/**************************************************************************/
/*  noise.cpp                                                             */
/**************************************************************************/
/*                         This file is part of:                          */
/*                             GODOT ENGINE                               */
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/* Copyright (c) 2014-present Godot Engine contributors (see AUTHORS.md). */
/* Copyright (c) 2007-2014 Juan Linietsky, Ariel Manzur.                  */
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#include "noise.h"

#include <float.h>

Vector<Ref<Image>> Noise::_get_seamless_image(int p_width, int p_height, int p_depth, bool p_invert, bool p_in_3d_space, real_t p_blend_skirt, bool p_normalize) const {
	ERR_FAIL_COND_V(p_width <= 0 || p_height <= 0 || p_depth <= 0, Vector<Ref<Image>>());

	int skirt_width = MAX(1, p_width * p_blend_skirt);
	int skirt_height = MAX(1, p_height * p_blend_skirt);
	int skirt_depth = MAX(1, p_depth * p_blend_skirt);
	int src_width = p_width + skirt_width;
	int src_height = p_height + skirt_height;
	int src_depth = p_depth + skirt_depth;

	Vector<Ref<Image>> src = _get_image(src_width, src_height, src_depth, p_invert, p_in_3d_space, p_normalize);
	bool grayscale = (src[0]->get_format() == Image::FORMAT_L8);

	if (grayscale) {
		return _generate_seamless_image<uint8_t>(src, p_width, p_height, p_depth, p_invert, p_blend_skirt);
	} else {
		return _generate_seamless_image<uint32_t>(src, p_width, p_height, p_depth, p_invert, p_blend_skirt);
	}
}

Ref<Image> Noise::get_seamless_image(int p_width, int p_height, bool p_invert, bool p_in_3d_space, real_t p_blend_skirt, bool p_normalize) const {
	Vector<Ref<Image>> images = _get_seamless_image(p_width, p_height, 1, p_invert, p_in_3d_space, p_blend_skirt, p_normalize);
	if (images.size() == 0) {
		return Ref<Image>();
	}
	return images[0];
}

TypedArray<Image> Noise::get_seamless_image_3d(int p_width, int p_height, int p_depth, bool p_invert, real_t p_blend_skirt, bool p_normalize) const {
	Vector<Ref<Image>> images = _get_seamless_image(p_width, p_height, p_depth, p_invert, true, p_blend_skirt, p_normalize);

	TypedArray<Image> ret;
	ret.resize(images.size());
	for (int i = 0; i < images.size(); i++) {
		ret[i] = images[i];
	}
	return ret;
}

// Template specialization for faster grayscale blending.
template <>
uint8_t Noise::_alpha_blend<uint8_t>(uint8_t p_bg, uint8_t p_fg, int p_alpha) const {
	uint16_t alpha = p_alpha + 1;
	uint16_t inv_alpha = 256 - p_alpha;

	return (uint8_t)((alpha * p_fg + inv_alpha * p_bg) >> 8);
}

Vector<Ref<Image>> Noise::_get_image(int p_width, int p_height, int p_depth, bool p_invert, bool p_in_3d_space, bool p_normalize) const {
	ERR_FAIL_COND_V(p_width <= 0 || p_height <= 0 || p_depth <= 0, Vector<Ref<Image>>());

	Vector<Ref<Image>> images;
	images.resize(p_depth);

	if (p_normalize) {
		// Get all values and identify min/max values.
		LocalVector<real_t> values;
		values.resize(p_width * p_height * p_depth);

		real_t min_val = FLT_MAX;
		real_t max_val = -FLT_MAX;
		int idx = 0;
		for (int d = 0; d < p_depth; d++) {
			for (int y = 0; y < p_height; y++) {
				for (int x = 0; x < p_width; x++) {
					values[idx] = p_in_3d_space ? get_noise_3d(x, y, d) : get_noise_2d(x, y);
					if (values[idx] > max_val) {
						max_val = values[idx];
					}
					if (values[idx] < min_val) {
						min_val = values[idx];
					}
					idx++;
				}
			}
		}
		idx = 0;
		// Normalize values and write to texture.
		for (int d = 0; d < p_depth; d++) {
			Vector<uint8_t> data;
			data.resize(p_width * p_height);

