Instantiating spatial polygon without using a shapefile in R

So, the usual way we read a shapefile in R is via the maptools package, like this:

sfdata <- readShapeSpatial("/path/to/my/shapefile.shp", proj4string=CRS("+proj=longlat"))

However, I have a use case whereby I don't have a shapefile.shp but instead I have a series of polygon coordinates

16.484375 59.736328125,17.4951171875 55.1220703125,24.74609375 55.0341796875,22.5927734375 61.142578125,16.484375 59.736328125

and its corresponding projection

coord. ref. : +proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0 

How do I "instantiate" sfdata (which will be a "polygon object") directly from this data? (without going in a roundabout way of creating a shapefile with these data and then reading from the newly created shapefile)

Answer

First get the coordinates into a 2-column matrix:

> xym
         [,1]     [,2]
[1,] 16.48438 59.73633

[2,] 17.49512 55.12207
[3,] 24.74609 55.03418
[4,] 22.59277 61.14258
[5,] 16.48438 59.73633

Then create a Polygon, wrap that into a Polygons object, then wrap that into a SpatialPolygons object:

> library(sp)
> p = Polygon(xym)
> ps = Polygons(list(p),1)
> sps = SpatialPolygons(list(ps))

The reason for this level of complexity is that a Polygon is a simple ring, a Polygons object can be several rings with an ID (here set to 1) (so is like a single feature in a GIS) and a SpatialPolygons can have a CRS. Ooh, I should probably set it:

> proj4string(sps) = CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0")

If you want to turn it into a SpatialPolygonsDataFrame (which is what comes our of readShapeSpatial when the shapefile is polygons) then do:

> data = data.frame(f=99.9)
> spdf = SpatialPolygonsDataFrame(sps,data)
> spdf

giving this:

> summary(spdf)
Object of class SpatialPolygonsDataFrame
Coordinates:
       min      max
x 16.48438 24.74609
y 55.03418 61.14258
Is projected: FALSE 
proj4string :
[+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0]
Data attributes:

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   99.9    99.9    99.9    99.9    99.9    99.9