{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/pymanopt-a-python-toolbox-for-optimization-on","title":"Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation","arxiv_id":"1603.03236","date":"2016-03-10","proceeding":null,"authors":["James Townsend","Niklas Koep","Sebastian Weichwald"],"abstract":"Optimization on manifolds is a class of methods for optimization of an\nobjective function, subject to constraints which are smooth, in the sense that\nthe set of points which satisfy the constraints admits the structure of a\ndifferentiable manifold. While many optimization problems are of the described\nform, technicalities of differential geometry and the laborious calculation of\nderivatives pose a significant barrier for experimenting with these methods.\n  We introduce Pymanopt (available at https://pymanopt.github.io), a toolbox\nfor optimization on manifolds, implemented in Python, that---similarly to the\nManopt Matlab toolbox---implements several manifold geometries and optimization\nalgorithms. Moreover, we lower the barriers to users further by using automated\ndifferentiation for calculating derivative information, saving users time and\nsaving them from potential calculation and implementation errors.","url_abs":"http://arxiv.org/abs/1603.03236v4","url_pdf":"http://arxiv.org/pdf/1603.03236v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"pymanopt-a-python-toolbox-for-optimization-on","repo_url":"https://github.com/pymanopt/pymanopt","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok","spdx":"BSD-3-Clause"}}],"tasks":[{"task_slug":"riemannian-optimization","task_name":"Riemannian optimization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1603.03236","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1603.03236"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/pymanopt/pymanopt","reach":{"status":"ok","spdx":"BSD-3-Clause"}}],"summary":{"unverified":1},"by_repo_kind":{"official":{"samples":1,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"89bb6b15282d9df6","entry":"raise_not_implemented_error","repo":"pymanopt/pymanopt","repo_kind":"official","path":"src/pymanopt/manifolds/manifold.py","file_url":"https://github.com/pymanopt/pymanopt/blob/HEAD/src/pymanopt/manifolds/manifold.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"89bb6b15282d9df6"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}