Often it's possible to write more efficient code for a matrix that is known to have certain properties e.g. Here, Julia was able to detect that B is in fact symmetric, and used a more appropriate factorization. See the documentation on factorize for more information. In addition, Julia provides many factorizations which can be used to speed up problems such as linear solve or matrix exponentiation by pre-factorizing a matrix into a form more amenable (for performance or memory reasons) to the problem. Basic operations, such as tr, det, and inv are all supported: julia> A = Īs well as other useful operations, such as finding eigenvalues or eigenvectors: julia> A = In addition to (and as part of) its support for multi-dimensional arrays, Julia provides native implementations of many common and useful linear algebra operations which can be loaded with using LinearAlgebra.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |