64 lines
2.1 KiB
R
64 lines
2.1 KiB
R
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#' Matrix Times Vectorized Kronecker product
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#'
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#' \deqn{C = A vec(B_1\otimes ... \otimes B_r)}{%
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#' C = A vec(B_1 %x% ... %x% B_r)}
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#'
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#' This function is equivalent to `c(A %*% c(Reduce("%x%", Bs)))`.
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#'
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#' @param A matrix of dimensions `n` by `pp * qq`
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#' @param Bs list of matrices such that the product there Kronecker product has
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#' dimensions `pp` by `qq`.
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#'
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#' @returns vector of length `n`
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#'
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#' @examples
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#' n <- 17
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#' p <- c(2, 5, 11)
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#' q <- c(3, 7, 13)
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#'
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#' A <- matrix(rnorm(n * prod(p * q)), n)
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#' Bs <- Map(matrix, Map(rnorm, p * q), p)
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#'
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#' stopifnot(all.equal(
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#' c(A %*% c(Reduce(`%x%`, Bs))),
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#' mtvk(A, Bs)
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#' ))
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#'
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#' @note May be slower than `c(A %*% c(Reduce("%x%", Bs)))`.
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#' @TODO C++ version using Rcpp is much faster than plain C using `R`s C API!
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#'
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#' @export
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mtvk <- function(A, Bs) {
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c(A %*% c(Reduce("%x%", Bs)))
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# storage.mode(A) <- "double"
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# Bs <- Map(`storage.mode<-`, Bs, list("double"))
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# .Call("C_mtvk", A, Bs)
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}
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# n <- 17
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# p <- rev(c(11, 7, 20))
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# q <- rev(c(13, 5, 30))
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# r <- length(p)
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# A <- matrix(rnorm(n * prod(p * q)), n)
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# Bs <- Map(matrix, Map(rnorm, p * q), p)
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# microbenchmark::microbenchmark(
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# A %*% c(Reduce("%x%", Bs)),
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# mtvk(A, Bs)
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# )
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# gcc -I"/usr/share/R/include" -DNDEBUG -fpic -g -O2 -fdebug-prefix-map=/build/r-base-zYgbYq/r-base-4.2.1=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -c mtvk.c -o mtvk.o
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# g++ -I"/usr/share/R/include" -DNDEBUG -fpic -g -O2 -fdebug-prefix-map=/build/r-base-zYgbYq/r-base-4.2.1=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -c mtvk.cpp -o mtvk.o \
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# -std=gnu++14 -I"/usr/local/lib/R/site-library/Rcpp/include" -I"/home/loki/Work/tensorPredictors/wip"
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# g++ -shared -L/usr/lib/R/lib -Wl,-Bsymbolic-functions -Wl,-z,relro -o sourceCpp_2.so mtvk.o -L/usr/lib/R/lib -lR \
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# -std=gnu++14
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# gcc -shared -L/usr/lib/R/lib -Wl,-Bsymbolic-functions -Wl,-z,relro -o tensorPredictors.so -L/usr/lib/R/lib -lR \
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# init.o mcrossprod.o mtvk.o poi.o ttm.o -lblas -lgfortran -lm -lquadmath
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