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Merge pull request #44832 from nathansmith339/opensimplex-optimization

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OpenSimplex data optimization
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Rémi Verschelde 2021-01-07 10:51:30 +01:00 committed by GitHub
parent 2e1abfb90f 041fe20f64
commit 55e876777c
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GPG key ID: 4AEE18F83AFDEB23
2 changed files with 8 additions and 16 deletions
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4
modules/opensimplex/doc_classes/OpenSimplexNoise.xml
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@ -32,7 +32,7 @@
<argument index="1" name="height" type="int">
</argument>
<description>
Generate a noise image with the requested [code]width[/code] and [code]height[/code], based on the current noise parameters.
Generate a noise image in [constant Image.FORMAT_L8] format with the requested [code]width[/code] and [code]height[/code], based on the current noise parameters.
</description>
</method>
<method name="get_noise_1d" qualifiers="const">
@ -108,7 +108,7 @@
<argument index="0" name="size" type="int">
</argument>
<description>
Generate a tileable noise image, based on the current noise parameters. Generated seamless images are always square ([code]size[/code] × [code]size[/code]).
Generate a tileable noise image in [constant Image.FORMAT_L8] format, based on the current noise parameters. Generated seamless images are always square ([code]size[/code] × [code]size[/code]).
</description>
</method>
</methods>

20
modules/opensimplex/open_simplex_noise.cpp
View file

@ -104,7 +104,7 @@ void OpenSimplexNoise::set_lacunarity(float p_lacunarity) {
Ref<Image> OpenSimplexNoise::get_image(int p_width, int p_height) const {
Vector<uint8_t> data;
data.resize(p_width * p_height * 4);
data.resize(p_width * p_height);
uint8_t *wd8 = data.ptrw();
@ -112,21 +112,17 @@ Ref<Image> OpenSimplexNoise::get_image(int p_width, int p_height) const {
for (int j = 0; j < p_width; j++) {
float v = get_noise_2d(j, i);
v = v * 0.5 + 0.5; // Normalize [0..1]
uint8_t value = uint8_t(CLAMP(v * 255.0, 0, 255));
wd8[(i * p_width + j) * 4 + 0] = value;
wd8[(i * p_width + j) * 4 + 1] = value;
wd8[(i * p_width + j) * 4 + 2] = value;
wd8[(i * p_width + j) * 4 + 3] = 255;
wd8[(i * p_width + j)] = uint8_t(CLAMP(v * 255.0, 0, 255));
}
}
Ref<Image> image = memnew(Image(p_width, p_height, false, Image::FORMAT_RGBA8, data));
Ref<Image> image = memnew(Image(p_width, p_height, false, Image::FORMAT_L8, data));
return image;
}
Ref<Image> OpenSimplexNoise::get_seamless_image(int p_size) const {
Vector<uint8_t> data;
data.resize(p_size * p_size * 4);
data.resize(p_size * p_size);
uint8_t *wd8 = data.ptrw();
@ -147,15 +143,11 @@ Ref<Image> OpenSimplexNoise::get_seamless_image(int p_size) const {
float v = get_noise_4d(x, y, z, w);
v = v * 0.5 + 0.5; // Normalize [0..1]
uint8_t value = uint8_t(CLAMP(v * 255.0, 0, 255));
wd8[(i * p_size + j) * 4 + 0] = value;
wd8[(i * p_size + j) * 4 + 1] = value;
wd8[(i * p_size + j) * 4 + 2] = value;
wd8[(i * p_size + j) * 4 + 3] = 255;
wd8[(i * p_size + j)] = uint8_t(CLAMP(v * 255.0, 0, 255));
}
}
Ref<Image> image = memnew(Image(p_size, p_size, false, Image::FORMAT_RGBA8, data));
Ref<Image> image = memnew(Image(p_size, p_size, false, Image::FORMAT_L8, data));
return image;
}