Create PC algo tutorial

Signed-off-by: Robert Ness <robertness@gmail.com>
py-why · Dec 31, 2022 · d8d85af · d8d85af
1 parent 4d9a788
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Showing 10 changed files with 510 additions and 15 deletions.
diff --git a/.gitignore b/.gitignore
@@ -8,6 +8,10 @@ __pycache__/
 # C extensions
 *.so
 
+# possibly produced from drawing graphs
+*.gv
+*.png
+
 junit-results.xml
 
 # Distribution / packaging

diff --git a/README.md b/README.md
@@ -49,5 +49,8 @@ To install the package from github, clone the repository and then `cd` into the
     # for graph functionality
     poetry install --extras graph_func
 
+    # to load datasets used in tutorials
+    poetry install --extras data
+
     # if you would like an editable install of dodiscover for dev purposes
     pip install -e .
diff --git a/doc/conf.py b/doc/conf.py
@@ -263,6 +263,10 @@
     "image_scrapers": scrapers,
 }
 
+# prevent jupyter notebooks from being run even if empty cell
+nbsphinx_execute = "never"
+nbsphinx_allow_errors = True
+
 # Custom sidebar templates, maps document names to template names.
 html_sidebars = {
     "index": ["search-field.html"],

diff --git a/doc/index.rst b/doc/index.rst
@@ -15,13 +15,13 @@ Contents
 --------
 
 .. toctree::
-   :maxdepth: 1
+   :maxdepth: 2
    :caption: Getting started:
 
    installation
    api
    use
-   tutorials
+   tutorials/index
    whats_new
 
 .. toctree::

diff --git a/doc/tutorials.rst b/doc/tutorials.rst
diff --git a/doc/tutorials/index.rst b/doc/tutorials/index.rst
@@ -0,0 +1,18 @@
+*********
+Tutorials
+*********
+
+.. _models_tutorials:
+
+Basic causal discovery models without latent confounders
+========================================================
+The first tutorial presents several algorithms for causal discovery without latent confounding: the Peters and Clarke (PC) algorithm. 
+These models provide a basis for learning causal structure from data when we make the **assumption** that there are
+no latent confounders.
+
+.. toctree::
+   :maxdepth: 1
+   :titlesonly:
+
+   markovian/pc
+