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.

翻译：[翻译摘要] 从实验数据中可靠地提取参数是光谱学、衍射、光致发光、色谱分析、显微成像及时间分辨测量中定量分析的核心。我们提出FitED，一款基于Python的桌面应用程序，用于一维科学数据的交互式与自动化非线性拟合。FitED将直观的图形化工作流与数值后端相结合，能够拟合经典峰形及用户定义的任意解析函数。该软件支持高斯、洛伦兹、伪Voigt及精确面积归一化Voigt峰形，并涵盖指数衰减、拉伸指数、饱和曲线及光谱学特定响应函数等自定义函数。它集成了稳健的文本文件导入、感兴趣区域选择、背景建模、参数边界约束、加权策略、自动化预拟合搜索、迭代峰形细化、残差可视化、会话持久化以及拟合曲线、分量、报告与元数据的结构化导出功能。通过融合数学透明性与实用易用性，FitED旨在使非线性拟合更具可重复性与可访问性，同时保留经验丰富的实验研究人员所需的参数级控制精度。