doc review: use :class: to link to the ref manual, rollback link to the user manual

1 files changed, 2 insertions, 2 deletions

diff --git a/src/python/doc/rips_complex_user.rst b/src/python/doc/rips_complex_user.rst
index 868ef0e7..6048cc4e 100644
--- a/src/python/doc/rips_complex_user.rst
+++ b/src/python/doc/rips_complex_user.rst
@@ -378,7 +378,7 @@ Example from a point cloud combined with DistanceToMeasure
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 Combining with DistanceToMeasure, one can compute the DTM-filtration of a point set, as in `this notebook <https://github.com/GUDHI/TDA-tutorial/blob/master/Tuto-GUDHI-DTM-filtrations.ipynb>`_. 
-Remark that `DTM Rips Complex (user manual) <rips_complex_user.html#dtm-rips-complex>`_ class provides exactly this function.
+Remark that `DTMRipsComplex <rips_complex_user.html#dtm-rips-complex>`_ class provides exactly this function.
 
 .. testcode::
 
@@ -403,7 +403,7 @@ The output is:
 DTM Rips Complex
 ----------------
 
-`DTMRipsComplex (reference manual) <rips_complex_ref.html#dtm-rips-complex-reference-manual>`_ builds a simplicial complex from a point set or a full distance matrix (in the form of ndarray), as described in the above example.
+:class:`~gudhi.dtm_rips_complex.DTMRipsComplex` builds a simplicial complex from a point set or a full distance matrix (in the form of ndarray), as described in the above example.
 This class constructs a weighted Rips complex giving larger weights to outliers, which reduces their impact on the persistence diagram. See `this notebook <https://github.com/GUDHI/TDA-tutorial/blob/master/Tuto-GUDHI-DTM-filtrations.ipynb>`_ for some experiments.
 
 .. testcode::