From 5141caeff03f1e8c8c4ccae1ee7ca43fbcb2925f Mon Sep 17 00:00:00 2001
From: ROUVREAU Vincent <vincent.rouvreau@inria.fr>
Date: Sun, 31 May 2020 11:01:24 +0200
Subject: It was not markdown but rst...

---
 src/python/CMakeLists.txt   |  2 +-
 src/python/introduction.md  | 30 ------------------------------
 src/python/introduction.rst | 33 +++++++++++++++++++++++++++++++++
 src/python/setup.py.in      |  2 +-
 4 files changed, 35 insertions(+), 32 deletions(-)
 delete mode 100644 src/python/introduction.md
 create mode 100644 src/python/introduction.rst

(limited to 'src/python')

diff --git a/src/python/CMakeLists.txt b/src/python/CMakeLists.txt
index d4cb7477..fee6b6f5 100644
--- a/src/python/CMakeLists.txt
+++ b/src/python/CMakeLists.txt
@@ -236,7 +236,7 @@ if(PYTHONINTERP_FOUND)
     file(COPY "gudhi/weighted_rips_complex.py" DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/gudhi")
 
     # Other .py files
-    file(COPY "introduction.md" DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/")
+    file(COPY "introduction.rst" DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/")
 
     add_custom_command(
         OUTPUT gudhi.so
diff --git a/src/python/introduction.md b/src/python/introduction.md
deleted file mode 100644
index 3277e0ac..00000000
--- a/src/python/introduction.md
+++ /dev/null
@@ -1,30 +0,0 @@
-![](https://gudhi.inria.fr/images/gudhi_architecture.png)
-
-#Introduction
-
-The Gudhi library is an open source library for Computational Topology and
-Topological Data Analysis (TDA). It offers state-of-the-art algorithms
-to construct various types of simplicial complexes, data structures to
-represent them, and algorithms to compute geometric approximations of shapes
-and persistent homology.
-
-The GUDHI library offers the following interoperable modules:
-* Complexes:
-   * Cubical
-   * Simplicial: Rips, Witness, Alpha and Čech complexes
-   * Cover: Nerve and Graph induced complexes
-* Data structures and basic operations:
-   * Simplex tree, Skeleton blockers and Toplex map
-   * Construction, update, filtration and simplification
-* Topological descriptors computation
-* Manifold reconstruction
-* Topological descriptors tools:
-   * Bottleneck distance
-   * Statistical tools
-   * Persistence diagram and barcode
-
-For more information about Topological Data Analysis and its workflow, please
-refer to the [Wikipedia TDA dedicated page][1].
-
- [1]: https://en.wikipedia.org/wiki/Topological_data_analysis
-
diff --git a/src/python/introduction.rst b/src/python/introduction.rst
new file mode 100644
index 00000000..2cc4642e
--- /dev/null
+++ b/src/python/introduction.rst
@@ -0,0 +1,33 @@
+.. figure::
+    https://gudhi.inria.fr/images/gudhi_architecture.png
+    :figclass: align-center
+    :width: 100 %
+    :alt: GUDHI
+
+Introduction
+============
+
+The Gudhi library is an open source library for Computational Topology and
+Topological Data Analysis (TDA). It offers state-of-the-art algorithms
+to construct various types of simplicial complexes, data structures to
+represent them, and algorithms to compute geometric approximations of shapes
+and persistent homology.
+
+The GUDHI library offers the following interoperable modules:
+
+* Complexes:
+   * Cubical
+   * Simplicial: Rips, Witness, Alpha and Čech complexes
+   * Cover: Nerve and Graph induced complexes
+* Data structures and basic operations:
+   * Simplex tree, Skeleton blockers and Toplex map
+   * Construction, update, filtration and simplification
+* Topological descriptors computation
+* Manifold reconstruction
+* Topological descriptors tools:
+   * Bottleneck distance
+   * Statistical tools
+   * Persistence diagram and barcode
+
+For more information about Topological Data Analysis and its workflow, please
+refer to the `Wikipedia TDA dedicated page <https://en.wikipedia.org/wiki/Topological_data_analysis>`_.
diff --git a/src/python/setup.py.in b/src/python/setup.py.in
index ff000a2c..4725bb44 100644
--- a/src/python/setup.py.in
+++ b/src/python/setup.py.in
@@ -65,7 +65,7 @@ for module in pybind11_modules:
 
 # read the contents of introduction.md
 this_directory = path.abspath(path.dirname(__file__))
-with open(path.join(this_directory, 'introduction.md'), encoding='utf-8') as f:
+with open(path.join(this_directory, 'introduction.rst'), encoding='utf-8') as f:
     long_description = f.read()
 
 setup(
-- 
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