{ "data": { "question": { "questionId": "2801", "questionFrontendId": "2711", "boundTopicId": null, "title": "Difference of Number of Distinct Values on Diagonals", "titleSlug": "difference-of-number-of-distinct-values-on-diagonals", "content": "
Given a 0-indexed 2D grid
of size m x n
, you should find the matrix answer
of size m x n
.
The value of each cell (r, c)
of the matrix answer
is calculated in the following way:
topLeft[r][c]
be the number of distinct values in the top-left diagonal of the cell (r, c)
in the matrix grid
.bottomRight[r][c]
be the number of distinct values in the bottom-right diagonal of the cell (r, c)
in the matrix grid
.Then answer[r][c] = |topLeft[r][c] - bottomRight[r][c]|
.
Return the matrix answer
.
A matrix diagonal is a diagonal line of cells starting from some cell in either the topmost row or leftmost column and going in the bottom-right direction until reaching the matrix's end.
\n\nA cell (r1, c1)
belongs to the top-left diagonal of the cell (r, c)
, if both belong to the same diagonal and r1 < r
. Similarly is defined bottom-right diagonal.
\n
Example 1:
\n\n\n\nInput: grid = [[1,2,3],[3,1,5],[3,2,1]]\nOutput: [[1,1,0],[1,0,1],[0,1,1]]\nExplanation: The 1st diagram denotes the initial grid. \nThe 2nd diagram denotes a grid for cell (0,0), where blue-colored cells are cells on its bottom-right diagonal.\nThe 3rd diagram denotes a grid for cell (1,2), where red-colored cells are cells on its top-left diagonal.\nThe 4th diagram denotes a grid for cell (1,1), where blue-colored cells are cells on its bottom-right diagonal and red-colored cells are cells on its top-left diagonal.\n- The cell (0,0) contains [1,1] on its bottom-right diagonal and [] on its top-left diagonal. The answer is |1 - 0| = 1.\n- The cell (1,2) contains [] on its bottom-right diagonal and [2] on its top-left diagonal. The answer is |0 - 1| = 1.\n- The cell (1,1) contains [1] on its bottom-right diagonal and [1] on its top-left diagonal. The answer is |1 - 1| = 0.\nThe answers of other cells are similarly calculated.\n\n\n
Example 2:
\n\n\nInput: grid = [[1]]\nOutput: [[0]]\nExplanation: - The cell (0,0) contains [] on its bottom-right diagonal and [] on its top-left diagonal. The answer is |0 - 0| = 0.\n\n\n
\n
Constraints:
\n\nm == grid.length
n == grid[i].length
1 <= m, n, grid[i][j] <= 50
Compiled with clang 11
using the latest C++ 20 standard.
Your code is compiled with level two optimization (-O2
). AddressSanitizer is also enabled to help detect out-of-bounds and use-after-free bugs.
Most standard library headers are already included automatically for your convenience.
\"], \"java\": [\"Java\", \"OpenJDK 17
. Java 8 features such as lambda expressions and stream API can be used.
Most standard library headers are already included automatically for your convenience.
\\r\\nIncludes Pair
class from https://docs.oracle.com/javase/8/javafx/api/javafx/util/Pair.html.
Python 2.7.12
.
Most libraries are already imported automatically for your convenience, such as array, bisect, collections. If you need more libraries, you can import it yourself.
\\r\\n\\r\\nFor Map/TreeMap data structure, you may use sortedcontainers library.
\\r\\n\\r\\nNote that Python 2.7 will not be maintained past 2020. For the latest Python, please choose Python3 instead.
\"], \"c\": [\"C\", \"Compiled with gcc 8.2
using the gnu11 standard.
Your code is compiled with level one optimization (-O1
). AddressSanitizer is also enabled to help detect out-of-bounds and use-after-free bugs.
Most standard library headers are already included automatically for your convenience.
\\r\\n\\r\\nFor hash table operations, you may use uthash. \\\"uthash.h\\\" is included by default. Below are some examples:
\\r\\n\\r\\n1. Adding an item to a hash.\\r\\n
\\r\\nstruct hash_entry {\\r\\n int id; /* we'll use this field as the key */\\r\\n char name[10];\\r\\n UT_hash_handle hh; /* makes this structure hashable */\\r\\n};\\r\\n\\r\\nstruct hash_entry *users = NULL;\\r\\n\\r\\nvoid add_user(struct hash_entry *s) {\\r\\n HASH_ADD_INT(users, id, s);\\r\\n}\\r\\n\\r\\n\\r\\n\\r\\n
2. Looking up an item in a hash:\\r\\n
\\r\\nstruct hash_entry *find_user(int user_id) {\\r\\n struct hash_entry *s;\\r\\n HASH_FIND_INT(users, &user_id, s);\\r\\n return s;\\r\\n}\\r\\n\\r\\n\\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\\r\\n\"], \"csharp\": [\"C#\", \"\"], \"javascript\": [\"JavaScript\", \"
Node.js 16.13.2
.
Your code is run with --harmony
flag, enabling new ES6 features.
lodash.js library is included by default.
\\r\\n\\r\\nFor 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.
\"], \"ruby\": [\"Ruby\", \"Ruby 3.1
Some common data structure implementations are provided in the Algorithms module: https://www.rubydoc.info/github/kanwei/algorithms/Algorithms
\"], \"swift\": [\"Swift\", \"Swift 5.5.2
.
Go 1.21
Support https://godoc.org/github.com/emirpasic/gods@v1.18.1 library.
\"], \"python3\": [\"Python3\", \"Python 3.10
.
Most libraries are already imported automatically for your convenience, such as array, bisect, collections. If you need more libraries, you can import it yourself.
\\r\\n\\r\\nFor Map/TreeMap data structure, you may use sortedcontainers library.
\"], \"scala\": [\"Scala\", \"Scala 2.13.7
.
Kotlin 1.9.0
.
Rust 1.58.1
Supports rand v0.6\\u00a0from crates.io
\"], \"php\": [\"PHP\", \"PHP 8.1
.
With bcmath module
\"], \"typescript\": [\"Typescript\", \"TypeScript 5.1.6, Node.js 16.13.2
.
Your code is run with --harmony
flag, enabling new ES2022 features.
lodash.js library is included by default.
\"], \"racket\": [\"Racket\", \"Run with Racket 8.3
.
Dart 2.17.3
\\r\\n\\r\\nYour code will be run directly without compiling
\"]}", "libraryUrl": null, "adminUrl": null, "challengeQuestion": null, "__typename": "QuestionNode" } } }