Metadata-Version: 2.1
Name: lptlib
Version: 0.0.1a9
Summary: One-way coupled Lagrangian Particle Tracking algorithms.
Author: Dilip Kalagotla
Author-email: dilipkalagotla@gmail.com
Project-URL: homepage, https://github.com/kalagotla/project-arrakis
Project-URL: issues, https://github.com/kalagotla/project-arrakis/issues
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: pandas
Requires-Dist: seaborn
Requires-Dist: tqdm

# lptlib (Lagrangian Particle Tracking Library)
### Previously project-arrakis

Python based particle tracking algorithms for CFD data

A highly parallelized set of Lagrangian Particle Tracking (LPT) algorithms based on Python to post-process steady and unsteady CFD data. An advanced programming interface (API) is developed for uncertainty quantification of optical velocimetry data.

# Installation:
Run the following command in the terminal to install the package:
```pip install lptlib```

### LPT Algorithms:

A sample code to start off is presented in main.py
