org.apache.commons.math3.analysis.interpolation.LoessInterpolator Java Examples

@Override
@SuppressWarnings({"unchecked"})
public Object doWork(Object... objects) throws IOException{

  Object first = objects[0];

  double[] x = null;
  double[] y = null;

  if(objects.length == 1) {
    //Only the y values passed
    y = ((List) first).stream().mapToDouble(value -> ((Number) value).doubleValue()).toArray();
    x = new double[y.length];
    for(int i=0; i<y.length; i++) {
      x[i] = i;
    }
  } else if(objects.length == 2) {
    Object second = objects[1];
    x = ((List) first).stream().mapToDouble(value -> ((Number) value).doubleValue()).toArray();
    y = ((List) second).stream().mapToDouble(value -> ((Number) value).doubleValue()).toArray();
  }

  LoessInterpolator interpolator = new LoessInterpolator(bandwidth, robustIterations);
  double[] smooth = interpolator.smooth(x, y);

  List<Number> list = new ArrayList<>();
  for(double yvalue : smooth) {
    list.add(yvalue);
  }

  PolynomialSplineFunction spline = interpolator.interpolate(x, y);

  VectorFunction vec = new VectorFunction(spline, list);
  vec.addToContext("x", x);
  vec.addToContext("y", y);

  return vec;
}
 

@Override
	public int calculateOrder(AFPChain afpChain, Atom[] ca) throws RefinerFailedException {

		try {

			RotationAxis axis = new RotationAxis(afpChain);
			logger.info("Calculating rotation samples");
			Pair<double[],double[]> pair = RotationOrderDetector.sampleRotations(ca, axis, degreeSampling);
			logger.info("Smoothing with LOESS");
			LoessInterpolator loess = new LoessInterpolator(bandwidth, robustnessIterations, loessAccuracy);

			double[] smoothed = loess.smooth(pair.getKey(), pair.getValue());
			logger.info("Counting Peaks");
			
			int nPeaks = countPeaks(smoothed, epsilon * Math.PI/180);
			logger.info("Found {} peaks",nPeaks);
			
			/*
			 *  TODO Currently this isn't likely to handle order=1 well,
			 *  since C1 cases can easily have, say, exactly 5 peaks.
			 *  We will need to combine this with some smarter fitting method.
			 */

			return nPeaks; // for now
			
//			return nPeaks>maxOrder? 1 : nPeaks;

		} catch (Exception e) {
			throw new RefinerFailedException(e);
		}

	}
 

private TimesAndValues padEdges(double[] ts, double[] xs) {
  // Find step between times
  double step = Math.abs(ts[1] - ts[0]);
  // Times (assuming uniform
  double[] paddedTimes = new double[ts.length + 2];
  System.arraycopy(ts, 0, paddedTimes, 1, ts.length);
  paddedTimes[0] = paddedTimes[1] - step;
  paddedTimes[paddedTimes.length - 1] = paddedTimes[paddedTimes.length - 2] + step;

  // Series
  double[] paddedSeries = new double[xs.length + 2];
  System.arraycopy(xs, 0, paddedSeries, 1, xs.length);

  // Use Loess at ends to pad
  // n.b. For some reason, this can result in NaN values - perhaps similar to
  // https://issues.apache.org/jira/browse/MATH-296. If we see NaN, just "extrapolate" by copying
  // the end points :(

  double left = paddedSeries[1];
  double right = paddedSeries[paddedSeries.length - 2];

  double bandwidth = 0.3;
  if (ts.length * bandwidth > 2) {
    PolynomialSplineFunction loess = new LoessInterpolator(bandwidth, 2).interpolate(ts, xs);

    double loessLeft = loess.value(ts[0]);
    if (!Double.isNaN(loessLeft)) {
      left = loessLeft;
    }

    double loessRight = loess.value(ts[ts.length - 1]);
    if (!Double.isNaN(loessRight)) {
      right = loessRight;
    }
  }

  paddedSeries[0] = left;
  paddedSeries[paddedSeries.length - 1] = right;

  return new TimesAndValues(paddedTimes, paddedSeries);
}
 

/**
 * Performs weighted Loess smoothing on a series.
 *
 * <p>
 *   Does not assume contiguous time.
 * </p>
 *
 * @param times
 *  The times.
 * @param series
 *  The time series data.
 * @param bandwidth
 *  The amount of neighbor points to consider for each point in Loess.
 * @param weights
 *  The weights to use for smoothing, if null, equal weights are assumed.
 * @return
 *  Loess-smoothed series.
 */
private double[] loessSmooth(double[] times,
                             double[] series,
                             double bandwidth,
                             double[] weights) {
  if (weights == null) {
    return new LoessInterpolator(
        bandwidth,
        config.getLoessRobustnessIterations()).smooth(times, series);
  } else {
    return new LoessInterpolator(
        bandwidth,
        config.getLoessRobustnessIterations()).smooth(times, series, weights);
  }
}