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Kde

Kernel Density Estimation: accelerated, multi-dimensional, and adaptive bandwidth

Install / Use

/learn @icecube/Kde
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

kde

Multi-dimenstional Kernel Density Estimation (KDE) including adaptive bandwidths and C and CUDA implementations for specific cases.

Authors

Sebastian Schoenen (schoenen@physik.rwth-aachen.de) and Martin Leuermann for the IceCube collaboration.

Installation Instructions

Download the software into directory <DIR>. There should be a subdirectory named "kde" within the <DIR> directory.

To install in a location independent of your system Python files, install via the following command:

$ pip install <DIR>[cuda] --user

where [cuda] is optional, ensuring support for GPU.

To install with references to the source code where it is downloaded (so that changes in the sourcecode are reflected immediately):

$ pip install -e <DIR>[cuda] --user

View on GitHub
GitHub Stars14
CategoryDevelopment
Updated8mo ago
Forks8

Languages

Python

Security Score

82/100

Audited on Jul 25, 2025

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