From ac17ab9f16dd89ea0e6d9675ba91a547296b8ff2 Mon Sep 17 00:00:00 2001 From: youngyangyang04 <826123027@qq.com> Date: Thu, 17 Dec 2020 15:42:21 +0800 Subject: [PATCH] Update --- README.md | 4 +- ...\345\214\205\351\227\256\351\242\2301.png" | Bin 0 -> 37807 bytes ...\345\214\205\351\227\256\351\242\2302.png" | Bin 0 -> 39753 bytes ...\345\214\205\351\227\256\351\242\2303.png" | Bin 0 -> 38371 bytes ...\345\214\205\351\227\256\351\242\2304.png" | Bin 0 -> 42037 bytes ...73\351\231\244\345\205\203\347\264\240.md" | 25 ++- ...22\345\205\245\344\275\215\347\275\256.md" | 10 +- ...\346\227\213\347\237\251\351\230\265II.md" | 24 ++- ...40\344\272\214\345\217\211\346\240\221.md" | 2 +- ...04\345\255\220\346\225\260\347\273\204.md" | 21 +- ...15\345\273\272\351\230\237\345\210\227.md" | 179 +++++++++++++++--- ...53\346\211\213\347\273\255\350\264\271.md" | 102 ++++++++++ ...54\346\260\264\346\211\276\351\233\266.md" | 82 +++++++- ...42\351\205\222\351\227\256\351\242\230.md" | 53 ++++++ 14 files changed, 449 insertions(+), 53 deletions(-) create mode 100644 "pics/\345\212\250\346\200\201\350\247\204\345\210\222-\350\203\214\345\214\205\351\227\256\351\242\2301.png" create mode 100644 "pics/\345\212\250\346\200\201\350\247\204\345\210\222-\350\203\214\345\214\205\351\227\256\351\242\2302.png" create mode 100644 "pics/\345\212\250\346\200\201\350\247\204\345\210\222-\350\203\214\345\214\205\351\227\256\351\242\2303.png" create mode 100644 "pics/\345\212\250\346\200\201\350\247\204\345\210\222-\350\203\214\345\214\205\351\227\256\351\242\2304.png" create mode 100644 "problems/0714.\344\271\260\345\215\226\350\202\241\347\245\250\347\232\204\346\234\200\344\275\263\346\227\266\346\234\272\345\220\253\346\211\213\347\273\255\350\264\271.md" diff --git a/README.md b/README.md index cb55bbbcd0..0b3a5a3f52 100644 --- a/README.md +++ b/README.md @@ -213,6 +213,7 @@ * [本周小结!(贪心算法系列二)](https://mp.weixin.qq.com/s/RiQri-4rP9abFmq_mlXNiQ) * [贪心算法:加油站](https://mp.weixin.qq.com/s/aDbiNuEZIhy6YKgQXvKELw) * [贪心算法:分发糖果](https://mp.weixin.qq.com/s/8MwlgFfvaNYmjGwjuMlETQ) + * [贪心算法:柠檬水找零](https://mp.weixin.qq.com/s/0kT4P-hzY7H6Ae0kjQqnZg) * 动态规划 @@ -375,6 +376,7 @@ |[0701.二叉搜索树中的插入操作](https://github.com/youngyangyang04/leetcode/blob/master/problems/0701.二叉搜索树中的插入操作.md) |二叉搜索树 |简单|**递归** **迭代**| |[0705.设计哈希集合](https://github.com/youngyangyang04/leetcode/blob/master/problems/0705.设计哈希集合.md) |哈希表 |简单|**模拟**| |[0707.设计链表](https://github.com/youngyangyang04/leetcode/blob/master/problems/0707.设计链表.md) |链表 |中等|**模拟**| +|[0714.买卖股票的最佳时机含手续费](https://github.com/youngyangyang04/leetcode/blob/master/problems/0714.买卖股票的最佳时机含手续费.md) |贪心 动态规划 |中等|**贪心** **动态规划** 和122.买卖股票的最佳时机II类似,贪心的思路很巧妙| |[0763.划分字母区间](https://github.com/youngyangyang04/leetcode/blob/master/problems/0763.划分字母区间.md) |贪心 |中等|**双指针/贪心** 体现贪心尽可能多的思想| |[0738.单调递增的数字](https://github.com/youngyangyang04/leetcode/blob/master/problems/0738.