R: Calculates recursion information from the 3D trajectory

getRecursions3D {recurse}

R Documentation

Calculates recursion information from the 3D trajectory

Description

A sphere of radius R is drawn around each point in the trajectory. The number of revisits is calculated as the number of segments of the trajectory passing through that sphere.

Usage

getRecursions3D(
  x,
  radius,
  threshold = 0,
  timeunits = c("hours", "secs", "mins", "days"),
  verbose = TRUE
)

## S3 method for class 'data.frame'
getRecursions3D(
  x,
  radius,
  threshold = 0,
  timeunits = c("hours", "secs", "mins", "days"),
  verbose = TRUE
)

Arguments

`x`	A data frame with the trajectory data in five columns (the x-coordinate, the y-coordinate, the z-coordinate, the datetime, and the animal id).
`radius`	numeric radius to use in units of the (x,y,z) location data to detect recursions.
`threshold`	a time difference (in units `timeunits`) to ignore excursions outside the radius. Defaults to 0.
`timeunits`	character string specifying units to calculate time differences in for the time spans inside the radius and since the visit in `revisitStats`. Defaults to hours.
`verbose`	`TRUE` to output complete information (can be large for large input data frames) or `FALSE` to output basic information.

Details

For each point in the trajectory, a sphere of radius R is drawn around that point. Then the number of segments of the trajectory passing through that sphere is counted. This is the number of revisits, so each point will have at least one revisit (the initial visit). For each revisit, the time spent inside the sphere is calculated, as well as the time since the last visit (NA for the first visit). In order to calculate the time values, the crossing time of the radius is calculated by assuming linear movement at a constant speed between the points inside and outside the sphere.

Projection. Consider the projection used. Since segments are counted passing through spheres drawn around points, an equal area projection would ensure similar size comparisons (e.g., spTransform).

Either single or multiple individuals are supported, but be aware that this function will be slow with large amounts of data (e.g. millions of points), so consider pre-specifying the locations (getRecursionsAtLocations) or use clustering. Multiple individuals are handled via the id column of the data.frame.

Value

A list with several components, revisits and residenceTime are vectors of the same length as the x dataframe. revisits is the number of revisits for each location, where 1 means that there were no revisits, only the initial visit. residenceTime is the total time spent withing the radius. radius is the specified radius used for all the calculations. timeunits is the specified time units used to specify timespans.

When verbose = TRUE, additional information is also returned, dists and revisitStats. Next, dists gives the distance matrix between all locations. Finally, revisitStats gives further statistics on each visit. These are calculated per location (i.e., no aggregation of nearby points is performed), and give the index and location of the point of the track at the center of the radius, the radius entrance and exit time of the track for that visit, how much time was spent inside the radius, and how long since the last visit (NA for the first visit).

Methods (by class)

getRecursions3D(data.frame): Get recursions for a data.frame object consisting of columns x, y, z, datetime, and id

Author(s)

Chloe Bracis <cbracis@uw.edu>

Examples

data(martin)
revisits = getRecursions(martin, radius = 1)
plot(revisits, martin, legendPos = c(10, -15))
drawCircle(10, -10, 1)

[Package recurse version 1.4.0 Index]