Installation

This page provides general information on installation. Detailed installation instructions for some specific systems can also be found on the wiki.

Requirements

simsopt is a python package focused on stellarator optimization and requires python version 3.7 or higher. simsopt also requires some mandatory python packages, listed in requirements.txt and in the [options] section of setup.cfg. These packages are all installed automatically when you install using pip or another python package manager such as conda, as discussed below. If you prefer to install via python setup.py install or python setup.py develop, you will need to install these python packages manually using pip or conda, e.g. with pip install -r requirements.txt.

Optional Packages

Several other optional packages are needed for certain aspects of simsopt, such as running SPEC or VMEC, visualization/graphics, and building the documentation. These requirements can be found in the [options.extras_require] section of setup.cfg. Also,

  • For MPI support:

    • mpi4py

  • For VMEC support:

    • https://github.com/hiddenSymmetries/vmec2000 Note that the python extension in this repository is required to run VMEC or optimize VMEC configurations, but is not needed for computing properties of existing wout output files.

  • For computing Boozer coordinates:
  • For SPEC support:

    • py_spec

    • pyoculus

    • h5py

For requirements of separate physics modules like VMEC, see the documentation of the module you wish to use.

Virtual Environments

This is an optional step, but users are strongly encouraged to use a python virtual environment to install simsopt. There are two popular ways to create a python virtual environment using either venv module supplied with python or the conda virtual environment.

venv

A python virtual envionment can be created with venv using

python3 -m venv <path/to/new/virtual/environment>

Activate the newly created virtual environmnet (for bash shell)

. <path/to/new/virtual/environment>/bin/activate

If you are on a different shell, use the activate file with an appropriate extension reflecting the shell type. For more information, please refer to venv official documentation.

conda

Install either miniconda or anaconda. If you are on a HPC system, anaconda is either available by default or via a module.

A conda python virtual environment can be created by running

conda create -n <your_virtual_env_name> python=3.8

For the new virtual environment, python version 3.8 was chosen in the above command, but you are free to choose any version you want. The newly created virtual environment can be activated with a simple command

conda activate <your_virtual_env_name>

After activating the conda virtual environment, the name of the environment should appear in the shell prompt.

Installation methods

PyPi

This works for both venv and conda virtual environments.

pip install simsopt

Running the above command will install simsopt and all of its mandatory dependencies. To install optional dependencies related to SPEC and MPI, run the following command:

pip install simsopt[MPI,SPEC]

On some systems, you may not have permission to install packages to the default location. In this case, add the --user flag to pip so the package can be installed for your user only:

pip install --user simsopt

conda

A pre-compiled conda package for simsopt is available. This installation approach works only with conda virtual environments. First we need to add conda-forge as one of the channels.

conda config --add channels conda-forge
conda config --set channel_priority strict

Then install simsopt by running

conda install -c hiddensymmetries simsopt

From source

This approach works for both venv and conda virtual environments. First, install git if not already installed. Then clone the repository using

git clone https://github.com/hiddenSymmetries/simsopt.git

Then install the package to your local python environment with

cd simsopt
pip install -e .

The -e flag makes the installation “editable”, meaning that the installed package is a pointer to your local repository rather than being a copy of the source files at the time of installation. Hence, edits to code in your local repository are immediately reflected in the package you can import.

Again, if you do not have permission to install python packages to the default location, add the --user flag to pip so the package can be installed for your user only:

pip install --user -e .

Warning

Installation from local source creates a directory called build. If you are reinstalling simsopt from source after updating the code by making local changes or by git pull, remove the directory build before reinstalling.

If you want to build SIMSOPT locally with the optional dependencies, you can run

pip install --user -e .[MPI,SPEC]

However, if you’re using a zsh terminal (example: latest Macbook versions), you’ll need to run instead

pip install --user -e ".[MPI,SPEC]"

Docker container

A docker image with simsopt along with its dependencies, VMEC, SPEC, and BOOZ_XFORM pre-installed is available from docker hub. This container allows you to use simsopt without having to compile any code yourself. After installing docker, you can run the simsopt container directly from the docker image uploaded to Docker Hub.

docker run -it --rm hiddensymmetries/simsopt python

The above command should load the python shell that comes with the simsopt docker container. When you run it first time, the image is downloaded automatically, so be patient. More information about using simsopt with Docker can be found here.

Post-Installation

If the installation is successful, simsopt will be added to your python environment. You should now be able to import the module from python:

>>> import simsopt