[ buster ]
[ Bron: pysparse ]
Pakket: python-sparse (1.1.1-2)
Verwijzigingen voor python-sparse
Debian bronnen:
Het bronpakket pysparse downloaden:
Beheerders:
- Debian Science Maintainers (QA-pagina, Mailarchief)
- package has bad maintainer field (QA-pagina)
- IV (QA-pagina)
Externe bronnen:
- Homepage [pysparse.sourceforge.net]
Vergelijkbare pakketten:
Sparse linear algebra extension for Python
This provides a set of sparse matrix types for Python, with modules which implement:
- Iterative methods for solving linear systems of equations - A set of standard preconditioners - An interface to a direct solver for sparse linear systems of equations - The JDSYM eigensolver
All of these modules are implemented as C extension modules based on standard sparse and dense matrix libraries (UMFPACK/AMD, SuperLU, BLAS/LAPACK) for maximum performance and robustness.
Andere aan python-sparse gerelateerde pakketten
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- dep: libamd2 (>= 1:4.5.2)
- approximate minimum degree ordering library for sparse matrices
-
- dep: libblas3
- Basic Linear Algebra Reference implementations, shared library
- of libblas.so.3
- virtueel pakket geboden door libatlas3-base, libblas3, libblis2-openmp, libblis2-pthread, libblis2-serial, libopenblas-base
-
- dep: libc6 (>= 2.4)
- GNU C Bibliotheek: Gedeelde bibliotheken
Ook een virtueel pakket geboden door: libc6-udeb
-
- dep: liblapack3
- Library of linear algebra routines 3 - shared version
- of liblapack.so.3
- virtueel pakket geboden door libatlas3-base, liblapack3, libopenblas-base
-
- dep: libsuperlu5
- Direct solution of large, sparse systems of linear equations
-
- dep: libumfpack5 (>= 1:4.5.2)
- sparse LU factorization library
-
- dep: python
- interactive high-level object-oriented language (Python2 version)
- dep: python (<< 2.8)
- dep: python (>= 2.7~)
-
- dep: python-numpy (>= 1:1.14.3)
- Numerical Python adds a fast array facility to the Python language
-
- dep: python-numpy-abi9
- virtueel pakket geboden door python-numpy
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- sug: python-sparse-examples
- Sparse linear algebra extension for Python: documentation