How-to: asap kde
=========

``asap kde sub_command`` is for performing kernel density estimation of the data. One can do the cluster using the high-dimensional design matrix generated by ``asap gen_desc``, or the low-dimensional projections of the design matrix generated by the command ``asap map``. 

Overview of sub-commands
------------------------

sub-commands that select the specific algorithm for kernel density estimations:

==============  =======================================
option          description 
==============  =======================================
  kde_internal  Internal implementation of KDE
  kde_scipy     Scipy implementation of KDE
  kde_sklearn   Scikit-learn implementation of KDE
  plot_pca      Plot the KDE results using a PCA map
==============  =======================================


.. click:: asaplib.cli.cmd_asap:kde
   :prog: asap kde
   :nested: full

.. note::  More documentation to be added.