mgs/median-comparison
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using uint32 instead of size_t

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incredibleLeitman 2020-10-17 00:30:07 +02:00
parent 1e2abe1341
commit c8db9109c6
2 changed files with 47 additions and 63 deletions
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58
MedianOfMedians.h
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@ -4,32 +4,29 @@
// 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/
int findMedian(std::vector<size_t> values)
uint32_t findMedian(std::vector<uint32_t> values)
{
size_t median;
size_t size = values.size();
median = values[(size / 2)];
return median;
return values[(values.size() / 2)];
}
int findMedianOfMedians(std::vector<std::vector<size_t> > values)
uint32_t findMedianOfMedians(std::vector<std::vector<uint32_t> > values)
{
std::vector<size_t> medians;
std::vector<uint32_t> medians;
for (size_t i = 0; i < values.size(); i++) {
size_t m = findMedian(values[i]);
uint32_t m = findMedian(values[i]);
medians.push_back(m);
}
return findMedian(medians);
}
size_t getMedianOfMedians(const std::vector<size_t> values, size_t k)
uint32_t getMedianOfMedians(const std::vector<uint32_t> values, uint32_t k)
{
// Divide the list into n/5 lists of 5 elements each
std::vector<std::vector<size_t> > vec2D;
std::vector<std::vector<uint32_t> > vec2D;
size_t count = 0;
while (count != values.size()) {
size_t countRow = 0;
std::vector<size_t> row;
std::vector<uint32_t> row;
while ((countRow < 5) && (count < values.size()))
{
row.push_back(values[count]);
@ -40,10 +37,10 @@ size_t getMedianOfMedians(const std::vector<size_t> values, size_t k)
}
// Calculating a new pivot for making splits
size_t m = findMedianOfMedians(vec2D);
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<size_t> L1, L2;
std::vector<uint32_t> L1, L2;
for (size_t i = 0; i < vec2D.size(); i++)
{
@ -73,19 +70,19 @@ size_t getMedianOfMedians(const std::vector<size_t> values, size_t k)
// A simple function to find median of arr[].
// This is called only for an array of size 5 in this program.
int findMedian(size_t arr[], int n)
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(size_t arr[], int l, int r, int 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] == x)
if (arr[i] == pivotValue)
break;
swap(&arr[i], &arr[r]);
@ -93,7 +90,7 @@ int partition(size_t arr[], int l, int r, int x)
i = l;
for (int j = l; j < r; j++)
{
if (arr[j] <= x)
if (arr[j] <= pivotValue)
{
i++;
swap(&arr[i], &arr[j]);
@ -106,10 +103,7 @@ int partition(size_t arr[], int l, int r, int x)
// 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)
size_t getMedianOfMedians(size_t* arr, int l, int r, int k)
{
// If k is smaller than number of elements in array
if (k > 0 && k <= r - l + 1)
uint32_t getMedianOfMedians(uint32_t* arr, int l, int r, int k)
{
int n = r - l + 1; // Number of elements in arr[l..r]
@ -117,7 +111,7 @@ size_t getMedianOfMedians(size_t* arr, int l, int r, int k)
// 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!
size_t* median = new size_t[(n + 4) / 5];
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);
@ -128,25 +122,15 @@ size_t getMedianOfMedians(size_t* arr, int l, int r, int k)
}
// Find median of all medians using recursive call.
// If median[] has only one element, then no need
// of recursive call
int medOfMed = (i == 1) ? median[i - 1] :
getMedianOfMedians(median, 0, i - 1, i / 2);
// 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 position is same as k
if (pos - l == k - 1)
return arr[pos];
if (pos - l > k - 1) // If position is more, recur for left
if (pos - l == k - 1) return arr[pos];
else if (pos - l > k - 1)
return getMedianOfMedians(arr, l, pos - 1, k);
// Else recur for right subarray
return getMedianOfMedians(arr, pos + 1, r, k - pos + l - 1);
}
// If k is more than number of elements in array
return SIZE_MAX;
else return getMedianOfMedians(arr, pos + 1, r, k - pos + l - 1);
}

14
MedianQuicksort.h
View File

@ -1,8 +1,8 @@
#pragma once
size_t pivotPartition(std::vector<size_t>& values, size_t left, size_t right) {
size_t pivotIndex = left + (right - left) / 2;
size_t pivotValue = values[pivotIndex];
uint32_t pivotPartition(std::vector<uint32_t>& values, uint32_t left, uint32_t right) {
uint32_t pivotIndex = left + (right - left) / 2;
uint32_t pivotValue = values[pivotIndex];
int i = left;
int j = right;
while (i <= j) {
@ -15,7 +15,7 @@ size_t pivotPartition(std::vector<size_t>& values, size_t left, size_t right) {
j--;
}
if (i <= j) {
std::swap(values[i], values[j]);
swap(&values[i], &values[j]);
i++;
j--;
}
@ -23,16 +23,16 @@ size_t pivotPartition(std::vector<size_t>& values, size_t left, size_t right) {
return i;
}
void quicksort(std::vector<size_t>& values, size_t left, size_t right)
void quicksort(std::vector<uint32_t>& values, uint32_t left, uint32_t right)
{
if (left < right) {
size_t pivotIndex = pivotPartition(values, left, right);
uint32_t pivotIndex = pivotPartition(values, left, right);
quicksort(values, left, pivotIndex - 1);
quicksort(values, pivotIndex, right);
}
}
size_t getQuicksortMedian(std::vector<size_t> values, size_t i)
uint32_t getQuicksortMedian(std::vector<uint32_t> values, uint32_t i)
{
//std::qsort(numbers); // only takes array param -> custom implementation with vector
quicksort(values, 0, values.size() - 1);