These tutorials illustrate the main fitting features. Their names are related to the aspect which is treated in the code.
In the tables below the tutorials are grouped according to what is fitted, e.g histograms and graphs, and the dimensionality. In addition, the tables include a column with the fit funcions used in the tutorials (e.g gaus, expo or user defined functions), and how they are combined (e.g sum or convolution).
Explore the examples below or go to the Fitting user guide. A list of all the Fit tutorials can be found here.
| Tutorial | Description | Fit functions | |
|---|---|---|---|
| fit1.C | Simple fitting example (1-d histogram with an interpreted function). | user defined | |
| fit1.py | Fit example. | ||
| myfit.C | Get in memory an histogram from a root file and fit a user defined function. | user defined | |
| vectorizedFit.C | Tutorial for creating a Vectorized TF1 function using a formula expression and use it for fitting an histogram. | gaus | |
| ErrorIntegral.C | Estimate the error in the integral of a fitted function taking into account the errors in the parameters resulting from the fit. | user defined | |
| TestBinomial.C | Perform a fit to a set of data with binomial errors like those derived from the division of two histograms. | user defined | |
| ConfidenceIntervals.C | Illustrates TVirtualFitter::GetConfidenceIntervals. This method computes confidence intervals for the fitted function. | linear, gaus, user defined | |
| minuit2GausFit.C | Perform fits with different configurations using Minuit2. | gaus | |
| fitcont.C | Example illustrating how to draw the n-sigma contour of a Minuit fit. | gaus | |
| combinedFit.C | combinedFit.py | Combined (simultaneous) fit of two histogram with separate functions and some common parameters. | expo + gaus |
| fitNormSum.C | fitNormSum.py | Tutorial for normalized sum of two functions Here: a background exponential and a crystalball function. | expo + crystalball |
| FittingDemo.C | Example for fitting signal/background. | quadratic + Lorenzian | |
| fithist.C | Example of fit where the model is histogram + function. | histogram + function | |
| fitExclude.C | Illustrates how to fit excluding points in a given range. | mulitple linear | |
| multifit.C | multifit.py | Fitting multiple functions to different ranges of a 1-D histogram. | multiple gaus |
| fitConvolution.C | fitConvolution.py | Tutorial for convolution of two functions. | expo * gaus |
| langaus.C | Convoluted Landau and Gaussian Fitting Function (using ROOT's Landau and Gauss functions). | Langdau * gaus | |
| minuit2FitBench.C | Demonstrate performance and usage of Minuit2 and Fumili2 for monodimensional fits. | Langdau * gaus | |
| Tutorial | Description | Fit functions |
|---|---|---|
| fit2.C | Fitting a 2-D histogram. | user defined |
| fit2a.C | Fitting a 2-D histogram (a variant). | user defined |
| fit2d.C | Example illustrating how to fit a 2-d histogram of type y=f(x). | pol1 |
| TwoHistoFit2D.C | Example to fit two histograms at the same time. | user defined |
| fit2dHist.C | Example to fit two histograms at the same time via the Fitter class. | user defined |
| fitslicesy.C | Illustrates how to use the TH1::FitSlicesY function. It uses the TH2F histogram generated in macro hsimple.C | |
| minuit2FitBench2D.C | Minuit2 fit 2D benchmark. | gaus |
| Tutorial | Description | Fit functions |
|---|---|---|
| fitLinear.C | Example of fitting with a linear function, using TLinearFitter. This example is for a TGraphErrors, but it can also be used when fitting a histogram, a TGraph2D or a TMultiGraph. | user defined |
| fitLinearRobust.C | This tutorial shows how the least trimmed squares regression, included in the TLinearFitter class, can be used for fitting in cases when the data contains outliers. | qubic |
| fitMultiGraph.C | Fitting a parabola to a multigraph of 3 partly overlapping graphs with different errors. | quadratic |
| ConfidenceIntervals.C | Illustrates TVirtualFitter::GetConfidenceIntervals. This method computes confidence intervals for the fitted function. | linear, gaus, user defined |
| Tutorial | Description | Fit functions |
|---|---|---|
| graph2dfit.C | Fitting a TGraph2D. | user defined |
| line3Dfit.C | Fitting of a TGraph2D with a 3D straight line. | linear |
| fitCircle.C | Generate points distributed with some errors around a circle. Fit a circle through the points and draw. | circle |
| ConfidenceIntervals.C | Illustrates TVirtualFitter::GetConfidenceIntervals. This method computes confidence intervals for the fitted function. | linear, gaus, user defined |
| Tutorial | Description | Fit functions |
|---|---|---|
| exampleFit3D.C | Example of fitting a 3D function. Typical multidimensional parametric regression where the predictor depends on 3 variables. | user defined |
| fitLinear2.C | Fit a 5d hyperplane by n points, using the linear fitter directly. | linear |
| multidimfit.C | Multi-Dimensional Parametrisation and Fitting. | user defined |
