| RE: [eigen] Predefined SymmetircMatirx, BandedMatrix and PositiveDefiniteMatrix in Eigen |
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- To: <eigen@xxxxxxxxxxxxxxxxxxx>
- Subject: RE: [eigen] Predefined SymmetircMatirx, BandedMatrix and PositiveDefiniteMatrix in Eigen
- From: "Hongyu Miao" <jackymiao@xxxxxxxxx>
- Date: Wed, 20 Jul 2011 10:30:48 -0400
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Thanks, Douglas. The SelfAdjointView does help. Will be there any plan to
implement BandedMatrix and PositiveDefiniteMatrix in EIGEN?
Best,
Jacky
-----Original Message-----
From: Listengine [mailto:listengine@xxxxxxxxxxxxxxxxx] On Behalf Of Douglas
Bates
Sent: Wednesday, July 20, 2011 10:16 AM
To: eigen@xxxxxxxxxxxxxxxxxxx
Subject: Re: [eigen] Predefined SymmetircMatirx, BandedMatrix and
PositiveDefiniteMatrix in Eigen
On Wed, Jul 20, 2011 at 8:08 AM, Hongyu Miao <jackymiao@xxxxxxxxx> wrote:
> Hi, All
>
> I?m wondering why there are not predefined data types for
> SymmetircMatirx, BandedMatrix and PositiveDefiniteMatrix in Eigen.
> These are important in computing and boost::ublas has all such things
> except for PositiveDefiniteMatrix.
But there is a SelfAdjointView class and a .selfadjointView() method for
symmetric matrix manipulations. Similarly TriangularView and
..triangularView() for triangular matrix manipulations. ublas uses packed
storage for symmetric and triangular matrices, if I recall correctly, but
Eigen uses the same underlying representation (full dense or sparse
matrices) with additional properties and access methods. There are
advantages and disadvantages to either approach.
It may be confusing that the term "self-adjoint" is used instead of
"symmetric" but for complex matrices there is a distinction between
symmetric and Hermitian so self-adjoint is a more precise term.