Module quantmath::math::interpolation[−][src]

Structs

CubicSpline	Cubic spline interpolation is continuous up to the second derivative. It builds sections of cubic curves, based on matching first derivatives at the pillar points. It is therefore generally smoother than a simple polynomial fit.
FlyweightLinear	Flyweight linear interpolation. In this interpolator, the data is kept externally, and passed into the interpolate function. This avoids the cost of creating a vector to hold the data internally.
Linear	Non-flyweight linear interpolation. In this interpolator, the data is kept internally, and passed into the constructor.

Extrapolation methods

FlyweightInterpolate	Interpolation with date or number for the abscissa and number for the ordinal. In this implementation, the array of points is supplied in the call to the interpolate function.
Interpolable	To use interpolation, the types along the x axis must be Interpolable
Interpolate	Interpolation with date or number for the abscissa and number for the ordinal. In this implementation, the array of points is supplied in the constructor to the interpolation object.

lerp	Low-level linear interpolation function. Guaranteed to exactly equal the end points y0 and y1 when the fraction t is equal to 0 and 1 respectively.
linear_interpolate	Linear interpolation function. The y value and result must be f64. The x value can be any type supporting subtraction giving a numeric type.
linear_interpolate_extrapolate	Helper function for linear interpolation and extrapolation.
validate_abscissae	You should invoke this method to validate that the curve contains suitable data for this interpolator. Otherwise you may get unexpected panics or incorrect values when interpolating. (Validates that the x values are strictly monotonic increasing and none is NaN.)