Most of the code is for the 1-dimensional Gomory-Johnson infinite group problem, including an electronic compendium of extreme functions.

See http://www.sagemath.org/doc/tutorial/ for information on how to use Sage.

Authors

See https://github.com/mkoeppe/cutgeneratingfunctionology/blob/master/AUTHORS.rst and also https://github.com/mkoeppe/cutgeneratingfunctionology/blob/master/THANKS.rst

License

The code is released under the GNU General Public License, version 2, or any later version as published by the Free Software Foundation.

Documentation

http://mkoeppe.github.io/cutgeneratingfunctionology/doc/html/

Using the cutgeneratingfunctionology package

There are many ways to run this package.

A. Run it online on mybinder.org

B. Install released version from PyPI and run it within conda

• Install Miniconda from https://docs.conda.io/en/latest/miniconda.html

• Set up the conda environment described in https://github.com/mkoeppe/cutgeneratingfunctionology/blob/master/environment.yml:

  e=environment.yml; curl -o $e https://raw.githubusercontent.com/mkoeppe/cutgeneratingfunctionology/master/$e
  conda env create -n sage-cgf -f $e
  conda activate sage-cgf
  

  This takes a while; it installs SageMath, which has many dependencies.

• Install PyPI package:

  pip install cutgeneratingfunctionology
  

• Start Sage. You can either use the terminal (IPython):

  sage
  

  or a Jupyter notebook:

  sage -n jupyter
  

• At the Sage prompt, type:

  import cutgeneratingfunctionology.igp as igp; from cutgeneratingfunctionology.igp import *
  

• Follow the instructions and examples in https://github.com/mkoeppe/cutgeneratingfunctionology/blob/master/demo.rst or https://github.com/mkoeppe/cutgeneratingfunctionology/blob/master/demo.ipynb .

C. Clone from GitHub and run it within conda

• Install Miniconda from https://docs.conda.io/en/latest/miniconda.html

• Clone the GitHub repository https://github.com/mkoeppe/cutgeneratingfunctionology.git:

  git clone https://github.com/mkoeppe/cutgeneratingfunctionology.git
  cd cutgeneratingfunctionology
  

• Set up the conda environment described in https://github.com/mkoeppe/cutgeneratingfunctionology/blob/master/environment.yml:

  conda env create -n sage-cgf -f environment.yml
  conda activate sage-cgf
  

  This takes a while; it installs SageMath which has many dependencies.

• (Optional:) Install the cutgeneratingfunctionology package using pip:

  pip install .
  

• Start Sage. You can either use the terminal (IPython):

  sage
  

  or a Jupyter notebook:

  sage -n jupyter
  

• At the Sage prompt, type:

  import cutgeneratingfunctionology.igp as igp; from cutgeneratingfunctionology.igp import *
  

• Follow the instructions and examples in https://github.com/mkoeppe/cutgeneratingfunctionology/blob/master/demo.rst or https://github.com/mkoeppe/cutgeneratingfunctionology/blob/master/demo.ipynb .

D. Run in a standalone installation of the SageMath distribution (no conda)

• Install the SageMath distribution:

  1. Either from source from http://www.sagemath.org/
  2. or with a binary from http://www.sagemath.org/

  The SageMath distribution brings its own installation of Python and many packages.

• Clone the GitHub repository https://github.com/mkoeppe/cutgeneratingfunctionology.git:

  git clone https://github.com/mkoeppe/cutgeneratingfunctionology.git
  cd cutgeneratingfunctionology
  

• (Optional:) Install optional SageMath distribution packages:

  sage -i lrslib pynormaliz
  

• Install the cutgeneratingfunctionology package using pip:

  sage -pip install .
  

• Start SageMath. You can either use the terminal (IPython):

  sage
  

  or a Jupyter notebook:

  sage -n jupyter
  

• At the Sage prompt, type:

  import cutgeneratingfunctionology.igp as igp; from cutgeneratingfunctionology.igp import *
  

• Follow the instructions and examples in https://github.com/mkoeppe/cutgeneratingfunctionology/blob/master/demo.rst or https://github.com/mkoeppe/cutgeneratingfunctionology/blob/master/demo.ipynb .