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Speeding up calculations using NumPyHave you ever had to leave your laptop in front of a fan while your Python code churns away at a problem...

Speeding up calculations using NumPy

Have you ever had to leave your laptop in front of a fan while your Python code churns away at a problem? Are you not sure how to make it run faster but everyone else seems to be able to do it? Do you just run into words like “profiler” on StackExchange? This tutorial will look at some simple computational problems and how to speed them up. I’ll focus on using the NumPy library which is a very fast array and mathematical library for Python. By breaking our problem into simple operations we can “vectorise” it and NumPy can do the calculations 10s of times faster than bare Python code. In this tutorial, we’ll look at how to vectorise a number of computational problems.

This is an interactive workshop, so attendees will need to bring their own laptop.

This tutorial will be taught by Dr. Chris Arridge who is a Reader in Planetary Physics in the Physics Department.

NOTE: This is in the CALC rooms in FST, but this maybe subject to change due to potential building works, if so a new location will be emailed out.