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@ -833,18 +833,23 @@ Image GenImagePerlinNoise(int width, int height, int offsetX, int offsetY, float |
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{ |
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for (int x = 0; x < width; x++) |
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{ |
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float nx = (float)(x + offsetX)*scale/(float)width; |
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float ny = (float)(y + offsetY)*scale/(float)height; |
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float nx = (float)(x + offsetX)*(scale/(float)width); |
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float ny = (float)(y + offsetY)*(scale/(float)height); |
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// Basic perlin noise implementation (not used) |
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//float p = (stb_perlin_noise3(nx, ny, 0.0f, 0, 0, 0); |
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// Calculate a better perlin noise using fbm (fractal brownian motion) |
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// Typical values to start playing with: |
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// lacunarity = ~2.0 -- spacing between successive octaves (use exactly 2.0 for wrapping output) |
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// gain = 0.5 -- relative weighting applied to each successive octave |
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// octaves = 6 -- number of "octaves" of noise3() to sum |
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float p = stb_perlin_fbm_noise3(nx, ny, 1.0f, 2.0f, 0.5f, 6); |
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// We need to normalize the data from [-1..1] to [0..1] |
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float np = (p + 1.0f)/2.0f; |
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// NOTE: We need to translate the data from [-1..1] to [0..1] |
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float p = (stb_perlin_fbm_noise3(nx, ny, 1.0f, 2.0f, 0.5f, 6) + 1.0f)/2.0f; |
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int intensity = (int)(p*255.0f); |
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int intensity = (int)(np*255.0f); |
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pixels[y*width + x] = (Color){ intensity, intensity, intensity, 255 }; |
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} |
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} |
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