persim.heat

persim.heat(dgm1, dgm2, sigma=0.4)[source]

Return the pseudo-metric between two diagrams based on the continuous heat kernel as described in “A Stable Multi-Scale Kernel for Topological Machine Learning” by Jan Reininghaus, Stefan Huber, Ulrich Bauer, and Roland Kwitt (CVPR 2015)

Parameters:

  • dgm1 (np.array (m,2)) – A persistence diagram

  • dgm2 (np.array (n,2)) – A persistence diagram

  • sigma (float) – Heat diffusion parameter (larger sigma makes blurrier)

Returns:

dist (float) – heat kernel distance between dgm1 and dgm2