Skip to main content

Plugins for LADiM

Project description

Plugins for LADiM

This repository contains plugins for the Lagrangian Advection and Diffusion Model (LADiM), which is the particle tracking software used at the Institute of Marine Research (IMR). (https://github.com/bjornaa/ladim)

Documentation and examples are provided for each model.

List of available plugins

Name Description
chemicals Passive tracer
egg Buoyant fish eggs
lunar_eel Glass eels with lunar compass
nk800met Module for utilizing forcing data from the met.no thredds server
release General module for creating release files
salmon_lice Salmon lice larvae
sandeel Sand eel larvae
sedimentation Sinking particles
utils General utility functions for IBMs

Installation

Install using the following commands (the first command can be skipped if LADiM is already present on your system):

pip install git+https://github.com/pnsaevik/ladim.git
pip install git+https://github.com/pnsaevik/ladim_plugins.git

The installation can be tested with the command

pytest -Wignore --pyargs ladim_plugins

This command will run ladim on each of the plugins, using the sample ladim.yaml and particle.rls files found in the subpackage folders. The tests succeed if ladim is present on the system, ladim_plugins is installed correctly, and the output from the ladim runs matches exactly with the out.nc files found in the subpackage folders.

Usage

  1. Copy ladim.yaml and particle.rls from the IBM subpackage of interest into the working directory.
  2. Make desired changes to the yaml and rls files. More detailed instructions are found in the README.md file within the subpackage.
  3. Run ladim and the output is written to out.nc.

Contribute

To add new plugins, contact the maintainer of the ladim_plugins repository. A properly structured IBM subpackage has the following ingredients:

  1. A file __init__.py containing the statement from .ibm import IBM
  2. The IBM module itself, named ibm.py
  3. A README.md file containing instructions for use
  4. A simple test example. This includes a ladim.yaml configuration file, a particles.rls release file, a forcing.nc forcing file (may be copied from another subpackage), and a ladim output file named out.nc.
  5. Optionally a test example for generating release files. This includes a release.yaml configuration file and an output release file named out.rls.
  6. Optionally additional automated test modules, named test_*.py

An ideal test example should be quick to run and easy to analyze, but still be complicated enough to demonstrate most capabilities of the IBM model. To achieve this, it may be a good idea to use only a few time steps and a few particles at selected positions. In some cases it may also be necessary to specify somewhat unrealistic particle parameters to demonstrate certain features.

The test is run using the command pytest -Wignore --pyargs ladim_plugins. The test succeeds if ladim is able to run the examples, and the output matches the contents of out.nc / out.rls.

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

ladim_plugins-2.1.0.tar.gz (22.4 MB view details)

Uploaded Source

Built Distribution

ladim_plugins-2.1.0-py3-none-any.whl (22.5 MB view details)

Uploaded Python 3

File details

Details for the file ladim_plugins-2.1.0.tar.gz.

File metadata

  • Download URL: ladim_plugins-2.1.0.tar.gz
  • Upload date:
  • Size: 22.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for ladim_plugins-2.1.0.tar.gz
Algorithm Hash digest
SHA256 10bf21c8571b43b83aaf7c5573c565578563bc0f48a1a9c9d2ec672fde8ea541
MD5 abcc2663d0a5a252150ee3e3f41de7cb
BLAKE2b-256 9aa8fd7220b48bc1a2519eb8daf62989d19c70b5c80f2f136cffa29a4f6ddb4e

See more details on using hashes here.

File details

Details for the file ladim_plugins-2.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for ladim_plugins-2.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 adbfa7cc55ddeb419cf3e0c047a971e9af307b200a8b09ba342b1210c703b9c5
MD5 c2ef3639770129a00f572e58a4072665
BLAKE2b-256 b99421d51b9d29d46b90469357970fcc615e29760ad8704d6f371e2dcd7e77f6

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