trspecfit 0.6.1

Fit 2D time- and energy-resolved spectroscopy data

trspecfit - 2D Time- and Energy-resolved Spectroscopy Fitting

trspecfit is a Python package for modeling and fitting 1D energy-resolved and 2D time-and-energy-resolved spectroscopy data. It extends lmfit with composable spectral components, parameter-level time dynamics, convolution kernels, and simulation tools so you can build, fit, and validate physically meaningful models in one workflow.

Capabilities

• Modular components (Gaussian, Voigt/GLP/GLS, Doniach-Sunjic, backgrounds, kernels)
• 1D and 2D model construction with time-dependent parameters
• Auxiliary-axis parameter profiles via add_par_profile(...)
• Global fitting via lmfit, including CI and optional MCMC (lmfit.emcee)
• Synthetic data generation (single spectra, 2D datasets, noisy realizations)
• Parameter-sweep simulation for validation and ML training data generation
• Centralized plot configuration via PlotConfig with per-plot overrides

Installation

These instructions assume Python 3.12+, pip, and virtual environment support are already installed.

Install from PyPI:

python -m pip install trspecfit

Or install with Jupyter support for the example notebooks:

python -m pip install "trspecfit[lab]"

Install from GitHub:

python -m pip install git+https://github.com/InfinityMonkeyAtWork/time-resolved-spectroscopy-fit.git

Quick Usage

from trspecfit import Project, File

project = Project(path='my_project', name='my_experiment')
file = File(parent_project=project, path='my_dataset',
            data=..., energy=..., time=...)

# Define baseline, load model, fit
file.define_baseline(time_start=0, time_stop=3)
file.load_model('models_energy.yaml', 'my_base_model')
file.set_fit_limits(energy_limits=[...], time_limits=[...])
file.fit_baseline('my_base_model')

# Load 2D energy model, add time dependence, fit
file.load_model('models_energy.yaml', 'my_2d_model')
file.add_time_dependence('my_2d_model', 'my_par', 'models_time.yaml', 'my_dynamics')
file.fit_2d('my_2d_model')

# Inspect results
df = file.get_fit_results(fit_type='2d')

For global fits, dynamics, profiles, and advanced workflows see the Quick Start and Examples.

Documentation

Full docs are hosted on Read the Docs: Installation | Quick Start | Examples | API Reference

Support and Community

• Questions and usage help: Discussions (Q&A)
• Ideas and brainstorming: Discussions (Ideas)
• Reproducible bugs and feature requests: Issues
• Maintainer response target: within 7 days

Development

# Create and activate virtual environment
# Linux / macOS
python3 -m venv .venv
source .venv/bin/activate
# OR Windows (PowerShell)
python -m venv .venv
.\.venv\Scripts\Activate

# [same commands for all platforms from here on]
# Install and setup
pip install -U pip
pip install -e ".[dev]"
python -m pre_commit install --install-hooks

# Commit changes
pytest
python -m pre_commit run --all-files

Repository Layout

• src/trspecfit/ - package source
• docs/ - Sphinx docs source
• examples/ - notebooks and YAML models
• tests/ - pytest test suite

Copyright Notice

time-resolved spectroscopy fit (trspecfit) Copyright (c) 2025, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved.

If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Intellectual Property Office at [e-mail].

NOTICE. This Software was developed under funding from the U.S. Department of Energy and the U.S. Government consequently retains certain rights. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, distribute copies to the public, prepare derivative works, and perform publicly and display publicly, and to permit others to do so.