本文整理汇总了Java中java.util.concurrent.ConcurrentSkipListSet.toArray方法的典型用法代码示例。如果您正苦于以下问题：Java ConcurrentSkipListSet.toArray方法的具体用法？Java ConcurrentSkipListSet.toArray怎么用？Java ConcurrentSkipListSet.toArray使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类java.util.concurrent.ConcurrentSkipListSet的用法示例。
在下文中一共展示了ConcurrentSkipListSet.toArray方法的4个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: convertSetsToArrays
import java.util.concurrent.ConcurrentSkipListSet; //导入方法依赖的package包/类
public void convertSetsToArrays() {
for (String clazz : tmpSetMap.keySet()) {
ConcurrentSkipListSet<Object> constantSet = tmpSetMap.get(clazz);
Object[] constantObjects = constantSet.toArray(new Object[constantSet.size()]);
arrayMap.put(clazz, constantObjects);
}
allValues = allValuesSet.toArray();
}
示例2: testToArray
import java.util.concurrent.ConcurrentSkipListSet; //导入方法依赖的package包/类
/**
* toArray contains all elements in sorted order
*/
public void testToArray() {
ConcurrentSkipListSet q = populatedSet(SIZE);
Object[] o = q.toArray();
for (int i = 0; i < o.length; i++)
assertSame(o[i], q.pollFirst());
}
示例3: doCalculation
import java.util.concurrent.ConcurrentSkipListSet; //导入方法依赖的package包/类
/**
* Do OBV Calculation when input is a ConcurrentSkipListSet
* @param orgData
*/
public void doCalculation(ConcurrentSkipListSet<OHLC> orgData){
//Convert set to array
Object[] rawData;
rawData = (Object[])orgData.toArray();
calculateObv(rawData);
}
示例4: doCalculation
import java.util.concurrent.ConcurrentSkipListSet; //导入方法依赖的package包/类
/**
* Most important method to calculate moving average data and store it in
* smaData set
* @param orgData original data used to calculate smaData
*/
public void doCalculation(ConcurrentSkipListSet<OHLC> orgData){
//Everytime is a new calculation
smaPrice.clear();
smaVolume.clear();
int avgOn = avgOnProperty.getValue();
CalculationBase calBase = calBaseProperty.getValue();
//If source data is empty or less or equals to avgOn do nothing
if (orgData.isEmpty() || orgData.size() < avgOn){
return;
}
//Convert set to array
Object[] rawData;
rawData = (Object[])orgData.toArray();
//Start calculation
for (int i = 0; i<=rawData.length - avgOn; i++){
float totalPrice = 0f;
double totalVolume = 0l;
OHLC ohlc = null;
for(int j = i; j < i + avgOn; j++){
ohlc = (OHLC)rawData[j];
switch(calBase){
case OPEN:
totalPrice += ohlc.getOpen();
break;
case HIGH:
totalPrice += ohlc.getHigh();
break;
case LOW:
totalPrice += ohlc.getLow();
break;
case CLOSE:
totalPrice += ohlc.getClose();
break;
case MIDDIUM:
totalPrice += ((float)(ohlc.getHigh() + ohlc.getLow()) /(float)2);
break;
case TYPICAL:
totalPrice += (((float)(ohlc.getHigh() + ohlc.getLow() + ohlc.getClose()))/ (float)3);
break;
case WEIGHTED:
totalPrice += (((float)(ohlc.getHigh() + ohlc.getLow() + ohlc.getClose() + ohlc.getClose()))/ (float)4);
break;
case VOLUME:
totalVolume += ohlc.getVolume();
break;
}
}
float avgPrice = totalPrice / avgOn;
double avgVolume = totalVolume / avgOn;
if (ohlc != null){
if (calBase == CalculationBase.VOLUME){
//Volume is using Million as the units
//And it is keep 4 digits floating point
avgVolume/=1000000;
avgVolume *= 10000;
avgVolume = (float)Math.round(avgVolume);
avgVolume /= 10000;
smaVolume.put(ohlc.getDate(), avgVolume);
} else {
//round to 4 digits floating points
avgPrice *= 10000;
avgPrice = Math.round(avgPrice);
avgPrice /= 10000;
smaPrice.put(ohlc.getDate(), avgPrice);
}
}
}
}