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* Arrowheads in multi-edge digraphs (Emily Kirkman) -- This feature has been in Sage even before this release. However, in version 3.4, Emily worked on enhancing the visualization of multi-edge digraphs. In a multi-edge digraph, the arrowheads pointing to a vertex are now clearly displayed. Here's [[attachment:a plot]] of a multi-edge digraph, produced using the following code: {{{ sage: S = SupersingularModule(389) sage: D = DiGraph(S.hecke_matrix(2)) sage: D.plot(vertex_size=50).show(figsize=10) }}} == Linear Algebra == * Optimize transpose and antitranspose for dense matrices (Rob Beezer, Yann Laigle-Chapuy) -- A rewrite of sections of the method {{{transpose()}}} in the class {{{sage.matrix.matrix_dense.Matrix_dense}}}, resulting in improved performance of between 15% to 18%, depending on the computer architecture. For a system with architecture {{{ CPU: Intel(R) Core(TM)2 Duo CPU T5450 @ 1.66GHz RAM: 2066004 KB Linux kernel: 2.6.24-23 }}} one would obtain the following timing and memory statistics for a 3000x3000 identity matrix: {{{ # BEFORE sage: m=identity_matrix(3000) sage: time m2=m.transpose(); m3=m.antitranspose() CPU times: user 14.13 s, sys: 1.11 s, total: 15.44 s Wall time: 15.44 s sage: get_memory_usage() 1254.28125 # AFTER sage: m=identity_matrix(3000) sage: time m2=m.transpose(); m3=m.antitranspose() CPU times: user 2.92 s, sys: 0.46 s, total: 3.38 s Wall time: 3.38 s sage: get_memory_usage() 835.6171875 }}} Furthermore, on KUbuntu 8.10 with architecture {{{ CPU: Intel(R) Core(TM)2 Duo CPU E8500 @ 3.16GHz RAM: 8 GB }}} for a 5000x5000 identity matrix, the new improved time would be about 2.46 seconds. * Optimize transpose for integer and rational dense matrices (Yann Laigle-Chapuy) -- New methods {{{transpose()}}} and {{{antitranspose()}}} for the classes {{{sage.matrix.matrix_integer_dense.Matrix_integer_dense}}} and {{{sage.matrix.matrix_rational_dense.Matrix_rational_dense}}}. The new method {{{transpose()}}} returns the transpose of an integer (respectively rational) dense matrix without changing the original matrix itself. In addition, the new method {{{antitranspose()}}} returns the antitranspose of an integer (respectively rational) matrix, leaving the original matrix unchanged. |
Sage 3.4 Release Tour
Sage 3.4 was released on FIXME. For the official, comprehensive release note, please refer to sage-3.4.txt. The following points are some of the foci of this release:
- Merging of Jon Hanke's quadratic forms code
- Sphinxifying the Sage documentation and move its content to the main Sage development repository
All tickets in the 3.4 milestone can be found on the trac server. Here's a summary of features in this release, categorized under various headings.
Algebra
Build
Combinatorics
Distribution
Doctest
Documentation
Graphics
Arrowheads in multi-edge digraphs (Emily Kirkman) -- This feature has been in Sage even before this release. However, in version 3.4, Emily worked on enhancing the visualization of multi-edge digraphs. In a multi-edge digraph, the arrowheads pointing to a vertex are now clearly displayed. Here's a plot of a multi-edge digraph, produced using the following code:
sage: S = SupersingularModule(389) sage: D = DiGraph(S.hecke_matrix(2)) sage: D.plot(vertex_size=50).show(figsize=10)
Linear Algebra
Optimize transpose and antitranspose for dense matrices (Rob Beezer, Yann Laigle-Chapuy) -- A rewrite of sections of the method transpose() in the class sage.matrix.matrix_dense.Matrix_dense, resulting in improved performance of between 15% to 18%, depending on the computer architecture. For a system with architecture
CPU: Intel(R) Core(TM)2 Duo CPU T5450 @ 1.66GHz RAM: 2066004 KB Linux kernel: 2.6.24-23
one would obtain the following timing and memory statistics for a 3000x3000 identity matrix:# BEFORE sage: m=identity_matrix(3000) sage: time m2=m.transpose(); m3=m.antitranspose() CPU times: user 14.13 s, sys: 1.11 s, total: 15.44 s Wall time: 15.44 s sage: get_memory_usage() 1254.28125 # AFTER sage: m=identity_matrix(3000) sage: time m2=m.transpose(); m3=m.antitranspose() CPU times: user 2.92 s, sys: 0.46 s, total: 3.38 s Wall time: 3.38 s sage: get_memory_usage() 835.6171875
Furthermore, on KUbuntu 8.10 with architectureCPU: Intel(R) Core(TM)2 Duo CPU E8500 @ 3.16GHz RAM: 8 GB
for a 5000x5000 identity matrix, the new improved time would be about 2.46 seconds.Optimize transpose for integer and rational dense matrices (Yann Laigle-Chapuy) -- New methods transpose() and antitranspose() for the classes sage.matrix.matrix_integer_dense.Matrix_integer_dense and sage.matrix.matrix_rational_dense.Matrix_rational_dense. The new method transpose() returns the transpose of an integer (respectively rational) dense matrix without changing the original matrix itself. In addition, the new method antitranspose() returns the antitranspose of an integer (respectively rational) matrix, leaving the original matrix unchanged.
Miscellaneous
Notebook
Number Theory
Numerical
Packages
Update the libgcrypt spkg to libgcrypt-1.4.3.p0.spkg (Michael Abshoff) -- Originally based on Gnu Privacy Guard (GnuPG), libgcrypt is a general purpose library of cryptographic primitives. As such, it does not provide an implementation of any cryptographic protocols, but rather serves as a collection of cryptographic building blocks.
Update the Python spkg to python-2.5.2.p9.spkg (Michael Abshoff) -- Python is a general purpose, object oriented programming language. Together with various other open source components, Python serves as a fundamental tool that unify the components of Sage under a common interface.
Porting
Quadratic Forms
Merge Jon Hanke's quadratic forms code (Gonzalo Tornaria, Michael Abshoff) -- John Hanke has written a substantial amount of Sage code for working with quadratic forms. Hanke's code can serve as base for further enhancement to the case of binary quadratic forms, which are quadratic forms involving two variables. There are currently a number of patches on the trac server for enhancing the functionalities of binary quadratic forms.
Solaris
User Interface