Edward Smith

Dr Edward Smith is a research associate working on multi-scale modelling of fluid mechanics, in particular the coupling of simulations methods including continuum based computational fluid dynamics (CFD), molecular dynamics (MD) and granular mechanics discrete element method (DEM). Please see my personal website http://www.edwardsmith.co.uk Software My research is heavily based on software and I aim to promote best practice as a software sustainability institute (SSI) fellow (https://www.software.ac.uk/fellows/edward-smith). Our open-source coupling software, freely available at: http://www.cpl-library.org CPL library links codes written in different languages together using MPI to facilitate easy-to-use, reliable and highly-scalable coupled simulation. We provide cross language bindings in Fortran, C, C and Python; detailed documentation including a quick start guide and numerous examples are available on the website. These examples focus on giving a clear introduction to the software with a number of graphical examples. The software is under version control at github; linked to Travis CI for continuous integration unit and integration testing utilising both pytest and google test frameworks. An introduction to Python In order to address the lack of general Python teaching here at Imperial, I put together and gave a three part introduction course through the HPC support here at Imperial. This class was aimed at beginners and also for those who want to switch from Matlab to Python. 1) Introduction to Python for scientific computing, 3/3/17 (Slides) (Solutions) a) Motivation for using Python. b) Introduction to programming in Python c) Python concepts (lists, iterators, etc) and discussion of the differences to other languages. d) Scientific libraries numpy and matplotlib. e) Examples of usage for scientific problems. 2) Further details of the Python language, 10/3/17 (Slides) (Solutions) a) More on Python data structures: concepts like references, immutable, lists, data organisation with Dictionaries and numpy arrays. b) Use of functions and design of interfaces. c) Introduction to classes and objects. d) Structuring a project, importing modules and writing tests. d) Examples of usage for scientific problems. 3) Python libraries, 17/3/17 (Slides) (Solutions) a) Using Python to read files (ascii, binary, hp5) and plot. b) Running parameter studies by calling executables repeatedly with subprocess. c) Designing a basic Graphical User Interface. d) Unit testing frameworks and version control. e) Other libraries and how to wrap your own code from fortran, c++, etc HPC Summer School 2017 Given the interest in this course, I am running this again as part of the summer school. This is split over two days: Python for Beginners: (Slides) (Solutions) Scientific Python: (Slides) (hands-on) (Solutions) The modular and object oriented approach taught in these course is the basis for open-source visualisation software, pydataview.

• Faculty of Engineering