexture2D> noise_texture = memnew(NoiseTexture2D);
+
+ Ref<FastNoiseLite> noise = memnew(FastNoiseLite);
+ noise_texture->set_noise(noise);
+
+ Ref<Gradient> gradient = memnew(Gradient);
+ Vector<Gradient::Point> points;
+ points.push_back({ 0.0, Color(1, 0, 0) });
+ points.push_back({ 1.0, Color(0, 0, 1) });
+ gradient->set_points(points);
+ noise_texture->set_color_ramp(gradient);
+ noise_texture->set_width(16);
+ noise_texture->set_height(16);
+ noise_texture->set_generate_mipmaps(true);
+
+ Ref<NoiseTextureTester> tester = memnew(NoiseTextureTester(noise_texture.ptr()));
+ noise_texture->connect("changed", callable_mp(tester.ptr(), &NoiseTextureTester::check_mip_and_color_ramp));
+ MessageQueue::get_singleton()->flush();
+}
+
+TEST_CASE("[NoiseTexture2D][SceneTree] Generating a normal map without mipmaps") {
+ Ref<NoiseTexture2D> noise_texture = memnew(NoiseTexture2D);
+
+ Ref<FastNoiseLite> noise = memnew(FastNoiseLite);
+ noise->set_frequency(0.5);
+ noise_texture->set_noise(noise);
+ noise_texture->set_width(16);
+ noise_texture->set_height(16);
+ noise_texture->set_as_normal_map(true);
+ noise_texture->set_bump_strength(0.5);
+ noise_texture->set_generate_mipmaps(false);
+
+ Ref<NoiseTextureTester> tester = memnew(NoiseTextureTester(noise_texture.ptr()));
+ noise_texture->connect("changed", callable_mp(tester.ptr(), &NoiseTextureTester::check_normal_map));
+ MessageQueue::get_singleton()->flush();
+}
+
+TEST_CASE("[NoiseTexture2D][SceneTree] Generating a seamless noise texture") {
+ Ref<NoiseTexture2D> noise_texture = memnew(NoiseTexture2D);
+
+ Ref<FastNoiseLite> noise = memnew(FastNoiseLite);
+ noise->set_frequency(0.5);
+ noise_texture->set_noise(noise);
+ noise_texture->set_width(16);
+ noise_texture->set_height(16);
+ noise_texture->set_seamless(true);
+
+ Ref<NoiseTextureTester> tester = memnew(NoiseTextureTester(noise_texture.ptr()));
+
+ SUBCASE("Grayscale(L8) 16x16, with seamless blend skirt of 0.05") {
+ noise_texture->set_seamless_blend_skirt(0.05);
+ noise_texture->connect("changed", callable_mp(tester.ptr(), &NoiseTextureTester::check_seamless_texture_grayscale));
+ MessageQueue::get_singleton()->flush();
+ }
+
+ SUBCASE("16x16 modulated with default (transparent)black and white gradient (RGBA8), with seamless blend skirt of 1.0") {
+ Ref<Gradient> gradient = memnew(Gradient);
+ Vector<Gradient::Point> points;
+ points.push_back({ 0.0, Color(0, 0, 0, 0) });
+ points.push_back({ 1.0, Color(1, 1, 1, 1) });
+ gradient->set_points(points);
+ noise_texture->set_color_ramp(gradient);
+ noise_texture->set_seamless_blend_skirt(1.0);
+ noise_texture->connect("changed", callable_mp(tester.ptr(), &NoiseTextureTester::check_seamless_texture_rgba));
+ MessageQueue::get_singleton()->flush();
+ }
+}
+
+} //namespace TestNoiseTexture2D
+
+#endif // TEST_NOISE_TEXTURE_2D_H