mirror of
https://github.com/godotengine/godot
synced 2024-11-02 08:18:44 +00:00
199 lines
8.2 KiB
C++
199 lines
8.2 KiB
C++
/**************************************************************************/
|
|
/* 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);
|
|
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));
|
|
}
|