CurveFitter (ImageJ 1.51e API)

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ij.measure
Class CurveFitter

java.lang.Object
  ij.measure.CurveFitter

All Implemented Interfaces:: UserFunction

public class CurveFitter
extends Object
implements UserFunction
extends Object
implements UserFunction

Curve fitting class based on the Simplex method in the Minimizer class Notes on fitting polynomial functions: (i) The range of x values should not be too far from 0, especially for higher-order polynomials. For polynomials of 4th order, the average x value should fulfill |xMean| < 2*(xMax-xMin). For polynomials of 5th order or higher, the x range should encompass x=0; and for 7th and 8th order it is desirable to have x=0 near the center of the x range. (ii) In contrast to some fitting algorithms using the normal equations and matrix inversion, the simplex algorithm used here can cope with parameters having very different orders of magnitude, as long as the coefficients of the polynomial are within a reasonable range (say, 1e-80 to 1e80). Thus, it is usually not needed to scale the x values, even for high-order polynomials. Version history: 2008-01-21: Modified to do Gaussian fitting by Stefan Woerz (s.woerz at dkfz.de). 2012-01-30: Modified for external Minimizer class and UserFunction fit by Michael Schmid. - Also fixed incorrect equation string for 'Gamma Variate' & 'Rodbard (NIH Image)', - Added 'Inverse Rodbard', 'Exponential (linear regression)', 'Power (linear regression)' functions and polynomials of order 5-8. Added 'nicely' sorted list of types. - Added absolute error for minimizer to avoid endless minimization if exact fit is possible. - Added 'initialParamVariations' (order of magnitude if parameter variations) - this is important for safer and better convergence. - Linear regression for up to 2 linear parameters, reduces the number of parameters handled by the simplex Minimizer and improves convergence. These parameters can be an offset and either a linear slope or a factor that the full function is multiplied with. 2012-10-07: added GAUSSIAN_NOOFFSET fit type 2012-11-20: Bugfix: exception on Gaussian&Rodbard with initial params, bad initial params for Gaussian 2013-09-24: Added "Exponential Recovery (no offset)" and "Chapman-Richards" (3-parameter) fit types. 2013-10-11: bugfixes, added setStatusAndEsc to show iterations and enable abort by ESC 2015-03-26: bugfix, did not use linear regression for RODBARD

Field Summary
`static int`	`CHAPMAN` Constants for the built-in fit functions
`static int`	`EXP_RECOVERY` Constants for the built-in fit functions
`static int`	`EXP_RECOVERY_NOOFFSET` Constants for the built-in fit functions
`static int`	`EXP_REGRESSION` Constants for the built-in fit functions
`static int`	`EXP_WITH_OFFSET` Constants for the built-in fit functions
`static int`	`EXPONENTIAL` Constants for the built-in fit functions
`static String[]`	`fitList` Names of the built-in fit functions
`static String[]`	`fList` Equations of the built-in fit functions
`static int`	`GAMMA_VARIATE` Constants for the built-in fit functions
`static int`	`GAUSSIAN` Constants for the built-in fit functions
`static int`	`GAUSSIAN_NOOFFSET` Constants for the built-in fit functions
`static int`	`INV_RODBARD` Constants for the built-in fit functions
`static int`	`IterFactor` Deprecated. now in the Minimizer class (since ImageJ 1.46f). (probably of not much value for anyone anyhow?)
`static int`	`LOG` Constants for the built-in fit functions
`static int`	`LOG2` Constants for the built-in fit functions
`static int`	`POLY2` Constants for the built-in fit functions
`static int`	`POLY3` Constants for the built-in fit functions
`static int`	`POLY4` Constants for the built-in fit functions
`static int`	`POLY5` Constants for the built-in fit functions
`static int`	`POLY6` Constants for the built-in fit functions
`static int`	`POLY7` Constants for the built-in fit functions
`static int`	`POLY8` Constants for the built-in fit functions
`static int`	`POWER` Constants for the built-in fit functions
`static int`	`POWER_REGRESSION` Constants for the built-in fit functions
`static int`	`RODBARD` Constants for the built-in fit functions
`static int`	`RODBARD2` Constants for the built-in fit functions
`static int[]`	`sortedTypes` Nicer sequence of the built-in function types
`static int`	`STRAIGHT_LINE` Constants for the built-in fit functions

Constructor Summary
`CurveFitter(double[] xData, double[] yData)` Construct a new CurveFitter.

