Report `n`

patches or turtles randomly selected among `agents`

.

nOf(agents, n) # S4 method for matrix,numeric nOf(agents, n)

agents | Matrix (ncol = 2) with the first column "pxcor" and the second column "pycor" representing the patches coordinates, or Matrix (ncol = 3) with the first column "pxcor" and the second column "pycor" representing the patches coordinates and the third column "id", or AgentMatrix object representing the moving agents, or Matrix (ncol = 2) with the first column "whoTurtles" and the second column "id". |
---|---|

n | Integer. Number of patches or turtles to select from |

Matrix (ncol = 2, nrow = `n`

) with the first column "pxcor"
and the second column "pycor" representing the coordinates of the
selected patches from `agents`

, or

Matrix (ncol = 2) with the first column "pxcor"
and the second column "pycor" representing the coordinates of the
selected patches from `agents`

, `n`

per individual "id", or

AgentMatrix (nrow = `n`

) representing the turtles
selected from `agents`

,

Integer. Vector of "who" numbers for the selected turtles from
`agents`

, `n`

per individual "id".

`n`

must be less or equal the number of patches
or turtles in `agents`

.

If `agents`

is a matrix with ncol = 3, the selection of `n`

random patches is done per individual "id". The order of the patches
coordinates returned follow the order of "id".
If `agents`

is a matrix (ncol = 2) with columns "whoTurtles" and
"id", the selection of `n`

random turtles (defined by their "whoTurtles")
is done per individual "id". The order of the "who" numbers returned
follow the order of "id".

Wilensky, U. 1999. NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University. Evanston, IL.

https://ccl.northwestern.edu/netlogo/docs/dictionary.html#n-of

# Patches w1 <- createWorld(minPxcor = 0, maxPxcor = 4, minPycor = 0, maxPycor = 4) pSelect <- nOf(agents = patches(w1), n = 5) # Turtles t1 <- createTurtles(n = 10, coords = randomXYcor(w1, n = 10)) tSelect <- nOf(agents = t1, n = 2)