tutorials: better presentation

epfl-lts2 · Aug 13, 2017 · cd1268b · cd1268b
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diff --git a/doc/tutorials/demo.rst b/doc/tutorials/demo.rst
@@ -1,6 +1,6 @@
-========
-GSP Demo
-========
+=========================
+Introduction to the PyGSP
+=========================
 
 This tutorial shows basic operations of the toolbox.
 To start open a python shell (IPython is recommended here) and import the pygsp. You would probably also import numpy as you will need it to create matrices and arrays.
@@ -14,7 +14,6 @@ The first step is to create a graph, there's a general class that can be used to
 >>> W = np.random.rand(400, 400)
 >>> G = pygsp.graphs.Graph(W)
 
-
 You have now a graph structure ready to be used everywhere in the box! Check the :ref:`reference-guide` to know more about the Graph class and it's subclasses.
 You can also check the included methods for all graphs with the usual help function.
 
@@ -70,8 +69,7 @@ You can also put multiple functions in a list to define a filterbank!
 
 Here's our low pass filter.
 
-
-To accompain our new filter, let's create a nice signal on the logo by setting each letter to a certain value and then adding some random noise.
+To go with our new filter, let's create a nice signal on the logo by setting each letter to a certain value and then adding some random noise.
 
 >>> f = np.zeros((G.N,))
 >>> f[G.info['idx_g']-1] = - 1
@@ -92,7 +90,6 @@ Finally here's the noisy signal and the denoised version right under.
 .. image:: img/noisy_logo.*
 .. image:: img/denoised_logo.*
 
-So here are the basics for the PyGSP toolbox, if you want more informations you can check the doc in :ref:`the reference guide section <reference-guide>`.
-
+So here are the basics for the PyGSP toolbox, please check the other tutorials or the `reference guide <reference-guide>` for more.
 
 Enjoy the toolbox!
diff --git a/doc/tutorials/demo_graph_tv.rst b/doc/tutorials/demo_graph_tv.rst
@@ -1,9 +1,9 @@
-************************************************************************
-GSP Graph TV Demo - Reconstruction of missing sample on a graph using TV
-************************************************************************
+=====================================================
+Reconstruction of missing samples on a graph using TV
+=====================================================
 
 Description
-###########
+-----------
 
 Reconstruction of missing sample on a graph using TV
 
@@ -39,7 +39,7 @@ This previous problem has an identical solution as:
 It is simply a projection on the B2-ball.
 
 Results and code
-################
+----------------
 
 >>> from pygsp import graphs, plotting
 >>> import numpy as np
@@ -98,9 +98,8 @@ mask and addition of noise. More than half of the vertices are set to 0.
 
 This figure shows the reconstructed signal thanks to the algorithm.
 
-
 Comparison with Tikhonov regularization
-#######################################
+---------------------------------------
 
 We can also use the Tikhonov regularizer that will promote smoothness.
 In this case, we solve:

diff --git a/doc/tutorials/demo_pyramid.rst b/doc/tutorials/demo_pyramid.rst
@@ -1,8 +1,8 @@
-================
-GSP Demo Pyramid
-================
+============================================
+Graph multiresolution: reduction and pyramid
+============================================
 
-In this demonstration file, we show how to reduce a graph using the GSPBox. Then we apply the pyramid to simple signal.
+In this demonstration file, we show how to reduce a graph using the PyGSP. Then we apply the pyramid to simple signal.
 To start open a python shell (IPython is recommended here) and import the required packages. You would probably also import numpy as you will need it to create matrices and arrays.
 
 >>> import numpy as np

diff --git a/doc/tutorials/demo_wavelet.rst b/doc/tutorials/demo_wavelet.rst
@@ -1,8 +1,6 @@
-================
-GSP Wavelet Demo
-================
-
-* Introduction to spectral graph wavelet with the PyGSP
+=======================================
+Introduction to spectral graph wavelets
+=======================================
 
 Description
 -----------

diff --git a/doc/tutorials/index.rst b/doc/tutorials/index.rst
@@ -6,7 +6,7 @@ The following are some tutorials which show and explain how to use the toolbox
 to solve some real problems.
 
 .. toctree::
-    :maxdepth: 2
+    :maxdepth: 1
 
     demo
     demo_wavelet