search_geodesic: A pseudo-derivative, line search algorithm.

In tourr: Tour Methods for Multivariate Data Visualisation

A pseudo-derivative, line search algorithm.

Description

This is a novel method for finding more interesting projections for the guided tour. It works by first taking a small step in n random directions, and then picking the direction that looks most promising (based on the height of the index function), which is effectively a gradient search. Then it performs a linear search along the geodesic in that direction, traveling up to half way around the sphere.

Usage

search_geodesic(
  current,
  alpha = 1,
  index,
  tries,
  max.tries = 5,
  ...,
  n = 5,
  delta = 0.01,
  cur_index = NA
)

Arguments

current	starting projection
alpha	maximum distance to travel (currently ignored)
index	interestingness index function
tries	the counter of the outer loop of the opotimiser
max.tries	maximum number of failed attempts before giving up
...	other arguments being passed into the search_geodesic()
n	number of random steps to take to find best direction
delta	step size for evaluation of best direction
cur_index	index value for starting projection, set NA if it needs to be calculated

Details

You should not to have call this function directly, but should supply it to the guided_tour as a search strategy.

Examples

animate_xy(flea[, 1:6], guided_tour(holes(), search_f = search_geodesic))

tourr documentation built on May 29, 2024, 11:22 a.m.