tests/sparse_matrix.R

In coop: Co-Operation: Fast Covariance, Correlation, and Cosine Similarity Operations

library(coop)
m <- 30
n <- 10


test <- function(dense, sparse)
{
  t1 <- coop::cosine(dense)
  t2 <- coop::cosine(sparse)
  stopifnot(all.equal(t1, t2))
  
  ### these will fail because we use a cholesky to compute the inverse
  # t1 <- coop::cosine(dense, inverse=TRUE)
  # t2 <- coop::cosine(sparse, inverse=TRUE)
  # stopifnot(all.equal(t1, t2))
}


if (suppressPackageStartupMessages(require(slam)))
{
  suppressPackageStartupMessages(library(slam))
  set.seed(1234)
  
  ### Very sparse, has column of 0's
  x <- coop:::dense_stored_sparse_mat(m, n, prop=.05)
  coo <- as.simple_triplet_matrix(x)
  test(x, coo)
  
  colnames(x) <- sample(letters, size=n, replace=TRUE)
  coo <- as.simple_triplet_matrix(x)
  test(x, coo)
  
  ### Not very sparse
  x <- coop:::dense_stored_sparse_mat(m, n, prop=.25)
  coo <- as.simple_triplet_matrix(x)
  test(x, coo)
  
  colnames(x) <- sample(letters, size=n, replace=TRUE)
  coo <- as.simple_triplet_matrix(x)
  test(x, coo)
}



if (suppressPackageStartupMessages(require(Matrix)))
{
  suppressPackageStartupMessages(library(Matrix))
  set.seed(1234)
  
  ### Very sparse, has column of 0's
  x <- coop:::dense_stored_sparse_mat(m, n, prop=.05)
  csc <- as(x, "sparseMatrix")
  test(x, csc)
  
  colnames(x) <- sample(letters, size=n, replace=TRUE)
  csc <- as(x, "sparseMatrix")
  test(x, csc)
  
  ### Not very sparse
  x <- coop:::dense_stored_sparse_mat(m, n, prop=.25)
  csc <- as(x, "sparseMatrix")
  test(x, csc)
  
  colnames(x) <- sample(letters, size=n, replace=TRUE)
  csc <- as(x, "sparseMatrix")
  test(x, csc)
}