Apache Commons Math3探索之多项式曲线拟合实现代码

// ... 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 

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