Leetcode547 朋友圈 图的DFS与unionFind算法
DFS 解法:
public final int findCircleNum(int[][] M) { if (M == null || M.length == 0) return 0; int re = 0; for (int i = 0; i < M.length; i++) { for (int j = 0; j < M[0].length; j++) { if (M[i][j] != 1) continue; M[i][j] = 0; search(M, j, i + 1); re++; } } return re; } private final void search(int[][] M, int x, int begin) { for (int i = 0; i < M.length; i++) { if (M[i][x] == 1) { M[i][x] = 0; search(M, i, begin + 1); } } }
unionFind 解法:
int[] parents; private final int find(int point) { if (parents[point] == point) return point; return find(parents[point]); } private final void union(int point0, int point1) { int parent0 = find(point0); int parent1 = find(point1); if (parent0 == parent1) return; for (int i = 0; i < parents.length; i++) { if (parents[i] == parent1) parents[i] = parent0; } } public final int findCircleNum(int[][] M) { if (M.length == 0) return 0; int re = 0, len = M.length; parents = new int[len]; for (int i = 0; i < len; i++) parents[i] = i; for (int i = 0; i < len; i++) { for (int j = 0; j < len; j++) if (M[i][j] == 1) union(i, j); } for (int i = 0; i < len; i++) { if (parents[i] == i) re++; } return re; }
union 方法时间复杂度为 O(N),采用树形结构,优化 union 方法:
int[] parents; private final int find(int point) { if (parents[point] == point) return point; return find(parents[point]); } private final void union(int point0, int point1) { int parent0 = find(point0); int parent1 = find(point1); if (parent0 == parent1) return; parents[parent1]=parent0; } public final int findCircleNum(int[][] M) { if (M.length == 0) return 0; int re = 0, len = M.length; parents = new int[len]; for (int i = 0; i < len; i++) parents[i] = i; for (int i = 0; i < len; i++) { for (int j = 0; j < len; j++) if (M[i][j] == 1) union(i, j); } for (int i = 0; i < len; i++) { if (parents[i] == i) re++; } return re; }
在构建树的过程中,因为简单的挑选 point0 为根,很容易造成树的深度过深。采用基于重量选取根的方式减少树的深度:
int[] parents; int[] weights; private final int find(int point) { if (parents[point] == point) return point; return find(parents[point]); } private final void union(int point0, int point1) { int parent0 = find(point0); int parent1 = find(point1); if (parent0 == parent1) return; if (weights[parent0] >= weights[parent1]) { parents[parent1] = parent0; weights[parent0] += weights[parent1]; } else { parents[parent0] = parent1; weights[parent1] += weights[parent0]; } } public final int findCircleNum(int[][] M) { if (M.length == 0) return 0; int re = 0, len = M.length; parents = new int[len]; weights = new int[len]; for (int i = 0; i < len; i++) parents[i] = i; for (int i = 0; i < len; i++) { for (int j = 0; j < len; j++) if (M[i][j] == 1) union(i, j); } for (int i = 0; i < len; i++) { if (parents[i] == i) re++; } return re; }
基于深度(秩)可以进一步减小树的深度:
int[] parents; int[] heights; private final int find(int point) { if (parents[point] == point) return point; return find(parents[point]); } private final void union(int point0, int point1) { int parent0 = find(point0); int parent1 = find(point1); if (parent0 == parent1) return; if (heights[parent0] > heights[parent1]) parents[parent1] = parent0; else if (heights[parent0] < heights[parent1]) parents[parent0] = parent1; else { parents[parent1] = parent0; heights[parent0]++; } } public final int findCircleNum(int[][] M) { if (M.length == 0) return 0; int re = 0, len = M.length; parents = new int[len]; heights = new int[len]; for (int i = 0; i < len; i++) parents[i] = i; for (int i = 0; i < len; i++) { for (int j = 0; j < len; j++) if (M[i][j] == 1) union(i, j); } for (int i = 0; i < len; i++) { if (parents[i] == i) re++; } return re; }
因为构建树只是为了确定以根节点划分的关系集合,下方节点的从属关系并不重要。保证根节点不变的情况下压缩路径,进一步减小树的深度:
int[] parents; private final int find(int point) { if (parents[point] == point) return point; return parents[point] = find(parents[point]); } private final void union(int point0, int point1) { int parent0 = find(point0); int parent1 = find(point1); if (parent0 != parent1) parents[parent0] = parent1; } public final int findCircleNum(int[][] M) { if (M.length == 0) return 0; int re = 0, len = M.length; parents = new int[len]; for (int i = 0; i < len; i++) parents[i] = i; for (int i = 0; i < len; i++) { for (int j = 0; j < len; j++) if (M[i][j] == 1) union(i, j); } for (int i = 0; i < len; i++) { if (parents[i] == i) re++; } return re; }
js unionFind算法:
var findCircleNum = function (M) { let len = M.length; let parents = []; for (let i = 0; i < len; i++) parents[i] = i; for (let i = 0; i < len; i++) { for (let j = 0; j < len; j++) { if (M[i][j] == 1) union(i, j,parents); } } let re = 0; for (let i = 0; i < len; i++) { if (parents[i] == i) re++; } return re; }; var union = function (point0, point1, parents) { let root0 = find(point0, parents); let root1 = find(point1, parents); if (root0 == root1) return; parents[root1] = root0; } var find = function (point, parents) { if (parents[point] == point) return point; return parents[point] = find(parents[point], parents); }
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