Software

• PyTMRC (by A. Bittracher and M. Mollenhauer)

  The Python Transition Manifold Reaction Coordinate package for computing reaction coordinates of high-dimensional stochastic systems is based on the transition manifold data analysis framework. Based on:

  A. Bittracher, P. Koltai, S. Klus, R. Banisch, M. Dellnitz, Ch. Schütte. Transition Manifolds of Complex Metastable Systems. Journal of Nonlinear Science 28(2): 471–512, 2018. DOI: 10.1007/s00332-017-9415-0.

  A. Bittracher, S. Klus, B. Hamzi, P. Koltai, and Ch. Schütte. Dimensionality Reduction of Complex Metastable Systems via Kernel Embeddings of Transition Manifolds. Journal of Nonlinear Science 31, 3. 2021. DOI: 10.1007/s00332-020-09668-z.

• PyTPT (by L. Helfmann and E. Ribera Borrell)

  Python package for the Transition Path Theory (TPT) analysis of stationary Markov chains, periodically driven Markov chains, and for time-inhomogeneous Markov chains over finite time intervals. Based on:

  L. Helfmann, E. Ribera Borrell, Ch. Schütte, and P. Koltai. Extending Transition Path Theory: Periodically-Driven and Finite-Time Dynamics. Journal of Nonlinear Science 30, 3321-3366, 2020. DOI: 10.1007/s00332-020-09652-7.

• SINAR (by N. Wulkow)

  Matlab code for learning sparse nonlinear autoregressive models from trajectory data; in particular with an application in opinion dynamics. Based on:

  N. Wulkow, P. Koltai, Ch. Schütte. Memory-based reduced modelling and data-based estimation of opinion spreading. Journal of Nonlinear Science 31, 19, 2021. DOI: 10.1007/s00332-020-09673-2.

• pyDiffMap (by R. Banisch, E. H. Thiede, Z. Trstanova)

  An open-source project to develop a robust and accessible diffusion map code for public use. Includes implementations of target measure diffusion maps and local kernel diffusion maps, based on:

  R. Banisch, Z. Trstanova, A. Bittracher, S. Klus, and P. Koltai. Diffusion maps tailored to arbitrary non-degenerate Itô processes. Applied and Computational Harmonic Analysis 48(1), 242-265, 2020. DOI: 10.1016/j.acha.