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Diffstat (limited to 'src/python/doc/nerve_gic_complex_user.rst')
| -rw-r--r-- | src/python/doc/nerve_gic_complex_user.rst | 7 |
1 files changed, 2 insertions, 5 deletions
diff --git a/src/python/doc/nerve_gic_complex_user.rst b/src/python/doc/nerve_gic_complex_user.rst index 0e67fc78..8633cadb 100644 --- a/src/python/doc/nerve_gic_complex_user.rst +++ b/src/python/doc/nerve_gic_complex_user.rst @@ -12,7 +12,7 @@ Definition Visualizations of the simplicial complexes can be done with either neato (from `graphviz <http://www.graphviz.org/>`_), `geomview <http://www.geomview.org/>`_, -`KeplerMapper <https://github.com/MLWave/kepler-mapper>`_. +`KeplerMapper <https://github.com/scikit-tda/kepler-mapper>`_. Input point clouds are assumed to be OFF files (cf. `OFF file format <fileformats.html#off-file-format>`_). Covers @@ -50,7 +50,7 @@ The cover C comes from the preimages of intervals (10 intervals with gain 0.3) covering the height function (coordinate 2), which are then refined into their connected components using the triangulation of the .OFF file. -.. testcode:: +.. code-block:: python import gudhi nerve_complex = gudhi.CoverComplex() @@ -99,9 +99,6 @@ the program output is: [-0.171433, 0.367393] [-0.909111, 0.745853] 0 interval(s) in dimension 1: - -.. testoutput:: - Nerve is of dimension 1 - 41 simplices - 21 vertices. [0] [1] |