`gridded-methods.Rd`

returns logical (TRUE or FALSE) telling whether the object is gridded or not; in assignment promotes a non-gridded structure to a gridded one, or demotes a gridded structure back to a non-structured one.

```
gridded(obj)
gridded(obj) <- value
fullgrid(obj)
fullgrid(obj) <- value
gridparameters(obj)
```

- obj
object deriving from class "Spatial" (for gridded), or object of class SpatialGridDataFrame-class (for fullgrid and gridparameters)

- value
logical replacement values, TRUE or FALSE

- obj = "Spatial"
object deriving from class "Spatial"

if obj derives from class Spatial, gridded(object) will tell whether it is has topology on a regular grid; if assigned TRUE, if the object derives from SpatialPoints and has gridded topology, grid topology will be added to object, and the class of the object will be promoted to SpatialGrid-class or SpatialGridDataFrame-class

`fullgrid`

returns a logical, telling whether the grid is full
and ordered (i.e., in full matrix form), or whether it is not full
or unordered (i.e. a list of points that happen to lie on a grid. If
assigned, the way the points are stored may be changed. Changing a set
of points to full matrix form and back may change the original order of
the points, and will remove duplicate points if they were present.

`gridparameters`

returns, if `obj`

inherits from
SpatialGridDataFrame its grid parameters, else it returns numeric(0). The
returned value is a data.frame with three columns, named cellcentre.offset
("lower left cell centre coordinates"), cellsize, and cells.dim (cell
dimension); the rows correspond to the spatial dimensions.

```
# just 9 points on a grid:
x <- c(1,1,1,2,2,2,3,3,3)
y <- c(1,2,3,1,2,3,1,2,3)
xy <- cbind(x,y)
S <- SpatialPoints(xy)
class(S)
#> [1] "SpatialPoints"
#> attr(,"package")
#> [1] "sp"
plot(S)
gridded(S) <- TRUE
gridded(S)
#> [1] TRUE
class(S)
#> [1] "SpatialPixels"
#> attr(,"package")
#> [1] "sp"
summary(S)
#> Object of class SpatialPixels
#> Coordinates:
#> min max
#> x 0.5 3.5
#> y 0.5 3.5
#> Is projected: NA
#> proj4string : [NA]
#> Number of points: 9
#> Grid attributes:
#> cellcentre.offset cellsize cells.dim
#> x 1 1 3
#> y 1 1 3
plot(S)
gridded(S) <- FALSE
gridded(S)
#> [1] FALSE
class(S)
#> [1] "SpatialPoints"
#> attr(,"package")
#> [1] "sp"
# data.frame
data(meuse.grid)
coordinates(meuse.grid) <- ~x+y
gridded(meuse.grid) <- TRUE
plot(meuse.grid) # not much good
summary(meuse.grid)
#> Object of class SpatialPixelsDataFrame
#> Coordinates:
#> min max
#> x 178440 181560
#> y 329600 333760
#> Is projected: NA
#> proj4string : [NA]
#> Number of points: 3103
#> Grid attributes:
#> cellcentre.offset cellsize cells.dim
#> x 178460 40 78
#> y 329620 40 104
#> Data attributes:
#> part.a part.b dist soil ffreq
#> Min. :0.0000 Min. :0.0000 Min. :0.0000 1:1665 1: 779
#> 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.1193 2:1084 2:1335
#> Median :0.0000 Median :1.0000 Median :0.2715 3: 354 3: 989
#> Mean :0.3986 Mean :0.6014 Mean :0.2971
#> 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:0.4402
#> Max. :1.0000 Max. :1.0000 Max. :0.9926
```