org.freehep.math.minuit
Class MnScan
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- org.freehep.math.minuit.MnApplication
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- org.freehep.math.minuit.MnScan
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public class MnScan extends MnApplication
MnScan scans the value of the user function by varying one parameter. It is sometimes useful for debugging the user function or finding a reasonable starting point.
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Constructor Summary
Constructors Constructor and Description MnScan(FCNBase fcn, double[] par, double[] err)construct from FCNBase + double[] for parameters and errors with default strategyMnScan(FCNBase fcn, double[] par, double[] err, int stra)construct from FCNBase + double[] for parameters and errorsMnScan(FCNBase fcn, double[] par, MnUserCovariance cov)construct from FCNBase + double[] for parameters and MnUserCovariance with default strategyMnScan(FCNBase fcn, double[] par, MnUserCovariance cov, int stra)construct from FCNBase + double[] for parameters and MnUserCovarianceMnScan(FCNBase fcn, MnUserParameters par)construct from FCNBase + MnUserParameters with default strategyMnScan(FCNBase fcn, MnUserParameters par, int stra)construct from FCNBase + MnUserParametersMnScan(FCNBase fcn, MnUserParameters par, MnUserCovariance cov)construct from FCNBase + MnUserParameters + MnUserCovariance with default strategyMnScan(FCNBase fcn, MnUserParameters par, MnUserCovariance cov, int stra)construct from FCNBase + MnUserParameters + MnUserCovarianceMnScan(FCNBase fcn, MnUserParameterState par, MnStrategy str)construct from FCNBase + MnUserParameterState + MnStrategy
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method and Description java.util.List<Point>scan(int par)java.util.List<Point>scan(int par, int maxsteps)java.util.List<Point>scan(int par, int maxsteps, double low, double high)Scans the value of the user function by varying parameter number par, leaving all other parameters fixed at the current value.-
Methods inherited from class org.freehep.math.minuit.MnApplication
add, add, add, checkAnalyticalDerivatives, covariance, error, error, errorDef, errors, fcnbase, fix, fix, index, minimize, minimize, minimize, name, numOfCalls, parameters, params, precision, release, release, removeLimits, removeLimits, setCheckAnalyticalDerivatives, setError, setError, setErrorDef, setLimits, setLimits, setPrecision, setUseAnalyticalDerivatives, setValue, setValue, state, strategy, useAnalyticalDerivaties, value, value, variableParameters
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Constructor Detail
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MnScan
public MnScan(FCNBase fcn, double[] par, double[] err)
construct from FCNBase + double[] for parameters and errors with default strategy
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MnScan
public MnScan(FCNBase fcn, double[] par, double[] err, int stra)
construct from FCNBase + double[] for parameters and errors
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MnScan
public MnScan(FCNBase fcn, double[] par, MnUserCovariance cov)
construct from FCNBase + double[] for parameters and MnUserCovariance with default strategy
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MnScan
public MnScan(FCNBase fcn, double[] par, MnUserCovariance cov, int stra)
construct from FCNBase + double[] for parameters and MnUserCovariance
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MnScan
public MnScan(FCNBase fcn, MnUserParameters par)
construct from FCNBase + MnUserParameters with default strategy
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MnScan
public MnScan(FCNBase fcn, MnUserParameters par, int stra)
construct from FCNBase + MnUserParameters
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MnScan
public MnScan(FCNBase fcn, MnUserParameters par, MnUserCovariance cov)
construct from FCNBase + MnUserParameters + MnUserCovariance with default strategy
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MnScan
public MnScan(FCNBase fcn, MnUserParameters par, MnUserCovariance cov, int stra)
construct from FCNBase + MnUserParameters + MnUserCovariance
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MnScan
public MnScan(FCNBase fcn, MnUserParameterState par, MnStrategy str)
construct from FCNBase + MnUserParameterState + MnStrategy
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Method Detail
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scan
public java.util.List<Point> scan(int par)
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scan
public java.util.List<Point> scan(int par, int maxsteps)
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scan
public java.util.List<Point> scan(int par, int maxsteps, double low, double high)
Scans the value of the user function by varying parameter number par, leaving all other parameters fixed at the current value. If par is not specified, all variable parameters are scanned in sequence. The number of points npoints in the scan is 40 by default, and cannot exceed 100. The range of the scan is by default 2 standard deviations on each side of the current best value, but can be specified as from low to high. After each scan, if a new minimum is found, the best parameter values are retained as start values for future scans or minimizations. The curve resulting from each scan can be plotted on the output terminal using MnPlot in order to show the approximate behaviour of the function.
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