leetcode-problemset/leetcode-cn/originData/maximize-grid-happiness.json

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            "title": "Maximize Grid Happiness",
            "titleSlug": "maximize-grid-happiness",
            "content": "<p>You are given four integers, <code>m</code>, <code>n</code>, <code>introvertsCount</code>, and <code>extrovertsCount</code>. You have an <code>m x n</code> grid, and there are two types of people: introverts and extroverts. There are <code>introvertsCount</code> introverts and <code>extrovertsCount</code> extroverts.</p>\n\n<p>You should decide how many people you want to live in the grid and assign each of them one grid cell. Note that you <strong>do not</strong> have to have all the people living in the grid.</p>\n\n<p>The <strong>happiness</strong> of each person is calculated as follows:</p>\n\n<ul>\n\t<li>Introverts <strong>start</strong> with <code>120</code> happiness and <strong>lose</strong> <code>30</code> happiness for each neighbor (introvert or extrovert).</li>\n\t<li>Extroverts <strong>start</strong> with <code>40</code> happiness and <strong>gain</strong> <code>20</code> happiness for each neighbor (introvert or extrovert).</li>\n</ul>\n\n<p>Neighbors live in the directly adjacent cells north, east, south, and west of a person&#39;s cell.</p>\n\n<p>The <strong>grid happiness</strong> is the <strong>sum</strong> of each person&#39;s happiness. Return<em> the <strong>maximum possible grid happiness</strong>.</em></p>\n\n<p>&nbsp;</p>\n<p><strong>Example 1:</strong></p>\n<img alt=\"\" src=\"https://assets.leetcode.com/uploads/2020/11/05/grid_happiness.png\" style=\"width: 261px; height: 121px;\" />\n<pre>\n<strong>Input:</strong> m = 2, n = 3, introvertsCount = 1, extrovertsCount = 2\n<strong>Output:</strong> 240\n<strong>Explanation:</strong> Assume the grid is 1-indexed with coordinates (row, column).\nWe can put the introvert in cell (1,1) and put the extroverts in cells (1,3) and (2,3).\n- Introvert at (1,1) happiness: 120 (starting happiness) - (0 * 30) (0 neighbors) = 120\n- Extrovert at (1,3) happiness: 40 (starting happiness) + (1 * 20) (1 neighbor) = 60\n- Extrovert at (2,3) happiness: 40 (starting happiness) + (1 * 20) (1 neighbor) = 60\nThe grid happiness is 120 + 60 + 60 = 240.\nThe above figure shows the grid in this example with each person&#39;s happiness. The introvert stays in the light green cell while the extroverts live on the light purple cells.\n</pre>\n\n<p><strong>Example 2:</strong></p>\n\n<pre>\n<strong>Input:</strong> m = 3, n = 1, introvertsCount = 2, extrovertsCount = 1\n<strong>Output:</strong> 260\n<strong>Explanation:</strong> Place the two introverts in (1,1) and (3,1) and the extrovert at (2,1).\n- Introvert at (1,1) happiness: 120 (starting happiness) - (1 * 30) (1 neighbor) = 90\n- Extrovert at (2,1) happiness: 40 (starting happiness) + (2 * 20) (2 neighbors) = 80\n- Introvert at (3,1) happiness: 120 (starting happiness) - (1 * 30) (1 neighbor) = 90\nThe grid happiness is 90 + 80 + 90 = 260.\n</pre>\n\n<p><strong>Example 3:</strong></p>\n\n<pre>\n<strong>Input:</strong> m = 2, n = 2, introvertsCount = 4, extrovertsCount = 0\n<strong>Output:</strong> 240\n</pre>\n\n<p>&nbsp;</p>\n<p><strong>Constraints:</strong></p>\n\n<ul>\n\t<li><code>1 &lt;= m, n &lt;= 5</code></li>\n\t<li><code>0 &lt;= introvertsCount, extrovertsCount &lt;= min(m * n, 6)</code></li>\n</ul>\n",
