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-rw-r--r--src/Nerve_GIC/doc/Intro_graph_induced_complex.h8
1 files changed, 4 insertions, 4 deletions
diff --git a/src/Nerve_GIC/doc/Intro_graph_induced_complex.h b/src/Nerve_GIC/doc/Intro_graph_induced_complex.h
index f30d51a4..9d7883e0 100644
--- a/src/Nerve_GIC/doc/Intro_graph_induced_complex.h
+++ b/src/Nerve_GIC/doc/Intro_graph_induced_complex.h
@@ -93,9 +93,9 @@ namespace graph_induced_complex {
* \subsection gicexample Example
*
* This example builds the GIC of a point cloud sampled on a 3D human shape (human.off).
- * The cover C comes from the preimages of intervals (with length 0.1 and gain 0)
+ * The cover C comes from the preimages of intervals (with length 0.075 and gain 0)
* covering the height function (coordinate 2),
- * and the graph G comes from a Rips complex built with threshold 0.1.
+ * and the graph G comes from a Rips complex built with threshold 0.075.
* Note that if the gain is too big, the number of cliques increases a lot,
* which make the computation time much larger.
*
@@ -103,7 +103,7 @@ namespace graph_induced_complex {
*
* When launching:
*
- * \code $> ./GIC ../../../data/points/human.off 0.1 2 0.1 0
+ * \code $> ./GIC ../../../data/points/human.off 0.075 2 0.075 0
* \endcode
*
* the program output is:
@@ -159,7 +159,7 @@ namespace graph_induced_complex {
* <a target="_blank" href="https://github.com/MLWave/kepler-mapper"> Kepler-Mapper </a> library.
* One can visualize data by launching:
*
- * \code python visu.py && firefox SC_visu.html
+ * \code python visu.py && firefox SC.html
* \endcode
*
* \copyright GNU General Public License v3.