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Dyad ID

Source: R/dyad_id.R
dyad_id.Rd

Generate a dyad ID for edge list generated by edge_nn or edge_dist.

Usage

dyad_id(DT = NULL, id1 = NULL, id2 = NULL)

Arguments

DT

input data.table with columns id1 and id2, as generated by edge_dist or edge_nn

id1

ID1 column name generated by edge_dist or edge_nn

id2

ID2 column name generated by edge_dist or edge_nn

Value

dyad_id returns the input data.table with appended "dyadID" column

Details

An undirected edge identifier between, for example individuals A and B will be A-B (and reverse B and A will be A-B). Internally sorts and pastes id columns.

More details in the edge and dyad vignette (in progress).

Examples

# Load data.table
library(data.table)

# Read example data
DT <- fread(system.file("extdata", "DT.csv", package = "spatsoc"))

# Cast the character column to POSIXct
DT[, datetime := as.POSIXct(datetime, tz = 'UTC')]
#>            ID        X       Y            datetime population
#>        <char>    <num>   <num>              <POSc>      <int>
#>     1:      A 715851.4 5505340 2016-11-01 00:00:54          1
#>     2:      A 715822.8 5505289 2016-11-01 02:01:22          1
#>     3:      A 715872.9 5505252 2016-11-01 04:01:24          1
#>     4:      A 715820.5 5505231 2016-11-01 06:01:05          1
#>     5:      A 715830.6 5505227 2016-11-01 08:01:11          1
#>    ---                                                       
#> 14293:      J 700616.5 5509069 2017-02-28 14:00:54          1
#> 14294:      J 700622.6 5509065 2017-02-28 16:00:11          1
#> 14295:      J 700657.5 5509277 2017-02-28 18:00:55          1
#> 14296:      J 700610.3 5509269 2017-02-28 20:00:48          1
#> 14297:      J 700744.0 5508782 2017-02-28 22:00:39          1

# Temporal grouping
group_times(DT, datetime = 'datetime', threshold = '20 minutes')
#>            ID        X       Y            datetime population minutes timegroup
#>        <char>    <num>   <num>              <POSc>      <int>   <int>     <int>
#>     1:      A 715851.4 5505340 2016-11-01 00:00:54          1       0         1
#>     2:      A 715822.8 5505289 2016-11-01 02:01:22          1       0         2
#>     3:      A 715872.9 5505252 2016-11-01 04:01:24          1       0         3
#>     4:      A 715820.5 5505231 2016-11-01 06:01:05          1       0         4
#>     5:      A 715830.6 5505227 2016-11-01 08:01:11          1       0         5
#>    ---                                                                         
#> 14293:      J 700616.5 5509069 2017-02-28 14:00:54          1       0      1393
#> 14294:      J 700622.6 5509065 2017-02-28 16:00:11          1       0      1394
#> 14295:      J 700657.5 5509277 2017-02-28 18:00:55          1       0      1440
#> 14296:      J 700610.3 5509269 2017-02-28 20:00:48          1       0      1395
#> 14297:      J 700744.0 5508782 2017-02-28 22:00:39          1       0      1396

# Edge list generation
edges <- edge_dist(
    DT,
    threshold = 100,
    id = 'ID',
    coords = c('X', 'Y'),
    timegroup = 'timegroup',
    returnDist = TRUE,
    fillNA = TRUE
  )

# Generate dyad IDs
dyad_id(edges, 'ID1', 'ID2')
#> Key: <timegroup, ID1>
#>        timegroup    ID1    ID2  distance dyadID
#>            <int> <char> <char>     <num> <char>
#>     1:         1      A   <NA>        NA   <NA>
#>     2:         1      B      G  5.782904    B-G
#>     3:         1      C   <NA>        NA   <NA>
#>     4:         1      D   <NA>        NA   <NA>
#>     5:         1      E      H 65.061671    E-H
#>    ---                                         
#> 22985:      1440      G   <NA>        NA   <NA>
#> 22986:      1440      H   <NA>        NA   <NA>
#> 22987:      1440      I      C  2.831071    C-I
#> 22988:      1440      I      F  7.512922    F-I
#> 22989:      1440      J   <NA>        NA   <NA>