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make_matrix <- function(nrow, ncol, frac_zero = 0.8, frac_na = 0){
n_total <- ncol * nrow
data <- rnorm(n = n_total, mean=0, sd=10)
data[sample(seq_len(n_total), size = round(n_total * frac_zero))] <- 0
data[sample(seq_len(n_total), size = round(n_total * frac_na))] <- NA
matrix(data, nrow=nrow, ncol=ncol)
}
make_matrix_with_all_features <- function(nrow, ncol){
if(ncol < 8){
stop("Too few columns")
}
mat <- make_matrix(nrow, ncol, frac_zero = 0.8)
# All observed
mat[,1] <- rnorm(nrow)
# All zero
mat[,2] <- 0
# Some missing
mat[7, 3] <- NA
# All missing
mat[,4] <- NA
# Some infinite
mat[1, 5] <- Inf
mat[3, 6] <- -Inf
# Some with known value
mat[1, 7] <- 42
mat
}
make_matrix_with_all_features_with_explicit_zeros <- function(nrow, ncol, frac_zero = 0.7){
i <- c(sample.int(nrow, round(nrow * ncol * (1-frac_zero)), replace = TRUE), 4, 1, 2)
j <- c(sample.int(ncol, round(nrow * ncol * (1-frac_zero)), replace = TRUE), 1, 3, 2)
x <- c(rpois(n = round(nrow * ncol * (1-frac_zero)), lambda = 0.5), NA, NA, -1)
Matrix::sparseMatrix(i = i, j = j, x = x, dims = c(nrow, ncol))
}
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