General
=======

Overview
--------

``treegp`` is a python gaussian process code that perform 1D and 2D interpolation.

``treegp`` have some specific features compared to other gaussian processes available code:

*   Hyperparameters estimation will scale in :math:`{\cal{O}}(N \log(N))` with the the 2-points correlation function estimation compared to :math:`{\cal{O}}(N^3)` with the classical maximum likelihood.
    
*   Gaussian process interpolation can be performed around a mean function
    
*   Tools are given to compute the mean function (``meanify``)

``treegp`` was originally developed for Point Spread Function interpolation within `Piff <https://github.com/rmjarvis/Piff>`_. There is a specific article that describes the math used in ``treegp`` in the context of modelling astrometric shifts of the Subaru Telescope due to atmospheric turbulences. This article can be found 
`here <https://arxiv.org/abs/2103.09881>`_.


Installation
------------

The easiest way to install is usually::

  pip install treegp

which will install the latest released version.

If you would instead like to install the development version, you can do so via::

  git clone https://github.com/PFLeget/treegp.git
  cd treegp/
  python setup.py install


Dependencies
------------

``treegp`` has for now the following dependencies (see the quick
installs below):

- libraries listed in the `requirements <requirements.txt>`_ file


Python
``````

``treegp`` is regularly tested on Python 3.7, 3.8, 3.9 and 3.10.  It may work in other
versions of Python (e.g. pypy), but these are not currently supported.