单调递增的数字.md) |贪心算法 |中等|**贪心算法** 思路不错,贪心好题| |[0739.每日温度](https://github.com/youngyangyang04/leetcode/blob/master/problems/0739.每日温度.md) |栈 |中等|**单调栈** 适合单调栈入门| @@ -388,7 +390,7 @@ |[0973.最接近原点的K个点](https://github.com/youngyangyang04/leetcode/blob/master/problems/0973.最接近原点的K个点.md) |优先级队列 |中等|**优先级队列**| |[0977.有序数组的平方](https://github.com/youngyangyang04/leetcode/blob/master/problems/0977.有序数组的平方.md) |数组 |中等|**双指针** 还是比较巧妙的| |[1002.查找常用字符](https://github.com/youngyangyang04/leetcode/blob/master/problems/1002.查找常用字符.md) |栈 |简单|**栈**| -|[1005.K次取反后最大化的数组和](https://github.com/youngyangyang04/leetcode/blob/master/problems/1005.K次取反后最大化的数组和.md) |贪心/排序 |**贪心算法** 贪心基础题目| +|[1005.K次取反后最大化的数组和](https://github.com/youngyangyang04/leetcode/blob/master/problems/1005.K次取反后最大化的数组和.md) |贪心/排序 |简单|**贪心算法** 贪心基础题目| |[1047.删除字符串中的所有相邻重复项](https://github.com/youngyangyang04/leetcode/blob/master/problems/1047.删除字符串中的所有相邻重复项.md) |哈希表 |简单|**哈希表/数组**| |[1049.最后一块石头的重量II](https://github.com/youngyangyang04/leetcode/blob/master/problems/1049.最后一块石头的重量II.md) |动态规划 |中等|**01背包**| |[1207.独一无二的出现次数](https://github.com/youngyangyang04/leetcode/blob/master/problems/1207.独一无二的出现次数.md) |哈希表 |简单|**哈希** 两层哈希| diff --git "a/pics/\345\212\250\346\200\201\350\247\204\345\210\222-\350\203\214\345\214\205\351\227\256\351\242\2301.png" "b/pics/\345\212\250\346\200\201\350\247\204\345\210\222-\350\203\214\345\214\205\351\227\256\351\242\2301.png" new file mode 100644 index 0000000000000000000000000000000000000000..dd51c5a93fc59b7c90f39765b5c9b6ca6f93a4b2 GIT binary patch literal 37807 zcmeFZc{G&&|38dO!W$J*Wa(29Ld7JzR@s-ag+U8ygkliJjHTsWLLtl8i(%|bw!w%> zAxq5I8D$;&KE_z?*Yy7U-rqXs{^vgDcc1&*=luRCx|+GJ*Y&!d>*M)&T+dC6ba=Rg zxmZ|OcyzB{F=JubgJfZ09p1MW9O?R7R~YH{ zh4tAz7Ix-Gz#ryE!PnDRS@wXRtjuF+Z2#+j_aM{u{IB0xhnXL|taHPNg+-f1_sT`{ zN363$97zIKH+Pp@`ugD7`yqk`7*m0(7ra#0)b~hDD5l(MQyDpO_TA3Q$%L!wT}Rp; zyIe5Hy47}z*Cj&Y+7(H+t%ZvBPgDAu)D&wKx25e{zO5p2d|M4@T^4YQuED`UXFptQ 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zm1OPw=KN-$mgGJ30L8k~zjm6ZqM49=Gg+(!scQ_j7v%T0Ew>bnMdSy@{=Ikpv2-xM zTDjZgA;0}0r@R$^I+t=NvsGQe%MZR+$Q$Mx$-&_}RSwj-Ww4UWmB!^4W>To=AM?HJ73FmwUP8Wa!34R`AD=P$x|GCt{TRo@WI zG%-n}4V~4b&O$DHe@RvAe%q!tGW2Hg2>iXs3vO_6l+ZkV0{P#IQ?&5kiphT!ZI$p~ zV!8MGH~htV{5|i69l^xSqx}BQX)6q~F9IeO$*DfezdncK6PUO=!PdW>6(K(gyMs;t kdzZj8^1mLg0`1YSjyFH#Un4G(K!HCp5--JzMfLsu7f2RQkN^Mx literal 0 HcmV?d00001 diff --git "a/problems/0027.\347\247\273\351\231\244\345\205\203\347\264\240.md" "b/problems/0027.\347\247\273\351\231\244\345\205\203\347\264\240.md" index 71f2af5c75..637bd5ad9d 100644 --- "a/problems/0027.\347\247\273\351\231\244\345\205\203\347\264\240.md" +++ "b/problems/0027.\347\247\273\351\231\244\345\205\203\347\264\240.md" @@ -1,13 +1,21 @@ -> 笔者在BAT从事技术研发多年,利用工作之余重刷leetcode,更多原创文章请关注公众号「代码随想录」。 - -# 题目地址 - -https://leetcode-cn.com/problems/remove-element/ +

