Condensed Table of Contents
Containers
Concepts
Type Generators
Type Selectors
Classes
Adaptors
Functions
Tags
Iterators
Concepts
Functions
Classes
Adaptors
Algorithms
Function Objects
FAST Library
BLAIS LIbrary
MTL to LAPACK Interface
Utilities
Bibliography
Categorized index
Detailed Table of Contents
1. Containers
Concepts
ColumnMatrix
A Column-Oriented MTL
Matrix
DiagonalMatrix
A Diagonally-Oriented
Matrix
MTL_Object_Model
The MTL Object Memory Model
Matrix
The MTL
Matrix
Concept
RowMatrix
A Row-Oriented MTL
Matrix
TwoDStorage
The MTL TwoD Storage Concept
Vector
The MTL
Vector
Concept
Container type generators
band_view
Band View
Matrix
Type Constructor
block_view
Block View
Matrix
Type Constructor
matrix
Matrix
type generators class.
symmetric_view
Symmetric View
Matrix
Type Constructor
tri_view
Triangle View Creation Helper Fuctor
triangle_view
Triangle View
Matrix
Type Constructor
Container type selectors
Container classes
array2D
Array 2-D Container
compressed1D
Compressed Sparse
Vector
external2D
External2D Storage Type
external_vec
External 1-D Container
generic_dense2D
Generic Dense 2-D Container
partitioned
Dense2D Storage Type
Container adaptors
block2D
Block View TwoD Storage
linalg_vec
Linalg
Vector
Adaptor
scaled1D
Scaled Container
scaled2D
Scaled 2D container adaptor
sparse1D
Sparse 1-D Container Adaptor
strided1D
Strided
Vector
Adaptor
Container functions
scaled
Shortcut for Creating a Scaled Argument
strided
Shortcut for Creating a Strided Argument
blocked
Blocked
Matrix
Generator
blocked
Blocked
Matrix
Generator
rows
Access the row-wise view of the
matrix
columns
Access the column-wise view of the
matrix
trans
Swap the orientation of a
matrix
.
Container tags
column_matrix_traits
Column
Matrix
Traits
diagonal_matrix_traits
Diagonal
Matrix
Traits
linalg_traits
Linear Algebra Object (
Matrix
and
Vector
) Traits
matrix_traits
The "traits" class for MTL matrices.
not_strideable
Identifies matrices that can not be used with the rows and columns functions
row_matrix_traits
Row
Matrix
Traits
strideable
Identifies matrices that can be used with the rows and columns functions
2. Iterators
Concepts
IndexedIterator
IndexedIterator
Iterator functions
trans_iter
Helper function for creating a transforming iterator
Iterator classes
compressed_iter
Compressed Storage Iterator
Iterator adaptors
dense_iterator
dense iterator
scale_iterator
scale iterator
sparse_iterator
Sparse
Vector
Iterator
strided_iterator
strided iterator
transform_iterator
Tranforming Iterator
3. Algorithms
sum
Sum:
s <- sum_i(x(i))
scale
Scale:
A <- alpha*A or x <- alpha x
set_diagonal
Set Diagonal:
A(i,i) <- alpha
two_norm
Two Norm:
s <- sqrt(sum_i(|x(i)^2|))
sum_squares
Sum of the Squares
one_norm
One Norm:
s <- sum(|x_i|) or s <- max_j(sum_i(|A(i,j)|))
infinity_norm
Infinity Norm:
s <- max_i(sum_j(|A(i,j)|)) or s <- max_i(|x(i)|)
max_index
Max Index:
i <- index of max(|x(i)|)
max_abs_index
Maximum Absolute Index:
i <- index of max(|x(i)|)
min_index
Minimum Index:
i <- index of min(x(i))
min_abs_index
Minimum Absolute Index:
i <- index of min(|x(i)|)
max
Max Value:
s <- max(x(i))
min
Min Value:
s <- min(x_i)
transpose
Transpose in Place:
A <- A^T
conj_transpose
Transpose in Place:
A <- A^T
transpose
Transpose:
B <- A^T
mult
Multiplication:
z <- A x + y
_mult
Matrix
Vector
Multiplication:
y <- A x
tri_solve
Triangular Solve:
x <- T^{-1} * x
tri_solve
Triangular Solve:
B <- A^{-1} * B or B <- B * A^{-1}
rank_one_update
Rank One Update:
A <- A + x * y^T
