Package space.kscience.kmath.interpolation
Types
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class LinearInterpolator<T : Comparable<T>>(algebra: Field<T>) : PolynomialInterpolator<T>
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Reference JVM implementation: https://github.com/apache/commons-math/blob/master/src/main/java/org/apache/commons/math4/analysis/interpolation/LinearInterpolator.java
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interface PolynomialInterpolator<T : Comparable<T>> : Interpolator<T, T, T>
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And interpolator returning PiecewisePolynomial function
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class SplineInterpolator<T : Comparable<T>>(algebra: Field<T>, bufferFactory: MutableBufferFactory<T>) : PolynomialInterpolator<T>
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Generic spline interpolator. Not recommended for performance critical places, use platform-specific and type specific ones.
Functions
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fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolate(data: List<Pair<T, T>>): (T) -> T?
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fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolate(data: Map<T, T>): (T) -> T?
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fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolate(data: List<Pair<T, T>>, defaultValue: T): (T) -> T
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fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolate(data: Map<T, T>, defaultValue: T): (T) -> T
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fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolate(x: Buffer<T>, y: Buffer<T>): (T) -> T?
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fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolate(x: Buffer<T>, y: Buffer<T>, defaultValue: T): (T) -> T
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fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolatePolynomials(data: List<Pair<T, T>>): PiecewisePolynomial<T>
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fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolatePolynomials(data: Map<T, T>): PiecewisePolynomial<T>
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fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolatePolynomials(x: Buffer<T>, y: Buffer<T>): PiecewisePolynomial<T>
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fun <T : Comparable<T>> Field<T>.splineInterpolator(bufferFactory: MutableBufferFactory<T>): SplineInterpolator<T>
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Properties
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val <T : Comparable<T>> Field<T>.linearInterpolator: LinearInterpolator<T>
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