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DREiMac is a library for topological data coordinatization, visualization, and dimensionality reduction. DREiMac is able to find topology-preserving representations of point clouds taking values in the circle, in higher dimensional tori, in the real and complex projective space, and in lens spaces.

In a few words, DREiMac takes as input a point cloud together with a topological feature of the point cloud (in the form of a persistent cohomology class), and returns a map from the point cloud to a well-understood topological space (a circle, a product of circles, a projective space, or a lens space), which preserves the given topological feature in a precise sense.

complex/rips custom/distance lang/python type/dimensionality-reduction type/persistence type/representative vis/diagram