			uint8_t *wd8 = data.ptrw();
			uint8_t ivalue;

			for (int y = 0; y < p_height; y++) {
				for (int x = 0; x < p_width; x++) {
					if (max_val == min_val) {
						ivalue = 0;
					} else {
						ivalue = static_cast<uint8_t>(CLAMP((values[idx] - min_val) / (max_val - min_val) * 255.f, 0, 255));
					}

					if (p_invert) {
						ivalue = 255 - ivalue;
					}

					wd8[x + y * p_width] = ivalue;
					idx++;
				}
			}
			Ref<Image> img = memnew(Image(p_width, p_height, false, Image::FORMAT_L8, data));
			images.write[d] = img;
		}
	} else {
		// Without normalization, the expected range of the noise function is [-1, 1].

		for (int d = 0; d < p_depth; d++) {
			Vector<uint8_t> data;
			data.resize(p_width * p_height);

			uint8_t *wd8 = data.ptrw();

			uint8_t ivalue;
			int idx = 0;
			for (int y = 0; y < p_height; y++) {
				for (int x = 0; x < p_width; x++) {
					float value = (p_in_3d_space ? get_noise_3d(x, y, d) : get_noise_2d(x, y));
					ivalue = static_cast<uint8_t>(CLAMP(value * 127.5f + 127.5f, 0.0f, 255.0f));
					wd8[idx] = p_invert ? (255 - ivalue) : ivalue;
					idx++;
				}
			}

			Ref<Image> img = memnew(Image(p_width, p_height, false, Image::FORMAT_L8, data));
			images.write[d] = img;
		}
	}

	return images;
}

Ref<Image> Noise::get_image(int p_width, int p_height, bool p_invert, bool p_in_3d_space, bool p_normalize) const {
	Vector<Ref<Image>> images = _get_image(p_width, p_height, 1, p_invert, p_in_3d_space, p_normalize);
	if (images.is_empty()) {
		return Ref<Image>();
	}
	return images[0];
}

TypedArray<Image> Noise::get_image_3d(int p_width, int p_height, int p_depth, bool p_invert, bool p_normalize) const {
	Vector<Ref<Image>> images = _get_image(p_width, p_height, p_depth, p_invert, true, p_normalize);

	TypedArray<Image> ret;
	ret.resize(images.size());
	for (int i = 0; i < images.size(); i++) {
		ret[i] = images[i];
	}
	return ret;
}

void Noise::_bind_methods() {
	// Noise functions.
	ClassDB::bind_method(D_METHOD("get_noise_1d", "x"), &Noise::get_noise_1d);
	ClassDB::bind_method(D_METHOD("get_noise_2d", "x", "y"), &Noise::get_noise_2d);
	ClassDB::bind_method(D_METHOD("get_noise_2dv", "v"), &Noise::get_noise_2dv);
	ClassDB::bind_method(D_METHOD("get_noise_3d", "x", "y", "z"), &Noise::get_noise_3d);
	ClassDB::bind_method(D_METHOD("get_noise_3dv", "v"), &Noise::get_noise_3dv);

	// Textures.
	ClassDB::bind_method(D_METHOD("get_image", "width", "height", "invert", "in_3d_space", "normalize"), &Noise::get_image, DEFVAL(false), DEFVAL(false), DEFVAL(true));
	ClassDB::bind_method(D_METHOD("get_seamless_image", "width", "height", "invert", "in_3d_space", "skirt", "normalize"), &Noise::get_seamless_image, DEFVAL(false), DEFVAL(false), DEFVAL(0.1), DEFVAL(true));
	ClassDB::bind_method(D_METHOD("get_image_3d", "width", "height", "depth", "invert", "normalize"), &Noise::get_image_3d, DEFVAL(false), DEFVAL(true));
	ClassDB::bind_method(D_METHOD("get_seamless_image_3d", "width", "height", "depth", "invert", "skirt", "normalize"), &Noise::get_seamless_image_3d, DEFVAL(false), DEFVAL(0.1), DEFVAL(true));
}