{ "data": { "question": { "questionId": "2625", "questionFrontendId": "2536", "boundTopicId": null, "title": "Increment Submatrices by One", "titleSlug": "increment-submatrices-by-one", "content": "

You are given a positive integer n, indicating that we initially have an n x n 0-indexed integer matrix mat filled with zeroes.

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You are also given a 2D integer array query. For each query[i] = [row1i, col1i, row2i, col2i], you should do the following operation:

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Return the matrix mat after performing every query.

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Example 1:

\n\"\"\n
\nInput: n = 3, queries = [[1,1,2,2],[0,0,1,1]]\nOutput: [[1,1,0],[1,2,1],[0,1,1]]\nExplanation: The diagram above shows the initial matrix, the matrix after the first query, and the matrix after the second query.\n- In the first query, we add 1 to every element in the submatrix with the top left corner (1, 1) and bottom right corner (2, 2).\n- In the second query, we add 1 to every element in the submatrix with the top left corner (0, 0) and bottom right corner (1, 1).\n
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Example 2:

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\nInput: n = 2, queries = [[0,0,1,1]]\nOutput: [[1,1],[1,1]]\nExplanation: The diagram above shows the initial matrix and the matrix after the first query.\n- In the first query we add 1 to every element in the matrix.\n
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Constraints:

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(listof (listof exact-integer?)) (listof (listof exact-integer?)))\n\n )", "__typename": "CodeSnippetNode" }, { "lang": "Erlang", "langSlug": "erlang", "code": "-spec range_add_queries(N :: integer(), Queries :: [[integer()]]) -> [[integer()]].\nrange_add_queries(N, Queries) ->\n .", "__typename": "CodeSnippetNode" }, { "lang": "Elixir", "langSlug": "elixir", "code": "defmodule Solution do\n @spec range_add_queries(n :: integer, queries :: [[integer]]) :: [[integer]]\n def range_add_queries(n, queries) do\n\n end\nend", "__typename": "CodeSnippetNode" }, { "lang": "Dart", "langSlug": "dart", "code": "class Solution {\n List> rangeAddQueries(int n, List> queries) {\n\n }\n}", "__typename": "CodeSnippetNode" } ], "stats": "{\"totalAccepted\": \"14.4K\", \"totalSubmission\": \"30.8K\", \"totalAcceptedRaw\": 14407, \"totalSubmissionRaw\": 30840, \"acRate\": \"46.7%\"}", "hints": [ "Imagine each row as a separate array. Instead of updating the whole submatrix together, we can use prefix sum to update each row separately.", "For each query, iterate over the rows i in the range [row1, row2] and add 1 to prefix sum S[i][col1], and subtract 1 from S[i][col2 + 1].", "After doing this operation for all the queries, update each row separately with S[i][j] = S[i][j] + S[i][j - 1]." ], "solution": null, "status": null, "sampleTestCase": "3\n[[1,1,2,2],[0,0,1,1]]", "metaData": "{\n \"name\": \"rangeAddQueries\",\n \"params\": [\n {\n \"name\": \"n\",\n \"type\": \"integer\"\n },\n {\n \"type\": \"integer[][]\",\n \"name\": \"queries\"\n }\n ],\n \"return\": {\n \"type\": \"integer[][]\"\n }\n}", "judgerAvailable": true, "judgeType": "large", "mysqlSchemas": [], "enableRunCode": true, "enableTestMode": false, "enableDebugger": true, "envInfo": "{\"cpp\": [\"C++\", \"

Compiled with clang 11 using the latest C++ 17 standard.

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Your code is compiled with level two optimization (-O2). AddressSanitizer is also enabled to help detect out-of-bounds and use-after-free bugs.

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Most standard library headers are already included automatically for your convenience.

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OpenJDK 17. Java 8 features such as lambda expressions and stream API can be used.

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Most standard library headers are already included automatically for your convenience.

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Includes Pair class from https://docs.oracle.com/javase/8/javafx/api/javafx/util/Pair.html.

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Python 2.7.12.

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Most libraries are already imported automatically for your convenience, such as array, bisect, collections. If you need more libraries, you can import it yourself.

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For Map/TreeMap data structure, you may use sortedcontainers library.

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Note that Python 2.7 will not be maintained past 2020. For the latest Python, please choose Python3 instead.

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Compiled with gcc 8.2 using the gnu11 standard.

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Your code is compiled with level one optimization (-O1). AddressSanitizer is also enabled to help detect out-of-bounds and use-after-free bugs.

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Most standard library headers are already included automatically for your convenience.

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For hash table operations, you may use uthash. \\\"uthash.h\\\" is included by default. Below are some examples:

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1. Adding an item to a hash.\\r\\n

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2. Looking up an item in a hash:\\r\\n

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\\r\\n\\r\\n

3. Deleting an item in a hash:\\r\\n

\\r\\nvoid delete_user(struct hash_entry *user) {\\r\\n    HASH_DEL(users, user);  \\r\\n}\\r\\n
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C# 10 with .NET 6 runtime

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Node.js 16.13.2.

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Your code is run with --harmony flag, enabling new ES6 features.

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lodash.js library is included by default.

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For Priority Queue / Queue data structures, you may use 5.3.0 version of datastructures-js/priority-queue and 4.2.1 version of datastructures-js/queue.

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Ruby 3.1

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Some common data structure implementations are provided in the Algorithms module: https://www.rubydoc.info/github/kanwei/algorithms/Algorithms

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Swift 5.5.2.

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Go 1.17.6.

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Support https://godoc.org/github.com/emirpasic/gods library.

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Python 3.10.

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Most libraries are already imported automatically for your convenience, such as array, bisect, collections. If you need more libraries, you can import it yourself.

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For Map/TreeMap data structure, you may use sortedcontainers library.

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Scala 2.13.7.

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Kotlin 1.3.10.

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Rust 1.58.1

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Supports rand v0.6\\u00a0from crates.io

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PHP 8.1.

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With bcmath module

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TypeScript 4.5.4, Node.js 16.13.2.

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Run with Racket 8.3.

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Dart 2.17.3

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Your code will be run directly without compiling

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