hep.aida.ref.optimizer.fminuit
Class MinuitCommands

java.lang.Object
  org.freehep.math.fminuit.FMinuitCommands
      hep.aida.ref.optimizer.fminuit.MinuitCommands

public class MinuitCommands
extends org.freehep.math.fminuit.FMinuitCommands

Minuit commands.

Author:

Tony Johnson, Victor Serbo, Max Turri, Mark Donszelmann

Field Summary

protected static int	DETAILED_OUTPUT
protected static int	MATRIX_DIAGONAL_APPROX
protected static int	MATRIX_FULL_ACCURATE
protected static int	MATRIX_FULL_FORCED_POS
protected static int	MATRIX_NOT_CALCULATED The possible status of the covariance matrix
protected static int	MAXIMAL_OUTPUT
protected static int	MIGRAD_MIN
protected static int	MINIMAL_OUTPUT
protected static int	MINIMIZE_MIN
protected static int	NO_OUTPUT The printout levels for the minimizer output are the following:
protected static int	NORMAL_OUTPUT
protected static int	SIMPLEX_MIN The different types of minimization.

Constructor Summary

protected

MinuitCommands(MinuitOptimizer theOptimizer) Default constructor.

Method Summary

protected double[][]	calculateContour(String parName1, String parName2) Calculate the Error Matrix in the current configuration.
protected double[][]	calculateContour(String parName1, String parName2, int nPoints)
protected double[][]	calculateContour(String parName1, String parName2, int nPoints, double nSigmas)
protected void	fixVariable(String varName)
protected double[][]	getCovarianceMatrix()
protected double	getErrorDef() Get the value of UP, the errorDefinition.
protected int	getNVariables() Get the number of (released) variables in the minimization.
protected int	getStatus() Get the status of the fit.
protected void	loadAndInitialize()
protected void	minos() Perform the Minos error analysis on the specified variables.
protected void	optimize(String method, int maxIterations, double tolerance) Minimize the function.
protected void	resetMinuit() Reset Minuit.
protected void	setErrorDef(int errDef) Set the Error Definition, the Minuit UP value.
protected void	setErrorDefinition(double errDef)
protected void	setFunction(hep.aida.IFunction function, MinuitOptimizer optimizer) Set the function to be minimized.
protected void	setPrecision(double precision) Informs Minuit on the machin precision.
void	setPrintLevel(int printLevel)
protected void	setStrategy(int strategy) Set the strategy to be used in calculating the first and second derivative and in certain optimization methods.
protected void	setUseFunctionGradient(boolean useFunctionGradient) Tell Minuit if the derivatives provided by the function are to be used.
protected void	updateFunction(MinuitOptimizer optimizer)

Methods inherited from class org.freehep.math.fminuit.FMinuitCommands

evaluateDerivatives, evaluateFunction, finalizeFunction, initializeFunction, jmncont, jmnemat, jmnerrs, jmnexcm, jmninit, jmnparm, jmnpout, jmnseti, jmnstat, loadAndInitialize

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

MATRIX_NOT_CALCULATED

protected static final int MATRIX_NOT_CALCULATED

The possible status of the covariance matrix

See Also:

Constant Field Values

MATRIX_DIAGONAL_APPROX

protected static final int MATRIX_DIAGONAL_APPROX

See Also:

Constant Field Values

MATRIX_FULL_FORCED_POS

protected static final int MATRIX_FULL_FORCED_POS

See Also:

Constant Field Values

MATRIX_FULL_ACCURATE

protected static final int MATRIX_FULL_ACCURATE

See Also:

Constant Field Values

NO_OUTPUT

protected static final int NO_OUTPUT

The printout levels for the minimizer output are the following:

See Also:

Constant Field Values

MINIMAL_OUTPUT

protected static final int MINIMAL_OUTPUT

See Also:

Constant Field Values

NORMAL_OUTPUT

protected static final int NORMAL_OUTPUT

See Also:

Constant Field Values

DETAILED_OUTPUT

protected static final int DETAILED_OUTPUT

See Also:

Constant Field Values

MAXIMAL_OUTPUT

protected static final int MAXIMAL_OUTPUT

See Also:

Constant Field Values

SIMPLEX_MIN

protected static final int SIMPLEX_MIN

The different types of minimization.

