## ----包括= false ---------------------------------------------------------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ------------------------------------------------------------------------------------------------------------------------库（SparsematrixStats）＃矩阵定义了稀疏矩阵类＃DGCMATRIX，我们将使用库（矩阵）＃用于可重复性set.seed（1）## ------------------------------------------------------------------------------------------------------------------------------- customer_ids <- seq_len(100) item_ids <- seq_len(30) n_transactions <- 1000 customer <- sample(customer_ids, size = n_transactions, replace = TRUE, prob = runif(100)) item <- sample(item_ids, size = n_transactions, replace = TRUE, prob = runif(30)) tmp <- table(paste0(customer, "-", item)) tmp2 <- strsplit(names(tmp), "-") purchase_table <- data.frame( customer = as.numeric(sapply(tmp2, function(x) x[1])), item = as.numeric(sapply(tmp2, function(x) x[2])), n = as.numeric(tmp) ) head(purchase_table, n = 10) ## ----------------------------------------------------------------------------- purchase_matrix <- sparseMatrix(purchase_table$customer, purchase_table$item, x = purchase_table$n, dims = c(100, 30), dimnames = list(customer = paste0("Customer_", customer_ids), item = paste0("Item_", item_ids))) purchase_matrix[1:10, 1:15] ## ----------------------------------------------------------------------------- # How often was each item bough in total? colSums2(purchase_matrix) # What is the range of number of items each # customer bought? head(rowRanges(purchase_matrix)) # What is the variance in the number of items # each customer bought? head(rowVars(purchase_matrix)) # How many items did a customer not buy at all, one time, 2 times, # or exactly 4 times? head(rowTabulates(purchase_matrix, values = c(0, 1, 2, 4))) ## ----------------------------------------------------------------------------- mat <- matrix(0, nrow=10, ncol=6) mat[sample(seq_len(60), 4)] <- 1:4 # Convert dense matrix to sparse matrix sparse_mat <- as(mat, "dgCMatrix") sparse_mat ## ----------------------------------------------------------------------------- apply(mat, 2, var) ## ----------------------------------------------------------------------------- matrixStats::colVars(mat) ## ----------------------------------------------------------------------------- sparseMatrixStats::colVars(sparse_mat) ## ----------------------------------------------------------------------------- big_mat <- matrix(0, nrow=1e4, ncol=50) big_mat[sample(seq_len(1e4 * 50), 5000)] <- rnorm(5000) # Convert dense matrix to sparse matrix big_sparse_mat <- as(big_mat, "dgCMatrix") ## ----------------------------------------------------------------------------- bench::mark( sparseMatrixStats=sparseMatrixStats::colVars(big_sparse_mat), matrixStats=matrixStats::colVars(big_mat), apply=apply(big_mat, 2, var) ) ## ----------------------------------------------------------------------------- sessionInfo()