+ +

+

+ + + + + + +

> 移除元素想要高效的话,不是很简单! # 编号:27. 移除元素 +题目地址:https://leetcode-cn.com/problems/remove-element/ + 给你一个数组 nums 和一个值 val,你需要 原地 移除所有数值等于 val 的元素,并返回移除后数组的新长度。 不要使用额外的数组空间,你必须仅使用 O(1) 额外空间并**原地**修改输入数组。 @@ -112,7 +120,8 @@ public: }; ``` -拓展: 也可以一个指向前面,一个指向后面,遇到需要删除的就交换,最后返回指针的位置加1,只不过这么做更改了数组元素的位置了,不算是移除元素。 - -> 更多算法干货文章持续更新,可以微信搜索「代码随想录」第一时间围观,关注后,回复「Java」「C++」 「python」「简历模板」「数据结构与算法」等等,就可以获得我多年整理的学习资料。 +**循序渐进学算法,认准「代码随想录」,Carl手把手带你过关斩将!** +

+ +

diff --git "a/problems/0035.\346\220\234\347\264\242\346\217\222\345\205\245\344\275\215\347\275\256.md" "b/problems/0035.\346\220\234\347\264\242\346\217\222\345\205\245\344\275\215\347\275\256.md" index 0cbe7be81b..5c6a154554 100644 --- "a/problems/0035.\346\220\234\347\264\242\346\217\222\345\205\245\344\275\215\347\275\256.md" +++ "b/problems/0035.\346\220\234\347\264\242\346\217\222\345\205\245\344\275\215\347\275\256.md" @@ -44,7 +44,7 @@ 这道题目,要在数组中插入目标值,无非是这四种情况。 - +![35_搜索插入位置3](https://img-blog.csdnimg.cn/20201216232148471.png) * 目标值在数组所有元素之前 * 目标值等于数组中某一个元素 @@ -85,13 +85,13 @@ public: 效率如下: - +![35_搜索插入位置](https://img-blog.csdnimg.cn/20201216232127268.png) ## 二分法 既然暴力解法的时间复杂度是O(n),就要尝试一下使用二分查找法。 - +![35_搜索插入位置4](https://img-blog.csdnimg.cn/202012162326354.png) 大家注意这道题目的前提是数组是有序数组,这也是使用二分查找的基础条件。 @@ -101,7 +101,7 @@ public: 大体讲解一下二分法的思路,这里来举一个例子,例如在这个数组中,使用二分法寻找元素为5的位置,并返回其下标。 - +![35_搜索插入位置5](https://img-blog.csdnimg.cn/20201216232659199.png) 二分查找涉及的很多的边界条件,逻辑比较简单,就是写不好。 @@ -151,7 +151,7 @@ public: 时间复杂度:O(1) 效率如下: - +![35_搜索插入位置2](https://img-blog.csdnimg.cn/2020121623272877.png) ## 二分法第二种写法 diff --git "a/problems/0059.\350\236\272\346\227\213\347\237\251\351\230\265II.md" "b/problems/0059.\350\236\272\346\227\213\347\237\251\351\230\265II.md" index c5c3301a49..111be4c443 100644 --- "a/problems/0059.\350\236\272\346\227\213\347\237\251\351\230\265II.md" +++ "b/problems/0059.\350\236\272\346\227\213\347\237\251\351\230\265II.md" @@ -1,12 +1,22 @@ -> 笔者在BAT从事技术研发多年,利用工作之余重刷leetcode,更多原创文章请关注公众号「代码随想录」。 -# 题目地址 -https://leetcode-cn.com/problems/spiral-matrix-ii/ +

+ +

+

+ + + + + + +

+ > 一进循环深似海,从此offer是路人 # 题目59.螺旋矩阵II +题目地址:https://leetcode-cn.com/problems/spiral-matrix-ii/ 给定一个正整数 n,生成一个包含 1 到 n2 所有元素,且元素按顺时针顺序螺旋排列的正方形矩阵。 示例: @@ -48,7 +58,7 @@ https://leetcode-cn.com/problems/spiral-matrix-ii/ 那么我按照左闭右开的原则,来画一圈,大家看一下: - +![螺旋矩阵](https://img-blog.csdnimg.cn/2020121623550681.png) 这里每一种颜色,代表一条边,我们遍历的长度,可以看出每一个拐角处的处理规则,拐角处让给新的一条边来继续画。 @@ -111,5 +121,9 @@ public: } }; ``` -> 更过算法干货文章持续更新,可以微信搜索「代码随想录」第一时间围观,关注后,回复「Java」「C++」 「python」「简历模板」「数据结构与算法」等等,就可以获得我多年整理的学习资料。 +**循序渐进学算法,认准「代码随想录」,Carl手把手带你过关斩将!** + +

+ +

diff --git "a/problems/0106.\344\273\216\344\270\255\345\272\217\344\270\216\345\220\216\345\272\217\351\201\215\345\216\206\345\272\217\345\210\227\346\236\204\351\200\240\344\272\214\345\217\211\346\240\221.md" "b/problems/0106.\344\273\216\344\270\255\345\272\217\344\270\216\345\220\216\345\272\217\351\201\215\345\216\206\345\272\217\345\210\227\346\236\204\351\200\240\344\272\214\345\217\211\346\240\221.md" index 9b8295b11a..892f21676d 100644 --- "a/problems/0106.\344\273\216\344\270\255\345\272\217\344\270\216\345\220\216\345\272\217\351\201\215\345\216\206\345\272\217\345\210\227\346\236\204\351\200\240\344\272\214\345\217\211\346\240\221.md" +++ "b/problems/0106.\344\273\216\344\270\255\345\272\217\344\270\216\345\220\216\345\272\217\351\201\215\345\216\206\345\272\217\345\210\227\346\236\204\351\200\240\344\272\214\345\217\211\346\240\221.md" @@ -1,7 +1,7 @@ ## 题目地址 https://leetcode-cn.com/problems/construct-binary-tree-from-inorder-and-postorder-traversal/ -> 给出两个序列 +> 给出两个序列 (可以加unorder_map优化一下) 看完本文,可以一起解决如下两道题目 diff --git "a/problems/0209.\351\225\277\345\272\246\346\234\200\345\260\217\347\232\204\345\255\220\346\225\260\347\273\204.md" "b/problems/0209.\351\225\277\345\272\246\346\234\200\345\260\217\347\232\204\345\255\220\346\225\260\347\273\204.md" index f206d64163..1dd5ba15f1 100644 --- "a/problems/0209.\351\225\277\345\272\246\346\234\200\345\260\217\347\232\204\345\255\220\346\225\260\347\273\204.md" +++ "b/problems/0209.\351\225\277\345\272\246\346\234\200\345\260\217\347\232\204\345\255\220\346\225\260\347\273\204.md" @@ -1,10 +1,21 @@ -## 题目地址 -https://leetcode-cn.com/problems/minimum-size-subarray-sum/ +

