S2 Coursework

This is my repository for the S2 coursework. The code for this project is in the Jupyter Notebooks in the root directory of this repository.

• notebook1.ipynb contains the code for parts (a) - (e) of the coursework.
• notebook2.ipynb contains the code for parts (f) - (g) of the coursework.

The report for this project is in pdf format and is located in the report directory.

How to run the Jupyter Notebooks

Clone this GitLab repository to your local machine.

git clone https://gitlab.developers.cam.ac.uk/phy/data-intensive-science-mphil/assessments/s2_coursework/fm565.git

Create a conda environment by running:

conda env create -f environment.yml

in the root directory of this repository.

This will create a new conda environment called S2Coursework. This will install the necessary packages for this project, listed in the requirements.txt file.

Activate the environment by running:

conda activate S2Coursework

This may automatically create a Jupyter Kernel for the new environment. If not, you can create a kernel manually e.g.

python -m ipykernel install --user --name S2Coursework --display-name "S2Coursework"

You should now be able to run the notebooks in this repository.

To deactivate the conda environment, run conda deactivate.

Declaration of Use of Autogeneration Tools

Microsoft Copilot was used in the following code:

• In part (d), Copilot suggested the use of jnp.eye(27)[i], etc. to add/subtract delta from one element of an array.
• The remainder of the code is my own work, with inspiration from the S2 course Jupyter notebooks shown in lectures for part (f).

A declaration of the use of generative tools in writing the report is given in the report itself.