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Create sparse integer vector

Source: R/sparse_integer.R
sparse_integer.Rd

Construction of vectors where only values and positions are recorded. The Length and default values determine all other information.

Usage

sparse_integer(values, positions, length, default = 0L)

Arguments

values

integer vector, values of non-zero entries.

positions

integer vector, indices of non-zero entries.

length

integer value, Length of vector.

default

integer value, value at indices not specified by positions. Defaults to 0L. Cannot be NA.

Value

sparse integer vector

Details

values and positions are expected to be the same length, and are allowed to both have zero length.

Allowed values for value is integer values. This means that the double vector c(1, 5, 4) is accepted as it can be losslessly converted to the integer vector c(1L, 5L, 4L). Missing values such as NA and NA_real_ are allowed. Everything else is disallowed, This includes Inf and NaN. The values are also not allowed to take the same value as default.

positions should be integers or integer-like doubles. Everything else is not allowed. Positions should furthermore be positive (0 not allowed), unique, and in increasing order. Lastly they should all be smaller that length.

For developers:

setting options("sparsevctrs.verbose_materialize" = TRUE) will print a message each time a sparse vector has been forced to materialize.

See also

sparse_double() sparse_character()

Examples

sparse_integer(integer(), integer(), 10)
#>  [1] 0 0 0 0 0 0 0 0 0 0

sparse_integer(c(4, 5, 7), c(2, 5, 10), 10)
#>  [1] 0 4 0 0 5 0 0 0 0 7

str(
  sparse_integer(c(4, 5, 7), c(2, 5, 10), 1000000000)
)
#>  int [1:1000000000] 0 4 0 0 5 0 0 0 0 7 ...