guided_tour | R Documentation |
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.
guided_tour(
index_f,
d = 2,
alpha = 0.5,
cooling = 0.99,
max.tries = 25,
max.i = Inf,
search_f = search_geodesic,
n_sample = 100,
...
)
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 |
max.i |
the maximum index value, stop search if a larger value is found |
search_f |
the search strategy to use: |
n_sample |
number of samples to generate if |
... |
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, preferably between 0 and 1.
search_geodesic
, search_better
,
search_better_random
for different search strategies
flea_std <- apply(flea[,1:6], 2, function(x) (x-mean(x))/sd(x))
animate_xy(flea_std, guided_tour(holes()), sphere = TRUE)
animate_xy(flea_std, guided_tour(holes(), search_f = search_better_random), sphere = TRUE)
animate_dist(flea_std, guided_tour(holes(), 1), sphere = TRUE)
animate_xy(flea_std, guided_tour(lda_pp(flea$species)), sphere = TRUE, col = flea$species)
# 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_std[, 1:3]
tries <- replicate(5, save_history(f, guided_tour(holes())), simplify = FALSE)
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