+ +

+

+ + + + + + +

> 滑动窗口拯救了你 # 题目209.长度最小的子数组 +题目链接: https://leetcode-cn.com/problems/minimum-size-subarray-sum/ + 给定一个含有 n 个正整数的数组和一个正整数 s ,找出该数组中满足其和 ≥ s 的长度最小的 连续 子数组,并返回其长度。如果不存在符合条件的子数组,返回 0。 示例: @@ -107,5 +118,9 @@ public: 时间复杂度:O(n) 空间复杂度:O(1) -> 更多算法干货文章持续更新,可以微信搜索「代码随想录」第一时间围观,关注后,回复「Java」「C++」 「python」「简历模板」「数据结构与算法」等等,就可以获得我多年整理的学习资料。 +**循序渐进学算法,认准「代码随想录」,Carl手把手带你过关斩将!** + +

+ +

diff --git "a/problems/0406.\346\240\271\346\215\256\350\272\253\351\253\230\351\207\215\345\273\272\351\230\237\345\210\227.md" "b/problems/0406.\346\240\271\346\215\256\350\272\253\351\253\230\351\207\215\345\273\272\351\230\237\345\210\227.md" index 6441101039..fa7a360769 100644 --- "a/problems/0406.\346\240\271\346\215\256\350\272\253\351\253\230\351\207\215\345\273\272\351\230\237\345\210\227.md" +++ "b/problems/0406.\346\240\271\346\215\256\350\272\253\351\253\230\351\207\215\345\273\272\351\230\237\345\210\227.md" @@ -1,49 +1,147 @@ +

