najuzilu / myst-parser.example-project

An self contained example project for testing and development of myst syntax using myst-parser

myst.example-project

An self contained example project for testing and development of myst syntax

Required software

• html theme: https://github.com/pandas-dev/pydata-bootstrap-sphinx-theme

Creating an environment to work with the MyST-parser

1. Run conda create -n myst_parser_env and source activate myst_parser_env where myst_parser_env is the name of the virutal environment
2. Run conda install pip which will install pip in your virtual environment
3. Find your anaconda environment directory, for example: opt/anaconda3/envs/myst_parser_env
4. Install package by doing: opt/anaconda3/envs/myst_parser_env/bin/pip install -e "git+https://github.com/ExecutableBookProject/MyST-Parser.git#egg=myst-parser[sphinx]"

Converting rST to MyST

We use the Pandoc package to convert files from rST to Pandoc syntax.

1. Install Pandoc package by running: brew install pandoc
2. Run the following bash script to convert from rST to Pandoc syntax:

FILES=source_rst/*.rst
for f in $FILES

do
	s="${f##*/}"                                         # remove path
	filename="source/${s%.*}-MyST"                       # remove file suffix
	echo "Converting $f to $filename.md"
	`pandoc $f -f rst -t markdown -o $filename.md`
done

Work in Progress

• Decision on MyST footnote reference: update this MyST file finite_markov-MyST.md
• Test cross-references: finite_markov has a potential test-case @JIT
• Comment label in math equation? % doesn't work
• Math labels are not always present post conversion (this information is not present at all in the document)
• Check whether using int footnote produces a bug for [^1]
• Add space: [Tau86]George Tauchen.
• References appear after citations by design. Does it make sense?
• Remove "\n" from citation because it does not render in MyST

rST to Pandoc to MyST

rST	Pandoc	MyST
---	\-\--	---
`P`	[P]{.title-ref}	`P`
`rich`	[rich]{.title-ref}	`rich`
:eq:`fin_mc_fr`	`fin_mc_fr`{.interpreted-text role="eq"}	{math:numref}`fin_mc_fr`
:doc:`lecture on AR(1) processes <ar1_processes>`	`lecture on AR(1) processes <ar1_processes>`{.interpreted-text role="doc"}	[lecture on AR(1) processes](ar1_processes)
:cite:`caplin1985variability`	`caplin1985variability`{.interpreted-text role="cite"}	{cite}`caplin1985variability`

1. Also .. code:: ipython3 > {.sourceCode .ipython3}

.. code-block:: python3

    P = [[0.4, 0.6], 
         [0.2, 0.8]]

```{.sourceCode .python3}
	P = [[0.4, 0.6], 
	     [0.2, 0.8]]
```

```python
P = [[0.4, 0.6], 
     [0.2, 0.8]]
```

.. _new_interp_sd:

This gives us another way to interpret the stationary distribution --- provided that the convergence result in :eq:`llnfmc0` is valid.

::: {#new_interp_sd}
This gives us another way to interpret the stationary distribution ---
provided that the convergence result in `llnfmc0`{.interpreted-text
role="eq"} is valid.
:::

(new_interp_sd)=

This gives us another way to interpret the stationary distribution --- provided that the convergence result in :eq:`llnfmc0` is valid.

.. code-block:: none

    d -> h;

``` {.sourceCode .none}
d -> h;
```

```
d -> h;
```

Even better, write a function that returns an instance of `QuantEcon.py's <http://quantecon.org/quantecon-py>`__ `MarkovChain` class.

Even better, write a function that returns an instance of
    [QuantEcon.py\'s](http://quantecon.org/quantecon-py)
    [MarkovChain]{.title-ref} class.

Even better, write a function that returns an instance of
    [QuantEcon.py\'s](http://quantecon.org/quantecon-py)
    `MarkovChain` class.

.. highlight:: python3

::: {.highlight}
python3
:::

******************
Inventory Dynamics
******************

Inventory Dynamics
==================

# Inventory Dynamics

************************************
:index:`Finite Markov Chains`
************************************

`Finite Markov Chains`{.interpreted-text role="index"}
======================================================

# Finite Markov Chains

.. contents:: :depth: 2

::: {.contents}

depth

:   2
:::

---
depth: 2
---

.. include:: /_static/includes/header.raw

```{note}
You can {download}`Download the source file for this page <./finite_markov-MyST.md>`
```

.. index::
    single: Markov process, inventory

::: {.index}
single: Markov process, inventory
:::

We can also approximate the distribution using a `kernel density estimator
<https://en.wikipedia.org/wiki/Kernel_density_estimation>`__. 

We can also approximate the distribution using a [kernel density
estimator
\<https://en.wikipedia.org/wiki/Kernel\_density\_estimation\>]{.title-ref}\_\_.

We can also approximate the distribution using a 
[kernel density estimator](https://en.wikipedia.org/wiki/Kernel_density_estimation/)

Note the broken link above.

HOWEVER

We will use a kernel density estimator from `scikit-learn <https://scikit-learn.org/stable/>`__

We will use a kernel density estimator from
[scikit-learn](https://scikit-learn.org/stable/)

We will use a kernel density estimator from
[scikit-learn](https://scikit-learn.org/stable/)

Note:

• Don't fully understand what :index: means in the lectures...

To do:

1. rST headings:

******************
Inventory Dynamics
******************

=========
----------
Documentation states that ********************** or ######## can also be used.