            "translatedTitle": "最大化网格幸福感",
            "translatedContent": "<p>给你四个整数 <code>m</code>、<code>n</code>、<code>introvertsCount</code> 和 <code>extrovertsCount</code> 。有一个 <code>m x n</code> 网格，和两种类型的人：内向的人和外向的人。总共有 <code>introvertsCount</code> 个内向的人和 <code>extrovertsCount</code> 个外向的人。</p>\n\n<p>请你决定网格中应当居住多少人，并为每个人分配一个网格单元。 注意，<strong>不必</strong> 让所有人都生活在网格中。</p>\n\n<p>每个人的 <strong>幸福感</strong> 计算如下：</p>\n\n<ul>\n\t<li>内向的人 <strong>开始</strong> 时有 <code>120</code> 个幸福感，但每存在一个邻居（内向的或外向的）他都会 <strong>失去</strong>  <code>30</code> 个幸福感。</li>\n\t<li>外向的人 <strong>开始</strong> 时有 <code>40</code> 个幸福感，每存在一个邻居（内向的或外向的）他都会 <strong>得到</strong>  <code>20</code> 个幸福感。</li>\n</ul>\n\n<p>邻居是指居住在一个人所在单元的上、下、左、右四个直接相邻的单元中的其他人。</p>\n\n<p><strong>网格幸福感</strong> 是每个人幸福感的 <strong>总和</strong> 。 返回 <strong>最大可能的网格幸福感</strong> 。</p>\n\n<p> </p>\n\n<p><strong>示例 1：</strong></p>\n<img alt=\"\" src=\"https://assets.leetcode-cn.com/aliyun-lc-upload/uploads/2020/11/15/grid_happiness.png\" style=\"width: 261px; height: 121px;\" />\n<pre>\n<strong>输入：</strong>m = 2, n = 3, introvertsCount = 1, extrovertsCount = 2\n<strong>输出：</strong>240\n<strong>解释：</strong>假设网格坐标 (row, column) 从 1 开始编号。\n将内向的人放置在单元 (1,1) ，将外向的人放置在单元 (1,3) 和 (2,3) 。\n- 位于 (1,1) 的内向的人的幸福感：120（初始幸福感）- (0 * 30)（0 位邻居）= 120\n- 位于 (1,3) 的外向的人的幸福感：40（初始幸福感）+ (1 * 20)（1 位邻居）= 60\n- 位于 (2,3) 的外向的人的幸福感：40（初始幸福感）+ (1 * 20)（1 位邻居）= 60\n网格幸福感为：120 + 60 + 60 = 240\n上图展示该示例对应网格中每个人的幸福感。内向的人在浅绿色单元中，而外向的人在浅紫色单元中。\n</pre>\n\n<p><strong>示例 2：</strong></p>\n\n<pre>\n<strong>输入：</strong>m = 3, n = 1, introvertsCount = 2, extrovertsCount = 1\n<strong>输出：</strong>260\n<strong>解释：</strong>将内向的人放置在单元 (1,1) 和 (3,1) ，将外向的人放置在单元 (2,1) 。\n- 位于 (1,1) 的内向的人的幸福感：120（初始幸福感）- (1 * 30)（1 位邻居）= 90\n- 位于 (2,1) 的外向的人的幸福感：40（初始幸福感）+ (2 * 20)（2 位邻居）= 80\n- 位于 (3,1) 的内向的人的幸福感：120（初始幸福感）- (1 * 30)（1 位邻居）= 90\n网格幸福感为 90 + 80 + 90 = 260\n</pre>\n\n<p><strong>示例 3：</strong></p>\n\n<pre>\n<strong>输入：</strong>m = 2, n = 2, introvertsCount = 4, extrovertsCount = 0\n<strong>输出：</strong>240\n</pre>\n\n<p> </p>\n\n<p><strong>提示：</strong></p>\n\n<ul>\n\t<li><code>1 <= m, n <= 5</code></li>\n\t<li><code>0 <= introvertsCount, extrovertsCount <= min(m * n, 6)</code></li>\n</ul>\n",
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href=\\\"https:\\/\\/github.com\\/datastructures-js\\/queue\\\" target=\\\"_blank\\\"> datastructures-js\\/queue<\\/a>\\u3002<\\/p>\"],\"ruby\":[\"Ruby\",\"<p>\\u4f7f\\u7528<code>Ruby 3.1<\\/code>\\u6267\\u884c<\\/p>\\r\\n\\r\\n<p>\\u4e00\\u4e9b\\u5e38\\u7528\\u7684\\u6570\\u636e\\u7ed3\\u6784\\u5df2\\u5728 Algorithms \\u6a21\\u5757\\u4e2d\\u63d0\\u4f9b\\uff1ahttps:\\/\\/www.rubydoc.info\\/github\\/kanwei\\/algorithms\\/Algorithms<\\/p>\"],\"swift\":[\"Swift\",\"<p>\\u7248\\u672c\\uff1a<code>Swift 