determining initial trajectory and landmarks

Description

determining initial trajectory and landmarks

Usage

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trajectory_landmarks(knn, data, s, partial_order = NULL, waypoints = 250,
  waypoints_seed = 123, metric = "euclidean", flock_waypoints = 2,
  band_sample = FALSE)

Arguments

knn

A sparse matrix of knn.

data

data.

s

The ID of starting point.

partial_order

A vector of IDs specified as recommended waypoints, NULL to ignore.

waypoints

Either the number of waypoints, or specify the waypoint IDs.

waypoints_seed

Random sampling seed, for reproducible results.

metric

Distance calculation metric for nearest neighbour detection.

flock_waypoints

Iteration of using nearest points around waypoint to adjust its position.

band_sample

if give more chance to nearest neighbours of starting point in randomly waypoints selection.

Value

a list

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