+ +

+

+ + + + + + +

-## 思路 +> 就不能好好站个队 + +# 406.根据身高重建队列 + +题目链接:https://leetcode-cn.com/problems/queue-reconstruction-by-height/ + +假设有打乱顺序的一群人站成一个队列,数组 people 表示队列中一些人的属性(不一定按顺序)。每个 people[i] = [hi, ki] 表示第 i 个人的身高为 hi ,前面 正好 有 ki 个身高大于或等于 hi 的人。 + +请你重新构造并返回输入数组 people 所表示的队列。返回的队列应该格式化为数组 queue ,其中 queue[j] = [hj, kj] 是队列中第 j 个人的属性(queue[0] 是排在队列前面的人)。 + +示例 1: +输入:people = [[7,0],[4,4],[7,1],[5,0],[6,1],[5,2]] +输出:[[5,0],[7,0],[5,2],[6,1],[4,4],[7,1]] +解释: +编号为 0 的人身高为 5 ,没有身高更高或者相同的人排在他前面。 +编号为 1 的人身高为 7 ,没有身高更高或者相同的人排在他前面。 +编号为 2 的人身高为 5 ,有 2 个身高更高或者相同的人排在他前面,即编号为 0 和 1 的人。 +编号为 3 的人身高为 6 ,有 1 个身高更高或者相同的人排在他前面,即编号为 1 的人。 +编号为 4 的人身高为 4 ,有 4 个身高更高或者相同的人排在他前面,即编号为 0、1、2、3 的人。 +编号为 5 的人身高为 7 ,有 1 个身高更高或者相同的人排在他前面,即编号为 1 的人。 +因此 [[5,0],[7,0],[5,2],[6,1],[4,4],[7,1]] 是重新构造后的队列。 + +示例 2: +输入:people = [[6,0],[5,0],[4,0],[3,2],[2,2],[1,4]] +输出:[[4,0],[5,0],[2,2],[3,2],[1,4],[6,0]] + +提示: + +* 1 <= people.length <= 2000 +* 0 <= hi <= 10^6 +* 0 <= ki < people.length + +题目数据确保队列可以被重建 + +# 思路 本题有两个维度,h和k,看到这种题目一定要想如何确定一个维度,然后在按照另一个维度重新排列。 +其实如果大家认真做了[贪心算法:分发糖果](https://mp.weixin.qq.com/s/8MwlgFfvaNYmjGwjuMlETQ),就会发现和此题有点点的像。 + +在[贪心算法:分发糖果](https://mp.weixin.qq.com/s/8MwlgFfvaNYmjGwjuMlETQ)我就强调过一次,遇到两个维度权衡的时候,一定要先确定一个维度,再确定另一个维度。 + **如果两个维度一起考虑一定会顾此失彼**。 -相信大家困惑的点是先确实k还是先确定h呢,也就是 究竟先按h排序呢,还先按照k排序呢? +对于本题相信大家困惑的点是先确定k还是先确定h呢,也就是究竟先按h排序呢,还先按照k排序呢? 如果按照k来从小到大排序,排完之后,会发现k的排列并不符合条件,身高也不符合条件,两个维度哪一个都没确定下来。 -那么按照身高h来排序呢,身高一定是从大到小排(身高相同k小的站前面),让高个子在前面。 +那么按照身高h来排序呢,身高一定是从大到小排(身高相同的话则k小的站前面),让高个子在前面。 **此时我们可以确定一个维度了,就是身高,前面的节点一定都比本节点高!** -此时只需要按照k为下表重新插入队列,就可以了呢,为什么呢? +那么只需要按照k为下标重新插入队列就可以了,为什么呢? 以图中{5,2} 为例: - +![406.根据身高重建队列](https://img-blog.csdnimg.cn/20201216201851982.png) + + +按照身高排序之后,优先按身高高的people的k来插入,后序插入节点也不会影响前面已经插入的节点,最终按照k的规则完成了队列。 -**都说用贪心算法,是贪心究竟贪在哪里呢?** +所以在按照身高从大到小排序后: -贪心在优先按照身高高的people的k来插入,后序插入节点也不会影响前面已经插入的节点,最终按照k的规则完成了队列。 +**局部最优:优先按身高高的people的k来插入。插入操作过后的people满足队列属性** -局部最优:优先按照身高搞的people的k来插入。插入操作过后的people满足队列属性 +**全局最优:最后都做完插入操作,整个队列满足题目队列属性** -全局最优:最后都做完插入操作,整个队列满足题目队列属性 +局部最优可推出全局最优,找不出反例,那就试试贪心。 -局部最优可推出全局最优。 +一些同学可能也会疑惑,你怎么知道局部最优就可以推出全局最优呢? 有数学证明么? -整个插入过程如下: +在贪心系列开篇词[关于贪心算法,你该了解这些!](https://mp.weixin.qq.com/s/O935TaoHE9Eexwe_vSbRAg)中,我已经讲过了这个问题了。 + +刷题或者面试的时候,手动模拟一下感觉可以局部最优推出整体最优,而且想不到反例,那么就试一试贪心,至于严格的数学证明,就不在讨论范围内了。 + +如果没有读过[关于贪心算法,你该了解这些!](https://mp.weixin.qq.com/s/O935TaoHE9Eexwe_vSbRAg)的同学建议读一下,相信对贪心就有初步的了解了。 + +回归本题,整个插入过程如下: + +排序完的people: +[[7,0], [7,1], [6,1], [5,0], [5,2],[4,4]] -排序完: -[[7,0], [7,1], [6,1], [5,0], [5,2],[4,4]] 插入的过程: -插入[7,0]:[[7,0]] -插入[7,1]:[[7,0],[7,1]] -插入[6,1]:[[7,0],[6,1],[7,1]] -插入[5,0]:[[5,0],[7,0],[6,1],[7,1]] -插入[5,2]:[[5,0],[7,0],[5,2],[6,1],[7,1]] -插入[4,4]:[[5,0],[7,0],[5,2],[6,1],[4,4],[7,1]] +插入[7,0]:[[7,0]] +插入[7,1]:[[7,0],[7,1]] +插入[6,1]:[[7,0],[6,1],[7,1]] +插入[5,0]:[[5,0],[7,0],[6,1],[7,1]] +插入[5,2]:[[5,0],[7,0],[5,2],[6,1],[7,1]] +插入[4,4]:[[5,0],[7,0],[5,2],[6,1],[4,4],[7,1]] +此时就按照题目的要求完成了重新排列。 C++代码如下: + +```C++ +// 版本一 +class Solution { +public: + static bool cmp(const vector a, const vector b) { + if (a[0] == b[0]) return a[1] < b[1]; + return a[0] > b[0]; + } + vector> reconstructQueue(vector>& people) { + sort (people.begin(), people.end(), cmp); + vector> que; + for (int i = 0; i < people.size(); i++) { + int position = people[i][1]; + que.insert(que.begin() + position, people[i]); + } + return que; + } +}; ``` +* 时间复杂度O(nlogn + n^3) +* 空间复杂度O(n) + +大家会发现这个n^3 是怎么来的? + +其实数组的插入操作复杂度是O(n^2):寻找插入元素位置O(1),插入元素O(n^2),因为插入元素后面的元素要整体向后移。 + +如果对数组的增删时间复杂度不清楚的话,可以做做这道题目[数组:就移除个元素很难么?](https://mp.weixin.qq.com/s/wj0T-Xs88_FHJFwayElQlA),数组中插入元素和删除元素都是O(n^2)的复杂度。 + +我们就是要模拟一个插入队列的行为,所以不应该使用数组,而是要使用链表! + +链表的插入操作复杂度是O(n):寻找插入元素位置O(n),插入元素O(1)。 + +可以看出使用链表的插入效率要比普通数组高出一个数量级! + +改成链表之后,C++代码如下: + +```C++ +// 版本二 class Solution { public: // 身高从大到小排(身高相同k小的站前面) @@ -53,16 +151,51 @@ public: } vector> reconstructQueue(vector>& people) { sort (people.begin(), people.end(), cmp); - list> que; // 使用list底层是链表实现,插入效率比vector高的多 + list> que; // list底层是链表实现,插入效率比vector高的多 for (int i = 0; i < people.size(); i++) { int position = people[i][1]; // 插入到下标为position的位置 std::list>::iterator it = que.begin(); - while (position--) { - it++; + while (position--) { // 寻找在插入位置 + it++; } - que.insert(it, people[i]); + que.insert(it, people[i]); } return vector>(que.begin(), que.end()); } }; ``` + +* 时间复杂度O(nlogn + n^2) +* 空间复杂度O(n) + +大家可以把两个版本的代码提交一下试试,就可以发现其差别了! + +# 总结 + +关于出现两个维度一起考虑的情况,我们已经做过两道题目了,另一道就是[贪心算法:分发糖果](https://mp.weixin.qq.com/s/8MwlgFfvaNYmjGwjuMlETQ)。 + +**其技巧都是确定一边然后贪心另一边,两边一起考虑,就会顾此失彼**。 + +这道题目可以说比[贪心算法:分发糖果](https://mp.weixin.qq.com/s/8MwlgFfvaNYmjGwjuMlETQ)难不少,其贪心的策略也是比较巧妙。 + +最后我给出了两个版本的代码,可以明显看是使用C++中的list(底层链表实现)比vector(数组)效率高得多。 + +**对使用某一种语言容器的使用,特性的选择都会不同程度上影响效率**。 + +所以很多人都说写算法题用什么语言都可以,主要体现在算法思维上,其实我是同意的但也不同意。 + +对于看别人题解的同学,题解用什么语言其实影响不大,只要题解把所使用语言特性优化的点讲出来,大家都可以看懂,并使用自己语言的时候注意一下。 + +对于写题解的同学,刷题用什么语言影响就非常大,如果自己语言没有学好而强调算法和编程语言没关系,其实是会误伤别人的。 + +**这也是我为什么统一使用C++写题解的原因**,其实用其他语言java、python、php、go啥的,我也能写,我的Github上也有用这些语言写的小项目,但写题解的话,我就不能保证把语言特性这块讲清楚,所以我始终坚持使用最熟悉的C++写题解。 + +**而且我在写题解的时候涉及语言特性,一般都会后面加上括号说明一下。没办法,认真负责就是我,哈哈**。 + +就酱,「代码随想录」一直都是干货满满,值得介绍给身边的朋友同学们! + +**循序渐进学算法,认准「代码随想录」,Carl手把手带你过关斩将!** + +

