| Title: | Sparse Matrix Format with Data on Disk |
|---|---|
| Description: | Provide a sparse matrix format with data stored on disk, to be used in both R and C++. This is intended for more efficient use of sparse data in C++ and also when parallelizing, since data on disk does not need copying. Only a limited number of features will be implemented. For now, conversion can be performed from a 'dgCMatrix' or a 'dsCMatrix' from R package 'Matrix'. A new compact format is also now available. |
| Authors: | Florian Privé [aut, cre] |
| Maintainer: | Florian Privé <[email protected]> |
| License: | GPL-3 |
| Version: | 0.7.3 |
| Built: | 2024-11-05 04:57:39 UTC |
| Source: | https://github.com/privefl/bigsparser |
SFBM.Accessor methods for class SFBM.
## S4 method for signature 'SFBM,ANY,ANY,ANY' x[i, j, ..., drop = FALSE] ## S4 method for signature 'SFBM_compact,ANY,ANY,ANY' x[i, j, ..., drop = FALSE] ## S4 method for signature 'SFBM_corr_compact,ANY,ANY,ANY' x[i, j, ..., drop = FALSE]## S4 method for signature 'SFBM,ANY,ANY,ANY' x[i, j, ..., drop = FALSE] ## S4 method for signature 'SFBM_compact,ANY,ANY,ANY' x[i, j, ..., drop = FALSE] ## S4 method for signature 'SFBM_corr_compact,ANY,ANY,ANY' x[i, j, ..., drop = FALSE]
x |
A SFBM object. |
i |
A vector of indices (or nothing). You can use positive and negative indices, and also logical indices (that are recycled). |
j |
A vector of indices (or nothing). You can use positive and negative indices, and also logical indices (that are recycled). |
... |
Not used. Just to make nargs work. |
drop |
Not implemented; always return a sparse matrix ( |
spmat <- Matrix::Diagonal(4, 0:3) spmat[4, 2] <- 5 spmat[1, 4] <- 6 spmat[3, 4] <- 7 spmat X <- as_SFBM(spmat) X[1:3, 2:3] X[, 4] # parameter drop is not implemented X[-1, 3:4] X$dense_acc(2:4, 3:4) X2 <- as_SFBM(spmat, compact = TRUE) X2[1:3, 2:3] X2$dense_acc(1:3, 2:3)spmat <- Matrix::Diagonal(4, 0:3) spmat[4, 2] <- 5 spmat[1, 4] <- 6 spmat[3, 4] <- 7 spmat X <- as_SFBM(spmat) X[1:3, 2:3] X[, 4] # parameter drop is not implemented X[-1, 3:4] X$dense_acc(2:4, 3:4) X2 <- as_SFBM(spmat, compact = TRUE) X2[1:3, 2:3] X2$dense_acc(1:3, 2:3)
SFBM.Dimension and type methods for class SFBM.
## S4 method for signature 'SFBM' dim(x) ## S4 method for signature 'SFBM' length(x) ## S4 method for signature 'SFBM' diag(x) ## S4 method for signature 'SFBM_compact' diag(x) ## S4 method for signature 'SFBM_corr_compact' diag(x)## S4 method for signature 'SFBM' dim(x) ## S4 method for signature 'SFBM' length(x) ## S4 method for signature 'SFBM' diag(x) ## S4 method for signature 'SFBM_compact' diag(x) ## S4 method for signature 'SFBM_corr_compact' diag(x)
x |
An object of class SFBM. |
A reference class for storing and accessing sparse matrix-like data stored in files on disk, in a compact format (when non-zero values in columns are contiguous).
It inherits the fields and methods from class SFBM.
A reference class for storing and accessing from disk a sparse correlation matrix where non-zero values in columns are mostly contiguous. It rounds correlation values with precision 1/32767 to store them using 2 bytes only. This class has been specifically designed for package 'bigsnpr'.
Convert a 'dgCMatrix' or 'dsCMatrix' to an SFBM_corr_compact.
as_SFBM_corr_compact(spmat, backingfile = tempfile())as_SFBM_corr_compact(spmat, backingfile = tempfile())
spmat |
A 'dgCMatrix' (non-symmetric sparse matrix of type 'double') or 'dsCMatrix' (symmetric sparse matrix of type 'double'). |
backingfile |
Path to file where to store data. Extension |
It inherits the fields and methods from class SFBM_compact.
The new SFBM_corr_compact.
spmat2 <- as(cor(iris[1:4]), "dsCMatrix") (X2 <- as_SFBM_corr_compact(spmat2)) (bin <- readBin(X2$sbk, what = integer(), size = 2, n = 100)) matrix(bin / 32767, 4) spmat2spmat2 <- as(cor(iris[1:4]), "dsCMatrix") (X2 <- as_SFBM_corr_compact(spmat2)) (bin <- readBin(X2$sbk, what = integer(), size = 2, n = 100)) matrix(bin / 32767, 4) spmat2
A reference class for storing and accessing sparse matrix-like data stored in files on disk.
