This is a convenience method that returns a data frame summarising the index values for multiple tour paths.
paths_index(bases_list, index_f)Arguments
- bases_list
list of histories produced by
save_history- index_f
index function to apply to each projection
Examples
# The max.tries is low for satisfying CRAN checks
# Increase it for using in practice
holes1d <- guided_tour(holes(), 1, max.tries=2)
# Perform guided tour 5 times, saving results
tries <- replicate(5, save_history(flea[, 1:6], holes1d), simplify = FALSE)
#> Converting input data to the required matrix format.
#> Value 2.541 0.0 % better
#> No better bases found after 2 tries. Giving up.
#> Final projection:
#> 0.517 -0.420 0.661 -0.330 0.059 0.079
#> Converting input data to the required matrix format.
#> Value 2.541 5.8 % better - NEW BASIS
#> Value 2.541 0.0 % better
#> No better bases found after 2 tries. Giving up.
#> Final projection:
#> -0.212 -0.208 0.333 0.551 0.084 0.700
#> Converting input data to the required matrix format.
#> Value 2.541 0.0 % better
#> No better bases found after 2 tries. Giving up.
#> Final projection:
#> 0.585 0.689 0.190 0.124 -0.318 0.173
#> Converting input data to the required matrix format.
#> Value 2.541 7.5 % better - NEW BASIS
#> Value 2.541 0.0 % better
#> No better bases found after 2 tries. Giving up.
#> Final projection:
#> 0.411 -0.201 -0.550 0.145 -0.683 -0.010
#> Converting input data to the required matrix format.
#> Value 2.541 0.0 % better
#> No better bases found after 2 tries. Giving up.
#> Final projection:
#> 0.254 0.533 0.631 0.458 -0.168 -0.123
# Interpolate between target bases
itries <- lapply(tries, interpolate)
paths <- paths_index(itries, holes())
head(paths)
#> try step value improvement
#> 1 1 1 2.541494 0.000000000
#> 2 2 1 2.401972 0.000000000
#> 3 2 2 2.492944 0.090971575
#> 4 2 3 2.442931 -0.050012650
#> 5 2 4 2.434656 -0.008275526
#> 6 2 5 2.541494 0.106838499
if (require(ggplot2)) {
ggplot(data = paths, aes(x=step, y=value, group = try)) + geom_line()
## ggplot(data = paths, aes(x=step, y=improvement, group = try)) + geom_line()
}
