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author | Marc Glisse <marc.glisse@inria.fr> | 2020-02-12 12:44:51 +0100 |
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committer | GitHub <noreply@github.com> | 2020-02-12 12:44:51 +0100 |
commit | bed30b19e57669c0b8ad385f1124586ed3499a2d (patch) | |
tree | 6ddbe2f3015899159818bd6e3003d78dd920d707 /README.md | |
parent | ee0f12f1df406c81c6ad860c494eed908021fad9 (diff) | |
parent | d6f3165831d20bf3a91f1ff7e9734a574eaa567a (diff) |
Merge pull request #182 from mglisse/ext
Interface to hera's Wasserstein distance
Diffstat (limited to 'README.md')
-rw-r--r-- | README.md | 9 |
1 files changed, 9 insertions, 0 deletions
@@ -10,6 +10,15 @@ The GUDHI library is a generic open source C++ library, with a Python interface, for Topological Data Analysis (TDA) and Higher Dimensional Geometry Understanding. The library offers state-of-the-art data structures and algorithms to construct simplicial complexes and compute persistent homology. +# Source code + +We recommend that users get official releases from [the GUDHI website](https://gudhi.inria.fr/). + +For potential contributors, to fully checkout GUDHI, after cloning the git repository, you may also need to checkout its submodules using +```sh +git submodule update --init +``` + # Compilation and installation To install GUDHI, you can follow the [C++ compilation procedure](https://gudhi.inria.fr/doc/latest/installation.html), the [Python compilation procedure](https://gudhi.inria.fr/python/latest/installation.html), use our [conda-forge package](https://gudhi.inria.fr/conda/), or [go with Docker](https://gudhi.inria.fr/dockerfile/). |