GAP 4.8.9 installation with standard packages -- copy to your CoCalc project to get it
PyNormaliz - An interface to Normaliz
What is PyNormaliz
PyNormaliz provides an interface to Normaliz (https://www.normaliz.uni-osnabrueck.de) via libNormaliz. It offers the complete functionality of Normaliz, and can be used interactively from python. For a first example, see this introduction by Richard Sieg.
Requirements
python 2.7 or higher or python 3.4 or higher
Normaliz 3.2.1 Oor higher (https://github.com/Normaliz/Normaliz/releases)
Installation
You need to have Normaliz properly installed and libNormaliz in your gcc's include path. On most systems, installing Normaliz via
is enough. If you prefer or are not able to install it, you need to set CPATH and LD_LIBRARY_PATH accordingly.
After that, you can install PyNormaliz via
Usage
The main command is Cone to create a cone, and the member functions of the cone class to compute properties. For a full list of input and output properties, see the Normaliz manual.
To create a cone, use
All possible Normaliz input properties can be given as keyword arguments.
To compute a property of the cone, use the provided getters, which corresponds to Normaliz compute goals.
You can pass options to the compute functions
Low level commands
There is also a low-level API, directly using C functions:
To create a cone, use
or, equivalently,
NmzCone can take an arbitrary number of arguments, either as separated arguments or in a list. First is always a string, describing an input property for Normaliz, followed by a (possibly empty) matrix.
NmzCompute takes a cone as first argument, followed by arbitrary many strings, or a list of strings, describing Normaliz output properties. NmzCompute lets Normaliz compute the necessary values, and returns true if everything was computed properly, false otherwise.
or
NmzIsComputed takes a cone and a string representing an output property, and returns true if the property is already computed for the cone, false otherwise.
NmzResult takes a cone and a string representing an output property, and returns the computed value of this property as a matrix, a list, or as a bool.