FitED: A User-Centric, Extensible Software Environment for Robust Peak-Profile and General Functional Data Fitting

TL;DR

FitED is a Python-based software tool designed for interactive and automated nonlinear fitting of one-dimensional scientific data, supporting various peak profiles and custom functions to enhance reproducibility and usability.

Contribution

It introduces a user-centric, extensible environment that combines graphical workflow with robust fitting capabilities for diverse analytical functions.

Findings

Supports multiple peak profiles including Gaussian, Lorentzian, and Voigt.

Enables custom function fitting such as exponential decays and saturation curves.

Provides comprehensive features like background modeling, parameter bounds, and session persistence.

Abstract

Reliable parameter extraction from experimental data is central to quantitative analysis in spectroscopy, diffraction, photoluminescence, chromatography, microscopy, and time-resolved measurements. We present FitED, a Python-based desktop application for interactive and automated nonlinear fitting of one-dimensional scientific data. FitED combines an accessible graphical workflow with a numerical backend capable of fitting both conventional peak profiles and arbitrary user-defined analytical functions. The software supports Gaussian, Lorentzian, Pseudo-Voigt, and exact area-normalized Voigt profiles, together with custom functions such as exponential decays, stretched exponentials, saturation curves, and spectroscopy-specific response functions. It integrates robust text-file import, region-of-interest selection, background modeling, parameter bounds, weighting strategies, automated pre-fit search, iterative peak refinement, residual visualization, session persistence, and structured export of fitted curves, components, reports, and metadata. By combining mathematical transparency with practical usability, FitED aims to make nonlinear fitting more reproducible and accessible while preserving the parameter-level control required by experienced experimental researchers.