This repository contains persistent homology related code which can be used to implement the approaches from [1] and [2] (see References)
A final code release is planned for late 2017.
The pershombox
package is dependent on some third party software tools which we do not provide here.
In order to install pershombox
you have to get those executables and tell pershombox
where
to find them by editing the corresponding entry in
pershombox/_software_backends/software_backends.cfg
.
Where to find the executables/sources and which software_backends.cfg
entry corresponds to them
is listed below.
Do not forget to chmod
executables on Unix-based systems!
-
DIPHA
: Source code. Entry:dipha
. -
Perseus
: Source code or precompiled executables. Entry:perseus
. -
hera
: Source code. We need thewasserstein_dist
executable ingeom_matching/wasserstein
. Entry:hera_wasserstein_dist
.
We plan to also support Dionysus (v2) in the future.
git clone https://github.com/DIPHA/dipha.git
cd dipha
mkdir build
cmake ..
make -j4
Then manipulate the software_backends.cfg
:
[paths]
# Configure the paths to the backend software here
# e.g., dipha=/home/myHome/dipha
# do not forget to chmod +x on unix bases systems
dipha=<path/to/your/dipha/executable/here> # <-- This is your modification
hera_wasserstein_dist=
perseus=
A short overview of the main features. For each of feature, there exists a tutorial in the
tutorials
subfolder.
Uses Perseus
to calculate persistence diagrams of filtrated Toplex. Tutorial
Uses DIPHA
to calculate persistence diagrams of a filtrated cubical complex. Tutorial
Calculates a normalized barycentric persistent homology transform of a given binary 2D cubical complex.Tutorial
Calculates a normalized barycentric persistent homology transform (residing on the 26-points Lebedev grid) of a given binary 3D cubical complex. See [1].
Calculates the 'shape' distance between two 2D persistent homology transforms. Tutorial
Calculates the 'shape' distance between two 3D persistent homology transforms, proposed in [1].
[1]
C. Hofer, R. Kwitt, M. Niethammer, Y. Hoeller, E. Trinka and A. Uhl.
Constructing Shape Spaces from a Topological Perspective, In: IPMI, 2017
@inproceedings{Hofer17a,
author = {C.~Hofer, R.~Kwitt, M.~Niethammer, Y.~Hoeller, E.~Trinka and A.~Uhl},
title = {Constructing Shape Spaces from a Topological Perspective},
booktitle = {IPMI},
year = {2017}}
[2]
C. Hofer, R. Kwitt, M. Niethammer and A. Uhl.
Deep Learning with Topological Signatures, In: NIPS, 2017
@inproceedings{Hofer17b,
author = {C.~Hofer, R.~Kwitt, M.~Niethammer, and A.~Uhl},
title = {Deep Learning with Topological Signatures},
booktitle = {NIPS},
year = {2017}}