Report the individuals among `turtles`

that are located on the `patches`

at
`(dx, dy)`

distances of the `agents`

.

```
turtlesAt(world, turtles, agents, dx, dy, breed, torus = FALSE)
# S4 method for worldNLR,agentMatrix,matrix,numeric,numeric,missing
turtlesAt(world, turtles, agents, dx, dy, torus)
# S4 method for worldNLR,agentMatrix,matrix,numeric,numeric,character
turtlesAt(world, turtles, agents, dx, dy, breed, torus = FALSE)
```

## Arguments

- world
`WorldMatrix`

or `worldArray`

object.

- turtles
`AgentMatrix`

object representing the moving `agents`

.

- agents
Matrix (`ncol`

= 2) with the first column `pxcor`

and the second
column `pycor`

representing the `patches`

coordinates, or

` `AgentMatrix` object representing the moving `agents`.`

- dx
Numeric. Vector of distances to the east (right) from the `agents`

.
If `dx`

is negative, the distance to the west (left) is computed.
`dx`

must be of length 1 or of the same length as number of `patches`

or `turtles`

in `agents`

.

- dy
Numeric. Vector of distances to the north (up) from the `agents`

.
If `dy`

is negative, the distance to the south is computed (down).
`dy`

must be of length 1 or of the same length as number of `patches`

or `turtles`

in `agents`

.

- breed
Characters. Vector of `breed`

names for the selected `turtles`

.
If missing, there is no distinction based upon `breed`

.

- torus
Logical to determine if the `world`

is wrapped. Default is
`torus = FALSE`

.

## Value

`AgentMatrix`

representing the individuals among `turtles`

of any of the given `breed`

, if specified,
which are located on the `patches`

at `(dx, dy)`

distances of the
`agents`

.

## Details

If the `patch`

at distance `(dx, dy)`

of an `agent`

is outside of the `world`

's extent and `torus = FALSE`

,
no `turtle`

is returned;
if `torus = TRUE`

, the `turtle`

located on the `patch`

whose coordinates
are defined from the wrapped `world`

is returned.

## References

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

## Examples

```
w1 <- createWorld(minPxcor = 0, maxPxcor = 9, minPycor = 0, maxPycor = 9)
t1 <- createTurtles(
n = 10, coords = cbind(xcor = 0:9, ycor = 0:9),
breed = c(rep("sheep", 5), rep("wolf", 5))
)
t2 <- turtlesAt(
world = w1, turtles = t1, agents = turtle(t1, who = 0),
dx = 1, dy = 1
)
t3 <- turtlesAt(
world = w1, turtles = t1,
agents = patch(w1, c(3, 4, 5), c(3, 4, 5)), dx = 1, dy = 1,
breed = "sheep"
)
```