上一篇文章我们介绍了Apache Commons Math3学习之数值积分实例代码,这里给大家分享math3多项式曲线拟合的相关内容,具体如下。
多项式曲线拟合:org.apache.commons.math3.fitting.PolynomialCurveFitter类。
用法示例代码:
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// ... 创建并初始化输入数据:
double[] x = new double[...];
double[] y = new double[...];
将原始的x-y数据序列合成带权重的观察点数据序列:
WeightedObservedPoints points = new WeightedObservedPoints();
// 将x-y数据元素调用points.add(x[i], y[i])加入到观察点序列中
// ...
PolynomialCurveFitter fitter = PolynomialCurveFitter.create(degree); // degree 指定多项式阶数
double[] result = fitter.fit(points.toList()); // 曲线拟合,结果保存于双精度数组中,由常数项至最高次幂系数排列
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首先要准备好待拟合的曲线数据x和y,这是两个double数组,然后把这两个数组合并到WeightedObservedPoints对象实例中,可以调用WeightedObservedPoints.add(x[i], y[i])将x和y序列中的数据逐个添加到观察点序列对象中。随后创建PolynomialCurveFitter对象,创建时要指定拟合多项式的阶数,注意阶数要选择适当,不是越高越好,否则拟合误差会很大。最后调用PolynomialCurveFitter的fit方法即可完成多项式曲线拟合,fit方法的参数通过WeightedObservedPoints.toList()获得。拟合结果通过一个double数组返回,按元素顺序依次是常数项、一次项、二次项、……。
完整的演示代码如下:
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interface TestCase
{
public Object run(List<Object> params) throws Exception;
public List<Object> getParams();
public void printResult(Object result);
}
class CalcCurveFitting implements TestCase
{
public CalcCurveFitting()
{
System.out.print( "本算例用于计算多项式曲线拟合。正在初始化 计算数据(" + arrayLength + "点, " + degree + "阶)... ..." );
inputDataX = new double [arrayLength];
// inputDataX = new double[] {1, 2, 3, 4, 5, 6, 7};
inputDataY = new double [inputDataX.length];
double [] factor = new double [degree + 1 ]; // N阶多项式会有N+1个系数,其中之一为常数项
for ( int index = 0 ; index < factor.length; index ++)
{
factor[index] = index + 1 ;
}
for ( int index = 0 ; index < inputDataY.length; index ++)
{
inputDataX[index] = index * 0.00001 ;
inputDataY[index] = calcPoly(inputDataX[index], factor); // y = sum(x[n) * fact[n])
// System.out.print(inputDataY[index] + ", ");
}
points = new WeightedObservedPoints();
for ( int index = 0 ; index < inputDataX.length; index ++)
{
points.add(inputDataX[index], inputDataY[index]);
}
System.out.println( "初始化完成" );
}
@Override
public List<Object> getParams()
{
List<Object> params = new ArrayList<Object>();
params.add(points);
return params;
}
@Override
public Object run(List<Object> params) throws Exception
{
PolynomialCurveFitter fitter = PolynomialCurveFitter.create(degree);
WeightedObservedPoints points = (WeightedObservedPoints)params.get( 0 );
double [] result = fitter.fit(points.toList());
return result;
}
@Override
public void printResult(Object result)
{
for ( double data : ( double [])result)
{
System.out.println(data);
}
}
private double calcPoly( double x, double [] factor)
{
double y = 0 ;
for ( int deg = 0 ; deg < factor.length; deg ++)
{
y += Math.pow(x, deg) * factor[deg];
}
return y;
}
private double [] inputDataX = null ;
private double [] inputDataY = null ;
private WeightedObservedPoints points = null ;
private final int arrayLength = 200000 ;
private final int degree = 5 ; // 阶数
}
public class TimeCostCalculator
{
public TimeCostCalculator()
{
}
/**
* 计算指定对象的运行时间开销。
*
* @param testCase 指定被测对象。
* @return 返回sub.run的时间开销,单位为s。
* @throws Exception
*/
public double calcTimeCost(TestCase testCase) throws Exception
{
List<Object> params = testCase.getParams();
long startTime = System.nanoTime();
Object result = testCase.run(params);
long stopTime = System.nanoTime();
testCase.printResult(result);
System.out.println( "start: " + startTime + " / stop: " + stopTime);
double timeCost = (stopTime - startTime) * 1 .0e- 9 ;
return timeCost;
}
public static void main(String[] args) throws Exception
{
TimeCostCalculator tcc = new TimeCostCalculator();
double timeCost;
System.out.println( "--------------------------------------------------------------------------" );
timeCost = tcc.calcTimeCost( new CalcCurveFitting());
System.out.println( "time cost is: " + timeCost + "s" );
System.out.println( "--------------------------------------------------------------------------" );
}
}
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总结
以上就是本文关于Apache Commons Math3探索之多项式曲线拟合实现代码的全部内容,希望对大家有所帮助。
原文链接:http://blog.csdn.net/kingfox/article/details/44118319