Installation

March 23, 2024 ยท View on GitHub

We provide several methods to install pyraws:

1. Build from source

For Linux, the installation is straightforward. You just need to run the following command from the main directory:

source pyraws_install.sh

Warning

Your datates should be placed in the /data directory in the main.

Tip

You can also install by the environment.yml.

2. PyPi

From CLI:

pip3 install pyraws

Warning

Create a file sys_cfg.py in the directory /pyraws/pyraws/, and add two variables as follows:

PYRAWS_HOME_PATH="Absolute path to the main pyraws directory."
DATA_PATH="Absolute path to the data directory."

By default the data directory is located in PyRawS main directory.

3. Docker Compose

PyRawS comes also delivered in a docker image. To use PyRawS with docker, you can pull the image or build it trough the Dockerfile.

We already set the docker-compose.yml file integrated with the capabilities of NVIDIA docker. You can run the container trough the compose API:

.devcontainer/ > docker-compose up --build

You can also run the container trough the devcontainer extension of VSCode, a devcontainer.json has been already provided.

Set-up for coregistration study

If you want to perform the coregistration study, you need to:

  1. clone the repository SuperGlue Inference and Evaluation Demo Script;
  2. rename the subdirectory models to superglue_models;
  3. move superglue_models into coregistration_study.

Coregistration study results can be generated by using the pyraws_coregistration_study.ipynb notebook. The database coregistration_study_db.csv containing info on the discarded eruption events is used to generate results in the notebook.