5.5.2<\\/code><\\/p>\\r\\n\\r\\n<p>\\u6211\\u4eec\\u901a\\u5e38\\u4fdd\\u8bc1\\u66f4\\u65b0\\u5230 <a href=\\\"https:\\/\\/swift.org\\/download\\/\\\" target=\\\"_blank\\\">Apple\\u653e\\u51fa\\u7684\\u6700\\u65b0\\u7248Swift<\\/a>\\u3002\\u5982\\u679c\\u60a8\\u53d1\\u73b0Swift\\u4e0d\\u662f\\u6700\\u65b0\\u7248\\u7684\\uff0c\\u8bf7\\u8054\\u7cfb\\u6211\\u4eec\\uff01\\u6211\\u4eec\\u5c06\\u5c3d\\u5feb\\u66f4\\u65b0\\u3002<\\/p>\"],\"golang\":[\"Go\",\"<p>\\u7248\\u672c\\uff1a<code>Go 1.17<\\/code><\\/p>\\r\\n\\r\\n<p>\\u652f\\u6301 <a href=\\\"https:\\/\\/godoc.org\\/github.com\\/emirpasic\\/gods\\\" target=\\\"_blank\\\">https:\\/\\/godoc.org\\/github.com\\/emirpasic\\/gods<\\/a> \\u7b2c\\u4e09\\u65b9\\u5e93\\u3002<\\/p>\"],\"python3\":[\"Python3\",\"<p>\\u7248\\u672c\\uff1a<code>Python 3.10<\\/code><\\/p>\\r\\n\\r\\n<p>\\u4e3a\\u4e86\\u65b9\\u4fbf\\u8d77\\u89c1\\uff0c\\u5927\\u90e8\\u5206\\u5e38\\u7528\\u5e93\\u5df2\\u7ecf\\u88ab\\u81ea\\u52a8 \\u5bfc\\u5165\\uff0c\\u5982<a href=\\\"https:\\/\\/docs.python.org\\/3\\/library\\/array.html\\\" target=\\\"_blank\\\">array<\\/a>, <a href=\\\"https:\\/\\/docs.python.org\\/3\\/library\\/bisect.html\\\" target=\\\"_blank\\\">bisect<\\/a>, <a href=\\\"https:\\/\\/docs.python.org\\/3\\/library\\/collections.html\\\" target=\\\"_blank\\\">collections<\\/a>\\u3002 \\u5982\\u679c\\u60a8\\u9700\\u8981\\u4f7f\\u7528\\u5176\\u4ed6\\u5e93\\u51fd\\u6570\\uff0c\\u8bf7\\u81ea\\u884c\\u5bfc\\u5165\\u3002<\\/p>\\r\\n\\r\\n<p>\\u5982\\u9700\\u4f7f\\u7528 Map\\/TreeMap \\u6570\\u636e\\u7ed3\\u6784\\uff0c\\u60a8\\u53ef\\u4f7f\\u7528 <a href=\\\"http:\\/\\/www.grantjenks.com\\/docs\\/sortedcontainers\\/\\\" target=\\\"_blank\\\">sortedcontainers<\\/a> \\u5e93\\u3002<\\/p>\"],\"scala\":[\"Scala\",\"<p>\\u7248\\u672c\\uff1a<code>Scala 2.13<\\/code><\\/p>\"],\"kotlin\":[\"Kotlin\",\"<p>\\u7248\\u672c\\uff1a<code>Kotlin 1.3.10<\\/code><\\/p>\"],\"rust\":[\"Rust\",\"<p>\\u7248\\u672c\\uff1a<code>rust 1.58.1<\\/code><\\/p>\\r\\n\\r\\n<p>\\u652f\\u6301 crates.io \\u7684 <a href=\\\"https:\\/\\/crates.io\\/crates\\/rand\\\" target=\\\"_blank\\\">rand<\\/a><\\/p>\"],\"php\":[\"PHP\",\"<p><code>PHP 8.1<\\/code>.<\\/p>\\r\\n\\r\\n<p>With bcmath module.<\\/p>\"],\"typescript\":[\"TypeScript\",\"<p>TypeScript 4.5.4<\\/p>\\r\\n\\r\\n<p>Compile Options: --alwaysStrict --strictBindCallApply --strictFunctionTypes --target ES2020<\\/p>\"],\"racket\":[\"Racket\",\"<p><a href=\\\"https:\\/\\/docs.racket-lang.org\\/guide\\/performance.html#%28tech._c%29\\\" target=\\\"_blank\\\">Racket CS<\\/a> v8.3<\\/p>\\r\\n\\r\\n<p>\\u4f7f\\u7528 #lang racket<\\/p>\\r\\n\\r\\n<p>\\u5df2\\u9884\\u5148 (require data\\/gvector data\\/queue data\\/order data\\/heap). \\u82e5\\u9700\\u4f7f\\u7528\\u5176\\u5b83\\u6570\\u636e\\u7ed3\\u6784\\uff0c\\u53ef\\u81ea\\u884c require\\u3002<\\/p>\"],\"erlang\":[\"Erlang\",\"Erlang\\/OTP 24.2\"],\"elixir\":[\"Elixir\",\"Elixir 1.13.0 with Erlang\\/OTP 24.2\"]}",
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