| Ifit.C | Example of a program to fit non-equidistant data points. | user defined |
Files | |
| file | combinedFit.C |
  Combined (simultaneous) fit of two histogram with separate functions and some common parameters | |
| file | combinedFit.py |
| Combined (simultaneous) fit of two histogram with separate functions and some common parameters | |
| file | ConfidenceIntervals.C |
| Illustrates TVirtualFitter::GetConfidenceIntervals This method computes confidence intervals for the fitted function | |
| file | ErrorIntegral.C |
| Estimate the error in the integral of a fitted function taking into account the errors in the parameters resulting from the fit. | |
| file | exampleFit3D.C |
| example of fitting a 3D function Typical multidimensional parametric regression where the predictor depends on 3 variables | |
| file | fit1.C |
| Simple fitting example (1-d histogram with an interpreted function) | |
| file | fit1.py |
| Fit example. | |
| file | fit2.C |
| Fitting a 2-D histogram This tutorial illustrates : | |
| file | fit2a.C |
| Fitting a 2-D histogram (a variant) This tutorial illustrates : | |
| file | fit2d.C |
| Example illustrating how to fit a 2-d histogram of type y=f(x) | |
| file | fit2dHist.C |
| Example to fit two histograms at the same time via the Fitter class. | |
| file | fitCircle.C |
| Generate points distributed with some errors around a circle Fit a circle through the points and draw To run the script, do, eg | |
| file | fitcont.C |
| Example illustrating how to draw the n-sigma contour of a Minuit fit. | |
| file | fitConvolution.C |
| Tutorial for convolution of two functions | |
| file | fitConvolution.py |
| Tutorial for convolution of two functions | |
| file | fitExclude.C |
| Illustrates how to fit excluding points in a given range. | |
| file | fithist.C |
| Example of fit where the model is histogram + function | |
| file | fitLinear.C |
| Example of fitting with a linear function, using TLinearFitter This example is for a TGraphErrors, but it can also be used when fitting a histogram, a TGraph2D or a TMultiGraph | |
| file | fitLinear2.C |
| Fit a 5d hyperplane by n points, using the linear fitter directly | |
| file | fitLinearRobust.C |
| This tutorial shows how the least trimmed squares regression, included in the TLinearFitter class, can be used for fitting in cases when the data contains outliers. | |
| file | fitMultiGraph.C |
| fitting a parabola to a multigraph of 3 partly overlapping graphs with different errors | |
| file | fitNormSum.C |
| Tutorial for normalized sum of two functions Here: a background exponential and a crystalball function Parameters can be set: | |
| file | fitNormSum.py |
| Tutorial for normalized sum of two functions Here: a background exponential and a crystalball function Parameters can be set: | |
| file | fitpanel_playback.C |
| This file will test all the transient frames (aka Dialog windows) displayed in the fitpanel, as the rest of the functionality is tried automatically with the UnitTest.C unit. | |
| file | fitslicesy.C |
| Illustrates how to use the TH1::FitSlicesY function It uses the TH2F histogram generated in macro hsimple.C It invokes FitSlicesY and draw the fitted "mean" and "sigma" in 2 sepate pads. | |
| file | FittingDemo.C |
| Example for fitting signal/background. | |
| file | graph2dfit.C |
| Fitting a TGraph2D | |
| file | Ifit.C |
| Example of a program to fit non-equidistant data points | |
| file | langaus.C |
| Convoluted Landau and Gaussian Fitting Function (using ROOT's Landau and Gauss functions) | |
| file | line3Dfit.C |
| Fitting of a TGraph2D with a 3D straight line | |
| file | minuit2FitBench.C |
| Demonstrate performance and usage of Minuit2 and Fumili2 for monodimensional fits. | |
| file | minuit2FitBench2D.C |
| Minuit2 fit 2D benchmark. | |
| file | minuit2GausFit.C |
| Perform fits with different configurations using Minuit2 | |
| file | multidimfit.C |
| Multi-Dimensional Parametrisation and Fitting | |
| file | multifit.C |
| Fitting multiple functions to different ranges of a 1-D histogram Example showing how to fit in a sub-range of an histogram A histogram is created and filled with the bin contents and errors defined in the table below. | |
| file | multifit.py |
| Fitting multiple functions to different ranges of a 1-D histogram Example showing how to fit in a sub-range of an histogram A histogram is created and filled with the bin contents and errors defined in the table below. | |
| file | myfit.C |
| Get in memory an histogram from a root file and fit a user defined function. | |
| file | TestBinomial.C |
| Perform a fit to a set of data with binomial errors like those derived from the division of two histograms. | |
| file | TwoHistoFit2D.C |
| Example to fit two histograms at the same time. | |
| file | vectorizedFit.C |
| Tutorial for creating a Vectorized TF1 function using a formula expression and use it for fitting an histogram | |
