Getting Started#

These instructions will help you get started with MED; the only quirk of the library is that we need to install Julia beforehand - this is a modern, powerful programming language that resembles MATLAB, but is compiled to high-performance machine code (kinda like C/C++/Rust) - it’s really lovely and I highly recommend it, but we don’t need to write any Julia in MED. The symbolic regression engine that we use to derive equations automatically is written in Julia - which is why it’s powerful enough to derive and fit thousands of equations per second.

You can find a nice Julia configuration tutorial for Visual Studio Code here.

Installation#

Before the medeq library is published to PyPI, you can install it directly from this GitHub repository:

$> pip install git+https://github.com/uob-positron-imaging-centre/MED

Alternatively, you can download all the code and run pip install . inside its directory:

$> git clone https://github.com/uob-positron-imaging-centre/MED
$> cd MED
$MED> pip install .

If you would like to modify the source code and see your changes without reinstalling the package, use the -e flag for a development installation:

$MED> pip install -e .

Julia#

To discover underlying equations and see interactive plots of system responses, uncertainties and model outputs, you need to install Julia (a beautiful, high-performance programming language) on your system and the PySR library:

  1. Install Julia manually (see Julia downloads, version >=1.8 is recommended).

  2. import medeq; medeq.install()