Skip to content

Getting started

This guide contains some information on how to get started with the automatic calibration. Please consider also reading the README.md file in the git repository for more information.

Prerequisites

The automatic calibration requires redis for on-memory data storage. As redis operates only on Linux systems, the calibration has to run either on one of:

  • Linux distributions
  • WSL (Windows Subsystem for Linux) environments, installed on a Windows system. WSL requires Windows 10 and a version of at least 1903.

Installation instructions for redis can be found here: https://redis.io/docs/getting-started/installation/install-redis-on-linux/

The link for the redis installation also contains instructions on how to start a redis instance. However, if you already have redis installed, you can run it using:

1
redis-server --port YOUR_REDIS_PORT

Usually, redis will run automatically on port 6379, but in a shared environment please check with others to get your redis port, since you would overwrite each other's memory.

Installation

The first step during the installation is to clone the repository. Please note that the link below is the link to the public mirror of the repository on GitHub. If you are developing code, most likely, you have to replace it with the link to the development server.

1
git clone git@github.com:tergite/tergite-autocalibration.git

To manage Python packages, we are using the package manager conda. It is recommended to create an environment for your project - alternatively, you can also just use Python 3.12

1
conda create -n tac python=3.12 -y

Here, tac stands for tergite-autocalibration. We can activate and use the environment like this:

1
conda activate tac

If you are not using conda, activate the environment with:

1
source activate tac

Now, you should enter the repository folder, because the following commands have to be executed in there.

1
cd tergite-autocalibration

To install the repository in editable mode. In Python the editable mode is triggerd by the parameter -e. This means that when you changed and saved your code files, they will be automatically loaded into the environment without re-installation.

1
pip install -e .

Here . is the root directory (i.e. the directory that contains the pyproject.toml file)

Next steps:

  • Configuration files in case you are interested on how to configure the application and run the first experiments.
  • Developer guide in case you would like to start developing features for the automatic calibration.