com.metsci.glimpse.util.math.approx.ApproxSin Maven / Gradle / Ivy
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package com.metsci.glimpse.util.math.approx;
import static com.metsci.glimpse.util.math.MathConstants.TWO_PI;
import static java.lang.Math.floor;
/**
* Similar to the classes in {@link com.metsci.glimpse.util.math.fast}, but uses linear interpolation
* between samples instead of nearest-neighbor.
*
* Anecdotally, speed is about 12x faster than {@link Math#sin(double)}. With 100k samples, max error
* is around 5e-10. Max error decreases as the number of samples increases.
*/
public class ApproxSin
{
public static final double ONE_OVER_TWO_PI = 1.0 / TWO_PI;
protected final int n;
protected final double xMin;
protected final double xMax;
protected final double xStep;
protected final double oneOverXStep;
protected final double[] y;
public ApproxSin( int numSamples )
{
double xMinPrelim = 0.0;
double xMaxPrelim = TWO_PI;
double xStepPrelim = ( xMaxPrelim - xMinPrelim ) / ( numSamples - 1 );
// Avoid edge effects by tacking on an extra sample at each end
this.n = numSamples + 2;
this.xMin = xMinPrelim - xStepPrelim;
this.xMax = xMaxPrelim + xStepPrelim;
this.xStep = ( this.xMax - this.xMin ) / ( this.n - 1 );
this.oneOverXStep = 1.0 / this.xStep;
this.y = new double[ this.n ];
for ( int i = 0; i < this.n; i++ )
{
double x = this.xMin + ( i * this.xStep );
this.y[ i ] = Math.sin( x );
}
}
public static double normalizeAngleTwoPi( double x_RAD )
{
return ( x_RAD - ( TWO_PI * floor( x_RAD * ONE_OVER_TWO_PI ) ) );
}
public double sin( double x_RAD )
{
double x = normalizeAngleTwoPi( x_RAD );
// How many steps is x above xMin
double w = ( x - this.xMin ) * this.oneOverXStep;
int iBefore = ( int ) w;
double yBefore = this.y[ iBefore ];
double yAfter = this.y[ iBefore + 1 ];
double xFrac = w - iBefore;
return ( yBefore + ( xFrac * ( yAfter - yBefore ) ) );
}
}