gsw-xarray 0.2.1

Usage

import gsw_xarray as gsw

# Create a xarray.Dataset
import numpy as np
import xarray as xr
ds = xr.Dataset()
id = np.arange(3)
ds['id'] = xr.DataArray(id, coords={'id':id})
ds['CT'] = ds['id'] * 10
ds['CT'].attrs = {'standard_name':'sea_water_conservative_temperature'}
ds['SA'] = ds['id'] * 0.1 + 34
ds['SA'].attrs = {'standard_name':'sea_water_absolute_salinity'}

# Apply gsw functions
sigma0 = gsw.sigma0(SA=ds['SA'], CT=ds['CT'])
print(sigma0.attrs)

Outputs

{'standard_name': 'sea_water_sigma_t', 'units': 'kg/m^3'}

Don’t worry about usage with non xarray array objects, just use in all places you would the upstream library:

sigma0 = gsw.sigma0(id * 10, id * 0.1 + 34)
print(type(sigma0), sigma0)

Outputs

<class 'numpy.ndarray'> [-5.08964499  2.1101098   9.28348219]

Installation

pip install gsw_xarray

Contributor guide

All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. If you notice a bug or are missing a feature, fell free to open an issue in the GitHub issues page.

In order to contribute to gsw-xarray, please fork the repository and submit a pull request. A good step by step tutorial for starting with git can be found in the xarray contributor guide. A main difference is that we do not use conda as python environment, but poetry.

cd /path/to/your/gsw-xarray
poetry install

poetry shell

pytest gsw_xarray/tests