# Diagonalizing a 2x2 decision matrix

It's probably occurred to you that I've left you with four choices:

:::{table}
:align: center

| Command-line      | Notebook          |
| ----------------- | ----------------- |
| ROOT C++          | ROOT C++          |
| Python with ROOT  | Python with ROOT  |
:::

This tutorial is already too long, and I've taken longer than I
should have to offer you too many options. For simplicity, I've chosen
to present ROOT C++ on the command line in {ref}`cpath`, and Python with
ROOT in a Jupyter notebook in {ref}`pythonpath`. For {ref}`rdataframe`,
these choices don't matter much. 

If you choose to pursue one of the "off-diagonal" choices, you won't
have much trouble no matter which path you choose. You were previously introduced to
{ref}`ROOT C++ in a notebook <ckernel>`. To
run Python with ROOT on the command line (including magic commands), the
following will set you up on a Nevis particle-physics system:

    > module load root
    > ipython

{ref}`cpath` and {ref}`pythonpath` present the same commands,
exercises, and footnotes.[^f69] You might even be able to do both of
these parts; once you've learned C++, Python is pretty easy. Tack on
{ref}`rdataframe` for total ROOT mastery![^nope]

[^nope]: Uh, no. Remember, it takes a lifetime to learn ROOT. While it may take more than two
    days to go through all three instructional paths in this tutorial, it won't take
    your entire lifetime. 

:::{figure-md} matrix_transform-fig
:class: align-center

<img src="https://imgs.xkcd.com/comics/matrix_transform.png" alt="xkcd matrix_transform">

<https://xkcd.com/184/> by Randall Munroe
:::

[^f69]: The xkcd cartoons in the two parts are different, to give you an
    incentive to skim both.