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613 lines
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613 lines
29 KiB
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<a href="../MathNet.Numerics/NumericalBreakdownException.htm">NumericalBreakdownException</a>
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<a href="../MathNet.Numerics/Permutation.htm">Permutation</a>
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<a href="../MathNet.Numerics/Polynomial.htm">Polynomial</a>
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<a href="../MathNet.Numerics/Precision.htm">Precision</a>
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<a href="../MathNet.Numerics/SingularUMatrixException.htm">SingularUMatrixException</a>
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<a href="../MathNet.Numerics/Sorting.htm">Sorting</a>
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<a href="../MathNet.Numerics/Trig.htm">Trig</a>
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</ul>
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</div>
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</div>
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<div class="header">
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<p class="class"><strong>Type</strong> Interpolate</p>
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<p><strong>Namespace</strong> MathNet.Numerics</p>
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</div>
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<div class="sub-header">
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<div id="summary">Interpolation Factory.
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</div>
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<h3 class="section">Static Functions</h3>
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<ul>
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<li><a href="../MathNet.Numerics/Interpolate.htm#Common">Common</a></li>
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<li><a href="../MathNet.Numerics/Interpolate.htm#CubicSpline">CubicSpline</a></li>
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<li><a href="../MathNet.Numerics/Interpolate.htm#CubicSplineMonotone">CubicSplineMonotone</a></li>
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<li><a href="../MathNet.Numerics/Interpolate.htm#CubicSplineRobust">CubicSplineRobust</a></li>
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<li><a href="../MathNet.Numerics/Interpolate.htm#CubicSplineWithDerivatives">CubicSplineWithDerivatives</a></li>
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<li><a href="../MathNet.Numerics/Interpolate.htm#Linear">Linear</a></li>
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<li><a href="../MathNet.Numerics/Interpolate.htm#LogLinear">LogLinear</a></li>
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<li><a href="../MathNet.Numerics/Interpolate.htm#Polynomial">Polynomial</a></li>
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<li><a href="../MathNet.Numerics/Interpolate.htm#PolynomialEquidistant">PolynomialEquidistant</a></li>
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<li><a href="../MathNet.Numerics/Interpolate.htm#RationalWithoutPoles">RationalWithoutPoles</a></li>
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<li><a href="../MathNet.Numerics/Interpolate.htm#RationalWithPoles">RationalWithPoles</a></li>
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<li><a href="../MathNet.Numerics/Interpolate.htm#Step">Step</a></li>
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</ul>
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</div>
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<h3 class="section">Public Static Functions</h3>
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<div id="Common" class="method">
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<h4><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a> <strong>Common</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> points, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> values)</h4>
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<div class="content">Creates an interpolation based on arbitrary points. <blockquote class="remarks">
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if your data is already sorted in arrays, consider to use
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MathNet.Numerics.Interpolation.Barycentric.InterpolateRationalFloaterHormannSorted
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instead, which is more efficient.
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</blockquote>
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> points</h6>
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<p class="comments">The sample points t. </p>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> values</h6>
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<p class="comments">The sample point values x(t). </p>
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</div>
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<div class="return">
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<h5>Return</h5>
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<h6><code><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a></code></h6>
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<p>An interpolation scheme optimized for the given sample points and values,
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which can then be used to compute interpolations and extrapolations
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on arbitrary points. </p>
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</div>
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</div>
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</div>
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<div id="CubicSpline" class="method">
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<h4><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a> <strong>CubicSpline</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> points, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> values)</h4>
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<div class="content">Create an piecewise natural cubic spline interpolation based on arbitrary points,
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with zero secondary derivatives at the boundaries. <blockquote class="remarks">
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if your data is already sorted in arrays, consider to use
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MathNet.Numerics.Interpolation.CubicSpline.InterpolateNaturalSorted
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instead, which is more efficient.
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</blockquote>
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> points</h6>
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<p class="comments">The sample points t. </p>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> values</h6>
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<p class="comments">The sample point values x(t). </p>
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</div>
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<div class="return">
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<h5>Return</h5>
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<h6><code><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a></code></h6>
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<p>An interpolation scheme optimized for the given sample points and values,
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which can then be used to compute interpolations and extrapolations
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on arbitrary points. </p>
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</div>
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</div>
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</div>
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<div id="CubicSplineMonotone" class="method">
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<h4><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a> <strong>CubicSplineMonotone</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> points, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> values)</h4>
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<div class="content">Create a piecewise cubic monotone spline interpolation based on arbitrary points.
