Quickstart
In this section, you will find information on how to quickly run this module after a few simple steps.
In order to use the most up-to-date function version of the Isint-2DTExS
EoS module, replace <TAG>
in the following instructions by the version
indicated on the CE modules registry webpage.
On the Calculation Engine (CE)
In order to run the BQS EoS module on the MUSES CE, refer to the user manual’s Quick Start Guide to find instructions and exemples on how to submit jobs and retrieve the run outputs.
BQS EoS module’s characteristics to know when running on CE:
Name:
'eos_taylor_4d'
is the name of the module in the CE modules registry
Locally
Using Docker
The quickest way to run the BQS EoS module on your machine is by using the Docker container. First, make sure that you have Docker locally installed on your machine.
1. Pull Docker image
The recommended way to obtain the BQS EoS Docker container is to pull the latest version from the GitLab Container Registry:
docker pull registry.gitlab.com/nsf-muses/module-bqs-eos/module-bqs-eos:{TAG}
2. Run the module from the container
In order to run this container, you must at least have a minimal project directory, with an input/ folder containing a config.yaml file that is used to define the module’s parameters for the run, and and output/ folder. More information about the content of the config.yaml file can be found in the module’s OpenAPI specifications.
Once you have defined the parameters of your choice, you can run the container:
export DOCKER_IMAGE_NAME=registry.gitlab.com/nsf-muses/module-bqs-eos/module-bqs-eos
export DOCKER_IMAGE_TAG=<TAG>
docker run -it --rm --name BQS \
-v "${PWD}/input:/opt/input" \
-v "${PWD}/output:/opt/output" \
$DOCKER_IMAGE_NAME:$DOCKER_IMAGE_TAG python src/main.py input/config.yaml
The output files will appear in the output/ directory upon completion.
Without Docker
In order to run the module without Docker, one has to copy the BQS EoS repository on their local machine, and install the required libraries listed in requirements.txt.
Start by downloading the BQS EoS repository on your machine, either by going to the webpage and downloading it, or by using the command line:
git clone --depth 1 --branch <TAG> https://gitlab.com/nsf-muses/module-bqs-eos/module-bqs-eos.git
1. Install required packages
In order to run the module locally, the local machine must have an up-to-date version of the GCC compiler to compile and build the core code of the module written in C.
Running the module locally also requires an up-to-date version of python3 installed, including the following packages (listed in requirements.txt):
-
Note: we do recommend the use of a Python virtual environment to avoid potential conflicts with your local package installation. To create and activate a virtual environment, execute the following commands:
python3 -m venv .venv source .venv/bin/activate
Whenever you need to deactivate the virtual environment, simply type
deactivate
.
These libraries can all be easily installed using the pip
package manager.
Moreover, one can proceed by calling directly requirements.txt, using:
pip install --user -r module-bqs-eos/requirements.txt
If the installation of the Porter fails by this method, see more detailed instructions in the Porter README.
2. Compile and build
After successful installation of the required libraries, you need to compile and build the core code of the module:
cd module-bqs-eos/
make
The executable EoS_BQS will be created upon successful compilation and linking.
3. Run the module
Once all of the dependencies are successfully installed, and the project has been compiled, all that’s left to do is run the module.
First make sure that you have created a config.yaml containing the module configuration in the input/ directory. Then run:
python src/main.py input/config.yaml
The output files will appear in the output/ directory upon completion.