rank_one_conj
Rank One Update with conj():
A <- A + x * conj(y^T)
rank_two_update
Rank Two Update:
A <- A + x * y^T + y * x^T
rank_two_conj
Rank Two Update with conj():
A <- A + x * conj(y^T) + y * conj(x^T)
scatter
Scatter
y <- x
gather
Gather
y <- x
copy
Copy:
B <- A or y <- x
__add
Add:
z <- x + y
add
Add:
w <- x + y + z
add
Add:
B <- A + B or y <- x + y
ele_mult
Element-wise Multiplication:
z <- x O* y
ele_mult
Element-wise Multiply:
B <- A O* B
ele_div
Element-wise Division:
z <- x O/ y
swap
Swap:
B <-> A or y <-> x
dot
Dot Product:
s <- x . y + s
dot
Dot Product:
s <- x . y
dot
Dot Product (extended precision):
s <- x . y + s
dot_conj
Dot Conjugate:
s <- x . conj(y) + s
dot_conj
Dot Conjugate:
s <- x . conj(y)
lu_factor
LU Factorization of a general (dense)
matrix
lu_solve
LU Solve
lu_inverse
LU Inverse
4. Function Objects
givens_rotation
Givens Plane Rotation
givens_rotation__2
The specialization for complex numbers.
givens_rotation__3
The specialization for complex numbers.
givens_rotation__4
The specialization for complex numbers.
modified_givens
Modified Givens Transformation
5. Fixed Algorithm Size Template (FAST) Library
Functions
copy
Copy
transform
Transform (one input iterator)
transform
Transform (two input iterators)
fill
Fill
swap_ranges
Swap Ranges
accumulate
Accumulate (with default operation)
accumulate
Accumulate (with user-supplied operation)
inner_product
Inner Product (user supplied operators)
inner_product
Inner Product (with default operators)
Classes
6. Basic Linear Algebra Instruction Set (BLAIS) Library
add
Add y <- x + y
copy
Copy y <- x
copy__2
Copy B <- A
dot
Dot Product s <- x . y
mult
Multiplication y <- A x + y
mult__2
Multiplication C <- A * B
rank_one
Rank One Update A <- A + x * y^T
set
Set elements of vector x to alpha
set__2
Set
matrix
A to alpha
7. MTL to LAPACK Interface
Type Generators
lapack_matrix
Lapack
Matrix
Functions
gecon
Estimate the reciprocal of the condition number of a general
matrix
.
geev
Compute the eigenvalues.
geqpf
QR Factorization with Column Pivoting.
geqrf
QR Factorization of a General
Matrix
gesv
Solution to a linear system in a general
matrix
.
getrf
LU factorization of a general
matrix
A.
getrs
Solution to a system using LU factorization
geequ
Equilibrate and reduce condition number.
gelqf
Compute an LQ factorization.
orglq
Generate a
matrix
Q with orthonormal rows.
orgqr
Generate a
matrix
Q with orthonormal columns.
8. Utilities
Concepts
Indexer
Maps from
Matrix
coordinates to TwoD coordinates
Offset
Maps from TwoD coordinates to linear memory
Functions
read_dense_matlab
Read a Dense Real
Matrix
from a Matlab file (.mat)
write_dense_matlab
Write a Dense Real
Matrix
to a Matlab file (.mat)
read_sparse_matlab
Read a Sparse Real
Matrix
from a Matlab file (.mat)
write_sparse_matlab
Write a Sparse Real
Matrix
to a Matlab file (.mat)
Classes
banded_offset
Banded
Offset
Class
banded_view_offset
Banded View
Offset
Class
dimension
The Dimension Class
harwell_boeing_stream
A
Matrix
File Input Stream for Harwell-Boeing
Matrix
Files
matrix_market_stream
A
Matrix
File Input Stream for
Matrix
Market Files
packed_offset
Packed
Offset
Class
rect_offset
Rectangular
Offset
Class
strided_band_view_offset
Strided Band View
Offset
Class
strided_banded_offset
Strided Banded
Offset
strided_offset
Strided Rectangular
Offset
Class
strided_packed_offset
Strided Packed
Offset
Class
9. Bibliography
10. Categorized index
Copyright © 1998,1999 University of Notre Dame. All Rights Reserved.