Apache Commons Math3探索之多项式曲线拟合实现代码

时间:2022-01-22 06:16:18

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

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("--------------------------------------------------------------------------");
  }
}

总结

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原文链接:http://blog.csdn.net/kingfox/article/details/44118319