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