Introducing SpectraFit: An Open-Source Tool for Interactive Spectral Analysis

TL;DR

SpectraFit is an open-source tool that simplifies spectral analysis by enabling efficient peak fitting and promoting reproducibility through a file-locking system.

Contribution

SpectraFit introduces a user-friendly, open-source platform with a file-locking system to enhance transparency and reproducibility in spectral analysis.

Findings

SpectraFit supports interactive spectral fitting via CLI or Jupyter Notebook across multiple operating systems.

The file-locking system ensures data consistency by combining input, results, and fitting models in a single file.

Demonstration on iron–sulfur dimers shows SpectraFit's effectiveness in analyzing XAS spectra.

Abstract

In chemistry, analyzing
spectra through peak fitting is a crucial
task that helps scientists extract useful quantitative information
about a sample’s chemical composition or electronic structure.
To make this process more efficient, we have developed a new open-source
software tool called SpectraFit. This tool allows users to perform
quick data fitting using expressions of distribution and linear functions
through the command line interface (CLI) or Jupyter Notebook, which
can run on Linux, Windows, and MacOS, as well as in a Docker container.
As part of our commitment to good scientific practice, we have introduced
an output file-locking system to ensure the accuracy and consistency
of information. This system collects input data, results data, and
the initial fitting model in a single file, promoting transparency,
reproducibility, collaboration, and innovation. To demonstrate SpectraFit’s
user-friendly interface and the advantages of its output file-locking
system, we are focusing on a series of previously published iron–sulfur
dimers and their XAS spectra. We will show how to analyze the XAS
spectra via CLI and in a Jupyter Notebook by simultaneously fitting
multiple data sets using SpectraFit. Additionally, we will demonstrate
how SpectraFit can be used as a black box and white box solution,
allowing users to apply their own algorithms to engineer the data
further. This publication, along with its Supporting Information and
the Jupyter Notebook, serves as a tutorial to guide users through
each step of the process. SpectraFit will streamline the peak fitting
process and provide a convenient, standardized platform for users
to share fitting models, which we hope will improve transparency and
reproducibility in the field of spectroscopy.

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