这里是使用Apache Commons Math 3:实现直方图的简单方法。
final int BIN_COUNT = 20;
double[] data = {1.2, 0.2, 0.333, 1.4, 1.5, 1.2, 1.3, 10.4, 1, 2.0};
long[] histogram = new long[BIN_COUNT];
org.apache.commons.math3.random.EmpiricalDistribution distribution = new org.apache.commons.math3.random.EmpiricalDistribution(BIN_COUNT);
distribution.load(data);
int k = 0;
for(org.apache.commons.math3.stat.descriptive.SummaryStatistics stats: distribution.getBinStats())
{
histogram[k++] = stats.getN();
}
据我所知,Apache Commons中没有良好的直方图类。 我最终写了自己的书。 如果您想要的只是从min到max线性分布的垃圾箱,那么编写非常容易。
可能是这样的:public static int[] calcHistogram(double[] data, double min, double max, int numBins) {
final int[] result = new int[numBins];
final double binSize = (max - min)/numBins;
for (double d : data) {
int bin = (int) ((d - min) / binSize);
if (bin < 0) { /* this data is smaller than min */ }
else if (bin >= numBins) { /* this data point is bigger than max */ }
else {
result[bin] += 1;
}
}
return result;
}
eDit
:这是一个例子。double[] data = { 2, 4, 6, 7, 8, 9 };
int[] histogram = calcHistogram(data, 0, 10, 4);
// This is a histogram with 4 bins, 0-2.5, 2.5-5, 5-7.5, 7.5-10.
assert histogram[0] == 1; // one point (2) in range 0-2.5
assert histogram[1] == 1; // one point (4) in range 2.5-5.
// etc..
提供一些有用的范围,过滤和计数功能。
public static long[] calcHistogram(double[] data, double min, double max, int numBins) {
final double interval = (max - min) / numBins;
return LongStream.range(0, numBins)
.map(n -> {
double binStart = min + n * interval;
double binEnd = min + (n + 1) * interval;
return Arrays.stream(data)
.filter(d -> d >= binStart && d < binEnd)
.count();
})
.toArray();
}
public static int[] calcHistogram(double[] data, double min, double max, int numBins) {
final int[] result = new int[numBins];
final double binSize = (max - min)/numBins;
for (double d : data) {
int bin = (int) ((d - min) / binSize); // changed this from numBins
if (bin < 0) { /* this data is smaller than min */ }
else if (bin >= numBins) { /* this data point is bigger than max */ }
else {
result[bin] += 1;
}
}
return result;
}
这是 @Altair7852的答案。
如果您想生成x值
histogram[] at index i)
private fun displayHistogram(binCount: Int, data: DoubleArray) {
val histogram = DoubleArray(binCount)
val distribution = org.apache.commons.math3.random.EmpiricalDistribution(binCount)
distribution.load(data)
var k = 0
for (stats in distribution.binStats) {
histogram[k++] = stats.n.toDouble()
}
val binSize = (data.max()!!.toDouble() - data.min()!!.toDouble()) / binCount
for (i in 0 until histogram.size) {
series2?.appendData(DataPoint(generateHistogramXValues(data.min()!!.toDouble(), histogram.size, binSize)[i], histogram[i]), false, histogram.count())
}
}
val xValuesArray = DoubleArray(numberOfBIns)
for (i in 0 until numberOfBIns) {
if (i == 0){
xValuesArray[i] = min
}else{
val previous = xValuesArray[i-1]
xValuesArray[i] = previous+binSize
}
}
return xValuesArray
}
图形库在Android上执行此操作,但是您可以在任何lib上使用它。