paleotree (version 3.1.3)

binTimeData: Bin Simulated Temporal Ranges in Discrete Intervals

Description

Converts a matrix of simulated continuous-time first occurrences and last occurrences for fossil taxa into first and last occurrences given in some set of simulated/placed discrete-time intervals, which is output along with information of the dates of the given intervals.

Usage

binTimeData(timeData, int.length = 1, start = NA, int.times = NULL)

Arguments

timeData

Two-column matrix of simulated first and last occurrences in absolute continuous time

int.length

Time interval length, default is 1 time unit

start

Starting time for calculating the intervals.

int.times

A two column matrix with the start and end times of the intervals to be used.

Value

A list containing:

int.times

A 2 column matrix with the start and end times of the intervals used; time decreases relative to the present.

taxon.times

A 2 column matrix with the first and last occurrences of taxa in the intervals listed in int.times, with numbers referring to the row of int.times.

Details

This function takes a simulated matrix of per-taxon first and last occurrences and, by dividing the time-scale into time intervals of non-zero length, lists taxon occurrences within those interval. By default, a set of sequential non-overlapping time-interval of equal non-zero length are used, with the length controlled by the argument int.length.

Alternatively, a two column matrix of interval start and end times to be used can be input via the argument int.times. None of these intervals can have a duration (temporal length) greater than zero. If a first or last appearance in the input range data could fit into multiple intervals (i.e. the input discrete time intervals are overlapping), then the appearance data is placed in the interval of the shortest duration. When output, the interval times matrix (see below) will be sorted from first to last.

This function is SPECIFICALLY for simulating the effect of having a discrete time-scale for analyses using simulations. This function should not be used for non-simulations uses, such as binning temporal occurrences for analyses of real data. In those case, the temporal ranges (which, in real data, will probably be given as discrete time intervals) should already be tabulated within discrete intervals prior to use in paleotree. The user should place the temporal information in a list object, as described for the output of binTimeData (see below).

As with many functions in the paleotree library, absolute time is always decreasing, i.e. the present day is zero. However, the numbering of intervals giving in the output increases with time, as these are numbered relative to each other, from first to last.

As of version 1.7 of paleotree, taxa which are extant as indicated in timeData as being in a time interval bounded (0,0), unless time-bins are preset using argument int.times (prior to version 1.5 they were erroneously listed as NA).

See Also

simFossilRecord, sampleRanges, taxicDivCont

Examples

# NOT RUN {
#Simulate some fossil ranges with simFossilRecord
set.seed(444)
record <- simFossilRecord(p = 0.1, q = 0.1, nruns = 1,
nTotalTaxa = c(30,40), nExtant = 0)
taxa <- fossilRecord2fossilTaxa(record)
#simulate a fossil record with imperfect sampling with sampleRanges()
rangesCont <- sampleRanges(taxa,r = 0.5)
#Now let's use binTimeData() to bin in intervals of 1 time unit
rangesDisc <- binTimeData(rangesCont,int.length = 1)
#plot with taxicDivDisc()
equalDiscInt <- taxicDivDisc(rangesDisc)

#example with pre-set intervals input (including overlapping)
presetIntervals <- cbind(c(1000,990,970,940),c(980,970,950,930))
rangesDisc1 <- binTimeData(rangesCont,int.times = presetIntervals)
taxicDivDisc(rangesDisc1)
#now let's plot diversity with (different) equal length intervals used above
taxicDivDisc(rangesDisc1,int.times = equalDiscInt[,1:2])

#example with extant taxa
set.seed(444)
record <- simFossilRecord(p = 0.1, q = 0.1, nruns = 1,
nTotalTaxa = c(30,40))
taxa <- fossilRecord2fossilTaxa(record)
#simulate a fossil record with imperfect sampling with sampleRanges()
rangesCont <- sampleRanges(taxa,r = 0.5,,modern.samp.prob = 1)
#Now let's use binTimeData() to bin in intervals of 1 time unit
rangesDisc <- binTimeData(rangesCont,int.length = 1)
#plot with taxicDivDisc()
taxicDivDisc(rangesDisc)

#example with pre-set intervals input (including overlapping)
presetIntervals <- cbind(c(40,30,20,10),c(30,20,10,0))
rangesDisc1 <- binTimeData(rangesCont,int.times = presetIntervals)
taxicDivDisc(rangesDisc1)

# }