Files
C-Plus-Plus/probability/windowed_median.cpp
2021-10-02 21:51:21 -04:00

175 lines
6.7 KiB
C++

/**
* \file
* \brief An implementation of a median calculation of a sliding window along a data stream
*/
#include <algorithm>
#include <iostream>
#include <list>
#include <set>
using namespace std;
/**
* \class WindowedMedian
* \brief A class to calculate the median of a leading sliding window at the back of a stream of integer values. Each insertion of a new value
* is O(logN) in time, where N is the size of the sliding window. Each retrieval of median is O(1) in time. Space complexity is O(N)
*/
class WindowedMedian {
const int _windowSize; // Sliding window size
list<int> _window; // A sliding window of values along the stream
multiset<int> _sortedValues; // A DS to represent a balanced multi-value binary search tree (BST)
multiset<int>::const_iterator _itMedian; // An iterator that points to the root of the multi-value BST
/**
* \brief Inserts a value to a sorted multi-value BST
* \param value Value to insert
*/
void insertToSorted(int value) {
_sortedValues.insert(value); // Insert value to BST - O(logN)
const auto sz = _sortedValues.size();
if (sz == 1) { // For the first value, set median iterator to BST root
_itMedian = _sortedValues.begin();
return;
}
// If new value goes to left tree branch, and number of elements is even, the new median in the balanced tree
// is the left child of the median before the insertion
if (value < *_itMedian && sz % 2 == 0)
--_itMedian; // O(1) - traversing one step to the left child
// However, if the new value goes to the right branch, the previous median's right child is the new median in
// the balanced tree
else if (value >= *_itMedian && sz % 2 != 0)
++_itMedian; // O(1) - traversing one step to the right child
}
/**
* \brief Erases a value to a sorted multi-value BST
* \param value Value to insert
*/
void eraseFromSorted(int value) {
const auto sz = _sortedValues.size();
// If the erased value is on the left branch or the median itself and the number of elements is even, the new
// median will be the right child of the current one
if (value <= *_itMedian && sz % 2 == 0)
++_itMedian; // O(1) - traversing one step to the right child
// However, is the erased value is on the right branch or the median itself, and the number of elements is odd,
// the new median will be the left child of the current one
else if (value >= *_itMedian && sz % 2 != 0)
--_itMedian; // O(1) - traversing one step to the left child
// Find the (first) position of the value we want to erase, and erase it
const auto it = _sortedValues.find(value); // O(logN)
_sortedValues.erase(it); // O(logN)
}
public:
/**
* \brief Constructs a WindowedMedian object
* \param windowSize Sliding window size
*/
WindowedMedian(int windowSize) : _windowSize(windowSize) {};
/**
* \brief Insert a new value to the stream
* \param value New value to insert
*/
void insert(int value) {
// Push new value to the back of the sliding window - O(1)
_window.push_back(value);
insertToSorted(value); // Insert value to the multi-value BST - O(logN)
if (_window.size() > _windowSize) { // If exceeding size of window, pop from its left side
eraseFromSorted(_window.front()); // Erase from the multi-value BST the window left side value
_window.pop_front(); // Pop the left side value from the window - O(1)
}
}
/**
* \brief Gets the median of the values in the sliding window
* \return Median of sliding window. For even window size return the average between the two values in the middle
*/
float getMedian() const {
if (_sortedValues.size() % 2 != 0)
return *_itMedian; // O(1)
return 0.5 * *_itMedian + 0.5 * *next(_itMedian); // O(1)
}
/**
* \brief A naive and inefficient method to obtain the median of the sliding window. Used for testing!
* \return Median of sliding window. For even window size return the average between the two values in the middle
*/
float getMedianNaive() const {
auto window = _window;
window.sort(); // Sort window - O(NlogN)
auto median = *next(window.begin(), window.size() / 2); // Find value in the middle - O(N)
if (window.size() % 2 != 0)
return median;
return 0.5 * median + 0.5 * *next(window.begin(), window.size() / 2 - 1); // O(N)
}
};
#include <vector>
/**
* \brief A testing function
* \param vals Stream of values
* \param windowSize Size of sliding window
*/
bool test(const vector<int> &vals, int windowSize) {
WindowedMedian windowedMedian(windowSize);
bool testSucceeded = true;
for (int i = 0; i < vals.size(); i++) {
windowedMedian.insert(vals[i]);
// Comparing medians: efficient function vs. Naive one
if (windowedMedian.getMedian() != windowedMedian.getMedianNaive()) {
cout << "i = " << i << ": " << windowedMedian.getMedian() << "!=" <<
windowedMedian.getMedianNaive() << endl;
testSucceeded = false;
}
}
return testSucceeded;
}
#include <cstdlib>
#include <ctime>
int main(int argc, const char * argv[]) {
cout << "TEST 1" << endl;
if (!test({1, 2, 3, 4, 5, 6, 7, 8, 9}, 3))
return -1;
cout << "TEST 2" << endl;
if (!test({9, 8, 7, 6, 5, 4, 3, 2, 1}, 3))
return -1;
cout << "TEST 3" << endl;
if (!test({9, 8, 7, 6, 5, 4, 5, 6}, 4))
return -1;
cout << "TEST 4" << endl;
if (!test({3, 3, 3, 3, 3, 3, 3, 3, 3}, 3))
return -1;
cout << "TEST 5" << endl;
if (!test({3, 3, 3, 3, -7, 3, 3, 3, 3}, 3))
return -1;
cout << "TEST 6" << endl;
if (!test({4, 3, 3, -5, 7, 1, 3, 4, 5}, 5))
return -1;
cout << "TEST 7" << endl;
if (!test({470211272, 101027544, 1457850878, 1458777923, 2007237709, 823564440, 1115438165, 1784484492,
74243042, 114807987}, 6))
return -1;
std::srand(static_cast<unsigned int>(std::time(nullptr)));
for (int i = 8; i < 100; i++) {
const auto n = 1 + std::rand() / ((RAND_MAX + 5u) / 20);
auto windowSize = 1 + std::rand() / ((RAND_MAX + 3u) / 10);
vector<int> vals;
for (int i = 0; i < n; i++)
vals.push_back(rand() - RAND_MAX);
cout << "TEST " << i << endl;
if (!test(vals, windowSize))
return -1;
}
return 0;
}