Examples of umontreal.iro.lecuyer.functionfit.SmoothingCubicSpline

umontreal.iro.lecuyer.functionfit.SmoothingCubicSpline

, fill arrays X and Y with n data points (x_i, y_i)
   // The points must be sorted with respect to x_i.

   double rho = 0.1;
   SmoothingCubicSpline fit = new SmoothingCubicSpline(X, Y, rho);

   int m = 40;
   double[] Xp = new double[m+1];       // Xp, Yp are spline points
   double[] Yp = new double[m+1];
   double h = (X[n-1] - X[0]) / m;      // step

   for (int i = 0; i <= m; i++) {
      double z = X[0] + i * h;
      Xp[i] = z;
      Yp[i] = fit.evaluate(z);          // evaluate spline at z
   }

      // on sait qu'il y a des points qui vont sortir du chart
      // initialisation d'une spline pour chaque courbe
      if (true) {
         spline = new SmoothingCubicSpline[tempSeriesCollection.getSeriesCount()];
         for (int i = 0; i < tempSeriesCollection.getSeriesCount(); i++)
            spline[i] = new SmoothingCubicSpline((tempSeriesCollection.getSeries(i).toArray())[0],
                                                 (tempSeriesCollection.getSeries(i).toArray())[1], 1);
      } else {
         spline = new AffineFit[tempSeriesCollection.getSeriesCount()];
         for (int i = 0; i < tempSeriesCollection.getSeriesCount(); i++)
            spline[i] = new AffineFit((tempSeriesCollection.getSeries(i).toArray())[0],

Related Classes of umontreal.iro.lecuyer.functionfit.SmoothingCubicSpline

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