Class ConstrainedCubicSplineInterpolator
- java.lang.Object
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- com.opengamma.strata.math.impl.interpolation.PiecewisePolynomialInterpolator
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- com.opengamma.strata.math.impl.interpolation.ConstrainedCubicSplineInterpolator
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public class ConstrainedCubicSplineInterpolator extends PiecewisePolynomialInterpolator
Cubic spline interpolation based on C.J.C. Kruger, "Constrained Cubic Spline Interpolation for Chemical Engineering Applications," 2002
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Constructor Summary
Constructors Constructor Description ConstrainedCubicSplineInterpolator()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description PiecewisePolynomialResult
interpolate(double[] xValues, double[] yValues)
Interpolate.PiecewisePolynomialResult
interpolate(double[] xValues, double[][] yValuesMatrix)
Interpolate.PiecewisePolynomialResultsWithSensitivity
interpolateWithSensitivity(double[] xValues, double[] yValues)
Derive interpolant on {xValues_i, yValues_i} and (yValues) node sensitivity.-
Methods inherited from class com.opengamma.strata.math.impl.interpolation.PiecewisePolynomialInterpolator
getPrimaryMethod, getValue, getValue, interpolate, interpolate, interpolate, interpolate, interpolate, interpolate
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Method Detail
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interpolate
public PiecewisePolynomialResult interpolate(double[] xValues, double[] yValues)
Description copied from class:PiecewisePolynomialInterpolator
Interpolate.- Specified by:
interpolate
in classPiecewisePolynomialInterpolator
- Parameters:
xValues
- X values of datayValues
- Y values of data- Returns:
PiecewisePolynomialResult
containing knots, coefficients of piecewise polynomials, number of intervals, degree of polynomials, dimension of spline
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interpolate
public PiecewisePolynomialResult interpolate(double[] xValues, double[][] yValuesMatrix)
Description copied from class:PiecewisePolynomialInterpolator
Interpolate.- Specified by:
interpolate
in classPiecewisePolynomialInterpolator
- Parameters:
xValues
- X values of datayValuesMatrix
- Y values of data- Returns:
- Coefficient matrix whose i-th row vector is {a_n, a_{n-1}, ... } of f(x) = a_n * (x-x_i)^n + a_{n-1} * (x-x_i)^{n-1} +... for the i-th interval
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interpolateWithSensitivity
public PiecewisePolynomialResultsWithSensitivity interpolateWithSensitivity(double[] xValues, double[] yValues)
Description copied from class:PiecewisePolynomialInterpolator
Derive interpolant on {xValues_i, yValues_i} and (yValues) node sensitivity.- Specified by:
interpolateWithSensitivity
in classPiecewisePolynomialInterpolator
- Parameters:
xValues
- X values of datayValues
- Y values of data- Returns:
PiecewisePolynomialResultsWithSensitivity
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