Fityk
Fityk is an open-source program for nonlinear fitting of analytical models to data. It has a graphical user interface and supports curve fitting and data visualization. Fityk supports many common fitting functions and can handle large data sets.
curve-fitting
data-visualization
nonlinear-regression
Fityk: Nonlinear Fitting Software for Curve Analysis
Open-source program for nonlinear fitting, curve fitting, and data visualization - find the best fit with Fityk
What is Fityk?
Fityk is a powerful and versatile open-source software for nonlinear curve fitting and data analysis. It offers a graphical user interface along with a command line interface and Python bindings. Some key features of Fityk include:
- Supports a wide range of analytical fitting functions including peaks, baselines, custom models defined by formulas
- Advanced fitting algorithms like Levenberg-Marquardt, Simplex, Genetic
- Handles large data sets with 100,000+ points efficiently
- Data visualization features like zooming, panning, error bars
- Automation capabilities via command line interface and scripting in languages like Python
- Cross-platform support for Linux, Windows and macOS
- Custom model plugin support to extend functionality
- Export results and plots to various formats
Fityk can analyze and model data from many domains like spectroscopy, chromatography, physics experiments among others. The easy-to-use GUI combined with advanced fitting capabilities make it useful for both beginners and experts. The open-source nature provides transparency and community support.
Fityk Features
Features
- Nonlinear curve fitting
- Built-in fitting functions
- Custom user-defined functions
- Interactive graphical user interface
- Data visualization
- Command line interface
- Scripting language for automation
- Multi-threading for faster computation
- Data analysis tools
Pricing
- Open Source
Pros
Free and open source
Cross-platform availability
User-friendly GUI
Powerful fitting capabilities
Customizable and extensible
Efficient computation engine
Can handle large data sets
Great community support
Cons
Steep learning curve
Limited documentation
Not very beginner friendly
GUI needs more polish
Lacks some advanced analysis features
Official Links
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