guided_tour: A guided tour path.
In nspyrison/tourr: Implement Tour Methods in R Code

Description Usage Arguments Details See Also Examples

Instead of choosing new projections at random like the grand tour, the guided tour always tries to find a projection that is more interesting than the current projection.

1 2	guided_tour(index_f, d = 2, alpha = 0.5, cooling = 0.99, max.tries = 25, search_f = search_geodesic, ...)

`index_f`	the index function to optimise.
`d`	target dimensionality
`alpha`	the initial size of the search window, in radians
`cooling`	the amount the size of the search window should be adjusted by after each step
`max.tries`	the maximum number of unsuccessful attempts to find a better projection before giving up
`search_f`	the search strategy to use
`...`	arguments sent to the search_f

Currently the index functions only work in 2d.

Usually, you will not call this function directly, but will pass it to a method that works with tour paths like animate, save_history or render.

cmass, holes and lda_pp for examples of index functions. The function should take a numeric matrix and return a single number, preferrably between 0 and 1. search_geodesic, search_better, search_better_random for different search strategies

animate_xy(flea[, 1:3], guided_tour(holes), sphere = TRUE)
animate_xy(flea[, 1:6], guided_tour(holes), sphere = TRUE)
animate_dist(flea[, 1:6], guided_tour(holes, 1), sphere = TRUE)

# save_history is particularly useful in conjunction with the
# guided tour as it allows us to look at the tour path in many different
# ways
f <- flea[, 1:3]
tries <- replicate(5, save_history(f, guided_tour(holes)), simplify = FALSE)