Matrix -package:cairo
Simple matrix operation for low-dimensional primitives.
Matrix representation suitable for BLAS/LAPACK computations.
This module corresponds to chapter 4 (Matrix Manipulation) of the GLU
specs.
Copied from Graphics.Rendering.Cairo.Matrix
Matrix datatype and operations.
Every provided example has been tested. Run cabal test for
further tests.
Type of matrices.
Elements can be of any type. Rows and columns are indexed starting by
1. This means that, if m :: Matrix a and i,j :: Int,
then m ! (i,j) is the element in the i-th row and
j-th column of m.
Routines and abstractions for Matrices and basic linear algebra over
fields or rings.
We stick to simple Int indices. Although advanced indices would be
nice e.g. for matrices with sub-matrices, this is not easily
implemented since arrays do only support a lower and an upper bound
but no additional parameters.
ToDo: - Matrix inverse, determinant (see htam:Matrix)
No description available in the introspection data.
Memory-managed wrapper type.
A
PangoMatrix specifies a transformation between user-space
and device coordinates.
The transformation is given by
x_device = x_user * matrix->xx + y_user * matrix->xy + matrix->x0;
y_device = x_user * matrix->yx + y_user * matrix->yy + matrix->y0;
Since: 1.6
Type synonym for a two-dimentsional array, or simply a matrix.
Type of matrices, parameterised on the type of values.
Sparse matrices are implemented as an ordered association list,
mapping coordinates to values.
A transformation matrix. An affine transformation a b c d e f
a b 0
c d 0
e f 1
Row-major matrix supporting efficient slice.
Algorithms operating on matrices.
These functions should give performance comparable with nested loop C
implementations.
If you care deeply about runtime performance then you may be better
off using a binding to LAPACK, such as hvector.