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The default value of the first column is set to have the same increment as the two previous rows, when possible. This allow faster data entry when the values of the first column are evenly separated.
229 lines
5.6 KiB
C++
229 lines
5.6 KiB
C++
#include "store.h"
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#include <assert.h>
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#include <float.h>
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#include <cmath>
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#include <string.h>
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#include <ion.h>
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using namespace Shared;
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namespace Statistics {
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Store::Store() :
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MemoizedCurveViewRange(),
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FloatPairStore(),
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m_barWidth(1.0),
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m_firstDrawnBarAbscissa(0.0)
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{
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}
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uint32_t Store::barChecksum() {
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double data[2] = {m_barWidth, m_firstDrawnBarAbscissa};
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size_t dataLengthInBytes = 2*sizeof(double);
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assert((dataLengthInBytes & 0x3) == 0); // Assert that dataLengthInBytes is a multiple of 4
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return Ion::crc32((uint32_t *)data, dataLengthInBytes/sizeof(uint32_t));
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}
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/* Histogram bars */
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double Store::barWidth() {
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return m_barWidth;
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}
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void Store::setBarWidth(double barWidth) {
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if (barWidth <= 0.0) {
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return;
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}
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m_barWidth = barWidth;
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}
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double Store::firstDrawnBarAbscissa() {
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return m_firstDrawnBarAbscissa;
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}
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void Store::setFirstDrawnBarAbscissa(double firstBarAbscissa) {
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m_firstDrawnBarAbscissa = firstBarAbscissa;
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}
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double Store::heightOfBarAtIndex(int index) {
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return sumOfValuesBetween(startOfBarAtIndex(index), endOfBarAtIndex(index));
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}
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double Store::heightOfBarAtValue(double value) {
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double width = barWidth();
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int barNumber = std::floor((value - m_firstDrawnBarAbscissa)/width);
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double lowerBound = m_firstDrawnBarAbscissa + barNumber*width;
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double upperBound = m_firstDrawnBarAbscissa + (barNumber+1)*width;
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return sumOfValuesBetween(lowerBound, upperBound);
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}
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double Store::startOfBarAtIndex(int index) {
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double firstBarAbscissa = m_firstDrawnBarAbscissa + m_barWidth*std::floor((minValue()- m_firstDrawnBarAbscissa)/m_barWidth);
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return firstBarAbscissa + index * m_barWidth;
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}
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double Store::endOfBarAtIndex(int index) {
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return startOfBarAtIndex(index+1);
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}
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double Store::numberOfBars() {
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double firstBarAbscissa = m_firstDrawnBarAbscissa + m_barWidth*std::floor((minValue()- m_firstDrawnBarAbscissa)/m_barWidth);
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return std::ceil((maxValue() - firstBarAbscissa)/m_barWidth)+1;
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}
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bool Store::scrollToSelectedBarIndex(int index) {
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float startSelectedBar = startOfBarAtIndex(index);
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float windowRange = m_xMax - m_xMin;
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float range = windowRange/(1+k_displayLeftMarginRatio+k_displayRightMarginRatio);
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if (m_xMin + k_displayLeftMarginRatio*range > startSelectedBar) {
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m_xMin = startSelectedBar - k_displayLeftMarginRatio*range;
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m_xMax = m_xMin + windowRange;
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return true;
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}
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float endSelectedBar = endOfBarAtIndex(index);
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if (endSelectedBar > m_xMax - k_displayRightMarginRatio*range) {
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m_xMax = endSelectedBar + k_displayRightMarginRatio*range;
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m_xMin = m_xMax - windowRange;
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return true;
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}
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return false;
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}
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/* Calculation */
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double Store::sumOfOccurrences() {
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return sumOfColumn(1);
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}
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double Store::maxValue() {
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double max = -DBL_MAX;
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for (int k = 0; k < m_numberOfPairs; k++) {
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if (m_data[0][k] > max && m_data[1][k] > 0) {
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max = m_data[0][k];
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}
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}
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return max;
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}
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double Store::minValue() {
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double min = DBL_MAX;
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for (int k = 0; k < m_numberOfPairs; k++) {
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if (m_data[0][k] < min && m_data[1][k] > 0) {
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min = m_data[0][k];
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}
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}
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return min;
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}
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double Store::range() {
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return maxValue()-minValue();
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}
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double Store::mean() {
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return sum()/sumOfColumn(1);
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}
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double Store::variance() {
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double m = mean();
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return squaredValueSum()/sumOfColumn(1) - m*m;
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}
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double Store::standardDeviation() {
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return std::sqrt(variance());
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}
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double Store::sampleStandardDeviation() {
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double n = sumOfColumn(1);
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double s = std::sqrt(n/(n-1.0));
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return s*standardDeviation();
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}
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double Store::firstQuartile() {
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int firstQuartileIndex = std::ceil(sumOfColumn(1)/4);
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return sortedElementNumber(firstQuartileIndex);
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}
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double Store::thirdQuartile() {
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int thirdQuartileIndex = std::ceil(3*sumOfColumn(1)/4);
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return sortedElementNumber(thirdQuartileIndex);
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}
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double Store::quartileRange() {
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return thirdQuartile()-firstQuartile();
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}
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double Store::median() {
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int total = sumOfColumn(1);
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int halfTotal = total/2;
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int totalMod2 = total - 2*halfTotal;
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if (totalMod2 == 0) {
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double minusMedian = sortedElementNumber(halfTotal);
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double maxMedian = sortedElementNumber(halfTotal+1);
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return (minusMedian+maxMedian)/2.0;
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} else {
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return sortedElementNumber(halfTotal+1);
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}
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}
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double Store::sum() {
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double result = 0;
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for (int k = 0; k < m_numberOfPairs; k++) {
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result += m_data[0][k]*m_data[1][k];
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}
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return result;
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}
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double Store::squaredValueSum() {
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double result = 0;
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for (int k = 0; k < m_numberOfPairs; k++) {
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result += m_data[0][k]*m_data[0][k]*m_data[1][k];
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}
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return result;
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}
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/* private methods */
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double Store::defaultValue(int i, int j) {
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if (i == 0) {
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return FloatPairStore::defaultValue(i, j);
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} else {
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return 1.0;
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}
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}
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double Store::sumOfValuesBetween(double x1, double x2) {
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int result = 0;
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for (int k = 0; k < m_numberOfPairs; k++) {
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if (m_data[0][k] < x2 && x1 <= m_data[0][k]) {
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result += m_data[1][k];
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}
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}
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return result;
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}
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double Store::sortedElementNumber(int k) {
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// TODO: use an other algorithm (ex quickselect) to avoid quadratic complexity
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double bufferValues[m_numberOfPairs];
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memcpy(bufferValues, m_data[0], m_numberOfPairs*sizeof(double));
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int sortedElementIndex = 0;
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double cumulatedSize = 0.0;
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while (cumulatedSize < k) {
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sortedElementIndex = minIndex(bufferValues, m_numberOfPairs);
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bufferValues[sortedElementIndex] = DBL_MAX;
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cumulatedSize += m_data[1][sortedElementIndex];
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}
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return m_data[0][sortedElementIndex];
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}
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int Store::minIndex(double * bufferValues, int bufferLength) {
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int index = 0;
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for (int i = 1; i < bufferLength; i++) {
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if (bufferValues[index] > bufferValues[i]) {
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index = i;
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}
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}
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return index;
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}
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}
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