See Also:

Constant Field Values

MIGRAD_MIN

protected static final int MIGRAD_MIN

See Also:

Constant Field Values

MINIMIZE_MIN

protected static final int MINIMIZE_MIN

See Also:

Constant Field Values

Constructor Detail

MinuitCommands

protected MinuitCommands(MinuitOptimizer theOptimizer)

Default constructor.

Method Detail

loadAndInitialize

protected void loadAndInitialize()

setPrintLevel

public void setPrintLevel(int printLevel)
                   throws IllegalArgumentException

Throws:

IllegalArgumentException

resetMinuit

protected void resetMinuit()

Reset Minuit.

setFunction

protected void setFunction(hep.aida.IFunction function,
                           MinuitOptimizer optimizer)

Set the function to be minimized. When setting a new function the minimizer is cleared of previous information.

Parameters:

function - The function to be minimized.

updateFunction

protected void updateFunction(MinuitOptimizer optimizer)

fixVariable

protected void fixVariable(String varName)

getStatus

protected int getStatus()

Get the status of the fit.

Returns:

The status of the fit based on the current status of the covariance matrix.

getNVariables

protected int getNVariables()

Get the number of (released) variables in the minimization.

Returns:

The number of variables in the minimization.

getErrorDef

protected double getErrorDef()

Get the value of UP, the errorDefinition.

Returns:

The number of UP.

setErrorDef

protected void setErrorDef(int errDef)

Set the Error Definition, the Minuit UP value. Minuit defines variable's errors as the change in the variable's value required to change the function value by the Error Definition (UP). For chiSquared fits UP=1, for negative log likelihood UP=0.5.

Parameters:

errDef - The new value for the Error Definition

setErrorDefinition

protected void setErrorDefinition(double errDef)

setUseFunctionGradient

protected void setUseFunctionGradient(boolean useFunctionGradient)

Tell Minuit if the derivatives provided by the function are to be used.

setStrategy

protected void setStrategy(int strategy)

Set the strategy to be used in calculating the first and second derivative and in certain optimization methods. It determines the reliability of the calculation as it changes the number of allowed function calls.

setPrecision

protected void setPrecision(double precision)

Informs Minuit on the machin precision.

optimize

protected void optimize(String method,
                        int maxIterations,
                        double tolerance)

Minimize the function.

Parameters:

method - The optimization method. It can be: - SIMPLEX performs a minimixation using the simplex method of Nedler and Mead. The minimization will stop after maxIter call have been performed or when the EDM is less than the tolerance (default is 0.1*UP) - MIGRAD The default minimization using the Migrad method. maxIter is the (optional) maximum amount of iterations; when this is reached the minimization will stopped even if it did not converge. The minimization converges when the EDM is less than 0.001*tolerance*UP. - MINIMIZE It starts by using the MIGRAD minimization; it this does not converge it switches to the SIMPLEX method. - IMPROVE If a previous minimization has converged and the function is in and optimal solution, it searches for additional global optimal points. The calculation will be stopped after maxIterations calls. - SEEK Causes a Monte Carlo minimization of the function, by choosing uniformely random values of the variables in an hypercube centered in the current variable values. The size of the hypercube is specified by the value of tolerance.

maxIterations - The maximum amount of allowed iterations.

tolerance - The tolerance for the minimization.

minos

protected void minos()

Perform the Minos error analysis on the specified variables. param maxIter The maximum number of iterations allowed. param vars The list of variables whose errors are to be recalculated. return true if the command was successfull; false otherwise. Check the status of the minimization to know what went wrong.

calculateContour

protected double[][] calculateContour(String parName1,
                                      String parName2)

Calculate the Error Matrix in the current configuration.

Returns:

true if the error matrix was calculated successfully. false otherwise.

calculateContour

protected double[][] calculateContour(String parName1,
                                      String parName2,
                                      int nPoints)

calculateContour

protected double[][] calculateContour(String parName1,
                                      String parName2,
                                      int nPoints,
                                      double nSigmas)

getCovarianceMatrix

protected double[][] getCovarianceMatrix()