Example usage for org.apache.commons.math3.analysis.polynomials PolynomialSplineFunction getKnots

Introduction

In this page you can find the example usage for org.apache.commons.math3.analysis.polynomials PolynomialSplineFunction getKnots.

Prototype

public double[] getKnots() 

Source Link

Document

Get an array copy of the knot points.

Usage

From source file:eu.tango.energymodeller.energypredictor.CpuOnlySplinePolynomialEnergyPredictor.java

/**
 * This ensures the CPU usage provided to the model is in the acceptable
 * range./*from w  w w.  j a v  a2s  .  c  o  m*/
 *
 * @param model The model to get the cpu usage for
 * @param usageCPU The amount of CPU load placed on the host
 * @return The cpu usage that is within the acceptable range.
 */
private double getCpuUsageValue(PolynomialSplineFunction model, double usageCPU) {
    /**
     * Interpolation is the process of fitting a line of best fit directly
     * to the datapoints gathered. The lowest value possible value to
     * predict from is therefore not likely to be 0.
     */
    if (usageCPU < model.getKnots()[0]) {
        return model.getKnots()[0];
    }
    if (usageCPU > model.getKnots()[model.getKnots().length - 1]) {
        return model.getKnots()[model.getKnots().length - 1];
    }
    return usageCPU;
}

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From source file:malware_classification.Malware_Classification.java

private ArrayList<double[]> interpolate_data(ArrayList<double[]> data_orig, ArrayList<double[]> timestamp_orig,
        int bin_size, int num_bins) {
    ArrayList<double[]> interp_data = new ArrayList<>();
    int num_points_orig = data_orig.size();
    // TODO: change some of the num_points_orig to num_bins
    double[] x = new double[num_points_orig];
    double[] y = new double[num_points_orig];
    int num_cols = data_orig.get(0).length;
    for (int i = 0; i < num_bins; i++) {
        interp_data.add(new double[num_cols]);
    }//from ww w.  j  a  v a2 s  . com

    for (int col = 0; col < num_cols; col++) {
        // To use LinearInterpolator, first need arrays
        for (int j = 0; j < num_points_orig; j++) {
            x[j] = timestamp_orig.get(j)[col];
            y[j] = data_orig.get(j)[col];
        }
        LinearInterpolator lin_interp = new LinearInterpolator();
        PolynomialSplineFunction interp_func = lin_interp.interpolate(x, y);
        for (int j = 0; j < num_bins; j++) {
            double curr_bin = bin_size * j;
            double[] knots = interp_func.getKnots();

            //                logger.info()
            if (interp_func.isValidPoint(curr_bin)) {
                interp_data.get(j)[col] = interp_func.value(curr_bin);
            } else if (knots[0] > curr_bin) //bin is too small
            {
                interp_data.get(j)[col] = y[0];
            } else if (knots[knots.length - 1] < curr_bin) // bin is larger than data
            {
                interp_data.get(j)[col] = y[y.length - 1];
            } else {
                logger.warning("Cannot interpolate at bin starting at " + curr_bin);
            }
        }
    }

    return interp_data;

}

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From source file:org.micromanager.plugins.magellan.acq.AcqDurationEstimator.java

private double interpolateOrExtrapolate(double[] x, double[] y, double xVal) {
    if (x.length == 1) {
        return y[0];
    }/*from  w w  w.ja  va2 s.c  om*/
    LinearInterpolator interpolator = new LinearInterpolator();
    PolynomialSplineFunction interpolant = interpolator.interpolate(x, y);
    if (xVal < interpolant.getKnots()[0]) {
        return interpolant.getKnots()[0];
    } else if (xVal > interpolant.getKnots()[interpolant.getN() - 1]) {
        return interpolant.getKnots()[interpolant.getN() - 1];
    } else {
        return interpolant.value(xVal);
    }
}

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