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This is a shape-preserving spline with continuous first derivative. <blockquote class="remarks">
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if your data is already sorted in arrays, consider to use
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MathNet.Numerics.Interpolation.CubicSpline.InterpolatePchipSorted
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instead, which is more efficient.
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</blockquote>
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> points</h6>
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<p class="comments">The sample points t. </p>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> values</h6>
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<p class="comments">The sample point values x(t). </p>
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</div>
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<div class="return">
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<h5>Return</h5>
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<h6><code><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a></code></h6>
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<p>An interpolation scheme optimized for the given sample points and values,
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which can then be used to compute interpolations and extrapolations
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on arbitrary points. </p>
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</div>
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</div>
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</div>
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<div id="CubicSplineRobust" class="method">
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<h4><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a> <strong>CubicSplineRobust</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> points, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> values)</h4>
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<div class="content">Create a piecewise cubic Akima spline interpolation based on arbitrary points.
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Akima splines are robust to outliers. <blockquote class="remarks">
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if your data is already sorted in arrays, consider to use
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MathNet.Numerics.Interpolation.CubicSpline.InterpolateAkimaSorted
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instead, which is more efficient.
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</blockquote>
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> points</h6>
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<p class="comments">The sample points t. </p>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> values</h6>
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<p class="comments">The sample point values x(t). </p>
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</div>
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<div class="return">
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<h5>Return</h5>
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<h6><code><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a></code></h6>
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<p>An interpolation scheme optimized for the given sample points and values,
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which can then be used to compute interpolations and extrapolations
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on arbitrary points. </p>
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</div>
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</div>
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</div>
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<div id="CubicSplineWithDerivatives" class="method">
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<h4><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a> <strong>CubicSplineWithDerivatives</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> points, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> values, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> firstDerivatives)</h4>
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<div class="content">Create a piecewise cubic Hermite spline interpolation based on arbitrary points
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and their slopes/first derivative. <blockquote class="remarks">
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if your data is already sorted in arrays, consider to use
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MathNet.Numerics.Interpolation.CubicSpline.InterpolateHermiteSorted
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instead, which is more efficient.
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</blockquote>
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> points</h6>
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<p class="comments">The sample points t. </p>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> values</h6>
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<p class="comments">The sample point values x(t). </p>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> firstDerivatives</h6>
|
|
<p class="comments">The slope at the sample points. Optimized for arrays. </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a></code></h6>
|
|
<p>An interpolation scheme optimized for the given sample points and values,
|
|
which can then be used to compute interpolations and extrapolations
|
|
on arbitrary points. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Linear" class="method">
|
|
<h4><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a> <strong>Linear</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> points, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> values)</h4>
|
|
<div class="content">Create a piecewise linear interpolation based on arbitrary points. <blockquote class="remarks">
|
|
if your data is already sorted in arrays, consider to use
|
|
MathNet.Numerics.Interpolation.LinearSpline.InterpolateSorted
|
|
instead, which is more efficient.
|
|
</blockquote>
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> points</h6>
|
|
<p class="comments">The sample points t. </p>
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> values</h6>
|
|
<p class="comments">The sample point values x(t). </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a></code></h6>
|
|
<p>An interpolation scheme optimized for the given sample points and values,
|
|
which can then be used to compute interpolations and extrapolations
|
|
on arbitrary points. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="LogLinear" class="method">
|
|
<h4><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a> <strong>LogLinear</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> points, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> values)</h4>
|
|
<div class="content">Create piecewise log-linear interpolation based on arbitrary points. <blockquote class="remarks">
|
|
if your data is already sorted in arrays, consider to use
|
|
MathNet.Numerics.Interpolation.LogLinear.InterpolateSorted
|
|
instead, which is more efficient.
|
|
</blockquote>
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> points</h6>
|
|
<p class="comments">The sample points t. </p>
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> values</h6>
|
|
<p class="comments">The sample point values x(t). </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a></code></h6>
|
|
<p>An interpolation scheme optimized for the given sample points and values,
|
|
which can then be used to compute interpolations and extrapolations
|
|
on arbitrary points. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Polynomial" class="method">
|
|
<h4><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a> <strong>Polynomial</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> points, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> values)</h4>
|
|
<div class="content">Create a Neville polynomial interpolation based on arbitrary points.
