Glossary

Anaconda

Python distrubution that makes installing packages like numpy easier for Windows. Includes over 700 packages. For a smaller, more minimal approach, see Miniconda. For more information, see https://www.anaconda.com/.

Anaconda Prompt

Modified Windows prompt to be used with the Anaconda python distrubution. Reconfigures python paths to point to packages installed via conda

conda

From https://www.conda.io/docs/:

Conda is an open source package management system and environment management system that runs on Windows, macOS, and Lunix. Conda quickly installs, runs, and updates packages and their dependncies

CI

Continuous integration. Software we utilize to check that pull requests don’t break the code.

git

Distributed version control system. Allows us to test and implement new features with ease. For more information, see https://git-scm.com.

Jupyter notebook

Powerful web application used in this project, for examples and tutorials containing real python code. From https://jupyter.org:

The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.

lint

Bits of potentially erroneous code. Can be identified by a linter

linter

Program that analyzes source code to check for errors, bugs, stylistic issues, and other potential hangups.

matplotlib

Primary python package for plotting data. Highly customizable and extensible. More information at https://matplotlib.org

Miniconda

Minimal installer for conda. From https://conda.io:

Miniconda is a small, bootstrap version of Anaconda that only includes conda, Python, the packages they depend on, and a small number of useful packages

numpy

Widely-used python package that allows multidimensional arrays and linear algebra routines. More information at https://www.numpy.org

pip

Recommended tool for installing Python packages. More at https://pypi.org/project/pip/

PyPI

Python package index. Where packages that can easily be fetched and installed via pip can be found. https://pypi.org

pytest

Fully featured python test runner. More at https://pytest.org/en/latest/

scipy

Widely-used python package that contains more mathematical support and data structures, such as sparse matrices. Not required for this package, but allows the sparsity of some matrices to be exploited. More information at https://docs.scipy.org/doc/scipy/reference/

SERPENT

Monte Carlo particle transport code developed at VTT Technical Research Centre of Finland, Ltd [serpent]. Produces output files that can be parsed by this project. More information, including distribution and licensing of SERPENT can be found at http://montecarlo.vtt.fi.

twine

Python package for interacting with and uploading packages to PyPI

yaml

Human-readable format used for configuration files in this project. For more information, see https://pyyaml.org/wiki/PyYAMLDocumentation