算法导论第四版学习——习题一Percolation
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题目正文:
http://coursera.cs.princeton.edu/algs4/assignments/percolation.html
作业难点:
1、backwash(倒灌)的判断,如果不使用另一个WeightedUnionFind对象,要在要求的时间和空间范围内实现是很困难的
和论坛里的学生一样,尝试只只使用上部的虚拟节点,下部判断联通使用循环+break,提交后不满足时间复杂度要求
你也可以不考虑backwash这种情况,因为backwash对连通性并没有直接影响
2、UnionFind数据结构是一维的,但是输入数据是二维的,不用说,这需要两个维度的转换
3、输入数据的下标是1到N,所以必须好好测试边界情况,这点可以用测试数据greeting57.txt测试
作业技巧:
1、一般来说避免不必要的计算,把某些固定的值缓存起来可以提高运行效率,比如计算mean和stddev
2、计算PercolationStats时,需要在未打开的site中按概率P取site打开
这一点其实用random一个站点,判断site已打开再循环找下一个site,直到找到未打开site,就可以满足要求了
应该有更有效率的方法,比如将所有site的下标按一维存储,每次将取出的site下标和最后一位互换,下次random时候取uniform(1,N-1),避免无效尝试,以此类推。
代码参考:
(这是我自己亲测100分的答案,不代表写得最好,请在自己实在完成不了的时候再看,不然的话做这个题目的意义一点都没有)
1 import edu.princeton.cs.algs4.WeightedQuickUnionUF; 2 3 4 public class Percolation { 5 private WeightedQuickUnionUF firstUnionFind; 6 private WeightedQuickUnionUF secondUnionFind; 7 private int row = 0; 8 private boolean[][] site; 9 10 public Percolation(int n) // create n-by-n grid, with all sites blocked 11 { 12 if (n <= 0) { 13 throw new IllegalArgumentException(); 14 } 15 16 firstUnionFind = new WeightedQuickUnionUF((n * n) + 2); 17 secondUnionFind = new WeightedQuickUnionUF((n * n) + 1); 18 row = n; 19 site = new boolean[n][n]; 20 } 21 22 public void open(int i, int j) // open site (row i, column j) if it is not open already 23 { 24 if ((i < 1) || (i > row) || (j < 1) || (j > row)) { 25 throw new IndexOutOfBoundsException(); 26 } 27 site[i - 1][j - 1] = true; 28 int self = (((i - 1) * row) + j) - 1; 29 int up = self - row; 30 int down = self + row; 31 int left = self - 1; 32 int right = self + 1; 33 34 if (i == 1) { 35 firstUnionFind.union(row * row, self); 36 secondUnionFind.union(row * row, self); 37 } 38 if (i == row) { 39 firstUnionFind.union(row * row+1, self); 40 } 41 42 if ((i != 1) && isOpen(i - 1, j)) { 43 firstUnionFind.union(up, self); 44 secondUnionFind.union(up, self); 45 } 46 47 if ((i != row) && isOpen(i + 1, j)) { 48 firstUnionFind.union(down, self); 49 secondUnionFind.union(down, self); 50 } 51 52 if ((j != 1) && isOpen(i, j - 1)) { 53 firstUnionFind.union(left, self); 54 secondUnionFind.union(left, self); 55 } 56 57 if ((j != row) && isOpen(i, j + 1)) { 58 firstUnionFind.union(right, self); 59 secondUnionFind.union(right, self); 60 } 61 } 62 63 public boolean isOpen(int i, int j) // is site (row i, column j) open? 64 { 65 if ((i < 1) || (i > row) || (j < 1) || (j > row)) { 66 throw new IndexOutOfBoundsException(); 67 } 68 return site[i - 1][j - 1]; 69 } 70 71 public boolean isFull(int i, int j) // is site (row i, column j) full? 72 { 73 if ((i < 1) || (i > row) || (j < 1) || (j > row)) { 74 throw new IndexOutOfBoundsException(); 75 } 76 int self = (((i - 1) * row) + j) - 1; 77 return secondUnionFind.connected(row * row, self); 78 } 79 80 public boolean percolates() // does the system percolate? 81 { 82 return firstUnionFind.connected(row * row + 1, row * row); 83 } 84 85 public static void main(String[] args) // test client (optional) 86 { 87 } 88 }
1 import edu.princeton.cs.algs4.StdOut; 2 import edu.princeton.cs.algs4.StdRandom; 3 import edu.princeton.cs.algs4.StdStats; 4 5 6 public class PercolationStats { 7 private int trys = 0; 8 private double[] successTrials; 9 private double mean = 0; 10 private double stddev = 0; 11 12 public PercolationStats(int n, int trials) // perform trials independent experiments on an n-by-n grid 13 { 14 if ((n <= 0) || (trials <= 0)) { 15 throw new IllegalArgumentException(); 16 } 17 18 trys = trials; 19 successTrials = new double[trys]; 20 21 for (int i = 0; i < trials; i++) { 22 successTrials[i] = 0; 23 24 Percolation percolationTries = new Percolation(n); 25 26 while (!percolationTries.percolates()) { 27 int a = StdRandom.uniform(1, n + 1); 28 int b = StdRandom.uniform(1, n + 1); 29 30 while (percolationTries.isOpen(a, b)) { 31 a = StdRandom.uniform(1, n + 1); 32 b = StdRandom.uniform(1, n + 1); 33 } 34 35 percolationTries.open(a, b); 36 successTrials[i]++; 37 } 38 39 successTrials[i] = successTrials[i] / (n * n); 40 } 41 mean = StdStats.mean(successTrials); 42 stddev = StdStats.stddev(successTrials); 43 } 44 45 public double mean() // sample mean of percolation threshold 46 { 47 return mean; 48 } 49 50 public double stddev() // sample standard deviation of percolation threshold 51 { 52 return stddev; 53 } 54 55 public double confidenceLo() // low endpoint of 95% confidence interval 56 { 57 return mean - ((1.96 * stddev) / Math.sqrt(trys)); 58 } 59 60 public double confidenceHi() // high endpoint of 95% confidence interval 61 { 62 return mean + ((1.96 * stddev) / Math.sqrt(trys)); 63 } 64 65 public static void main(String[] args) // test client (described below) 66 { 67 int n = Integer.parseInt(args[0]); 68 int trials = Integer.parseInt(args[1]); 69 PercolationStats percolationStatsCase = new PercolationStats(n, trials); 70 StdOut.printf("%-24s", "mean"); 71 StdOut.printf("= %.16f\\n", percolationStatsCase.mean()); 72 StdOut.printf("%-24s", "stddev"); 73 StdOut.printf("= %.18f\\n", percolationStatsCase.stddev()); 74 StdOut.printf("%-24s", "95% confidence interval"); 75 StdOut.printf("= %.16f, %.16f\\n", percolationStatsCase.confidenceLo(), 76 percolationStatsCase.confidenceHi()); 77 } 78 }
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