87 lines
3.4 KiB
C++
87 lines
3.4 KiB
C++
#include <iostream>
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#include <algorithm> // std::nth_element
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#include "common.h"
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#include "fileHandler.h"
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#include "Timing.h"
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#include "MedianQuicksort.h"
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#include "MedianOfMedians.h"
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#include "RandomizedSelect.h"
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#include "Wirth.h"
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// TODO:
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// - combine partition function
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// - fix Median of Medians
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int main(int argc, char** argv)
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{
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// read test values from input file
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std::string type = "init\t\t\t\t\t";
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Timing::getInstance()->startRecord(type);
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std::vector<uint32_t > numbers = readFromFile("testdata");
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Timing::getInstance()->stopRecord(type);
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// index of median is exactly middle for odd datasets, not supported for even :p
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if (numbers.size() % 2 == 0)
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{
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// TODO: just use the next element? calc arithmetic mean?
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std::cout << "TODO: define how to handle even datasets" << std::endl;
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return 1;
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}
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uint32_t idxMed = (numbers.size() - 1) / 2;
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std::cout << "calculating median on index " << idxMed << " of " << numbers.size() << " elems..." << std::endl;
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// create an array from vector for algorithms using array params
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uint32_t* array = new uint32_t[numbers.size()];
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// vollständige Sortierung mit Quicksort und Ausgabe des mittleren Elements
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type = "quicksort median\t\t\t";
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Timing::getInstance()->startRecord(type);
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std::cout << type << getQuicksortMedian(numbers, idxMed) << std::endl;
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Timing::getInstance()->stopRecord(type);
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// comparison of std::qsort and std::sort
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// using std quicksort for array
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type = "array quicksort\t\t\t\t";
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std::copy(numbers.begin(), numbers.end(), array);
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Timing::getInstance()->startRecord(type);
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std::qsort(array, numbers.size(), sizeof(uint32_t), compare);
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std::cout << type << array[idxMed] << std::endl;
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Timing::getInstance()->stopRecord(type);
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// comparison "quick" sort with std::sort (introsort)
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type = "array std sort\t\t\t\t";
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std::copy(numbers.begin(), numbers.end(), array);
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Timing::getInstance()->startRecord(type);
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std::sort(array, array + numbers.size());
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std::cout << type << array[idxMed] << std::endl;
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Timing::getInstance()->stopRecord(type);
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// vorgestellter Randomzized - Select rekursiv implementiert
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type = "randomized select\t\t\t";
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Timing::getInstance()->startRecord(type);
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std::cout << type << getRandomizedSelectMedian(numbers, 0, numbers.size() - 1, idxMed + 1) << std::endl;
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Timing::getInstance()->stopRecord(type);
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// ein weiterer Median - Algorithmus aus der Literatur - implemented with std::vector
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type = "vector median of medians\t\t";
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Timing::getInstance()->startRecord(type);
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std::cout << type << getMedianOfMedians(numbers, 0, numbers.size() - 1, idxMed) << std::endl;
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Timing::getInstance()->stopRecord(type);
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// noch ein ein weiterer Median - Algorithmus weil wir so cool sind
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type = "wirth kth element\t\t\t";
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Timing::getInstance()->startRecord(type);
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std::cout << type << getWirthKthSmallest(numbers, idxMed) << std::endl;
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Timing::getInstance()->stopRecord(type);
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// Verwendung des C++ STL function templates nth_element
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type = "nth element\t\t\t\t";
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Timing::getInstance()->startRecord(type);
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std::nth_element(numbers.begin(), numbers.begin() + idxMed, numbers.end());
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std::cout << type << numbers[idxMed] << std::endl;
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Timing::getInstance()->stopRecord(type);
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Timing::getInstance()->print();
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return 0;
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} |