问题描述
对于一个正在进行的细胞自动机项目,我需要使用不同的算法和技术随机生成二维布尔数组.目前,我在应用程序中只有一种随机类型-遍历数组中的每个单元格并生成一个随机双精度变量,然后,如果随机数大于0.5,则将该单元格设置为true,否则将其设置为true.为假.
For a cellular automata project I'm working on I need to generate two dimensional boolean arrays randomly using different algorithms and techniques. At the moment I have just one type of randomization in the application - looping through every cell in the array and generating a random double variable, then if the random number is higher than 0.5 then I set that cell to true, if not it gets set to false.
我想研究使用更有趣的算法(例如Perlin Noise或类似的东西)生成这些布尔矩阵.如果您知道除Perlin Noise以外的任何其他东西,则用于地形生成或类似之类的噪声生成器可能会很好(Minecraft的世界一代给了我这个想法).
I would like to look into generating these boolean matrices using more interesting algorithms such as Perlin Noise or something like that. Noise generators that are used in terrain generation or something like that might be good if you know of any other than Perlin Noise (Minecraft's world generation gave me this idea).
唯一的问题是我不知道从哪里开始(有什么想法?):)
The only problem is I have no idea where to start (any ideas?) :)
推荐答案
我想到的第一件事是随机位移分形.它也可用于生成地形,并且比Perlin Noise更容易.
The first thing I thought of was a random displacement fractal. It is also used to generate terrain and is easier than Perlin Noise.
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();
}
}
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