Rwanderlust: R inplementation of wanderlust

In JinmiaoChenLab/uSORT: uSORT: A self-refining ordering pipeline for gene selection

Description

R inplementation of wanderlust

Usage

Rwanderlust(data, s, l = 15, k = 15, num_graphs = 1,
  num_waypoints = 250, waypoints_seed = 123, flock_waypoints = 2,
  metric = "euclidean", voting_scheme = "exponential",
  band_sample = FALSE, partial_order = NULL, verbose = TRUE)

Arguments

data	Input data matrix.
s	Starting point ID.
l	l nearest neighbours.
k	k nearest neighbours, k < l.
num_graphs	Number of repreated graphs.
num_waypoints	Number of waypoints to guide the trajectory detection.
waypoints_seed	The seed for reproducing the results.
flock_waypoints	The number of times for flocking the waypoints, default is 2.
metric	Distance calculation metric for nearest neighbour detection.
voting_scheme	The scheme of voting.
band_sample	Boolean, if band the sample
partial_order	default NULL
verbose	Boolean, if print the details

Value

a list containing Trajectory, Order, Waypoints

Author(s)

Hao Chen

Examples

set.seed(15)
shuffled_iris <- iris[sample(150, 150, replace = FALSE), ]
data <- shuffled_iris[,1:4]
data_label <- shuffled_iris[,5]
wishbone <- Rwanderlust(data = data, num_waypoints = 100, waypoints_seed = 2)
pd1 <- data.frame(id = wishbone$Trajectory, label=data_label, stringsAsFactors = FALSE)
pd2 <- data.frame(id = seq_along(row.names(data)), label=data_label, stringsAsFactors = FALSE)
#ggplot(pd1, aes(x=id, y=id, colour = label)) + geom_point() + theme_bw()
#ggplot(pd2, aes(x=id, y=id, colour = label)) + geom_point() + theme_bw()

JinmiaoChenLab/uSORT documentation built on May 7, 2019, 10:53 a.m.