gcfpy 0.1.0

Graphical Curve Fitting GUI for Python

Curve Graphical Curve Fitting

A Python-based graphical interface for fitting experimental data, built on top of lmfit, emcee, scipy and PyQt5. It allows interactive visualization, model customization, and multi-method fit analysis (1D and 2D).

---

Features

• Multi-tab GUI: manage several fit sessions in parallel

• Custom model editor: write formulas directly, with auto-detected parameters

• Fitting methods:

  • Least-squares (lmfit)
  • MCMC sampling (emcee)
  • Orthogonal Distance Regression (scipy.odr)

• Data types supported:

  • 1D fit (y = f(x)) with optional error bars
  • 2D fit (z = f(x, y)) with surface visualization

• Advanced visualization tools:

  • Residual plots and confidence intervals
  • 2D surface fit & scatter overlays
  • Component breakdown (for additive models)
  • MCMC diagnostics: chains, corner plots, autocorrelation

• Fit comparison manager: store, label and compare multiple models per dataset

• Data & results export/import (CSV)

Other tools such as PyModelFit, curvefitgui, or more general platforms like Veusz also provide GUI-based fitting capabilities.

---

Installing

git clone https://github.com/gcfpy/gcfpy
cd gcfpy
pip install -e .

---

Launch the Application

gcfpy

or

python -m gcfpy.app.main_window

---

Documentation

Read the docs.

It is possible to build the doc locally :

mkdocs serve

The full documentation is written in Markdown using MkDocs with the Material theme.

---

Contributions

We appreciate and welcome contributions. Small improvements or fixes are always appreciated.