Experimentalis

Experimentalis ("Experiment Analysis") is a Python library for experimental data analysis, model fitting, and time-series analysis.

It grew out of several thousand lines of analysis code that I developed over the course of several years for working with laboratory experiments, oscilloscopes, electronic circuits, and experimental measurements. What began as a collection of simple data-analysis and curve-fitting functions has gradually developed into a more general-purpose library for constructing, fitting, and analyzing mathematical models of experimental data.

The goal of Experimentalis is not to provide a single framework for experimental analysis, but rather a growing collection of useful tools and functions that can be composed together when analyzing real experimental data.

Installation

Experimentalis can be installed directly from PyPI:

pip install experimentalis

For the latest development version:

pip install git+https://github.com/mufaro3/experimentalis.git

Optional functionality can be installed using extras:

pip install "experimentalis[jupyter]"
pip install "experimentalis[ml]"

Development dependencies can be installed with:

pip install -e ".[ml,jupyter,lint,test,docs]"

Getting Started and Documentation

View some examples under the "examples" directory for how to use Experimentalis.

The full documentation, including examples and API reference, is available at:

https://moofy.org/experimentalis

The documentation is the best place to start if you want to understand how the library is organized and how its functions are intended to be used.

What is Experimentalis for?

Experimentalis is primarily intended for experimental and scientific computing, particularly tasks involving:

• Experimental data processing
• Time-series analysis
• Model fitting
• Curve fitting and parameter estimation
• Oscilloscope and circuit measurements
• Numerical analysis of experimental data
• Construction and analysis of mathematical models
• Visualization of experimental data

The library is deliberately fairly general. New functionality is added as new analysis problems arise, so its scope will continue to evolve over time.

Development

The source code is hosted on GitHub:

https://github.com/mufaro3/experimentalis

To set up a development environment:

git clone https://github.com/mufaro3/experimentalis.git
cd experimentalis
make setup

The repository includes a Makefile for common development tasks:

make test       # Run tests
make docs       # Build documentation
make docs-view  # Build and view documentation
make lint       # Run linters
make clean      # Remove build artifacts

Contributions, suggestions, and pull requests are welcome.

License

Experimentalis is released under the MIT License. See LICENSE for the full license text.

Experimentalis is a continually evolving collection of tools for experimental data analysis.