PyLandscapes: A Python Implementation of Persistence Landscapes

dc.contributor.author Angeloro, Gabrielle
dc.contributor.department Department of Mathematics
dc.contributor.majorProfessor Dr. Michael Catanzaro
dc.date 2021-06-02T13:06:00.000
dc.date.accessioned 2021-08-14T03:33:16Z
dc.date.available 2021-08-14T03:33:16Z
dc.date.copyright Wed Jan 01 00:00:00 UTC 2020
dc.date.embargo 2020-12-01
dc.date.issued 2021-01-01
dc.description.abstract <p>Persistent homology provides a geometric and topological view on data sets and is often used in conjunction with more traditional statistical methods. In this essay, we discuss a vectorization scheme of persistent homology, known as persistence landscapes. We develop a package in python to compute persistence landscapes and preform the necessary tasks for statistical analysis. This includes computing linear combinations and norms of persistence landscapes. We also present a modified algorithm to compute persistence landscapes on a user specified grid.</p>
dc.format.mimetype PDF
dc.identifier archive/lib.dr.iastate.edu/creativecomponents/705/
dc.identifier.articleid 1726
dc.identifier.contextkey 20361456
dc.identifier.doi https://doi.org/10.31274/cc-20240624-1175
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath creativecomponents/705
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/Ewpa4kDv
dc.source.bitstream archive/lib.dr.iastate.edu/creativecomponents/705/Angeloro_PyLandscapes.pdf|||Sat Jan 15 01:41:16 UTC 2022
dc.subject.disciplines Geometry and Topology
dc.subject.keywords Topological Data Analysis
dc.subject.keywords Persistence Landscapes
dc.subject.keywords Python Package
dc.subject.keywords Sci-kit TDA
dc.title PyLandscapes: A Python Implementation of Persistence Landscapes
dc.type creative component
dc.type.genre creative component
dspace.entity.type Publication
relation.isOrgUnitOfPublication 82295b2b-0f85-4929-9659-075c93e82c48
thesis.degree.discipline Mathematics
thesis.degree.level creativecomponent
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