Convert a 'dgCMatrix' or 'dsCMatrix' to an SFBM.
as_SFBM(spmat, backingfile = tempfile(), compact = FALSE)as_SFBM(spmat, backingfile = tempfile(), compact = FALSE)
spmat |
A 'dgCMatrix' (non-symmetric sparse matrix of type 'double') or 'dsCMatrix' (symmetric sparse matrix of type 'double'). |
backingfile |
Path to file where to store data. Extension |
compact |
Whether to use a compact format? Default is |
An object of class SFBM has many fields:
$address: address of the external pointer containing the underlying
C++ object to be used as a XPtr<SFBM> in C++ code
$extptr: (internal) use $address instead
$nrow: number of rows
$ncol: number of columns
$nval: number of non-zero values
$p: vector of column positions
$backingfile or $sbk: File with extension 'sbk' that stores the
data of the SFBM
$rds: 'rds' file (that may not exist) corresponding to the 'sbk' file
$is_saved: whether this object is stored in $rds?
And some methods:
$save(): Save the SFBM object in $rds. Returns the SFBM.
$add_columns(): Add new columns from a 'dgCMatrix' or a 'dsCMatrix'.
$dense_acc(): Equivalent to as.matrix(.[ind_row, ind_col]). Use with
caution; ind_row and ind_col must be positive indices within range.
The new SFBM.
spmat2 <- Matrix::Diagonal(4, 0:3) spmat2[4, 2] <- 5 spmat2[1, 4] <- 6 spmat2[3, 4] <- 7 spmat2 # Stores all (i, x) for x != 0 (X2 <- as_SFBM(spmat2)) matrix(readBin(X2$sbk, what = double(), n = 100), 2) # Stores only x, but all (even the zero ones) from first to last being not 0 (X3 <- as_SFBM(spmat2, compact = TRUE)) X3$first_i readBin(X3$sbk, what = double(), n = 100)spmat2 <- Matrix::Diagonal(4, 0:3) spmat2[4, 2] <- 5 spmat2[1, 4] <- 6 spmat2[3, 4] <- 7 spmat2 # Stores all (i, x) for x != 0 (X2 <- as_SFBM(spmat2)) matrix(readBin(X2$sbk, what = double(), n = 100), 2) # Stores only x, but all (even the zero ones) from first to last being not 0 (X3 <- as_SFBM(spmat2, compact = TRUE)) X3$first_i readBin(X3$sbk, what = double(), n = 100)
Products between an SFBM and a vector.
sp_prodVec(X, y) sp_cprodVec(X, y)sp_prodVec(X, y) sp_cprodVec(X, y)
X |
An SFBM. |
y |
A vector of same size of the number of columns of |
sp_prodVec(): the vector which is equivalent to X %*% y
if X was a dgCMatrix.
sp_cprodVec(): the vector which is equivalent to Matrix::crossprod(X, y)
if X was a dgCMatrix.
spmat <- Matrix::rsparsematrix(1000, 1000, 0.01) X <- as_SFBM(spmat) sp_prodVec(X, rep(1, 1000)) sp_cprodVec(X, rep(1, 1000))spmat <- Matrix::rsparsematrix(1000, 1000, 0.01) X <- as_SFBM(spmat) sp_prodVec(X, rep(1, 1000)) sp_cprodVec(X, rep(1, 1000))
Solve Ax=b where A is a symmetric SFBM, and b is a vector.
sp_solve_sym( A, b, add_to_diag = rep(0, ncol(A)), tol = 1e-10, maxiter = 10 * ncol(A) )sp_solve_sym( A, b, add_to_diag = rep(0, ncol(A)), tol = 1e-10, maxiter = 10 * ncol(A) )
A |
A symmetric SFBM. |
b |
A vector. |
add_to_diag |
Vector (or single value) to virtually add to
the diagonal of |
tol |
Tolerance for convergence. Default is |
maxiter |
Maximum number of iterations for convergence. |
The vector x, solution of Ax=b.
N <- 100 spmat <- Matrix::rsparsematrix(N, N, 0.01, symmetric = TRUE) X <- bigsparser::as_SFBM(as(spmat, "dgCMatrix")) b <- runif(N) test <- tryCatch(as.vector(Matrix::solve(spmat, b)), error = function(e) print(e)) test2 <- tryCatch(sp_solve_sym(X, b), error = function(e) print(e)) test3 <- as.vector(Matrix::solve(spmat + Matrix::Diagonal(N, 1:N), b)) test4 <- sp_solve_sym(X, b, add_to_diag = 1:N) all.equal(test3, test4)N <- 100 spmat <- Matrix::rsparsematrix(N, N, 0.01, symmetric = TRUE) X <- bigsparser::as_SFBM(as(spmat, "dgCMatrix")) b <- runif(N) test <- tryCatch(as.vector(Matrix::solve(spmat, b)), error = function(e) print(e)) test2 <- tryCatch(sp_solve_sym(X, b), error = function(e) print(e)) test3 <- as.vector(Matrix::solve(spmat + Matrix::Diagonal(N, 1:N), b)) test4 <- sp_solve_sym(X, b, add_to_diag = 1:N) all.equal(test3, test4)