Web Interface of AstroPlasma

This is a web interface for the AstroPlasma repository which allows you to interpolate the plasma properties from the pre-computed dataset from the cloudy.

Features

• Compute Ionization Fraction of the Specific Element and Ion
• Plot Ion fraction vs temperature graph for both CIE and PIE modes
• Plot emission spectrum of the elements
• Interactive graphs
• Simple file server to download the batch file on demand (used internally in upstream AstroPlasma repository)

Requirements

1. Docker engine
2. Poetry
3. Python 3.9+
4. Git CLI
5. Dataset mounted using nfs (Contact me or @dutta-alankar)

Setup

1. Clone the repository

   git clone https://github.com/tbhaxor/CloudyInterpolator.git
   cd CloudyInterpolator

2. Install the packages

   poetry install

   Note This command will automatically set-up virtual environment for you.

3. Provide environment file

   cat <<EOF > .env
   IONIZATION_DATASET_DIR='/path/to/directory/containing/ionization-batches'
   EMISSION_DATASET_DIR='/path/to/directory/containing/emission-batches'
   PY_ENV=dev
   EOF

   Note Omit PY_ENV=dev if you want to deploy it on the production

4. Migrate the database

   poetry run python manage.py migrate

Getting started

Once you have performed the steps from the Setup, you are good to go

poetry run python manage.py runserver

This will open the 8000 port by default, but you can change it using the following command

poetry run python manage.py runserver 127.0.0.1:<PORT>

Replace the placeholder <PORT> with the port number of your choice.

Using Docker Containers

Get rid of all the hassle of setup and getting started. You can use the following

Requirements Docker runtime and docker compose installed on your system

1. Generate docker compose file from the template file

   bash deployment/scripts/gen-docker-compose.bash -c http://example.com -i /path/to/ionization/dataset -e /path/to/emission/dataset

   Note Let's suppose I am hosting my webserver on the http://example.com, so it should be the value of -c argument. You can provide multiple origins separated by comma and without any spaces.

2. Run the workload

   docker-compose up --pull always

   Note You can access the server at port http://localhost:8000.

Using local configuration [[RECOMMENDED]]

The configuration template named as docker-compose.local.yml is now a recommended version as code is not frequently built.

1. Generate docker compose file from the template file

bash deployment/scripts/gen-docker-compose.bash -s docker-compose.local.yml -c http://example.com -i /path/to/ionization/dataset -e /path/to/emission/dataset

2. Install the dependencies

   poetry install

3. Generate static files

   poetry run ./manage.py collectstatic --noinput  --skip-checks

4. Run the server

   docker-compose up --pull always

   Note You can access the server at port http://localhost:8000.