public void FitsAtArbitraryPointsWithMaple(
[Values(0.1, 0.4, 1.1, 3.2, 4.5, 10.0, -10.0)] double t,
[Values(.487425, 1.6968, 3.081925, .9408, 7.265625, 592.5, 657.5)] double x,
[Values(1e-15, 1e-15, 1e-15, 1e-15, 1e-14, 1e-10, 1e-9)] double maxAbsoluteError)
{
IInterpolation interpolation = new EquidistantPolynomialInterpolation(_tmin, _tmax, _x);
Assert.AreEqual(x, interpolation.Interpolate(t), maxAbsoluteError, "Interpolation at {0}", t);
}
public void FitsAtSamplePoints()
{
IInterpolation interpolation = new EquidistantPolynomialInterpolation(_tmin, _tmax, _x);
for (int i = 0; i < _x.Length; i++)
{
Assert.AreEqual(_x[i], interpolation.Interpolate(i), "A Exact Point " + i);
}
}
public void PolynomialFitsAtArbitraryPointsWithMaple(
[Values(-2.4, -0.9, -0.5, -0.1, 0.1, 0.4, 1.2, 10.0, -10.0)] double t,
[Values(-4.5968, 1.65395, 0.21875, -0.84205, -1.10805, -1.1248, 0.5392, -4431.0, -5071.0)] double x,
[Values(1e-14, 1e-15, 1e-15, 1e-15, 1e-15, 1e-15, 1e-15, 1e-9, 1e-9)] double maxAbsoluteError)
{
IInterpolation interpolation = new EquidistantPolynomialInterpolation(_t, _x);
Assert.AreEqual(x, interpolation.Interpolate(t), maxAbsoluteError, "Interpolation at {0}", t);
}
public void SupportsLinearCase([Values(2, 4, 12)] int samples)
{
double[] x, y, xtest, ytest;
LinearInterpolationCase.Build(out x, out y, out xtest, out ytest, samples);
IInterpolation interpolation = new EquidistantPolynomialInterpolation(x, y);
for (int i = 0; i < xtest.Length; i++)
{
Assert.AreEqual(ytest[i], interpolation.Interpolate(xtest[i]), 1e-12, "Linear with {0} samples, sample {1}", samples, i);
}
}
public void PolynomialFitsAtArbitraryPointsWithMaple(double t, double x, double maxAbsoluteError)
{
IInterpolation interpolation = new EquidistantPolynomialInterpolation(_t, _x);
Assert.AreEqual(x, interpolation.Interpolate(t), maxAbsoluteError, "Interpolation at {0}", t);
}
/// <summary>
/// Create a polynomial interpolation based on equidistant sample points.
/// </summary>
/// <param name="leftBound">The leftmost (smallest) sample point t.</param>
/// <param name="rightBound">The rightmost (biggest) sample point t.</param>
/// <param name="values">The sample point values x(t). Supports both lists and arrays.</param>
/// <returns>
/// An interpolation scheme optimized for the given sample points and values,
/// which can then be used to compute interpolations and extrapolations
/// on arbitrary points.
/// </returns>
public static IInterpolationMethod CreateOnEquidistantPoints(
double leftBound,
double rightBound,
IList<double> values
)
{
EquidistantPolynomialInterpolation method = new EquidistantPolynomialInterpolation();
method.Init(leftBound, rightBound, values);
return method;
}
public void FitsAtArbitraryPointsWithMaple(double t, double x, double maxAbsoluteError)
{
IInterpolation interpolation = new EquidistantPolynomialInterpolation(Tmin, Tmax, _x);
Assert.AreEqual(x, interpolation.Interpolate(t), maxAbsoluteError, "Interpolation at {0}", t);
}