Reproducible Temperature Visualisations with MATLAB

This repo contains some simple visualisations of surface temperature data with MATLAB for you to run.

The goal is to demonstrate a reasonably reproducible project with some interesting data.

The data source used is "Compiled historical daily temperature and precipitation data for selected 210 U.S. cities" available on Carnegie Mellon University's data repository.

Dependencies

This project requires:

• MATLAB
• MATLAB Financial Toolbox (we use some handy date based analyses)

(Note: if you're using MATLAB online, you shouldn't have to think about dependencies.)

How to use this repo

The repo consists of:

• a livescript (temperature_visualisation.mlx) which shows how to use the code to obtain and visualise the data,
• a MATLAB project file (temperature_visualisations.prj) used to set up the path before running,
• a number of source code files located in the src directory.

via MATLAB Online

MATLAB Online is a license-free way to run MATLAB projects like this one in the cloud.

Open this project in MATLAB Online

Once you're up and running, the livescript temperature_visualisation.mlx should open up (open it if not), you can then step through section by section. Have fun!

On your local MATLAB installation

First, get the code with one of the following options:

• With git (recommended): Clone this repository either from the command line (git clone https://github.com/reproducibleMATLAB/temperature-visualisations.git) or using MATLAB's git integration. Open the folder up in MATLAB.
• Without git: From the repository's GitHub page, under the green Code button, select Download ZIP to download a zip file of the code. Unzip it somewhere useful and open the folder up in MATLAB.

Run the project file temperature_visualisation.prj to ensure that all the source code is on the PATH and all the dependencies are installed.

Once you're up and running, open the livescript temperature_visualisation.mlx, you can then step through section by section. Have fun!

Contributing

Contributions to the project are very welcome! They can take many forms:

• open an issue to point out an error or bug 🐛 or to make (helpful) suggestions.
• even better, contribute that code yourself by opening a pull request on GitHub!

Examples of possible contributions include:

• correcting the source code to make better use of community standards,
• adding tests,
• adding new visualisations,
• adding some analysis.

When making changes to the code, please take into account this advise:

• please follow MATLAB style guidelines,
• aim to make your code as reusable and modular as possible,
• add any new files to the project file,
• when editing binary files such as mlx files, be aware that git can't merge these very well, so keep changes small,
• Be friendly in your pull requests!