Skip to main content

Efficient and lazy computation of Water Mass Budgets in arbitrary sub-domains of C-grid ocean models

Project description

xwmb

xWMB is a Python package that provides a efficient and lazy computation of Water Mass Budgets in arbitrary sub-domains of C-grid ocean models. Most of the heavy lifting is done by dependency packages by the same team of developers:

  • sectionate: for computing transports normal to a section (open or closed)
  • regionate: for converting between gridded masks and the closed sections that bound them
  • xbudget: for model-agnostic wrangling of multi-level tracer budgets
  • xwmt: for computing bulk water mass transformations from these budgets

Documentation is not yet available, but the core API is illustrated in the example notebooks here and in each of the dependency packages.

If you use xwmb, please cite the companion manuscript: Henri F. Drake, Shanice Bailey, Raphael Dussin, Stephen M. Griffies, John Krasting, Graeme MacGilchrist, Geoffrey Stanley, Jan-Erik Tesdal, Jan D. Zika. Water Mass Transformation Budgets in Finite-Volume Generalized Vertical Coordinate Ocean Models. Journal of Advances in Modeling Earth Systems. 08 March 2025. DOI: doi.org/10.1029/2024MS004383

Quick Start Guide

Minimal installation within an existing environment

pip install xwmb

Installing from scratch using conda

This is the recommended mode of installation for developers.

git clone git@github.com:hdrake/xwmb.git
cd xwmb
conda env create -f docs/environment.yml
conda activate docs_env_xwmb
pip install -e .

You can verify that the package was properly installed by confirming it passes all of the tests with:

pytest -v

You can launch a Jupyterlab instance using this environment with:

python -m ipykernel install --user --name docs_env_xwmb --display-name "docs_env_xwmb"
jupyter-lab

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

xwmb-0.5.2.tar.gz (396.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

xwmb-0.5.2-py3-none-any.whl (8.3 kB view details)

Uploaded Python 3

File details

Details for the file xwmb-0.5.2.tar.gz.

File metadata

  • Download URL: xwmb-0.5.2.tar.gz
  • Upload date:
  • Size: 396.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.2

File hashes

Hashes for xwmb-0.5.2.tar.gz
Algorithm Hash digest
SHA256 d0f7cb94ed62119d66f3f45afe91bc1f92a0a6c240618693d6f48a9697e1aa28
MD5 08968470f03d46a74d2b3152aaf14ee6
BLAKE2b-256 b60a7283610a4f506584769401a919d4f4b8ca51082226ea4fe3ebdb4d5eaece

See more details on using hashes here.

File details

Details for the file xwmb-0.5.2-py3-none-any.whl.

File metadata

  • Download URL: xwmb-0.5.2-py3-none-any.whl
  • Upload date:
  • Size: 8.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.2

File hashes

Hashes for xwmb-0.5.2-py3-none-any.whl
Algorithm Hash digest
SHA256 467c61c15780ac886beaa140eb3c161e68989bf12f94198a48d245be8f9be776
MD5 972654c9062f5049acfc59b911e68c6a
BLAKE2b-256 bd5304a12b2d759b94a279ddbe86ac8d1e2b10df69321eb9b9b664c702e0ca87

See more details on using hashes here.

Supported by

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