Hướng dẫn binary search in python - tìm kiếm nhị phân trong python
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Khác nếu x lớn hơn phần tử giữa, thì x chỉ có thể nằm ở nửa bên phải (lớn hơn) sau phần tử giữa. Sau đó, chúng tôi áp dụng thuật toán một lần nữa cho nửa đúng. Python3Khác nếu X nhỏ hơn, mục tiêu X phải nằm ở một nửa bên trái (thấp hơn). Vì vậy, chúng tôi áp dụng thuật toán cho nửa trái. Đệ quy: Element is present at index 33 Element is present at index 34 Element is present at index 35 Element is present at index 36 Element is present at index 37 Element is present at index 38 Element is present at index 39 Element is present at index 30__ ‘ Element is present at index 334 Element is present at index 335 Element is present at index 336 Element is present at index 33 Element is present at index 347 Element is present at index 348 Element is present at index 33 Element is present at index 338 Element is present at index 339 Element is present at index 35 Element is present at index 347 Element is present at index 348 Element is present at index 334 Element is present at index 335 Element is present at index 342 Element is present at index 343 Element is present at index 344 Element is present at index 345 Element is present at index 334 Element is present at index 335 Element is present at index 351 Element is present at index 33 Element is present at index 344 Element is present at index 354 Element is present at index 33 Element is present at index 335 Element is present at index 343 Element is present at index 344 Element is present at index 362 Element is present at index 38 Element is present at index 364 Element is present at index 37 Element is present at index 366 Element is present at index 367____56 Element is present at index 369 Element is present at index 366 Element is present at index 371 Element is present at index 366 Element is present at index 373 Element is present at index 374 Element is present at index 375 Element is present at index 38 Element is present at index 371 Element is present at index 35 Element is present at index 395 Element is present at index 396 Element is present at index 397 Element is present at index 366 Element is present at index 399 Element is present at index 330 Element is present at index 347 Element is present at index 348 Element is present at index 35 Element is present at index 395 Element is present at index 396 Element is present at index 336 Element is present at index 337 Output: Element is present at index 378 Element is present at index 38 Element is present at index 380 Element is present at index 381 Element is present at index 366 Element is present at index 383 Element is present at index 384 Element is present at index 343 Element is present at index 344 Element is present at index 345
Element is present at index 3: O(logn) [NOTE: Recursion creates Call Stack] Iterative: Python3Độ phức tạp về thời gian: O (log n) Không gian phụ trợ: O (logn) & nbsp; & nbsp; [Lưu ý: đệ quy tạo ra ngăn xếp cuộc gọi] Element is present at index 33 Element is present at index 339 Element is present at index 301 Element is present at index 38 Element is present at index 381 Element is present at index 305 Element is present at index 38 Element is present at index 383 Element is present at index 308 Element is present at index 343 Element is present at index 344 Element is present at index 33 Element is present at index 34 Element is present at index 35 Element is present at index 36 Element is present at index 37 Element is present at index 38 Element is present at index 39‘ ‘ Element is present at index 334 Element is present at index 335 Element is present at index 336 Element is present at index 33 Element is present at index 347 Element is present at index 348 Element is present at index 30__ ‘ Element is present at index 334 Element is present at index 335 Element is present at index 351 Element is present at index 33 Element is present at index 344 Element is present at index 354 Element is present at index 33 Element is present at index 335 Element is present at index 343 Element is present at index 344 Element is present at index 362 Element is present at index 38 Element is present at index 364 Element is present at index 37 Element is present at index 366 Element is present at index 367____56 Element is present at index 369 Element is present at index 366 Element is present at index 371 Element is present at index 366 Element is present at index 373 Element is present at index 374 Element is present at index 375 Element is present at index 38 Element is present at index 371 Element is present at index 35 Element is present at index 395 Element is present at index 396 Element is present at index 397 Element is present at index 366 Element is present at index 399 Element is present at index 330 Element is present at index 347 Element is present at index 348 Element is present at index 35 Element is present at index 395 Element is present at index 396 Element is present at index 336 Element is present at index 337 Output: Element is present at index 3
Element is present at index 3: O(logn) [NOTE: Recursion creates Call Stack] Please refer to the article Binary Search for more details! Làm cách nào để tạo một tìm kiếm nhị phân trong Python?Algorithm... Độ phức tạp về thời gian: O (log n) Không gian phụ trợ: O (logn) & nbsp; & nbsp; [Lưu ý: đệ quy tạo ra ngăn xếp cuộc gọi] Element is present at index 33 Element is present at index 339 Element is present at index 301 Element is present at index 38 Element is present at index 381 Element is present at index 305 Element is present at index 38 Element is present at index 383 Element is present at index 308 Element is present at index 343 Element is present at index 344 Tìm kiếm nhị phân trong Python với ví dụ là gì?Element is present at index 30__ a searching algorithm which is used to search an element from a sorted array. It cannot be used to search from an unsorted array. Binary search is an efficient algorithm and is better than linear search in terms of time complexity. The time complexity of linear search is O(n). Làm thế nào để bạn viết một mã tìm kiếm nhị phân?
So sánh x với phần tử giữa .. Nếu x khớp với phần tử giữa, chúng ta sẽ trả về chỉ số giữa .. Khác nếu x lớn hơn phần tử giữa, thì x chỉ có thể nằm ở nửa bên phải Subarray sau phần tử giữa. Vì vậy, chúng tôi tái diễn cho nửa đúng .. Khác (x nhỏ hơn) tái diễn cho nửa bên trái .. Tìm kiếm nhị phân là một thuật toán tìm kiếm được sử dụng để tìm kiếm một phần tử từ một mảng được sắp xếp.Nó không thể được sử dụng để tìm kiếm từ một mảng chưa được phân loại.Tìm kiếm nhị phân là một thuật toán hiệu quả và tốt hơn so với tìm kiếm tuyến tính về độ phức tạp về thời gian.Độ phức tạp thời gian của tìm kiếm tuyến tính là O (N).a searching algorithm which is used to search an element from a sorted array. It cannot be used to search from an unsorted array. Binary search is an efficient algorithm and is better than linear search in terms of time complexity. The time complexity of linear search is O(n). Ví dụ tìm kiếm nhị phân trong Java.. lớp nhị phân nghiên cứu {. công khai static void BinarySearch (int arr [], int First, int cuối cùng, int key) {. Có chức năng tìm kiếm nhị phân trong Python không?int mid = (đầu tiên + cuối cùng)/2 ;.. It divides a list in half. If a specified value is higher than the middle number, the search focuses on the right of the list. Otherwise, the search looks for the number on the left of the list. |