Package com.opengamma.analytics.math.interpolation.data

Examples of com.opengamma.analytics.math.interpolation.data.Interpolator1DLogPiecewisePoynomialDataBundle

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  @Override
  public Double interpolate(final Interpolator1DDataBundle data, final Double value) {
    Validate.notNull(value, "value");
    Validate.notNull(data, "data bundle");
    Validate.isTrue(data instanceof Interpolator1DLogPiecewisePoynomialDataBundle);
    final Interpolator1DLogPiecewisePoynomialDataBundle polyData = (Interpolator1DLogPiecewisePoynomialDataBundle) data;
    final DoubleMatrix1D res = FUNC.evaluate(polyData.getPiecewisePolynomialResultsWithSensitivity(), value);
    return Math.exp(res.getEntry(0));
  }
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  @Override
  public double firstDerivative(final Interpolator1DDataBundle data, final Double value) {
    Validate.notNull(value, "value");
    Validate.notNull(data, "data bundle");
    Validate.isTrue(data instanceof Interpolator1DLogPiecewisePoynomialDataBundle);
    final Interpolator1DLogPiecewisePoynomialDataBundle polyData = (Interpolator1DLogPiecewisePoynomialDataBundle) data;
    final DoubleMatrix1D resValue = FUNC.evaluate(polyData.getPiecewisePolynomialResultsWithSensitivity(), value);
    final DoubleMatrix1D resDerivative = FUNC.differentiate(polyData.getPiecewisePolynomialResultsWithSensitivity(), value);
    return Math.exp(resValue.getEntry(0)) * resDerivative.getEntry(0);
  }
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  @Override
  public double[] getNodeSensitivitiesForValue(final Interpolator1DDataBundle data, final Double value) {
    Validate.notNull(value, "value");
    Validate.notNull(data, "data bundle");
    Validate.isTrue(data instanceof Interpolator1DLogPiecewisePoynomialDataBundle);
    final Interpolator1DLogPiecewisePoynomialDataBundle polyData = (Interpolator1DLogPiecewisePoynomialDataBundle) data;
    final double[] resSense = FUNC.nodeSensitivity(polyData.getPiecewisePolynomialResultsWithSensitivity(), value).getData();
    final double resValue = Math.exp(FUNC.evaluate(polyData.getPiecewisePolynomialResultsWithSensitivity(), value).getEntry(0));
    final double[] knotValues = data.getValues();
    final int nKnots = knotValues.length;
    final double[] res = new double[nKnots];
    for (int i = 0; i < nKnots; ++i) {
      res[i] = resSense[i] * resValue / knotValues[i];
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    final double[] logY = new double[nData];
    for (int i = 0; i < nData; ++i) {
      ArgumentChecker.isTrue(y[i] > 0., "y should be positive");
      logY[i] = Math.log(y[i]);
    }
    return new Interpolator1DLogPiecewisePoynomialDataBundle(new ArrayInterpolator1DDataBundle(x, logY, false), new MonotonicityPreservingCubicSplineInterpolator(new LogNaturalSplineHelper()));
  }
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    final double[] logY = new double[nData];
    for (int i = 0; i < nData; ++i) {
      ArgumentChecker.isTrue(y[i] > 0., "y should be positive");
      logY[i] = Math.log(y[i]);
    }
    return new Interpolator1DLogPiecewisePoynomialDataBundle(new ArrayInterpolator1DDataBundle(x, logY, true), new MonotonicityPreservingCubicSplineInterpolator(new LogNaturalSplineHelper()));
  }
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Related Classes of com.opengamma.analytics.math.interpolation.data.Interpolator1DLogPiecewisePoynomialDataBundle

  • com.opengamma.analytics.math.interpolation.LogNaturalCubicMonotonicityPreservingInterpolator1D
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