Metadata-Version: 2.4
Name: oceantracker
Version: 0.5.2.50
Summary: Fast offline Lagrangian particle tracking in the Ocean
Home-page: https://oceantracker.github.io/oceantracker/
Author: Ross Vennell & Laurin Steidle
Author-email: ross.vennell@cawthron.org.nz
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Oceanography
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE.md
Requires-Dist: numpy
Requires-Dist: numba
Requires-Dist: netcdf4
Requires-Dist: xarray
Requires-Dist: scipy
Requires-Dist: pyproj
Requires-Dist: setuptools
Requires-Dist: psutil
Requires-Dist: matplotlib
Requires-Dist: pyyaml
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-dist
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Dynamic: summary

# OceanTracker

## Fast particle tracking in structure and unstructured grids

OceanTracker is a fast extendable code for offline particle tracking in structured and  unstructured grids [1].
OceanTracker currently  supports structured grid ROMs and GLORYS (NEMO/COPERNICUS) 
for fixed z level vertical grids and unstructured grids of SCHISM 
(both original netcdf format and new format with variables split between files) and DELFT3D-FM.
Other formats added on request. 

Fast computational approaches to numerical interpolation makes OceanTracker extremely fast even on a single computer core [2]. 
In addition, intense computations are split to run in parallel across available physical computer cores.

OceanTracker’s speed enables millions of particles to be simulated. This significantly increases 
the range of particle behaviours that can be modeled and the quality of statistics derived from the particles. 
To eliminate the need to store and wade through the analysis of vast volumes of recorded particle tracks, the code has 
the ability to calculate statistics on the fly, such as heat maps and connectivity between regions.

OceanTracker code is highly flexible and extendable by the user, whether run by a new user with a text file of 
parameters, or by an expert adding their specialised code for novel particle behaviours or statistics, to the computational pipe line


[More about Ocean tracker and gallery](https://oceantracker.github.io/oceantracker/)

[Installing Oceantracker](https://oceantracker.github.io/oceantracker/_build/html/info/installing.html)

[Oceantracker User Guide](https://oceantracker.github.io/oceantracker/_build/html/info/users_guide.html)
  
[Running Oceantracker ](https://oceantracker.github.io/oceantracker/_build/html/info/running_ocean_tracker.html)

[Howto tutorials](https://oceantracker.github.io/oceantracker/_build/html/info/how_to.html)

[1] Vennell, R.,Steidle. L.,  Scheel, M.,Chaput. R., Knight, B. and Smeaton, M, OceanTracker 0.5: Fast Adaptable Lagrangian Particle Tracking in
Structured and Unstructured Grid, preprint, https://eartharxiv.org/repository/view/8387/ 

[2] Vennell, R., Scheel, M., Weppe, S., Knight, B. and Smeaton, M., 2021. Fast lagrangian particle tracking in unstructured ocean model grids , Ocean Dynamics, 71(4), pp.423-437.
