insertion-sort

问题 Following is my insertion sort code: void InsertionSort(vector<int> & ioList) { int n = ioList.size(); for (int i = 1 ; i < n ; ++i) { for (int j = 0 ; j <= i ; ++j) { //Shift elements if needed(insert at correct loc) if (ioList[j] > ioList[i]) { int temp = ioList[j]; ioList[j] = ioList[i]; ioList[i] = temp; } } } } The average complexity of the algorithm is O(n^2). From my understanding of big O notation, this is because we run two loops in this case(outer one n-1 times and inner one 1,2,..

问题 Good day SO community, I am a CS student currently performing an experiment combining MergeSort and InsertionSort. It is understood that for a certain threshold, S, InsertionSort will have a quicker execution time than MergeSort. Hence, by merging both sorting algorithms, the total runtime will be optimized. However, after running the experiment many times, using a sample size of 1000, and varying sizes of S, the results of the experiment does not give a definitive answer each time. Here is a

问题 If anyone can give some input on my logic, I would very much appreciate it. Which method runs faster for an array with all keys identical, selection sort or insertion sort? I think that this would be similar to when the array is already sorted, so that insertion sort will be linear, and the selection sort quadratic. Which method runs faster for an array in reverse order, selection sort or insertion sort? I think that they would run similarly, since the values at every position will have to be

问题 If anyone can give some input on my logic, I would very much appreciate it. Which method runs faster for an array with all keys identical, selection sort or insertion sort? I think that this would be similar to when the array is already sorted, so that insertion sort will be linear, and the selection sort quadratic. Which method runs faster for an array in reverse order, selection sort or insertion sort? I think that they would run similarly, since the values at every position will have to be

问题 In this program, I want to calculate the number of data comparisons in the insertion sort, but my code is not working as I expected. def insertionSort(list): numOfComp = 0 for i in range(1,len(list)): value = list[i] j = i - 1 while j>=0: if value < list[j]: list[j+1] = list[j] list[j] = value j = j - 1 numOfComp += 1 if value >= list[j]: numOfComp += 1 j = j - 1 else: break print("Number of data comparisons:",numOfComp) print("Sorted list:",list) 回答1: the problem is if value >= list[j]:

问题 I'm having trouble combining these two algorithms together. I've been asked to modify Binary Search to return the index that an element should be inserted into an array. I've been then asked to implement a Binary Insertion Sort that uses my Binary Search to sort an array of randomly generated ints . My Binary Search works the way it's supposed to, returning the correct index whenever I test it alone. I wrote out Binary Insertion Sort to get a feel for how it works, and got that to work as

问题 In Java, what is faster: to create, fill in and then sort an array of ints like below int[] a = int[1000]; for (int i = 0; i < a.length; i++) { // not sure about the syntax a[i] = Maths.rand(1, 500) // generate some random positive number less than 500 } a.sort(); // (which algorithm is best?) or insert-sort on the fly int[] a = int[1000]; for (int i = 0; i < a.length; i++) { // not sure about the syntax int v = Maths.rand(1, 500) // generate some random positive number less than 500 int p =

问题 I'm trying to write OpenMP solution for Insertion sort but I'm having problems to make it run in parallel and give correct results :). Is there any way to make Insertion sort it run in parallel. Here is my code: void insertionsort(int *A, int num) { // clock_t start, stop; // // start=clock(); int k; #pragma omp parallel for shared(A) private(k) for(int n = 1; n < num; n++) { int key = A[n]; k = n; #pragma omp critical for(;k>0 && A[k-1]> key;k--) { A[k] = A[k-1]; } A[k] = key; } // stop

问题 I'm trying to write OpenMP solution for Insertion sort but I'm having problems to make it run in parallel and give correct results :). Is there any way to make Insertion sort it run in parallel. Here is my code: void insertionsort(int *A, int num) { // clock_t start, stop; // // start=clock(); int k; #pragma omp parallel for shared(A) private(k) for(int n = 1; n < num; n++) { int key = A[n]; k = n; #pragma omp critical for(;k>0 && A[k-1]> key;k--) { A[k] = A[k-1]; } A[k] = key; } // stop

问题 So I was going through different sorting algorithms. But almost all the sorting algorithms require 2 loops to sort the array. The time complexity of Bubble sort & Insertion sort is O(n) for Best case but is O(n^2) as worst case which again requires 2 loops. Is there a way to sort an array in a single loop? 回答1: Here, a single-loop Bubble Sort in Python: def bubbly_sortish(data): for _ in xrange(len(data)**2): i, j = _/len(data), _%len(data) if i<j and data[i] > data[j]: data[i], data[j] =