ReduceLinAlg.jl
LINALG: Linear algebra package A selection of functions that are useful in the world of linear algebra
This Julia package relies on the Reduce.jl parser generator, Julia docs (stable / latest).
Meta-package ReduceAlgebra.jl, upstream docs (LINALG / pdf), Julia docs (stable / latest)
16.37 LINALG: Linear algebra package
This package provides a selection of functions that are useful in the world of linear algebra.
Author: Matt Rebbeck.
16.37.1 Introduction
This package provides a selection of functions that are useful in the world of linear algebra. These functions are described alphabetically in subsection 16.37.3 and are labelled 16.37.3.1 to 16.37.3.53. They can be classified into four sections(n.b: the numbers after the dots signify the function label in section 16.37.3).
Contributions to this package have been made by Walter Tietze (ZIB).
Library
ReduceLinAlg.hessian — Function.hessian(expr,var_list::Vector)Computes the Hessian matrix of expr with respect to the variables in var_list.
This is an n×n matrix where n is the number of variables and the (i,j)th entry is df(expr,var_list[i],var_list[j]).
ReduceLinAlg.mat_jacobian — Function.mat_jacobian(expr_list::Vector,var_list::Vector)Computes the Jacobian matrix of expr_list with respect to var_list.
This is a matrix whose (i,j)th entry is df(expr_list[i],var_list[j]). The matrix is n×m where n is the number of variables and m is the number of expressions.
ReduceLinAlg.jordan_block — Function.jordan_block(expr,square_size::Integer)Computes the square Jordan block matrix J of dimension square_size.
The entries of J are J[i,i] = expr for i = 1,...,n, J[i,i+1] = 1 for i = 1,...,n-1, and all other entries are 0.