net.grelf

## Interface Fitter

• All Known Implementing Classes:
Fitter_

`public interface Fitter`
Fits data to particular curves.
• ### Method Summary

All Methods
Modifier and Type Method and Description
`double` `getC()`
Get the intercept of the fitted straight line, as in y = Mx + c
`double` `getChiSq()`
Get the chi-squared fitting factor.
`double` `getM()`
Get the slope of the fitted straight line, as in y = Mx + C
`double` `getQ()`
Get quality factor Q.
`double` `getSigmaC()`
Get the standard deviation of the intercept of the fitted line.
`double` `getSigmaM()`
Get the standard deviation of the slope of the fitted line.
`boolean` `isFitted()`
`void` ```leastSquaresStraightLine(double[] x, double[] y, double[] sigmaY)```
Fit a straight line y = Mx + C to the given data points by the least squares method.
`double` `x(double y)`
Calculate the inverse: x for given y, using the fitted parameters, x = (y - C) / M.
`double` `y(double x)`
Calculate y for given x, using the fitted parameters, y = Mx + C.
• ### Method Detail

• #### isFitted

`boolean isFitted()`
• #### leastSquaresStraightLine

```void leastSquaresStraightLine(double[] x,
double[] y,
double[] sigmaY)```
Fit a straight line y = Mx + C to the given data points by the least squares method. The two arrays must be of the same length and that is the number of data points. After fitting the results are obtainable via the other methods of this class. The third parameter is a further array of the same length containing kown standard deviations of the measured values y, as weighting factors. If sigmaY is null all points are given equal weight.
• #### getM

`double getM()`
Get the slope of the fitted straight line, as in y = Mx + C
• #### getC

`double getC()`
Get the intercept of the fitted straight line, as in y = Mx + c
• #### getSigmaM

`double getSigmaM()`
Get the standard deviation of the slope of the fitted line.
• #### getSigmaC

`double getSigmaC()`
Get the standard deviation of the intercept of the fitted line.
• #### getChiSq

`double getChiSq()`
Get the chi-squared fitting factor.
• #### getQ

`double getQ()`
Get quality factor Q.
• #### y

`double y(double x)`
Calculate y for given x, using the fitted parameters, y = Mx + C. Returns 0.0 if not fitted.
• #### x

`double x(double y)`
Calculate the inverse: x for given y, using the fitted parameters, x = (y - C) / M. Returns 0.0 if not fitted.