virtualx-engine/modules/noise/noise.cpp

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/**************************************************************************/
/* noise.cpp */
/**************************************************************************/
/* 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. */
/**************************************************************************/
#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);
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);
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));
}