haxr 1.1.0

Companion library for the HAXR dataset

[Documentation 📚]

haxr

haxr is the companion library for the HAXR dataset. It is an easy-to-use, local-cache-based access layer for the dataset files and a collection of handy utilities for working with the data.

haxr releases are available as wheel packages for macOS, Windows and Linux on PyPI. Install it using pip:

pip install haxr

and find the documentation of the API here.

As a teaser, here is an example that plots the 1000th cycle of amerikahoeft_08-UTC.hdf:

import haxr
import matplotlib.pyplot as plt


def plot_cycle(store, station, split_hour_utc, cycle, file_name="demo.png"):
    chunk = store.get_chunk(station=station, split_hour_utc=split_hour_utc)
    with store.open(chunk.radar_file) as f:
        df = haxr.utilities.load_cycle(f, cycle)
        h, az_edges, r_edges = haxr.utilities.fill_histogram(
            az=df["az (degree)"], r=df["r (meter)"], weights=df["amp"]
        )
        x, y, v = haxr.utilities.histogram_to_cartesian_meshgrid(h, az_edges, r_edges)

    fig, ax = plt.subplots(figsize=(3, 3))
    ax.pcolormesh(x, y, v, cmap="plasma")
    ax.set_aspect("equal")
    ax.set_axis_off()

    fig.savefig(file_name, dpi=300)


with haxr.Store(base_url=haxr.DOI.latest) as store:
    plot_cycle(store, "amerikahoeft", split_hour_utc=8, cycle=1000)

Contributing 👷

Contributions are welcome! If you find any issues or have suggestions for improvements, please feel free to submit a pull request.

As a rule of thumb:

• For bugs and feature requests, please open a GitHub issue.
• For changes, please open a pull request.
• Small, focused PRs are easiest to review.
• Improvements for tests and doc are highly appreciated.

Development Setup

Clone the repository and set up a development environment. The project defines dependency groups (see pyproject.toml), including a dev group for development tools and a docs group for building the documentation.

Option A: uv (recommended)

git clone https://github.com/DLR-KN/haxr
cd haxr
uv sync --all-groups

If you only need the documentation toolchain:

uv sync --group docs

Option B: pip + venv

git clone https://github.com/DLR-KN/haxr
cd haxr
python3 -m venv .venv
source .venv/bin/activate
python -m pip install -e . --group dev --group docs

Pre-commit Hooks

To maintain code quality and avoid pushing invalid commits, we recommend using pre-commit hooks. These hooks perform automated checks before commits are made. To set up pre-commit hooks (part of the dev group), follow these steps:

pre-commit install

Optionally, run the hooks once on all files:

pre-commit run --all-files

Tests

We use pytest to orchestrate our tests. Run all tests via

uv run pytest

or, in a plain venv,

python -m pytest

Make sure to run tests before submitting a pull request to ensure that everything is functioning as expected.

Generate Documentation (optional)

We use Sphinx to automatically build the project documentation from the source tree and the docstrings in the codebase. All documentation-specific dependencies are bundled in the uv dependency group docs, so you can easily install them via

uv sync --group docs

Then, build the HTML docs:

uv run --group docs make -C docs html

and open docs/build/html/index.html in your browser.

Publishing to PyPI (maintainers)

This project uses uv to build and publish distributions manually (not part of the CI).

Build the sdist and wheel into dist/:

rm -rf dist/
uv build

and publish the artifacts in dist/ to PyPI:

uv publish