javaPlex
javaPlex - an extensible platform for persistence. javaPlex is the newest member of the Stanford-based Plex family of persistent homology and cohomology software packages. Written in Java, it is optimized for easy interfacing with Matlab as well as anything running in the Java ecosystem - including Processing, Scala, Jython, and Mathematica. javaPlex was written to create a platform easier to extend and experiment with than its predecessor jPlex. In its last release, the platform support absolute and relative persistence (co)homology, as well as hom-complexes of simplicial complexes, cellular and simplicial complex constructions and fast Vietoris-Rips and witness complex constructions. We will demonstrate the architecture, usage, development and extension features of javaPlex, focusing on interoperability with Matlab as an interface to the library.
Keywords for this software
References in zbMATH (referenced in 30 articles , 1 standard article )
Showing results 1 to 20 of 30.
Sorted by year (- Adams, Henry; Aminian, Manuchehr; Farnell, Elin; Kirby, Michael; Mirth, Joshua; Neville, Rachel; Peterson, Chris; Shonkwiler, Clayton: A fractal dimension for measures via persistent homology (2020)
- Cang, Zixuan; Munch, Elizabeth; Wei, Guo-Wei: Evolutionary homology on coupled dynamical systems with applications to protein flexibility analysis (2020)
- Chowdhury, Samir; Clause, Nathaniel; Mémoli, Facundo; Sánchez, Jose Ángel; Wellner, Zoe: New families of stable simplicial filtration functors (2020)
- Ruehle, Fabian: Data science applications to string theory (2020)
- Som, Anirudh; Ramamurthy, Karthikeyan Natesan; Turaga, Pavan: Geometric metrics for topological representations (2020)
- Wang, Dong; Zhao, Yi; Leng, Hui; Small, Michael: A social communication model based on simplicial complexes (2020)
- Cirafici, Michele: BPS spectra, barcodes and walls (2019)
- Cole, Alex; Shiu, Gary: Topological data analysis for the string landscape (2019)
- Mémoli, Facundo; Singhal, Kritika: A primer on persistent homology of finite metric spaces (2019)
- Salnikov, Vsevolod; Cassese, Daniele; Lambiotte, Renaud: Simplicial complexes and complex systems (2019)
- Alan Hylton, Gregory Henselman-Petrusek, Janche Sang, Robert Short: Tuning the Performance of a Computational Persistent Homology Package (2018) arXiv
- Brake, Danielle A.; Hauenstein, Jonathan D.; Regan, Margaret H.: polyTop: software for computing topology of smooth real surfaces (2018)
- Breiding, Paul; Kališnik, Sara; Sturmfels, Bernd; Weinstein, Madeleine: Learning algebraic varieties from samples (2018)
- Chowdhury, Samir; Mémoli, Facundo: A functorial Dowker theorem and persistent homology of asymmetric networks (2018)
- Xia, Kelin; Li, Zhiming; Mu, Lin: Multiscale persistent functions for biomolecular structure characterization (2018)
- Bauer, Ulrich; Kerber, Michael; Reininghaus, Jan; Wagner, Hubert: \textscPhat-- persistent homology algorithms toolbox (2017)
- Mittal, Khushboo; Gupta, Shalabh: Topological characterization and early detection of bifurcations and chaos in complex systems using persistent homology (2017)
- Toth, Csaba D. (ed.); Goodman, Jacob E. (ed.); O’Rourke, Joseph (ed.): Handbook of discrete and computational geometry (2017)
- Cirafici, Michele: Persistent homology and string vacua (2016)
- Kovacev-Nikolic, Violeta; Bubenik, Peter; Nikolić, Dragan; Heo, Giseon: Using persistent homology and dynamical distances to analyze protein binding (2016)