Categorygithub.com/gonum/matrix

modulepackage

0.0.0-20181209220409-c518dec07be9

Repository: https://github.com/gonum/matrix.git

Documentation: pkg.go.dev

# README

Gonum Matrix

This repository is no longer maintained. Development has moved to https://github.com/gonum/gonum.

This is a matrix package for the Go language.

Issues

If you find any bugs, feel free to file an issue on the github issue tracker for gonum/gonum if the bug exists in that reposity; no code changes will be made to this repository. Other discussions should be taken to the gonum-dev Google Group.

https://groups.google.com/forum/#!forum/gonum-dev

License

Please see github.com/gonum/gonum for general license information, contributors, authors, etc on the Gonum suite of packages.

# Packages

cmat128

This repository is no longer maintained.

conv

This repository is no longer maintained.

mat64

This repository is no longer maintained.

# Functions

Maybe

Maybe will recover a panic with a type mat64.Error from fn, and return this error as the Err field of an ErrorStack.

MaybeComplex

MaybeComplex will recover a panic with a type mat64.Error from fn, and return this error as the Err field of an ErrorStack.

MaybeFloat

MaybeFloat will recover a panic with a type mat64.Error from fn, and return this error as the Err field of an ErrorStack.

# Constants

ConditionTolerance

ConditionTolerance is the tolerance limit of the condition number.

CondNorm

CondNorm is the matrix norm used for computing the condition number by routines in the matrix packages.

CondNormTrans

CondNormTrans is the norm used to compute on A^T to get the same result as computing CondNorm on A.

GSVDNone

GSVDNone specifies that no singular vector should be computed during the decomposition.

GSVDQ

GSVDQ specifies that the Q singular vectors should be computed during the decomposition.

GSVDU

GSVDU specifies that the U singular vectors should be computed during the decomposition.

GSVDV

GSVDV specifies that the V singular vectors should be computed during the decomposition.

Lower

Lower specifies a lower triangular matrix.

SVDFull

SVDFull computes the full singular value decomposition, A = U * Σ * V^T where U is of size m×m, Σ is an m×n diagonal matrix, and V is an n×n matrix.

SVDNone

SVDNone specifies that no singular vectors should be computed during the decomposition.

SVDThin

SVDThin computes the thin singular vectors, that is, it computes A = U~ * Σ * V~^T where U~ is of size m×min(m,n), Σ is a diagonal matrix of size min(m,n)×min(m,n) and V~ is of size n×min(m,n).

Upper

Upper specifies an upper triangular matrix.