The tool allows users to exclude inactivate points from fitting operations and work with several datasets simultaneously. Moreover, Fityk enables users to perform 'Power Diffraction Analysis' using 'X-Ray' or 'Neutron' radiation and various wavelengths ('Cu', 'Ag', 'Mo','Fe', etc). The utility allows users to execute a script, use data point 'Transformations' or adjust the preferred 'Functions', with the possibility of choosing between a wide range of options, such as 'Quadratic', 'Cubic', 'Gaussian', 'Lorentzian', 'EMG', 'Polyline', 'ExpDecay', 'Voigt', 'Spline', 'DoniachSunjic' and many more, while also letting users create their own. Users can work in 'Data Range', 'Add Peak' or 'Baseline' mode, according to their needs. The interface of Fityk is quite easy to understand, offering a toolbar for quick access to the most commonly used functions, as well as a menu bar, a main plot and a right-size panel where certain values can be edited.įityk provides users with several fitting methods, namely 'Levenberg – Marquardt', 'Nelder - Mead Simplex' and 'Genetic Algorithm', which can be of use in multiple analysis. These require a bit of documentation before being able to work with them properly, as such it is less approachable for novice users, though the more advanced can certainly appreciate its complexity. The program is fairly simple to work with, requiring minimal levels of knowledge or experience with similar tools, yet it features a set of rather complex functions. It is aimed at experimental data resulted from a variety of domains, like chromatography, spectroscopy, crystallography and many others. You might want to explore the documentation to check if this package might be of any value to you.Fityk is an advanced and reliable software solution whose main purpose is to assist users in fitting data to nonlinear functions. The site linked above also includes access to a user-manual, Wiki, a journal, and FAQ's, (and I believe there is also support available via a user's forum). It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. ) and graphical techniques, and is highly extensible.One of R's strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed.Īt the link provided above, you can access and download free software designed especially for statistical computing and data anaylysis. provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering. R is a language and environment for statistical computing and graphics. If you have an on-going need for the modeling and analysis of data, you might want to check out This option doesn't presume much in the way of users' knowledge relating to statistical anaylysis. You might also want to take a look at scikits-learn (another python package), Īccessible via the link, and free to download, with access to documentation. You will have to install python, numpy and scipy. It's free and available on Windows, Linux and OS X. The 'splines' library for R can be used for this.Īlso, let me give an honorable mention to python. Here, we get around the lack of knowledge about the overall functional form, by modelling the curve locally. Īnother idea is doing a spline regression. It takes a bit of computational time, but it will be attempting to build a formula for your data. The approach is based on genetic algorithms which do a symbolic regression. It uses artifical intelligence to guess what formula might be generating your data. If I understand your question correctly, you want to fit a function to your data, but you don't have any idea what family of functions to use.
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