FitED is a new software package offering interactive and automated nonlinear fitting of conventional peak shapes and custom analytical functions to scientific 1D data.
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machinery that carries it, and where it could break.
The paper describes FitED as a user-friendly program built in Python for scientists who analyze data by matching mathematical curves to their measurements. It supports standard peak shapes used in spectroscopy and diffraction, including Gaussian, Lorentzian, Pseudo-Voigt, and area-normalized Voigt profiles. Users can also define their own functions such as exponential decays or saturation curves. The tool includes practical features like importing text files, selecting regions of interest, modeling backgrounds, setting parameter limits, weighting data points, and visualizing residuals. It aims to combine ease of use with the control needed by experienced researchers, making the fitting process more reproducible without requiring users to write their own code from scratch.
Core claim
We present FitED, a Python-based desktop application for interactive and automated nonlinear fitting of one-dimensional scientific data.
Load-bearing premise
That the described numerical backend correctly and robustly implements the listed peak profiles and custom functions without numerical instabilities or hidden fitting artifacts when applied to real experimental data.
read the original abstract
Reliable parameter extraction from experimental data is essential for quantitative analysis across spectroscopy, diffraction, photoluminescence, chromatography, microscopy, and time-resolved measurements. However, nonlinear fitting often remains difficult to reproduce, especially when complex models, correlated parameters, uncertain derived quantities, and user-dependent fitting choices are involved. We present FitED, a Python-based desktop application for nonlinear fitting of one-dimensional scientific data that combines an accessible graphical interface with a transparent and flexible numerical backend. FitED supports conventional peak profiles, including Gaussian, Lorentzian, Pseudo-Voigt, and exact area-normalized Voigt functions, as well as arbitrary user-defined analytical models for broader experimental applications. The software integrates local and global-search-assisted optimization strategies, automated model initialization, repeated stability testing, parameter-correlation analysis, and covariance-based propagation of uncertainty for derived quantities. By combining interactive usability with uncertainty-aware analysis and structured export of fitting results, FitED provides a practical platform for reproducible and interpretable fitting of experimental data. The software is intended to support both routine analysis and advanced model evaluation while preserving the parameter-level control required by experimental researchers.
Editorial analysis
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The paper is a software presentation and introduces no new mathematical axioms, free parameters, or invented physical entities. All listed capabilities rely on standard numerical libraries and conventional peak-profile definitions already present in the scientific literature.
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2026-05-07T04:43:01.950554+00:00
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