Skip to main content

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 project-arrakis

LPT Algorithms:

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

Metadata

Release files for project-arrakis 0.1.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for project-arrakis 0.1.2
File Interpreter ABI Platform
project_arrakis-0.1.2-py3-none-any.whl Python 3 none any Details

Release files / project_arrakis-0.1.2-py3-none-any.whl

Download URL project_arrakis-0.1.2-py3-none-any.whl
Size 45.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
23dd36890f0e57a6e965b44c4434ce8846250b0d1166fa5763ebaa94efb7d508
BLAKE2b-256 checksum
How to use checksums
cdaec659456f4e51881e2f736a27e8997c87d87a85b098a50c9cfd7f52f03c9b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.10.12

Release history Release notifications | RSS feed

This release

0.1.2 This release

1 release file

0.1.1

2 release files

0.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page