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switch to MatrixExtra (#68)
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david-cortes authored May 22, 2021
1 parent 6e72fed commit 08609e6
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Showing 17 changed files with 25 additions and 1,390 deletions.
4 changes: 2 additions & 2 deletions DESCRIPTION
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Expand Up @@ -40,9 +40,9 @@ License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
ByteCompile: true
Depends: R (>= 3.6.0), methods
Depends: R (>= 3.6.0), methods, MatrixExtra
Imports:
Matrix (>= 1.3),
Matrix (>= 1.3),
Rcpp (>= 0.11),
data.table (>= 1.10.0),
float (>= 0.2-2),
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7 changes: 0 additions & 7 deletions NAMESPACE
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Expand Up @@ -8,17 +8,10 @@ export(PureSVD)
export(ScaleNormalize)
export(WRMF)
export(ap_k)
export(as.coo.matrix)
export(as.csc.matrix)
export(as.csr.matrix)
export(detect_number_omp_threads)
export(ndcg_k)
export(soft_impute)
export(soft_svd)
exportMethods("%*%")
exportMethods("[")
exportMethods(crossprod)
exportMethods(tcrossprod)
import(Matrix)
import(Rcpp)
import(data.table)
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24 changes: 0 additions & 24 deletions R/RcppExports.R
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Expand Up @@ -53,30 +53,6 @@ arma_kmeans <- function(x, k, seed_mode, n_iter, verbose, result) {
.Call(`_rsparse_arma_kmeans`, x, k, seed_mode, n_iter, verbose, result)
}

check_is_seq <- function(indices) {
.Call(`_rsparse_check_is_seq`, indices)
}

copy_csr_rows <- function(indptr, indices, values, rows_take) {
.Call(`_rsparse_copy_csr_rows`, indptr, indices, values, rows_take)
}

copy_csr_rows_col_seq <- function(indptr, indices, values, rows_take, cols_take) {
.Call(`_rsparse_copy_csr_rows_col_seq`, indptr, indices, values, rows_take, cols_take)
}

copy_csr_arbitrary <- function(indptr, indices, values, rows_take, cols_take) {
.Call(`_rsparse_copy_csr_arbitrary`, indptr, indices, values, rows_take, cols_take)
}

csr_dense_tcrossprod <- function(x_csr_r, y_transposed, num_threads = 1L) {
.Call(`_rsparse_csr_dense_tcrossprod`, x_csr_r, y_transposed, num_threads)
}

dense_csc_prod <- function(x_r, y_csc_r, num_threads = 1L) {
.Call(`_rsparse_dense_csc_prod`, x_r, y_csc_r, num_threads)
}

top_product <- function(x, y, k, n_threads, not_recommend_r, exclude, glob_mean = 0.) {
.Call(`_rsparse_top_product`, x, y, k, n_threads, not_recommend_r, exclude, glob_mean)
}
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