/**************************************************************************/
/*  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.                 */
/**************************************************************************/

#pragma once

#include "../fastnoise_lite.h"

#include "tests/test_macros.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
