aboutsummaryrefslogtreecommitdiffhomepage
path: root/test/product.h
Commit message (Collapse)AuthorAge
* Adaptions from .lazy() towards .noalias().Gravatar Hauke Heibel2009-08-31
| | | | Added missing casts.
* big refactoring in Product.h:Gravatar Gael Guennebaud2009-08-05
| | | | | | | | - all specialized products now inherits ProductBase - the default product evaluated by Assign is still here, but it is currently enabled for small fixed sizes only - => this significantly speed up compilation for large matrices - I left the OuterProduct specialization empty as an exercise...
* * extended the cache friendly products to support C = alpha * A * M and C += ↵Gravatar Gael Guennebaud2009-07-07
| | | | | | | | | alpha * A * B * this allows to optimize xpr like C -= lazy_product, still have to catch "scalar_product_of_lazy_product" * started to support conjugate in cache friendly products (very useful to evaluate A * B.adjoint() without evaluating B.adjoint() into a temporary * compilation fix
* remove sentence "Eigen itself is part of the KDE project."Gravatar Benoit Jacob2009-05-22
| | | | it never made very precise sense. but now does it still make any?
* Update e-mail addressGravatar Benoit Jacob2008-11-24
|
* improve assertion checking in productGravatar Gael Guennebaud2008-10-25
|
* As discussed on ML:Gravatar Gael Guennebaud2008-10-24
| | | | | | | | | | * remove the automatic resizing feature of operator = * add function Matrix::set() to be used when the previous behavior is wanted * the default constructor of dynamic-size matrices now creates a "null" matrix (data=0, rows = cols = 0) instead of a 1x1 matrix * fix UnixX typos ;)
* * remove LargeBit and related stuffGravatar Gael Guennebaud2008-08-23
| | | | | | | * replaced the Flags template parameter of Matrix by StorageOrder and move it back to the 4th position such that we don't have to worry about the two Max* template parameters * extended EIGEN_USING_MATRIX_TYPEDEFS with the ei_* math functions
* Optimizations:Gravatar Gael Guennebaud2008-08-01
* faster matrix-matrix and matrix-vector products (especially for not aligned cases) * faster tridiagonalization (make it using our matrix-vector impl.) Others: * fix Flags of Map * split the test_product to two smaller ones