Skip to main content

Python package which will be used to ensure consistent data formats

Project description

cgul

Python package which will be used to ensure consistent data format when working with Xarray type data objects.

Usage

The primary function in cgul is cgul.translate_coords. This function operates on an xarray.Dataset or xarray.DataArray and translates the coordinates to the specified coordinate model. Several coordinate models are included in the package, and users are recommended to use the default CADS coordinate model. A typical use case woould be:

import xarray as xr
import cgul

infile = 'data_file.nc'
data = xr.open_dataset(infile)

# To harmonise the coordinates and unit names:
data_cgul = cgul.harmonise(
    data,
    coord_model=cgul.coordinate_models.CADS  # This is the default value, so optional in this case
)

# To just harmonise the coordinates:
data_cgul = cgul.translate_coordinates(
    data,
    coord_model=cgul.coordinate_models.CADS  # This is the default value, so optional in this case
)

It is is also possible to use command line executables to check files can be harmonised, or to produce netCDF files with harmonised coordinates and metadata:

# To check that $INFILE has contents that can be harmonised,
# this will print out the harmonised xarray.Dataset:
cgul harmonise --check $INFILE

# To produce an ouput file, $OUTFILE, which contains the harmonised version of
# the contents of $INFILE:
cgul harmonise --output $OUTFILE $INFILE

Workflow for developers/contributors

For best experience create a new conda environment (e.g. DEVELOP) with Python 3.10:

conda create -n DEVELOP -c conda-forge python=3.10
conda activate DEVELOP

Before pushing to GitHub, run the following commands:

  1. Update conda environment: make conda-env-update
  2. Install this package: pip install -e .
  3. Sync with the latest template (optional): make template-update
  4. Run quality assurance checks: make qa
  5. Run tests: make test
  6. Run the static type checker: make type-check
  7. Build the documentation (see Sphinx tutorial): make build-docs

License

Copyright 2017-2022, European Centre for Medium-Range Weather Forecasts (ECMWF).

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cgul-0.0.1.tar.gz (24.6 kB view details)

Uploaded Source

Built Distribution

cgul-0.0.1-py3-none-any.whl (20.3 kB view details)

Uploaded Python 3

File details

Details for the file cgul-0.0.1.tar.gz.

File metadata

  • Download URL: cgul-0.0.1.tar.gz
  • Upload date:
  • Size: 24.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.11

File hashes

Hashes for cgul-0.0.1.tar.gz
Algorithm Hash digest
SHA256 1c1c62b23b9336cb4fb5e2a7b0fe120e1bc17d905e626fa7a4685d9c2f12e916
MD5 ea0cd839ac4ef62897dec3cea016afb7
BLAKE2b-256 386eab57c5919156a166cd5cc86ee18b54c6662274077adf15a7aa9669e37d4c

See more details on using hashes here.

File details

Details for the file cgul-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: cgul-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 20.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.11

File hashes

Hashes for cgul-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 48bcdd8eaa899b409f4942f31864dccbe059f2e240877f926b229a500c4216ea
MD5 8c6037e6ec53c9069751a1aaf3fafff3
BLAKE2b-256 aa660d0da36bc55bb2aaab649e8e1b2c86da747d09adba7f75fbd25538d89805

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page