+ +

diff --git "a/problems/0714.\344\271\260\345\215\226\350\202\241\347\245\250\347\232\204\346\234\200\344\275\263\346\227\266\346\234\272\345\220\253\346\211\213\347\273\255\350\264\271.md" "b/problems/0714.\344\271\260\345\215\226\350\202\241\347\245\250\347\232\204\346\234\200\344\275\263\346\227\266\346\234\272\345\220\253\346\211\213\347\273\255\350\264\271.md" new file mode 100644 index 0000000000..3b5b634071 --- /dev/null +++ "b/problems/0714.\344\271\260\345\215\226\350\202\241\347\245\250\347\232\204\346\234\200\344\275\263\346\227\266\346\234\272\345\220\253\346\211\213\347\273\255\350\264\271.md" @@ -0,0 +1,102 @@ + +# 思路 +本题相对于[贪心算法:122.买卖股票的最佳时机II](https://mp.weixin.qq.com/s/VsTFA6U96l18Wntjcg3fcg),多添加了一个条件就是手续费。 + +## 贪心算法 + +在[贪心算法:122.买卖股票的最佳时机II](https://mp.weixin.qq.com/s/VsTFA6U96l18Wntjcg3fcg)中使用贪心策略不用关系具体什么时候买卖,只要收集每天的正利润,最后稳稳的就是最大利润了。 + +而本题有了手续费,就要关系什么时候买卖了,因为只计算所获得利润,可能不足以手续费。 + +如果使用贪心策略,就是最低值买,最高值(如果算上手续费还盈利)就卖。 + +此时无非就是要找到两个点,买入日期,和卖出日期。 + +* 买入日期:其实很好想,遇到更低点就记录一下。 +* 卖出日期:这个就不好算了,但也没有必要算出准确的卖出日期,只要当前价格大于(最低价格+费用),就可以收获利润,至于准确的卖出日期,就是连续收获利润区间里的最后一天。 + +所以我们在做收获利润操作的时候其实有两种情况: + +* 情况一:收获利润的这一天并不是收获利润区间里的最后一天(不是真正的卖出,相当于持有股票),所以后面要继续收获利润。 +* 情况二:收获利润的这一天是收获利润区间里的最后一天(相当于真正的卖出了),后面要重新记录最小价格了。 + +贪心算法C++代码如下: + +```C++ +class Solution { +public: + int maxProfit(vector& prices, int fee) { + int result = 0; + int minPrice = prices[0]; // 记录最低价格 + for (int i = 1; i < prices.size(); i++) { + // 买入 + if (prices[i] < minPrice) minPrice = prices[i]; // 情况二 + + // 计算利润,可能有多次计算利润,最后一次计算利润才是真正意义的卖出 + if (prices[i] > minPrice + fee) { + result += prices[i] - minPrice - fee; + minPrice = prices[i] - fee; // 情况一,这一步很关键 + } + } + return result; + } +}; +``` + +从代码中可以看出对情况一的操作,因为如果还在收获利润的区间里,表示并不是真正的卖出,而计算利润每次都要减去手续费, +**所以要让minPrice = prices[i] - fee;,这样在明天收获利润的时候,才不会多减一次手续费!** + +理解这里很关键,其实也是核心所在,很多题解关于这块都没有说清楚。 + +## 动态规划 + +我在「代码随想录」公众号里正在讲解贪心算法,将在下一个系列详细讲解动态规划,所以本题解先给出我的C++代码(带详细注释),感兴趣的同学可以自己先学习一下。 + +相对于[贪心算法:122.买卖股票的最佳时机II](https://mp.weixin.qq.com/s/VsTFA6U96l18Wntjcg3fcg)的动态规划解法中,只需要在计算卖出操作的时候减去手续费就可以了,代码几乎是一样的。 + +C++代码如下: + +```C++ +class Solution { +public: + int maxProfit(vector& prices, int fee) { + // dp[i][1]第i天持有的最多现金 + // dp[i][0]第i天持有股票所剩的最多现金 + int n = prices.size(); + vector> dp(n, vector(2, 0)); + dp[0][0] -= prices[0]; // 持股票 + for (int i = 1; i < n; i++) { + // 第i天持股票所剩最多现金 = max(第i-1天持股票所剩现金, 第i-1天持现金-买第i天的股票) + dp[i][0] = max(dp[i - 1][0], dp[i - 1][1] - prices[i]); + // 第i天持有最多现金 = max(第i-1天持有的最多现金,第i-1天持有股票所剩的最多现金+第i天卖出股票-手续费) + dp[i][1] = max(dp[i - 1][1], dp[i - 1][0] + prices[i] - fee); + } + return max(dp[n - 1][0], dp[n - 1][1]); + } +}; +``` + +当然可以对空间经行优化,因为当前状态只是依赖前一个状态。 + +C++ 代码如下: + +```C++ +class Solution { +public: + int maxProfit(vector& prices, int fee) { + int n = prices.size(); + int holdStock = (-1) * prices[0]; // 持股票 + int saleStock = 0; // 卖出股票 + for (int i = 1; i < n; i++) { + int previousHoldStock = holdStock; + holdStock = max(holdStock, saleStock - prices[i]); + saleStock = max(saleStock, previousHoldStock + prices[i] - fee); + } + return saleStock; + } +}; +``` + +细心的同学可能发现,在计算saleStock的时候 使用的已经是最新的holdStock了,理论上应该使用上一个状态的holdStock即(i-1时候的holdstock),但是 + + diff --git "a/problems/0860.\346\237\240\346\252\254\346\260\264\346\211\276\351\233\266.md" "b/problems/0860.\346\237\240\346\252\254\346\260\264\346\211\276\351\233\266.md" index ca11a168d8..21bc66bc94 100644 --- "a/problems/0860.\346\237\240\346\252\254\346\260\264\346\211\276\351\233\266.md" +++ "b/problems/0860.