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Bug fixes and improvements (#1348)

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* Add "reference" for EN version. Bug fixes.

* Unify the figure reference as "the figure below" and "the figure above".
Bug fixes.

* Format the EN markdown files.

* Replace "" with <u></u> for EN version and bug fixes

* Fix biary_tree_dfs.png

* Fix biary_tree_dfs.png

* Fix zh-hant/biary_tree_dfs.png

* Fix heap_sort_step1.png

* Sync zh and zh-hant versions.

* Bug fixes

* Fix EN figures

* Bug fixes

* Fix the figure labels for EN version
This commit is contained in:
Yudong Jin
2024-05-06 14:44:48 +08:00
committed by GitHub
parent 8e60d12151
commit c4a7966882
99 changed files with 615 additions and 259 deletions
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4
codes/typescript/chapter_dynamic_programming/coin_change.ts
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@ -31,7 +31,7 @@ function coinChangeDP(coins: Array<number>, amt: number): number {
return dp[n][amt] !== MAX ? dp[n][amt] : -1;
}
/* 零钱兑换：状态压缩后的动态规划 */
/* 零钱兑换：空间优化后的动态规划 */
function coinChangeDPComp(coins: Array<number>, amt: number): number {
const n = coins.length;
const MAX = amt + 1;
@ -61,7 +61,7 @@ const amt = 4;
let res = coinChangeDP(coins, amt);
console.log(`凑到目标金额所需的最少硬币数量为 ${res}`);
// 状态压缩后的动态规划
// 空间优化后的动态规划
res = coinChangeDPComp(coins, amt);
console.log(`凑到目标金额所需的最少硬币数量为 ${res}`);

4
codes/typescript/chapter_dynamic_programming/coin_change_ii.ts
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@ -30,7 +30,7 @@ function coinChangeIIDP(coins: Array<number>, amt: number): number {
return dp[n][amt];
}
/* 零钱兑换 II：状态压缩后的动态规划 */
/* 零钱兑换 II：空间优化后的动态规划 */
function coinChangeIIDPComp(coins: Array<number>, amt: number): number {
const n = coins.length;
// 初始化 dp 表
@ -59,7 +59,7 @@ const amt = 5;
let res = coinChangeIIDP(coins, amt);
console.log(`凑出目标金额的硬币组合数量为 ${res}`);
// 状态压缩后的动态规划
// 空间优化后的动态规划
res = coinChangeIIDPComp(coins, amt);
console.log(`凑出目标金额的硬币组合数量为 ${res}`);

4
codes/typescript/chapter_dynamic_programming/edit_distance.ts
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@ -90,7 +90,7 @@ function editDistanceDP(s: string, t: string): number {
return dp[n][m];
}
/* 编辑距离：状态压缩后的动态规划 */
/* 编辑距离：空间优化后的动态规划 */
function editDistanceDPComp(s: string, t: string): number {
const n = s.length,
m = t.length;
@ -141,7 +141,7 @@ console.log(`将 ${s} 更改为 ${t} 最少需要编辑 ${res} 步`);
res = editDistanceDP(s, t);
console.log(`将 ${s} 更改为 ${t} 最少需要编辑 ${res} 步`);
// 状态压缩后的动态规划
// 空间优化后的动态规划
res = editDistanceDPComp(s, t);
console.log(`将 ${s} 更改为 ${t} 最少需要编辑 ${res} 步`);

4
codes/typescript/chapter_dynamic_programming/knapsack.ts
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@ -84,7 +84,7 @@ function knapsackDP(
return dp[n][cap];
}
/* 0-1 背包：状态压缩后的动态规划 */
/* 0-1 背包：空间优化后的动态规划 */
function knapsackDPComp(
wgt: Array<number>,
val: Array<number>,
@ -127,7 +127,7 @@ console.log(`不超过背包容量的最大物品价值为 ${res}`);
res = knapsackDP(wgt, val, cap);
console.log(`不超过背包容量的最大物品价值为 ${res}`);
// 状态压缩后的动态规划
// 空间优化后的动态规划
res = knapsackDPComp(wgt, val, cap);
console.log(`不超过背包容量的最大物品价值为 ${res}`);

2
codes/typescript/chapter_dynamic_programming/min_cost_climbing_stairs_dp.ts
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@ -22,7 +22,7 @@ function minCostClimbingStairsDP(cost: Array<number>): number {
return dp[n];
}
/* 爬楼梯最小代价：状态压缩后的动态规划 */
/* 爬楼梯最小代价：空间优化后的动态规划 */
function minCostClimbingStairsDPComp(cost: Array<number>): number {
const n = cost.length - 1;
if (n === 1 || n === 2) {

4
codes/typescript/chapter_dynamic_programming/min_path_sum.ts
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@ -78,7 +78,7 @@ function minPathSumDP(grid: Array<Array<number>>): number {
return dp[n - 1][m - 1];
}
/* 最小路径和：状态压缩后的动态规划 */
/* 最小路径和：空间优化后的动态规划 */
function minPathSumDPComp(grid: Array<Array<number>>): number {
const n = grid.length,
m = grid[0].length;
@ -125,7 +125,7 @@ console.log(`从左上角到右下角的最小路径和为 ${res}`);
res = minPathSumDP(grid);
console.log(`从左上角到右下角的最小路径和为 ${res}`);
// 状态压缩后的动态规划
// 空间优化后的动态规划
res = minPathSumDPComp(grid);
console.log(`从左上角到右下角的最小路径和为 ${res}`);

4
codes/typescript/chapter_dynamic_programming/unbounded_knapsack.ts
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@ -33,7 +33,7 @@ function unboundedKnapsackDP(
return dp[n][cap];
}
/* 完全背包：状态压缩后的动态规划 */
/* 完全背包：空间优化后的动态规划 */
function unboundedKnapsackDPComp(
wgt: Array<number>,
val: Array<number>,
@ -66,7 +66,7 @@ const cap = 4;
let res = unboundedKnapsackDP(wgt, val, cap);
console.log(`不超过背包容量的最大物品价值为 ${res}`);
// 状态压缩后的动态规划
// 空间优化后的动态规划
res = unboundedKnapsackDPComp(wgt, val, cap);
console.log(`不超过背包容量的最大物品价值为 ${res}`);