This package provides a Python framework for analyzing data from the Active-Target Time Projection Chamber (AT-TPC) at the NSCL.

The following packages are required to use pytpc:

• numpy
• matplotlib
• scipy
• scikit-learn
• seaborn
• sphinx and sphinx-bootstrap-theme (if you want to build the documentation)

These should be installed automatically if you use the setup.py script.

The code itself was written and tested with Python 3.4. I don't believe it will work with Python 2.7, but anything is possible.

The easiest way to install the code is by satisfying the dependencies with Conda. Download and install conda from http://continuum.io/downloads (make sure you get the Python 3 version). Then install the dependencies with

conda install numpy scipy scikit-learn matplotlib seaborn

Next, if you're installing pytpc from the source code, run

python setup.py install

Read the documentation online at: https://groups.nscl.msu.edu/attpc/doc/pytpc

Most of the code has documentation written into it in the form of docstrings. There is also Sphinx documentation, which can be built by running make html from inside the docs directory.

Josh Bradt, bradt@nscl.msu.edu