Installation¶
There are two ways to install tensorwaves
. Even though the PyPI installation
is the fastest, we recommend following the Development mode
procedure.
Installation through PyPI¶
tensorwaves
is available as a PyPI package, so installation is super easy:
pip install tensorwaves
Et voilà, that’s it! You can try out whether the installation works by running:
import tensorwaves
from the Python interpreter. Note that PyPI only allows you to install specific releases, so we recommend using the more dynamic, ‘development mode’ instead.
Development mode¶
tensorwaves
is an academic research project and is bound to continuously
evolve. We therefore highly recommend installing tensorwaves
from the source
code, so that you work with the
latest version.
Moreover, since you read as far as this, you must have an interest in particle physics, and it is researchers like you who can help bring this project further! So please, follow the following sections to set up this ‘interactive installation’.
Step 1: Get the source code¶
The tensorwaves
source code is maintained through Git, so you need to install Git first. Once
you’ve done so, navigate to a suitable folder and run:
git clone git@github.com:ComPWA/tensorwaves.git
cd tensorwaves
After that, there should be a folder called tensorwaves
into which we
navigated just now. We’ll call this folder the local repository.
When new commits are merged into the master branch of tensorwaves, you need to update your local copy of the source code as follows:
git checkout master
git pull
It’s best to have a clean your working tree before you do a git pull.
Step 2: Create a virtual environment¶
It is safest to install tensorwaves
within a virtual environment, so that all
Python dependencies are contained within there. This is helpful in case
something goes wrong with the dependencies: you can just trash the environment
and recreate it. There are two options: Conda or Python’s venv.
Conda environment¶
Conda can be installed without administrator
rights, see instructions on this page. Once installed, navigate to the
local repository and create the Conda environment for
tensorwaves
as follows:
conda env create
This command uses the environment.yml file and
immediately installs tensorwaves
in development mode.
After Conda finishes creating the environment, you can activate it with as follows:
conda activate tw
You need to have the tw
environment activated whenever you want to run
tensorwaves
.
Python venv¶
Alternatively, you can use Python’s venv, if you have that available on your system. All you have to do, is navigate into local repository and run:
python3 -m venv ./venv
This creates a folder called venv
where all Python packages will be
contained. You first have to activate the environment, and will have to do so
whenever you want to run tensorwaves
.
source ./venv/bin/activate
Now you can safely install tensorwaves
in development mode:
pip install -e .
That’s it, now you’re all set to use tensorwaves!
Step 3: Test the installation¶
First, navigate out of the main directory of the local repository in order to make sure that tensorwaves
we run, is the
system installation and not the tensorwaves
folder in the current
working directory. Then, simply launch a Python interpreter and run:
import tensorwaves
If you don’t get any error messages, all worked out nicely!
For more thorough testing, navigate back to the you can run the unit tests:
pip install -e .[test] # install dependencies for testing
pytest -m "not slow"
After that, it’s worth having a look at the contribute page!