#7723: Sparse matrices for double fields
---------------------------+------------------------------------------------
   Reporter:  dagss        |       Owner:  jkantor             
       Type:  enhancement  |      Status:  new                 
   Priority:  major        |   Milestone:  sage-feature        
  Component:  numerical    |    Keywords:                      
Work_issues:               |      Author:  Dag Sverre Seljebotn
   Upstream:  N/A          |    Reviewer:                      
     Merged:               |  
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 Here's the beginnings of my work on sparse double matrices.

 This is based on 4.3.rc0. Note that I have *not* run the entire Sage test
 suite,
 only tests in the matrix package. I'm happy to run the entire suite once I
 know
 the final revision this will be rebased to, but 4.3.rc0 produces a few
 test
 failures in itself (=noise I'm not bothering with for the moment).

 There are three patches, which should be applied and reviewed in this
 order:

  - generic_multiply lets one override matrix multiplication with
    different parents.  This is in a seperate patch because it changes
    structure/element.pxd, causing a big recompile.

  - double_sparse is the main new classes

  - coo_format changes the matrix constructor to accept "coo=..." (see
 docstring
    in patch)

 More comments:

  - I will not introduce seperate classes for real and complex -- there
    will be other subclasses (Hermitian, strictly-diagonal etc.) and I
    don't want to double the size of the hierarchy. There are other
    (and better) ways to get efficient getitem/setitem without a speed
    penalty (such as introducing a seperate ItemAccessor protocol/class
    -- though for sparse matrices an if-test won't matter either).

  - Once this is accepted (and I have a general feel for what I do
    right and wrong) I hope to continue with solvers etc. (as I scratch my
 itches).

-- 
Ticket URL: <http://trac.sagemath.org/sage_trac/ticket/7723>
Sage <http://www.sagemath.org>
Sage: Creating a Viable Open Source Alternative to Magma, Maple, Mathematica, 
and MATLAB

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