Package gaia.cu9.ari.gaiaorbit.util.math

Class Lineard<T extends Vectord<T>>

  • All Implemented Interfaces:
    Pathd<T>
    public class Lineard<T extends Vectord<T>>
extends java.lang.Object
implements Pathd<T>

    • Field Summary

      Fields 
      Modifier and Type Field Description
      T[] controlPoints  

    • Constructor Summary

      Constructors 
      Constructor Description
      Lineard​(T[] controlPoints)  

    • Field Detail

      • controlPoints

        public T extends Vectord<T>[] controlPoints

    • Constructor Detail

      • Lineard

        public Lineard​(T[] controlPoints)

    • Method Detail

      • set

        public Lineard set​(T[] controlPoints)

      • valueAt

        public T valueAt​(T out,
                 double t)
        Specified by:
        valueAt in interface Pathd<T extends Vectord<T>>
        Returns:
        The value of the path at t where 0<=t<=1

      • approximate

        public double approximate​(T v)
        Specified by:
        approximate in interface Pathd<T extends Vectord<T>>
        Returns:
        The approximated value (between 0 and 1) on the path which is closest to the specified value. Note that the implementation of this method might be optimized for speed against precision, see Pathd.locate(Object) for a more precise (but more intensive) method.

      • locate

        public double locate​(T v)
        Specified by:
        locate in interface Pathd<T extends Vectord<T>>
        Returns:
        The precise location (between 0 and 1) on the path which is closest to the specified value. Note that the implementation of this method might be CPU intensive, see Pathd.approximate(Object) for a faster (but less precise) method.

      • approxLength

        public double approxLength​(int samples)
        Specified by:
        approxLength in interface Pathd<T extends Vectord<T>>
        Parameters:
        samples - The amount of divisions used to approximate length. Higher values will produce more precise results, but will be more CPU intensive.
        Returns:
        An approximated length of the spline through sampling the curve and accumulating the euclidean distances between the sample points.