SDO Center-to-Limb Variability (CLV) Pipeline

This package processes SDO data to recover trends in the center-to-limb variability of the solar radial velocity. v0.x.y is described in Palumbo et al. (2024b). The results of this paper can be reproduced using the showyourwork workflow from this repo.

Installation

The package is not published to PyPI; install it from this Git repository. The uv tool is recommended but not required.

As a dependency (use the library API)

To import sdo_clv_pipeline and call its API from your own code, install it straight from GitHub:

uv pip install "git+https://github.com/palumbom/sdo-clv-pipeline.git"
# or, with plain pip:
pip install "git+https://github.com/palumbom/sdo-clv-pipeline.git"

Then in Python:

import sdo_clv_pipeline

The interactive Qt matplotlib backend is optional; add the gui extra if you want it:

uv pip install "sdo_clv_pipeline[gui] @ git+https://github.com/palumbom/sdo-clv-pipeline.git"

Note: this installs the importable sdo_clv_pipeline package only. The command-line entry points (scripts/, batch/) are not packaged — to run the full pipeline end-to-end, clone the repo as in the next section.

For development (or to run the full pipeline)

Clone the repo and let uv build the locked environment (this installs the project in editable mode plus the dev dependency group from uv.lock):

git clone https://github.com/palumbom/sdo-clv-pipeline.git
cd sdo-clv-pipeline
uv sync

Optional extras are not installed by uv sync unless requested:

uv sync --extra test    # pytest, to run the test suite
uv sync --extra docs    # sphinx + theme, to build the docs
uv sync --extra gui     # PyQt backends for interactive plotting
uv sync --all-extras    # all of the above

Requires Python 3.12.

Citation

If you use this code in your research, please cite the relevant software release and paper.

Author & Contact

This repo is maintained by Michael Palumbo. You may contact him via his email - mpalumbo@flatironinstitute.org