tests/testthat/test-matrix.R

In arules: Mining Association Rules and Frequent Itemsets

e <- new("ngCMatrix")
x <- new("ngCMatrix", p   = as.integer(c(0,3,5,7,7,10)),
                      i   = as.integer(c(1,2,4,1,2,0,4,0,2,5)),
                      Dim = as.integer(c(6,5)))
rownames(x) <- paste("I", 1:6, sep = "")
colnames(x) <- paste("T", 1:5, sep = "")
#x

##
#unclass(x)

## validity
expect_true(getValidity(getClassDef("CsparseMatrix"))(x))
expect_true(.Call(arules:::R_valid_ngCMatrix, x))
expect_true(.Call(arules:::R_valid_ngCMatrix, e))

## reorder
expect_equal(.Call(arules:::R_recode_ngCMatrix, x, 6:1), x[6:1,])
expect_equal(.Call(arules:::R_recode_ngCMatrix, e, integer()), e)

## recode (add columns)
expect_identical(.Call(arules:::R_recode_ngCMatrix, x, c(1L,3:7)),
  as(rbind(x[1,,drop=FALSE], 
    Matrix(0, ncol = 5, sparse = TRUE), 
    x[2:6,, drop = FALSE]), "nsparseMatrix"))

## cbind
expect_identical(.Call(arules:::R_cbind_ngCMatrix, e, e), cbind(e,e))
expect_identical(.Call(arules:::R_cbind_ngCMatrix, x, x), cbind(x, x))

## logical OR
expect_identical(.Call(arules:::R_or_ngCMatrix, x, x), 
  as(x | x, "nsparseMatrix"))
expect_identical(.Call(arules:::R_or_ngCMatrix, e, e), 
  as(e | e, "nsparseMatrix"))

## crossprod and tcrossprod
expect_equal(.Call(arules:::R_crosstab_ngCMatrix, x, NULL, TRUE),
  as(Matrix::tcrossprod(as(as(x, "ngCMatrix"), "dsparseMatrix")), "matrix"))
expect_equal(.Call(arules:::R_crosstab_ngCMatrix, x, NULL, FALSE),
  as(Matrix::crossprod(as(as(x, "ngCMatrix"), "dsparseMatrix")), "matrix"))

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