java - Java 中的 Perlin 噪声

Question

对于我正在进行的元胞自动机项目，我需要使用不同的算法和技术随机生成二维 boolean 数组。目前，我在应用程序中只有一种随机化类型——循环遍历数组中的每个单元格并生成一个随机 double 变量，然后如果随机数高于 0.5，那么我将该单元格设置为 true，如果不是，则它被设置为假。

我想研究使用更有趣的算法(例如 Perlin 噪声或类似算法)来生成这些 boolean 矩阵。如果您知道除 Perlin Noise 以外的其他任何东西，那么用于地形生成或类似事物的噪声发生器可能会很好(Minecraft 的世界生成给了我这个想法)。

唯一的问题是我不知道从哪里开始(有什么想法吗？):)

Answer 1

我首先想到的是随机位移分形。它还用于生成地形，并且比 Perlin Noise 更容易。

package so;

import java.util.Random;

public class Noise {
    /** Source of entropy */
    private Random rand_;

    /** Amount of roughness */
    float roughness_;

    /** Plasma fractal grid */
    private float[][] grid_;


    /** Generate a noise source based upon the midpoint displacement fractal.
     * 
     * @param rand The random number generator
     * @param roughness a roughness parameter
     * @param width the width of the grid
     * @param height the height of the grid
     */
    public Noise(Random rand, float roughness, int width, int height) {
        roughness_ = roughness / width;
        grid_ = new float[width][height];
        rand_ = (rand == null) ? new Random() : rand;
    }


    public void initialise() {
        int xh = grid_.length - 1;
        int yh = grid_[0].length - 1;

        // set the corner points
        grid_[0][0] = rand_.nextFloat() - 0.5f;
        grid_[0][yh] = rand_.nextFloat() - 0.5f;
        grid_[xh][0] = rand_.nextFloat() - 0.5f;
        grid_[xh][yh] = rand_.nextFloat() - 0.5f;

        // generate the fractal
        generate(0, 0, xh, yh);
    }


    // Add a suitable amount of random displacement to a point
    private float roughen(float v, int l, int h) {
        return v + roughness_ * (float) (rand_.nextGaussian() * (h - l));
    }


    // generate the fractal
    private void generate(int xl, int yl, int xh, int yh) {
        int xm = (xl + xh) / 2;
        int ym = (yl + yh) / 2;
        if ((xl == xm) && (yl == ym)) return;

        grid_[xm][yl] = 0.5f * (grid_[xl][yl] + grid_[xh][yl]);
        grid_[xm][yh] = 0.5f * (grid_[xl][yh] + grid_[xh][yh]);
        grid_[xl][ym] = 0.5f * (grid_[xl][yl] + grid_[xl][yh]);
        grid_[xh][ym] = 0.5f * (grid_[xh][yl] + grid_[xh][yh]);

        float v = roughen(0.5f * (grid_[xm][yl] + grid_[xm][yh]), xl + yl, yh
                + xh);
        grid_[xm][ym] = v;
        grid_[xm][yl] = roughen(grid_[xm][yl], xl, xh);
        grid_[xm][yh] = roughen(grid_[xm][yh], xl, xh);
        grid_[xl][ym] = roughen(grid_[xl][ym], yl, yh);
        grid_[xh][ym] = roughen(grid_[xh][ym], yl, yh);

        generate(xl, yl, xm, ym);
        generate(xm, yl, xh, ym);
        generate(xl, ym, xm, yh);
        generate(xm, ym, xh, yh);
    }


    /**
     * Dump out as a CSV
     */
    public void printAsCSV() {
        for(int i = 0;i < grid_.length;i++) {
            for(int j = 0;j < grid_[0].length;j++) {
                System.out.print(grid_[i][j]);
                System.out.print(",");
            }
            System.out.println();
        }
    }


    /**
     * Convert to a Boolean array
     * @return the boolean array
     */
    public boolean[][] toBooleans() {
        int w = grid_.length;
        int h = grid_[0].length;
        boolean[][] ret = new boolean[w][h];
        for(int i = 0;i < w;i++) {
            for(int j = 0;j < h;j++) {
                ret[i][j] = grid_[i][j] < 0;
            }
        }
        return ret;
    }


    /** For testing */
    public static void main(String[] args) {
        Noise n = new Noise(null, 1.0f, 250, 250);
        n.initialise();
        n.printAsCSV();
    }
}