Individual coursework (50%)

The individual coursework is available: here (cy).

A mock coursework is available: here.

The topics for the individual coursework for the past few years have been:

• 2023-2024 here (cy) (solution)
  1. Differential equations
  2. Algebra
  3. Sequences
  4. Matrices
• 2022-2023:
  1. Sequences
  2. Probability
  3. Algebra
  4. Matrices
• 2021-2022:
  1. Matrices
  2. Sequences
  3. Matrices
  4. Calculus
• 2020-2021:
  1. Probability
  2. Combinatorics
  3. Calculus
  4. Sequences
• Mock here:
  1. Arithmetic
  2. Algebra
  3. Matrices
  4. Probability

Group project (50%)

Build a Python library to provide tools for a problem related to mathematics.

You will evidence your progress with 2 mediums:

1. A 2 page paper
2. A 15 minute recorded presentation

Your final submission should include the following 7 files:

1. A main.tex file: the source file for a 2 page paper written in LaTeX.
2. A main.pdf file: the pdf file for a 2 page paper written in LaTeX.
3. A <library>.py file: the source file for your Python library
4. A test_<library>.py file: the test files for your Python library
5. A README.md file: the documentation for your Python library
6. A presentation.mp4 (or similar file format): the video recording of your 15 minute presentation
7. A contribution.md file: a file describing the contributions of every member of your group.

Marking criteria

The various components of the submission should aim to demonstrate how the following aspects of the work have been addressed:

• Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
• A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is? [10%]
• State of the field: Do the authors describe how this software compares to other commonly used packages?
• Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
• References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?
• Functionality: Have the functional claims of the software been confirmed?
• Documentation: Does the documentation have a Tutorial, How to section, Reference and Explanation section? Is it clear? Is the source code clear?
• Modularity: Is the code written in a modular way?
• Testing: Have tests been written for all functionality of the software?
• Presentation: Was the presentation format used appropriately? Were the visual aids appropriate?

A suggestion would be to use the paper for the summary, statement of need and state of the field whereas the presentation can be used for the functionality, documentation, modularity and testing.

Note that this marking criteria has some overlap with the review criteria for the Journal of Open Source Software https://joss.readthedocs.io/en/latest/review_checklist.html. Some examples of papers written for that journal that can be helpful are:

• Matching: A Python library for solving matching games https://joss.theoj.org/papers/10.21105/joss.02169
• Nashpy: A Python library for the computation of Nash equilibria https://joss.theoj.org/papers/10.21105/joss.00904

Deadline: 2024-05-06 (Monday of week 12).

Past group projects

A list of titles of past projects:

2022-2023

• Predicting the Landing Point of a Ball using Python

• Modelling a pully system

• Cup2py - Proof of concent for recursive decentralised peer to peer communication protocal

• Music Maker: Python library generating sounds from mathematical expressions

• Modeling Lifts with Python: Lifts

• Base converter with Python

• Using code to create music: jam

• Breaking good: generating hydrocarbons

• Solving ciphers using Python: CiPy

• Rubik’s cube solver

• Wildflowers: sequences.py

• Shaper creator

• Appraisal: A Python library for Investment Appraisal

2021-2022

• Modelling Variations of the Josephus Problem with Python: Josephy

• A python library to summarise Basic Statistical Data

2020-2021

• Slopes: modelling objects on a slope

• Fractpy: generating fractals in Python

Log of past relevant classes

01/03/24: Individual Coursework Feedback

Thanks all for your efforts in doing the individual coursework!

12/08/23: Summary of mock coursework session

In class today I demonstrated how to submit and went over the mock coursework.

12/04/23: Summary of release of individual coursework

In class yesterday we took a look at the individual coursework.

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