|
|
If the points happen to be equidistant, consider to use the much more robust PolynomialEquidistant instead.
|
|
Otherwise, consider whether RationalWithoutPoles would not be a more robust alternative. <blockquote class="remarks">
|
|
if your data is already sorted in arrays, consider to use
|
|
MathNet.Numerics.Interpolation.NevillePolynomialInterpolation.InterpolateSorted
|
|
instead, which is more efficient.
|
|
</blockquote>
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> points</h6>
|
|
<p class="comments">The sample points t. </p>
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> values</h6>
|
|
<p class="comments">The sample point values x(t). </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a></code></h6>
|
|
<p>An interpolation scheme optimized for the given sample points and values,
|
|
which can then be used to compute interpolations and extrapolations
|
|
on arbitrary points. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="PolynomialEquidistant" class="method">
|
|
<h4><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a> <strong>PolynomialEquidistant</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> points, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> values)</h4>
|
|
<div class="content">Create a barycentric polynomial interpolation where the given sample points are equidistant. <blockquote class="remarks">
|
|
if your data is already sorted in arrays, consider to use
|
|
MathNet.Numerics.Interpolation.Barycentric.InterpolatePolynomialEquidistantSorted
|
|
instead, which is more efficient.
|
|
</blockquote>
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> points</h6>
|
|
<p class="comments">The sample points t, must be equidistant. </p>
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> values</h6>
|
|
<p class="comments">The sample point values x(t). </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a></code></h6>
|
|
<p>An interpolation scheme optimized for the given sample points and values,
|
|
which can then be used to compute interpolations and extrapolations
|
|
on arbitrary points. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="RationalWithoutPoles" class="method">
|
|
<h4><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a> <strong>RationalWithoutPoles</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> points, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> values)</h4>
|
|
<div class="content">Create a Floater-Hormann rational pole-free interpolation based on arbitrary points. <blockquote class="remarks">
|
|
if your data is already sorted in arrays, consider to use
|
|
MathNet.Numerics.Interpolation.Barycentric.InterpolateRationalFloaterHormannSorted
|
|
instead, which is more efficient.
|
|
</blockquote>
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> points</h6>
|
|
<p class="comments">The sample points t. </p>
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> values</h6>
|
|
<p class="comments">The sample point values x(t). </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a></code></h6>
|
|
<p>An interpolation scheme optimized for the given sample points and values,
|
|
which can then be used to compute interpolations and extrapolations
|
|
on arbitrary points. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="RationalWithPoles" class="method">
|
|
<h4><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a> <strong>RationalWithPoles</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> points, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> values)</h4>
|
|
<div class="content">Create a Bulirsch Stoer rational interpolation based on arbitrary points. <blockquote class="remarks">
|
|
if your data is already sorted in arrays, consider to use
|
|
MathNet.Numerics.Interpolation.BulirschStoerRationalInterpolation.InterpolateSorted
|
|
instead, which is more efficient.
|
|
</blockquote>
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> points</h6>
|
|
<p class="comments">The sample points t. </p>
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> values</h6>
|
|
<p class="comments">The sample point values x(t). </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a></code></h6>
|
|
<p>An interpolation scheme optimized for the given sample points and values,
|
|
which can then be used to compute interpolations and extrapolations
|
|
on arbitrary points. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Step" class="method">
|
|
<h4><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a> <strong>Step</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> points, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> values)</h4>
|
|
<div class="content">Create a step-interpolation based on arbitrary points. <blockquote class="remarks">
|
|
if your data is already sorted in arrays, consider to use
|
|
MathNet.Numerics.Interpolation.StepInterpolation.InterpolateSorted
|
|
instead, which is more efficient.
|
|
</blockquote>
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> points</h6>
|
|
<p class="comments">The sample points t. </p>
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> values</h6>
|
|
<p class="comments">The sample point values x(t). </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><a href="../MathNet.Numerics.Interpolation/IInterpolation.htm">IInterpolation</a></code></h6>
|
|
<p>An interpolation scheme optimized for the given sample points and values,
|
|
which can then be used to compute interpolations and extrapolations
|
|
on arbitrary points. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
|
|
|
|
<div id="footer">
|
|
<p>Based on v5.0.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
|
|
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
|
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</div>
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