Time each index evaluation for projections in the tour path.

Index evaluation timing may depend on the data distribution, we evaluate the computing time for a set of different projections to get an overview of the distribution of computing times.

Usage

time_sequence(d, t, idx, pmax)

Arguments

d: Input data in matrix format
t: List of projection matrices (e.g. interpolated tour path)
idx: Index function
pmax: Maximum number of projections to evaluate (cut t if longer than pmax)

Value

numeric vector containing all distances

Examples

d <- as.matrix(spiral_data(500, 4))
t <- purrr::map(1:10, ~ tourr::basis_random(4))
idx <- scag_index("stringy")
time_sequence(d, t, idx, 10)
#>        t  i
#> 1  0.048  1
#> 2  0.047  2
#> 3  0.046  3
#> 4  0.046  4
#> 5  0.047  5
#> 6  0.052  6
#> 7  0.046  7
#> 8  0.042  8
#> 9  0.055  9
#> 10 0.048 10