Experimentalis Documentation¶
Experimentalis (short for “Experimental Analysis”) is a Python library for experimental data analysis, model fitting, and time-series analysis.
The library grew out of several thousand lines of laboratory analysis code developed for working with experimental measurements, oscilloscopes, electronic circuits, and other physics experiments. Those functions have since been cleaned up, organized, tested, and documented into a more general purpose library for building and analyzing mathematical models of experimental data.
The library is continually evolving as new analysis problems arise, and is intended to serve as a growing collection of useful tools for experimental and scientific computing.
Installation¶
Experimentalis is available on PyPI and can be installed using pip:
pip install experimentalis
Once installed, the library can be imported normally:
import experimentalis
For the latest development version, the source code is available on GitHub:
Development Setup¶
If you would like to contribute to Experimentalis or work with the source code directly, first clone the repository:
git clone https://github.com/mufaro3/experimentalis.git
cd experimentalis
A development environment can then be created using:
make setup
If you intend to use the Jupyter notebooks and examples, a Jupyter kernel can also be installed with:
make kernel
The Makefile provides several other development commands. Run:
make
to see the available options.
Documentation¶
This documentation contains examples and detailed API references for the functions provided by Experimentalis. The library is organized into several general-purpose modules as well as extensions for specific experimental applications.
