xarray-subset-grid

Subset Xarray datasets in space while retaining the original grid for complex grid systems.

Installation

pip compatible

This package is available on pypi:

python -m pip install xarray-subset-grid

And also on conda-forge:

conda install -c conda-forge xarray-subset-grid

Usage

This package is designed to be used in conjunction with xarray. Given a CF Compliant xarray dataset named ds, this package can be accessed using the xsg accessor:

# Get the interprested grid class
grid = ds.xsg

# subset to only include temperature
ds_temp = ds.xsg.subset_vars(["temp"])

# subset by bounding box
ds_subset_bbox = ds.xsg.subset_bbox([-72, 32, -70, 35])

# or by polygon
poly = np.array(
    [
        [-72, 32],
        [-72, 33],
        [-73, 33],
        [-73, 31],
        [-72, 32],
    ]
)
ds_subset_poly = ds.xsg.subset_polygon(poly)

For full usage, see the example notebooks

Development

pip compatible

First, create a new virtualenv and activate it:

python -m venv venv
source venv/bin.activate

Then install the project in local edit mode:

pip install -e .

Once installed, the tests can be run:

python -m pytest

Or alternatively run the notebooks in the same virtualenv

pixi

Learn about pixi here: https://prefix.dev/

See the pixi docs for details, but for this setup:

There are three "environments" set up for pixi:

  • default
  • dev
  • examples

And three "tasks":

  • lint
  • test : run most of the tests
  • test_all : run the tests that access AWS -- i.e. download data directly.

To run the tests in an isolated environment:

pixi run -e dev test

Or with a specific python version:

pixi run -e test312 test

Options are: test310 test311 test312 test313

To run a shell to do dev work:

pixi shell -e dev

To run a shell in which you can run the examples (notebooks and al that):

pixi shell -e examples

To run a shell with everything (dev and example deps:

pixi shell -e all

Finally, to when the pyproject.toml is updated, be sure to update the pixi lockfile:

pixi install

conda

If you are using (or want to use) conda, you can install the dependencies with:

conda install --file conda_requirements.txt

That will get you the full set, including what you need to run the examples, etc.

If you need the development tools, you can also install:

conda install --file conda_requirements_dev.txt

(requirements should all be on the conda-forge channel)

Project links

Data verified by PyPI on Feb 11, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

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Owner

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1 maintainer

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Avatar for ChrisBarker-NOAA from gravatar.com ChrisBarker-NOAA

Credits

Author: Matthew Iannucci

GitHub Statistics

Data verified by PyPI on Feb 11, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

BSD License (BSD 3-Clause License)

Requires

Python >=3.10

Provides Extra

dev examples

Tags

xarray

Classifiers

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