#pragma once // https://en.wikipedia.org/wiki/Median_of_medians // https://oneraynyday.github.io/algorithms/2016/06/17/Median-Of-Medians/ // https://www.geeksforgeeks.org/kth-smallestlargest-element-unsorted-array-set-3-worst-case-linear-time/ uint32_t findMedian(std::vector values) { return values[(values.size() / 2)]; } uint32_t findMedianOfMedians(std::vector > values) { std::vector medians; for (size_t i = 0; i < values.size(); i++) { uint32_t m = findMedian(values[i]); medians.push_back(m); } return findMedian(medians); } uint32_t getMedianOfMedians(const std::vector values, uint32_t k) { // Divide the list into n/5 lists of 5 elements each std::vector > vec2D; size_t count = 0; while (count != values.size()) { size_t countRow = 0; std::vector row; while ((countRow < 5) && (count < values.size())) { row.push_back(values[count]); count++; countRow++; } vec2D.push_back(row); } // Calculating a new pivot for making splits uint32_t m = findMedianOfMedians(vec2D); // Partition the list into unique elements larger than 'm' (call this sublist L1) and those smaller them 'm' (call this sublist L2) std::vector L1, L2; for (size_t i = 0; i < vec2D.size(); i++) { for (size_t j = 0; j < vec2D[i].size(); j++) { if (vec2D[i][j] > m) { L1.push_back(vec2D[i][j]); } else if (vec2D[i][j] < m) { L2.push_back(vec2D[i][j]); } } } if (k <= L1.size()) { return getMedianOfMedians(L1, k); } else if (k > (L1.size() + 1)) { return getMedianOfMedians(L2, k - ((int)L1.size()) - 1); } return m; } // A simple function to find median of arr[]. // This is called only for an array of size 5 in this program. uint32_t findMedian(uint32_t arr[], int n) { std::sort(arr, arr + n); // Sort the array return arr[n / 2]; // Return middle element } // searches for x in arr[l..r], and partitions the array around x int partition(uint32_t arr[], int l, int r, uint32_t pivotValue) { // Search for x in arr[l..r] and move it to end int i; for (i = l; i < r; i++) if (arr[i] == pivotValue) break; swap(&arr[i], &arr[r]); // Standard partition algorithm i = l; for (int j = l; j < r; j++) { if (arr[j] <= pivotValue) { i++; swap(&arr[i], &arr[j]); } } swap(&arr[i], &arr[r]); return i; } // Returns k'th smallest element in arr[l..r] in worst case // linear time. ASSUMPTION: ALL ELEMENTS IN ARR[] ARE DISTINCT //int getMedianOfMedians(int arr[], int l, int r, int k) uint32_t getMedianOfMedians(uint32_t* arr, int l, int r, int k) { int n = r - l + 1; // Number of elements in arr[l..r] // Divide arr[] in groups of size 5, calculate median // of every group and store it in median[] array. // There will be floor((n + 4) / 5) groups; //int median[(n + 4) / 5]; // non VS compliant! uint32_t* median = new uint32_t[(n + 4) / 5]; int i = 0; for (i = 0; i < n / 5; i++) median[i] = findMedian(arr + l + i * 5, 5); if (i * 5 < n) //For last group with less than 5 elements { median[i] = findMedian(arr + l + i * 5, n % 5); i++; } // Find median of all medians using recursive call. // If median[] has only one element, then no need for recursive call uint32_t medOfMed = (i == 1) ? median[0] : getMedianOfMedians(median, 0, i - 1, i / 2); // Partition the array around a random element and // get position of pivot element in sorted array int pos = partition(arr, l, r, medOfMed); if (pos - l == k - 1) return arr[pos]; else if (pos - l > k - 1) return getMedianOfMedians(arr, l, pos - 1, k); else return getMedianOfMedians(arr, pos + 1, r, k - pos + l - 1); }