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authoryuichi-ike <yuichi.ike.1990@gmail.com>2020-05-22 10:22:31 +0900
committeryuichi-ike <yuichi.ike.1990@gmail.com>2020-05-22 10:22:31 +0900
commit2ccc5ea97a5979f80fec93863da5549e4e6f2eea (patch)
tree187d8a3b84d144755f63d69bd9581f4d662eca35 /src/python/doc
parentc4e93ba5f1d003c442e3d56d6a0b3e80651dd6ec (diff)
class name changed, documents modified
Diffstat (limited to 'src/python/doc')
-rw-r--r--src/python/doc/rips_complex_ref.rst4
-rw-r--r--src/python/doc/rips_complex_user.rst8
2 files changed, 7 insertions, 5 deletions
diff --git a/src/python/doc/rips_complex_ref.rst b/src/python/doc/rips_complex_ref.rst
index f781fd92..2aa6b268 100644
--- a/src/python/doc/rips_complex_ref.rst
+++ b/src/python/doc/rips_complex_ref.rst
@@ -32,9 +32,9 @@ Weighted Rips complex reference manual
DTM Rips complex reference manual
=================================
-.. autoclass:: gudhi.dtm_rips_complex.DtmRipsComplex
+.. autoclass:: gudhi.dtm_rips_complex.DTMRipsComplex
:members:
:undoc-members:
:show-inheritance:
- .. automethod:: gudhi.dtm_rips_complex.DtmRipsComplex.__init__ \ No newline at end of file
+ .. automethod:: gudhi.dtm_rips_complex.DTMRipsComplex.__init__ \ No newline at end of file
diff --git a/src/python/doc/rips_complex_user.rst b/src/python/doc/rips_complex_user.rst
index ac11a4b6..450e6c1a 100644
--- a/src/python/doc/rips_complex_user.rst
+++ b/src/python/doc/rips_complex_user.rst
@@ -378,6 +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 DTMRipsComplex class provides exactly this function.
.. testcode::
@@ -402,14 +403,15 @@ The output is:
DTM Rips Complex
----------------
-`DtmdRipsComplex <rips_complex_ref.html#dtm-rips-complex-reference-manual>`_ builds a simplicial complex from a point set or a full distence matrix (in the form of ndarray), as described in the above example.
+`DTMRipsComplex <rips_complex_ref.html#dtm-rips-complex-reference-manual>`_ builds a simplicial complex from a point set or a full distence 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::
import numpy as np
- from gudhi.dtm_rips_complex import DtmRipsComplex
+ from gudhi.dtm_rips_complex import DTMRipsComplex
pts = np.array([[2.0, 2.0], [0.0, 1.0], [3.0, 4.0]])
- dtm_rips = DtmRipsComplex(points=pts, k=2)
+ dtm_rips = DTMRipsComplex(points=pts, k=2)
st = dtm_rips.create_simplex_tree(max_dimension=2)
print(st.persistence())