Dimension reduction with Eilenberg-MacClane coordinates
Dimension Reduction with Eilenberg-MacLane Coordinates
Chris Tralie, Tom Mease, Jose Perea
DREiMac is a library for topological data coordinatization, visualization and dimensionality reduction. It leverages Eilenberg-MacLane spaces, and turns persistent cohomology computations into topology-preserving coordinates for data.
TO USE: interactively select persistent cohomlogy classes, parameters, and DREiMac will compute maps from the data to appropriate (low-dimensional skeleta of Eilenberg-MacLane) spaces consistent with the underlying data topology.
Code can be found in dreimac/. If you're using conda and would like to create a virtual environment first, type
conda create -n dreimac python=3.9
conda activate dreimac
Then, to install, type
git clone https://github.com/ctralie/DREiMac.git
pip install -e .
Then, you can import dreimac from any python file or notebook. For example, if you type the following from the root of the repository
then you will be able to interactively explore the notebooks we have setup
Code can be found in dreimacjs/ CircluarCoords.html and ripser.html are the entry points
Emscripten Compile options
emcc --bind -s ALLOW_MEMORY_GROWTH=1 -O3 ripser.cpp
- MIME Types for wasm files should be application/wasm
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.