package jasext.hist.function;

import jas2.hist.*;

/**
* The function represents the Landau distribution.
* This class represents a Landau distribution, as 
* approximated by the Moyal formula
* \[ Moyal(\lambda) = \frac{\exp{-0.5(\lambda+\exp{-\lambda})}}{\sqrt{2\pi}} \]
* See J.E. Moyal, Theory of ionization fluctuations, Phil. Mag. 46 (1955) 263.
* Note that this analytical approximation is too low in the tail.
* In order to allow for a fit, we define
* \[ \lambda = \frac{x - m}{s} \]
* with x the dataset variable. 
*  
**/


public class LandauFunction extends Fittable1DFunction implements HasHandles
{
	/**
	 * 
	 */
	private static final long serialVersionUID = 1L;
	public LandauFunction(double amplitude, double mean, double sigma)
	{
		this.max = amplitude;
		this.mean = mean;
		this.sigma = sigma;
	}
	public LandauFunction(double xmin, double xmax, double ymin, double ymax)
	{
		this.max = ymin + (ymax - ymin)*.8;
		this.mean = (xmin + xmax)/2;
		this.sigma = (xmax - xmin)/6;
	}
	public double valueAt(double x)
	{

                 double yy = ( x - mean ) / sigma;
                 double tt = Math.exp ( -0.5 * ( yy + Math.exp ( -1.0 * yy ) ) )
                     / Math.sqrt ( 2.0 * Math.PI );
                 return max * tt;

		// return max * Math.exp(-Math.pow((x-mean)/sigma,2)/2);
	}
	public double valueAt(double x, double[] a)
	{

                double yy = ( x - a[1] ) / a[2];
                double tt = Math.exp ( -0.5 * ( yy + Math.exp ( -1.0 * yy ) ) )
                     / Math.sqrt ( 2.0 * Math.PI );
                return a[0] * tt;

	}
	public String[] getParameterNames()
	{
		final String[] result = { "amplitude","mean","sigma" };
		return result;
	}
	public double[] getParameterValues()
	{
		final double[] result = { max, mean, sigma };
		return result;
	}
	public void setParameter(int index, double value)
	{ 
		if      (index == 0) max = value;
		else if (index == 1) mean = value;
		else if (index == 2) sigma = value;
		else throw new IllegalArgumentException("Invalid index to setParameter");

		clearFit();
		setChanged();
	}
	public void setFit(Fitter fit, double[] value)
	{ 
		if (value.length != 3) 
			throw new IllegalArgumentException("Argument to setParameters is of wrong length");

		max = value[0];
		mean = value[1];
		sigma = value[2];

		setFit(fit);
		setChanged();
	}
	public String getTitle()
	{
		return "Landau";
	}
	public Statistics getStatistics()
	{
		return this;
	}
	public Handle[] getHandles(double xLow, double xHigh, double yLow, double yHigh)
	{
		Handle[] result = new Handle[3];
		result[0] = new Handle()
		{
			public void moveTo(double x, double y)
			{
				mean = x;
				max = y;
				clearFit();
				setChanged();
			}
			public double getX()
			{
				return mean;
			}
			public double getY()
			{
				return max;
			}
		};
		result[1] = new Handle()
		{
			public void moveTo(double x, double y)
			{
				sigma = (mean - x)/fwhm;
				clearFit();
				setChanged();
			}
			public double getY()
			{
				return max/2;
			}
			public double getX()
			{
				return mean-sigma*fwhm;
			}
		};
		result[2] = new Handle()
		{
			public void moveTo(double x, double y)
			{
				sigma = (x - mean)/fwhm;
				clearFit();
				setChanged();
			}
			public double getY()
			{
				return max/2;
			}
			public double getX()
			{
				return mean+sigma*fwhm;
			}
		};
		return result;
	}
	private final static double fwhm = 2.354/2;
	private double max;
	private double mean;
	private double sigma;
}