A collection of tools to integrate WPS geogrid binary datasets into the xarray ecosystem. This package provides a function to open geogrid datasets, a configuration to change output format and a function to write data to disk.
To open a WPS geogrid dataset located under <path>, use:
import wps_xr
ds = wps_xr.open_dataset(<path>)
This provides the data in an xarray.Dataset object.
It also populates the donfig object wps_xr.config, which contains the configuration to be eventually written to the index file.
The routine to write data to disk is provided via the wps accessor.
An example for usgs data might look like this:
ds.wps.to_disk(<output_path>, var="usgs", tile_size=(1200,1200), force=True)
This method will not use the global and variable attributes. For output format configuration, please refer to the next section.
At the moment, the Dataset and DataArray attributes are only populated once and don't have an impact on the data being written to disk.
If you want to change the way the data is written, you have to use the index dict in the donfig object populated by open_dataset.
from wps_xr import config
config.set({"index.missing_value": -9999})
The wps accessor also provides a convenient plotting method:
ds.wps.plot(var="usgs")
It is mainly concerned with building the correct colorbar when encountering categorical data.
Dependencies in this package are managed by conda and poetry.
To install this package follow the following steps:
conda env create -f ci/environment.yml && conda activate wps_xr
poetry build wheel
Then the wps-xr*.whl file is built in ./dist/ and can be installed using pip install <file>.
In order to develop this package, again use conda and poetry.
conda env create -f ci/environment.yml && conda activate wps_xr
poetry install
Then the pytest-powered testing can be run using poetry run pytest .
To use pre-commit, after installing the dependencies execute poetry run pre-commit install.
- Add projections other than
regular_ll - Drop hard
daskdependency - Add tests for
index.missing_value