NAG Library for Python Training material

This repository contains tutorials and exercises that are used to support NAG's training courses for the NAG Library for Python.

NAG library for Python installation

The NAG library for Python comes in two versions. One is linked to the Intel MKL for improved linear algebra performance on x86 architectures and the other is linked to NAG's self contained linear algebra libraries.

When using Intel or AMD CPUs we recommend the use of the Intel MKL version of the NAG Library for Python.

Install using the following command

python -m pip install --extra-index-url https://www.nag.com/downloads/py/naginterfaces_mkl naginterfaces

Obtaining a license

Before you can use the NAG Library for Python, you'll need a license. Free trial licenses are available!

Run the following command to begin the licensing process and email support@nag.co.uk if you have any problems.

# This will launch a license request GUI on windows
# On Mac and Linux, it gives the information you need to send to support@nag.co.uk to request a trial license
python -m naginterfaces.kusari

More detailed installation instructions are available in the official documentation.
More detailed license management instructions are available at https://www.nag.com/numeric/py/nagdoc_latest/naginterfaces.kusari.html#kusari

Exercises

We have collected together a set of exerices in the folder hands-on-exercises. Solutions are in hands-on-solutions

Tutorials

Self-paced tutorials for various aspects of the library are in the tutorials folder.

The 3 levels of interface - A tutorial that explains the 3 different interface levels in the NAG Library for Python: library, base and _primitive

Further examples

The NAGPythonExamples repo contains a set of more detailed NAG Library for Python examples covering various areas of mathematics.

The NAG Library for Python also ships with a set of usage examples. To see them all, run the following command once you have installed the product.

python -m naginterfaces.library.examples --locate

numericalalgorithmsgroup/NAGPythonLibraryTraining

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