Method Summary
`int`	`doCustomFit(String equation, double[] initialParams, boolean showSettings)` Fit a function defined as a macro String like "y = a + bx + cx*x".
`void`	`doCustomFit(UserFunction userFunction, int numParams, String formula, double[] initialParams, double[] initialParamVariations, boolean showSettings)` Fit a function defined in a user plugin implementing the UserFunction interface Use getStatus() and/or getStatusString() to see whether fitting was (probably) successful and getParams() to access the result.
`void`	`doFit(int fitType)` Perform curve fitting with one of the built-in functions doFit(fitType) does the fit quietly Use getStatus() and/or getStatusString() to see whether fitting was (probably) successful and getParams() to access the result.
`void`	`doFit(int fitType, boolean showSettings)` Perform curve fitting with one of the built-in functions doFit(fitType, true) pops up a dialog allowing the user to set the initial fit parameters and various numbers controlling the Minimizer Use getStatus() and/or getStatusString() to see whether fitting was (probably) successful and getParams() to access the result.
`double`	`f(double x)` Returns the formula value for parameters 'p' at 'x'.
`double`	`f(double[] p, double x)` Returns the formula value for parameters 'p' at 'x'.
`static double`	`f(int fitType, double[] p, double x)` Returns value of built-in 'fitType' formula value for parameters "p" at "x"
`int`	`getFit()` returns the code of the fit type of the fit performed
`static int`	`getFitCode(String fitName)` Returns the code for a fit with given name as defined in fitList, or -1 if not found
`double`	`getFitGoodness()` Get a measure of "goodness of fit" where 1.0 is best.
`String`	`getFormula()` returns a String with the formula of the fit function used
`int`	`getIterations()` Get number of iterations performed.
`static int`	`getMax(double[] array)` Gets index of highest value in an array.
`int`	`getMaxIterations()` Get maximum number of iterations allowed (sum of iteration count for all restarts)
`Minimizer`	`getMinimizer()` Returns a reference to the Minimizer used, for accessing Minimizer methods directly.
`String`	`getName()` returns the name of the fit function of the fit performed
`int`	`getNumParams()` Get number of parameters for current fit formula Do not use before 'doFit', because the fit function would be undefined.
`double[]`	`getParams()` Get the result of fitting, i.e.
`double[]`	`getResiduals()` Returns residuals array, i.e., differences between data and curve.
`int`	`getRestarts()` Get maximum number of simplex restarts to do.
`String`	`getResultString()` Get a string with detailed description of the curve fitting results (several lines, including the fit parameters).
`double`	`getRSquared()` Returns R^2, where 1.0 is best.
`double`	`getSD()` Returns the standard deviation of the residuals.
`static String[]`	`getSortedFitList()` Returns an array of fit names with nicer sorting
`int`	`getStatus()`
`String`	`getStatusString()` Get a short text with a short description of the status.
`double`	`getSumResidualsSqr()`
`double[]`	`getXPoints()` returns the array with the x data
`double[]`	`getYPoints()` returns the array with the y data
`void`	`setInitialParameters(double[] initialParams)` Sets the initial parameters, which override the default initial parameters.
`void`	`setMaxError(double maxRelError)` Set the maximum error.
`void`	`setMaxIterations(int maxIter)` Set maximum number of iterations allowed (sum of iteration count for all restarts)
`void`	`setOffsetMultiplySlopeParams(int offsetParam, int multiplyParam, int slopeParam)` For improved fitting performance when using a custom fit formula, one may specify parameters that can be calculated directly by linear regression.
`void`	`setRestarts(int maxRestarts)` Set maximum number of simplex restarts to do.
`void`	`setStatusAndEsc(String ijStatusString, boolean checkEscape)` Create output on the number of iterations in the ImageJ Status line, e.g.
`double`	`userFunction(double[] params, double dummy)` This function is called by the Minimizer and calculates the sum of squared residuals for given parameters.

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Field Detail