The assessed work is focussed primarily on practical implementation of the ideas discussed in lectures. Here are some pointers on how to submit the assessed work:

• To do this module you will need to install git on your computer and register for a free account on github.
• You should answer the assignment questions in a Jupyter notebook. Any large pieces of code should be encapsulated into functions and organised in an external module. To get you started, there is an example of how to do this in Julia here: https://github.com/colm-connaughton/MA934_example_1.git
• You should complete an online declaration form for every piece of assessed work submitted via github.
• Questions which involve data or comparisons between theory and implementation should be answered using inline plots in your notebook. For this module, you are expected to produce plots to to a professional standard. This usually means changing the default behaviour of plotting functions and often requires reading documentation and googling for answers. Plots which are not to a professional standard will be marked down even if the results they contain are correct. This reflects the fact that publishers will refuse to accept your paper if the plots are not presented properly, even if the paper is correct. Common mistakes resulting in poor quality plots include
  
  • Fonts that are too small or too big.
  • Failure to choose the appropriate plot ranges or failure to choose appropriately between logarithmic and linear axes.
  • Failure to label axes properly, choose appropriate numbers of tics or label the tics on logarithmic axes with proper powers-of-ten notation. An axis with one or two tics is useless. Equally an axis with so many tics that all the tic labels are on top of each other is useless.
  • Failure to include a legend explaining what each trace on the plot is or use of meaningless labels in a legend.
  • Failure to make different lines distinguishable. Most journals will insist that all plots are comprehensible when printed in black and white. You therefore need to use different line styles or symbols in addition to colour to distinguish different traces.
  • Poor quality graphics resulting in pixellation or obfuscation of detail. Plots should be produced in a vector graphics language such as postscript (all reasonable graphics packages have the option to export a figure as postscript), even if they are subsequently sampled to produce a jpg.
  • Failure to include a caption summarising the main points of the figure.
  • Failure to plot error bars in cases where error bars are appropriate.
• You should organise your assignments as a single github repository containing the notebooks answering the questions and the code modules you have written to support them. This repository should be self-contained: when cloned it should contain everything required to run the notebooks.
• To submit your assignment please share your repository with me before the deadline - my github id is colm-connaughton. Obviously please make sure that you commit your work before the deadline - any commits later than the deadline will not be assessed. If you use multiple branches please make sure the final version is in the "master" branch.