mateable (version 0.3.3)

matingSummary: Summarize a Mating Scene

Description

Create a summary of information contained within a matingScene object.

Usage

matingSummary(
  scene,
  type = "auto",
  k = 1,
  compatMethod = "si_echinacea",
  as.data.frame = FALSE
)

Value

a list, list of lists, or dataframe containing summary information including:

temporal - year (year), population start date (popSt), mean individual start date (meanSD), standard deviation of start (sdSD), mean duration (meanDur), standard deviation of duration (sdDur), peakDay - day(s) on which highest number of individuals were receptive (peak), mean end date (meanED), standard deviation of end date (sdED), population end date (popEnd)

spatial - minimum x (minX), minimum y (minY), maximum x (maxX), maximum y (maxY), average distance to kth nearest neighbor as specified by k (k<n> where n is the input for k)

compatibility - number of mating types (nMatType), average number of compatible mates (meanComp)

If scene is a multi-year matingScene, then the output will be a list of lists, one list for each year. If as.data.frame = TRUE, the output will be a dataframe with columns containing summary information and, if applicable, an 'id' column identifying what portion of the matingSummary object it summarized. If the scene is a multi-year matingScene, then the output will be a list of dataframes, one list for each year.

Arguments

scene

a matingScene object

type

character. whether to do a temporal (t), spatial (s), or mating type (mt) summary. The default is "auto" which will automatically summarize all mating information in scene

k

integer. Which nearest neighbor to calculate (only for type == "s")

compatMethod

character indicating the method to use when calculating compatiblity. Defaults to "si_echinacea"

as.data.frame

logical. If TRUE, returns summary as a dataframe.

Examples

eelr <- makeScene(ech2012, startCol = "firstDay", endCol = "lastDay",
  xCol = "Ecoord", yCol = "Ncoord", idCol = "tagNo")
eelrSum <- matingSummary(eelr)
eelrSum[c("minX", "minY", "maxX", "maxY")]