1 | /**************************************************************************/ |
2 | /* noise.cpp */ |
3 | /**************************************************************************/ |
4 | /* This file is part of: */ |
5 | /* GODOT ENGINE */ |
6 | /* https://godotengine.org */ |
7 | /**************************************************************************/ |
8 | /* Copyright (c) 2014-present Godot Engine contributors (see AUTHORS.md). */ |
9 | /* Copyright (c) 2007-2014 Juan Linietsky, Ariel Manzur. */ |
10 | /* */ |
11 | /* Permission is hereby granted, free of charge, to any person obtaining */ |
12 | /* a copy of this software and associated documentation files (the */ |
13 | /* "Software"), to deal in the Software without restriction, including */ |
14 | /* without limitation the rights to use, copy, modify, merge, publish, */ |
15 | /* distribute, sublicense, and/or sell copies of the Software, and to */ |
16 | /* permit persons to whom the Software is furnished to do so, subject to */ |
17 | /* the following conditions: */ |
18 | /* */ |
19 | /* The above copyright notice and this permission notice shall be */ |
20 | /* included in all copies or substantial portions of the Software. */ |
21 | /* */ |
22 | /* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, */ |
23 | /* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF */ |
24 | /* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. */ |
25 | /* IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY */ |
26 | /* CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, */ |
27 | /* TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE */ |
28 | /* SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */ |
29 | /**************************************************************************/ |
30 | |
31 | #include "noise.h" |
32 | |
33 | #include <float.h> |
34 | |
35 | 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 { |
36 | ERR_FAIL_COND_V(p_width <= 0 || p_height <= 0 || p_depth <= 0, Vector<Ref<Image>>()); |
37 | |
38 | int skirt_width = MAX(1, p_width * p_blend_skirt); |
39 | int skirt_height = MAX(1, p_height * p_blend_skirt); |
40 | int skirt_depth = MAX(1, p_depth * p_blend_skirt); |
41 | int src_width = p_width + skirt_width; |
42 | int src_height = p_height + skirt_height; |
43 | int src_depth = p_depth + skirt_depth; |
44 | |
45 | Vector<Ref<Image>> src = _get_image(src_width, src_height, src_depth, p_invert, p_in_3d_space, p_normalize); |
46 | bool grayscale = (src[0]->get_format() == Image::FORMAT_L8); |
47 | |
48 | if (grayscale) { |
49 | return _generate_seamless_image<uint8_t>(src, p_width, p_height, p_depth, p_invert, p_blend_skirt); |
50 | } else { |
51 | return _generate_seamless_image<uint32_t>(src, p_width, p_height, p_depth, p_invert, p_blend_skirt); |
52 | } |
53 | } |
54 | |
55 | 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 { |
56 | Vector<Ref<Image>> images = _get_seamless_image(p_width, p_height, 1, p_invert, p_in_3d_space, p_blend_skirt, p_normalize); |
57 | return images[0]; |
58 | } |
59 | |
60 | 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 { |
61 | Vector<Ref<Image>> images = _get_seamless_image(p_width, p_height, p_depth, p_invert, true, p_blend_skirt, p_normalize); |
62 | |
63 | TypedArray<Image> ret; |
64 | ret.resize(images.size()); |
65 | for (int i = 0; i < images.size(); i++) { |
66 | ret[i] = images[i]; |
67 | } |
68 | return ret; |
69 | } |
70 | |
71 | // Template specialization for faster grayscale blending. |
72 | template <> |
73 | uint8_t Noise::_alpha_blend<uint8_t>(uint8_t p_bg, uint8_t p_fg, int p_alpha) const { |
74 | uint16_t alpha = p_alpha + 1; |
75 | uint16_t inv_alpha = 256 - p_alpha; |
76 | |
77 | return (uint8_t)((alpha * p_fg + inv_alpha * p_bg) >> 8); |
78 | } |
79 | |
80 | 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 { |
81 | ERR_FAIL_COND_V(p_width <= 0 || p_height <= 0 || p_depth <= 0, Vector<Ref<Image>>()); |
82 | |
83 | Vector<Ref<Image>> images; |
84 | images.resize(p_depth); |
85 | |
86 | if (p_normalize) { |
