xarray-subset-grid

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

Installation

pip compatible

This package is not yet released on pypi, for now install using git:

pip install xarray_subset_grid@git+https://github.com/asascience-open/xarray-subset-grid.git

Or clone the project from git and build / install it from there.

Usage

This package is designed to be used in conjuction 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 two "tasks":

• lint
• test

To run the tests in an isolated environment:

pixi run -e dev test

To run a shell to do dev work:

pixi shell -e dev

That will set up a conda environment with all the develop dependencies.

To run a shell in which you can run the examples:

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)