New tutorial on builtin configs

.gitignore

@@ -70,3 +70,6 @@ doc/source/auto_examples/
 
 # do not commit nose tests files
 *.noseids
+
+# no pip wheel metadata
+pip-wheel-metadata/

examples/tutorials/tuto_plot_basic.py

@@ -2,8 +2,7 @@
 Getting started: 5 minutes tutorial for `tofu`
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-This is a tutorial that aims to get a new user a little familiar with tofu's
- structure.
+This is a tutorial that aims to get a new user a little familiar with tofu's structure.
 """
 
 # The following imports matplotlib, preferably using a

examples/tutorials/tuto_plot_gallery_fusion_machines.py

@@ -0,0 +1,38 @@
+"""
+A gallery of Fusion Machines
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+This tutorial functions as a gallery of fusion machines that can easily be loaded with `tofu`.
+"""
+
+###############################################################################
+# We start by importing `tofu`.
+
+import tofu as tf
+
+###############################################################################
+# `tofu` provides a geometry helper function that allows creating a configuration with a single call.
+#
+# Calling with empty arguments results in a default configuration. At the time of writing, this is ITER.
+# By printing the `config` object, a text representation of its components is printed. This allows inspecting
+# component names, number of sections, color or visibility.
+
+config = tf.geom.utils.create_config()
+print(config)
+
+###############################################################################
+# To get a list of all available built-in configs, one has to know some details about `tofu`.
+# Configurations can either be accessed by names (ITER, WEST, JET).
+
+print(tf.geom.utils._DCONFIG_TABLE.keys())
+
+###############################################################################
+# With that being said, let's create a gallery of the "top 3" fusion machines provided by `tofu` to accelerate
+# diagnostic development.
+
+import matplotlib.pyplot as plt
+
+fig, ax = plt.subplots()
+for fusion_machine in ['ITER', 'WEST', 'JET']:
+    config = tf.geom.utils.create_config(fusion_machine)
+    config.plot()