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

. There should be a subdirectory named "kde" within the directory.

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

$ pip install

[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

[cuda] --user