sWanderlust

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Description

autoSPIN guided wanderlust. Specifically, we use autoSPIN to help find the starting point for wanderlust.

Usage

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sWanderlust(data, data_type = c("linear", "cyclical"),
  SPIN_option = c("STS", "neighborhood"), alpha = 0.2, sigma_width = 1,
  diffusionmap_components = 4, l = 15, k = 15, num_waypoints = 150,
  flock_waypoints = 2, waypoints_seed = 2711)

Arguments

data

data Input data matrix.

data_type

The data type which guides the autoSPIN sorting, including linear, cyclical.

SPIN_option

SPIN contains two options including STS(default), neighborhood.

alpha

alpha parameter for autoSPIN, default is 0.2.

sigma_width

Sigma width parameter for SPIN, default is 1.

diffusionmap_components

Number of components from diffusion map used for wanderlust analysis, default is 4.

l

Number of nearest neighbors, default is 15.

k

Number of nearest neighbors for repeating graphs, default is 15, should be less than or equal to l.

num_waypoints

Number of waypoint used for wanderlust, default is 150.

flock_waypoints

The number of times for flocking the waypoints, default is 2.

waypoints_seed

The seed for reproducing the results.

Value

a vector of the sorted oder.

Author(s)

Hao Chen

Examples

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set.seed(15)
shuffled_iris <- iris[sample(150, 150, replace = FALSE), ]
data <- shuffled_iris[,1:4]
data_label <- shuffled_iris[,5]
wishbone <- sWanderlust(data = data, num_waypoints = 100)

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