\346\237\240\346\252\254\346\260\264\346\211\276\351\233\266.md" @@ -1,21 +1,78 @@ -> 如果对贪心算法理论基础还不了解的话,可以看看这篇:[关于贪心算法,你该了解这些!](https://mp.weixin.qq.com/s/O935TaoHE9Eexwe_vSbRAg) ,相信看完之后对贪心就有基本的了解了。 -这道题目我们需要维护三种金额的数量,5,10和20。 +> 给我来一杯柠檬水 + +# 860.柠檬水找零 + +题目链接:https://leetcode-cn.com/problems/lemonade-change/ + +在柠檬水摊上,每一杯柠檬水的售价为 5 美元。 + +顾客排队购买你的产品,(按账单 bills 支付的顺序)一次购买一杯。 + +每位顾客只买一杯柠檬水,然后向你付 5 美元、10 美元或 20 美元。你必须给每个顾客正确找零,也就是说净交易是每位顾客向你支付 5 美元。 + +注意,一开始你手头没有任何零钱。 + +如果你能给每位顾客正确找零,返回 true ,否则返回 false 。 + +示例 1: +输入:[5,5,5,10,20] +输出:true +解释: +前 3 位顾客那里,我们按顺序收取 3 张 5 美元的钞票。 +第 4 位顾客那里,我们收取一张 10 美元的钞票,并返还 5 美元。 +第 5 位顾客那里,我们找还一张 10 美元的钞票和一张 5 美元的钞票。 +由于所有客户都得到了正确的找零,所以我们输出 true。 + +示例 2: +输入:[5,5,10] +输出:true + +示例 3: +输入:[10,10] +输出:false + +示例 4: +输入:[5,5,10,10,20] +输出:false +解释: +前 2 位顾客那里,我们按顺序收取 2 张 5 美元的钞票。 +对于接下来的 2 位顾客,我们收取一张 10 美元的钞票,然后返还 5 美元。 +对于最后一位顾客,我们无法退回 15 美元,因为我们现在只有两张 10 美元的钞票。 +由于不是每位顾客都得到了正确的找零,所以答案是 false。 + +提示: + +* 0 <= bills.length <= 10000 +* bills[i] 不是 5 就是 10 或是 20  + +# 思路 + +这是前几天的leetcode每日一题,感觉不错,给大家讲一下。 + +这道题目刚一看,可能会有点懵,这要怎么找零才能保证完整全部账单的找零呢? + +**但仔细一琢磨就会发现,可供我们做判断的空间非常少!** + +只需要维护三种金额的数量,5,10和20。 有如下三种情况: + * 情况一:账单是5,直接收下。 * 情况二:账单是10,消耗一个5,增加一个10 -* 情况三:账单是20,优先消耗一个10和一个5,如果不够,在消耗三个5 +* 情况三:账单是20,优先消耗一个10和一个5,如果不够,再消耗三个5 + +此时大家就发现 情况一,情况二,都是固定策略,都不用我们来做分析了,而唯一不确定的其实在情况三。 -这道题大家可能感觉纯模拟就可以了,其实这里有贪心,就在情况三中。 +而情况三逻辑也不复杂甚至感觉纯模拟就可以了,其实情况三这里是有贪心的。 账单是20的情况,为什么要优先消耗一个10和一个5呢? **因为美元10只能给账单20找零,而美元5可以给账单10和账单20找零,美元5更万能!** -局部最优:遇到账单20,优先消耗美元10,完成本次找零。全局最优:完成全部账单的找零。 +所以局部最优:遇到账单20,优先消耗美元10,完成本次找零。全局最优:完成全部账单的找零。 -局部最优可以推出全局最优,并找不出反例,那么就试试贪心。 +局部最优可以推出全局最优,并找不出反例,那么就试试贪心算法! C++代码如下: @@ -49,8 +106,19 @@ public: return true; } }; - ``` + +# 总结 + +咋眼一看好像很复杂,分析清楚之后,会发现逻辑其实非常固定。 + +这道题目可以告诉大家,遇到感觉没有思路的题目,可以静下心来把能遇到的情况分析一下,只要分析到具体情况了,一下子就豁然开朗了。 + +如果一直陷入想从整体上寻找找零方案,就会把自己陷进去,各种情况一交叉,只会越想越复杂了。 + +就酱,如果感觉「代码随想录」干货满满,就帮忙宣传一波吧,感激不尽! + + > **我是[程序员Carl](https://github.com/youngyangyang04),可以找我[组队刷题](https://img-blog.csdnimg.cn/20201115103410182.png),也可以在[B站上找到我](https://space.bilibili.com/525438321),本文[leetcode刷题攻略](https://github.com/youngyangyang04/leetcode-master)已收录,更多[精彩算法文章](https://mp.weixin.qq.com/mp/appmsgalbum?__biz=MzUxNjY5NTYxNA==&action=getalbum&album_id=1485825793120387074&scene=173#wechat_redirect)尽在公众号:[代码随想录](https://img-blog.csdnimg.cn/20201124161234338.png),关注后就会发现和「代码随想录」相见恨晚!** **如果感觉题解对你有帮助,不要吝啬给一个👍吧!** diff --git "a/problems/1518.\346\215\242\351\205\222\351\227\256\351\242\230.md" "b/problems/1518.\346\215\242\351\205\222\351\227\256\351\242\230.md" index b72d7d2dd5..3dbd7739f6 100644 --- "a/problems/1518.\346\215\242\351\205\222\351\227\256\351\242\230.md" +++ "b/problems/1518.\346\215\242\351\205\222\351\227\256\351\242\230.md" @@ -1,4 +1,57 @@ +# 1518.换酒问题 + +小区便利店正在促销,用 numExchange 个空酒瓶可以兑换一瓶新酒。你购入了 numBottles 瓶酒。 + +如果喝掉了酒瓶中的酒,那么酒瓶就会变成空的。 + +请你计算 最多 能喝到多少瓶酒。 + + +![1518.换酒问题](https://img-blog.csdnimg.cn/20201215173958151.png) + +输入:numBottles = 9, numExchange = 3 +输出:13 +解释:你可以用 3 个空酒瓶兑换 1 瓶酒。 +所以最多能喝到 9 + 3 + 1 = 13 瓶酒。 + +![1518.换酒问题](https://img-blog.csdnimg.cn/20201215174130529.png) + +输入:numBottles = 15, numExchange = 4 +输出:19 +解释:你可以用 4 个空酒瓶兑换 1 瓶酒。 +所以最多能喝到 15 + 3 + 1 = 19 瓶酒。 + +示例 3: +输入:numBottles = 5, numExchange = 5 +输出:6 + +示例 4: +输入:numBottles = 2, numExchange = 3 +输出:2 + +提示: + +* 1 <= numBottles <= 100 +* 2 <= numExchange <= 100 + +# 思路 + +这道题目其实是很简单的了,简单到大家都不以为这是贪心算法,哈哈 + +来分析一下: + +局部最优:每次换酒用尽可能多的酒瓶。全局最优:喝到最多的酒。 + +局部最优可以推出全局最优,那么这就是贪心! + +本题其实 + + +每次环境 + +其实思路是简单的,但本题在 + ``` // 这道题还是有陷阱啊,15 4 这个例子,答案应该是19 而不是18 class Solution {