87 | // Get all values and identify min/max values. |
88 | LocalVector<real_t> values; |
89 | values.resize(p_width * p_height * p_depth); |
90 | |
91 | real_t min_val = FLT_MAX; |
92 | real_t max_val = -FLT_MAX; |
93 | int idx = 0; |
94 | for (int d = 0; d < p_depth; d++) { |
95 | for (int y = 0; y < p_height; y++) { |
96 | for (int x = 0; x < p_width; x++) { |
97 | values[idx] = p_in_3d_space ? get_noise_3d(x, y, d) : get_noise_2d(x, y); |
98 | if (values[idx] > max_val) { |
99 | max_val = values[idx]; |
100 | } |
101 | if (values[idx] < min_val) { |
102 | min_val = values[idx]; |
103 | } |
104 | idx++; |
105 | } |
106 | } |
107 | } |
108 | idx = 0; |
109 | // Normalize values and write to texture. |
110 | for (int d = 0; d < p_depth; d++) { |
111 | Vector<uint8_t> data; |
112 | data.resize(p_width * p_height); |
113 | |
114 | uint8_t *wd8 = data.ptrw(); |
115 | uint8_t ivalue; |
116 | |
117 | for (int y = 0; y < p_height; y++) { |
118 | for (int x = 0; x < p_width; x++) { |
119 | if (max_val == min_val) { |
120 | ivalue = 0; |
121 | } else { |
122 | ivalue = static_cast<uint8_t>(CLAMP((values[idx] - min_val) / (max_val - min_val) * 255.f, 0, 255)); |
123 | } |
124 | |
125 | if (p_invert) { |
126 | ivalue = 255 - ivalue; |
127 | } |
128 | |
129 | wd8[x + y * p_width] = ivalue; |
130 | idx++; |
131 | } |
132 | } |
133 | Ref<Image> img = memnew(Image(p_width, p_height, false, Image::FORMAT_L8, data)); |
134 | images.write[d] = img; |
135 | } |
136 | } else { |
137 | // Without normalization, the expected range of the noise function is [-1, 1]. |
138 | |
139 | for (int d = 0; d < p_depth; d++) { |
140 | Vector<uint8_t> data; |
141 | data.resize(p_width * p_height); |
142 | |
143 | uint8_t *wd8 = data.ptrw(); |
144 | |
145 | uint8_t ivalue; |
146 | int idx = 0; |
147 | for (int y = 0; y < p_height; y++) { |
148 | for (int x = 0; x < p_width; x++) { |
149 | float value = (p_in_3d_space ? get_noise_3d(x, y, d) : get_noise_2d(x, y)); |
150 | ivalue = static_cast<uint8_t>(CLAMP(value * 127.5f + 127.5f, 0.0f, 255.0f)); |
151 | wd8[idx] = p_invert ? (255 - ivalue) : ivalue; |
152 | idx++; |
153 | } |
154 | } |
155 | |
156 | Ref<Image> img = memnew(Image(p_width, p_height, false, Image::FORMAT_L8, data)); |
157 | images.write[d] = img; |
158 | } |
159 | } |
160 | |
161 | return images; |
162 | } |
163 | |
164 | Ref<Image> Noise::get_image(int p_width, int p_height, bool p_invert, bool p_in_3d_space, bool p_normalize) const { |
165 | Vector<Ref<Image>> images = _get_image(p_width, p_height, 1, p_invert, p_in_3d_space, p_normalize); |
166 | return images[0]; |
167 | } |
168 | |
169 | TypedArray<Image> Noise::get_image_3d(int p_width, int p_height, int p_depth, bool p_invert, bool p_normalize) const { |
170 | Vector<Ref<Image>> images = _get_image(p_width, p_height, p_depth, p_invert, true, p_normalize); |
171 | |
172 | TypedArray<Image> ret; |
173 | ret.resize(images.size()); |
174 | for (int i = 0; i < images.size(); i++) { |
175 | ret[i] = images[i]; |
176 | } |
177 | return ret; |
178 | } |
179 | |
180 | void Noise::_bind_methods() { |
181 | // Noise functions. |
182 | ClassDB::bind_method(D_METHOD("get_noise_1d" , "x" ), &Noise::get_noise_1d); |
183 | ClassDB::bind_method(D_METHOD("get_noise_2d" , "x" , "y" ), &Noise::get_noise_2d); |
184 | ClassDB::bind_method(D_METHOD("get_noise_2dv" , "v" ), &Noise::get_noise_2dv); |
185 | ClassDB::bind_method(D_METHOD("get_noise_3d" , "x" , "y" , "z" ), &Noise::get_noise_3d); |
186 | ClassDB::bind_method(D_METHOD("get_noise_3dv" , "v" ), &Noise::get_noise_3dv); |
187 | |
188 | // Textures. |
189 | ClassDB::bind_method(D_METHOD("get_image" , "width" , "height" , "invert" , "in_3d_space" , "normalize" ), &Noise::get_image, DEFVAL(false), DEFVAL(false), DEFVAL(true)); |
190 | 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)); |
191 | ClassDB::bind_method(D_METHOD("get_image_3d" , "width" , "height" , "depth" , "invert" , "normalize" ), &Noise::get_image_3d, DEFVAL(false), DEFVAL(true)); |
192 | 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)); |
193 | } |
194 | |