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This package provides arithmetic functions for native R
matrices and bigmemory::big.matrix objects as well as
functions for QR factorization, Cholesky factorization, General
eigenvalue, and Singular value decomposition (SVD). A method matrix
multiplication and an arithmetic method -for matrix addition, matrix
difference- allows for mixed type operation -a matrix class object and a
big.matrix class object- and pure type operation for two big.matrix
class objects.
The package defines a number of global options that begin with
bigalgebra.
They include:
Option Default value * bigalgebra.temp_pattern with
default matrix_ * bigalgebra.tempdir with
default tempdir *
bigalgebra.mixed_arithmetic_returns_R_matrix with default
TRUE * bigalgebra.DEBUG with default
FALSE
The bigalgebra.tempdir option must be a function that
returns a temporary directory path used to big matrix results of BLAS
and LAPACK operations. The deault value is simply the default R
tempdir function.
The bigalgebra.temp_pattern is a name prefix for file
names of generated big matrix objects output as a result of BLAS and
LAPACK operations.
The bigalgebra.mixed_arithmetic_returns_R_matrix option
determines whether arithmetic operations involving an R matrix or vector
and a big.matrix matrix or vector return a big matrix (when the option
is FALSE), or return a normal R matrix
(TRUE).
The package is built, by default, with R’s native BLAS
libraries, which use 32-bit signed integer indexing. The default build
is limited to vectors of at most 2^31 - 1 entries and matrices with at
most 2^31 - 1 rows and 2^31 - 1 columns (note that standard R matrices
are limtied to 2^31 - 1 total entries).
The package includes a reference BLAS implementation that supports 64-bit integer indexing, relaxing the limitation on vector lengths and matrix row and column limits. Installation of this package with the 64-bit reference BLAS implementation may be performed from the command-line install:
REFBLAS=1 R CMD INSTALL bigalgebra
where bigalgebra is the source package (for example,
bigalgebra_0.9.0.tar.gz).
The package may also be build with user-supplied external BLAS and LAPACK libraries, in either 32- or 64-bit varieties. This is an advanced topic that requires additional Makevars modification, and may include adjustment of the low-level calling syntax depending on the library used.
Feel free to contact us for help installing and running the package.
This website and these examples were created by F. Bertrand.
Maintainer: Frédéric Bertrand frederic.bertrand@utt.fr.
You can install the released version of bigalgebra from CRAN with:
install.packages("bigalgebra")You can install the development version of bigalgebra from github with:
devtools::install_github("fbertran/bigalgebra")library("bigmemory")
A <- bigmemory::big.matrix(5,4,init = 1)
B <- bigmemory::big.matrix(4,4,init = 2)
C <- A %*% B # Returns a new big.matrix object
D <- A[] %*% B[] # Compute the same thing in R
print(C - D) # Compare the results (subtraction of an R matrix from a
#> [,1] [,2] [,3] [,4]
#> [1,] 0 0 0 0
#> [2,] 0 0 0 0
#> [3,] 0 0 0 0
#> [4,] 0 0 0 0
#> [5,] 0 0 0 0
# big.matrix)
# The next example illustrates mixing R and big.matrix objects. It returns by
# default (see # options("bigalgebra.mixed_arithmetic_returns_R_matrix")
D <- matrix(rnorm(16),4)
E <- A %*% DThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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