Reputation: 10123
My ultimate goal is to calculate Clark-Evans-Index (clarkevans.test
) for a list of data frames using package spatstat.
So I have a list of my point data:
points.li <- list(structure(list(x.n = c(-1.37977544977995, 0.0787053126116266,
-6.50583075192879, -9.17021249875416, -19.4146851390704, -22.7380870106472,
-20.3267566111816, -15.7328116296655, -8.74750043303314, -11.8963575795747
), y.n = c(13.1276911114957, 2.22311850078447, 9.48873515598742,
2.7986686485412, 2.56632386092958, -0.757078010647191, 6.88269379207495,
11.5304629645448, 19.131978467755, 28.8757897612883)), row.names = 1098:1107, class = "data.frame", .Names = c("x.n",
"y.n")), structure(list(x.n = c(0.104714438623701, 1.93357872460516,
1.51117985822383, 4.47756948027361, 0.710996014054978, -0.727469791776916,
0.694499984379773, 2.88088318987335, -5.90066975026119, -11.3699018974284
), y.n = c(-5.99908617093835, -9.09677268682439, -12.3075722803524,
-16.7105167948009, -16.2844860117843, -13.8809505330886, -19.88787745768,
-20.4985490229505, -14.9797228445106, -17.1780479345837)), row.names = 108:117, class = "data.frame", .Names = c("x.n",
"y.n")))
> points.li
[[1]]
x.n y.n
1098 -1.37977545 13.127691
1099 0.07870531 2.223119
1100 -6.50583075 9.488735
1101 -9.17021250 2.798669
1102 -19.41468514 2.566324
1103 -22.73808701 -0.757078
1104 -20.32675661 6.882694
1105 -15.73281163 11.530463
1106 -8.74750043 19.131978
1107 -11.89635758 28.875790
[[2]]
x.n y.n
108 0.1047144 -5.999086
109 1.9335787 -9.096773
110 1.5111799 -12.307572
111 4.4775695 -16.710517
112 0.7109960 -16.284486
113 -0.7274698 -13.880951
114 0.6945000 -19.887877
115 2.8808832 -20.498549
116 -5.9006698 -14.979723
117 -11.3699019 -17.178048
and a list of the plot coordinates:
ref.li <- list(structure(list(x.ref = c(-51.957519, -44.640527, 24.976003,
17.659011), y.ref = c(39.756418, -29.860112, -22.54312, 47.07341
)), class = "data.frame", row.names = c(NA, -4L), .Names = c("x.ref",
"y.ref")), structure(list(x.ref = c(15.613798, -52.306902, -35.372372,
32.548328), y.ref = c(40.306747, 23.372217, -44.548483, -27.613953
)), class = "data.frame", row.names = c(NA, -4L), .Names = c("x.ref",
"y.ref")))
> ref.li
[[1]]
x.ref y.ref
1 -51.95752 39.75642
2 -44.64053 -29.86011
3 24.97600 -22.54312
4 17.65901 47.07341
[[2]]
x.ref y.ref
1 15.61380 40.30675
2 -52.30690 23.37222
3 -35.37237 -44.54848
4 32.54833 -27.61395
I created a list of owin
objects:
library(spatstat)
bound.li <- lapply(ref.li, function(x) {owin(poly = list(x = x$x.ref, y = x$y.ref))})
> bound.li
[[1]]
window: polygonal boundary
enclosing rectangle: [-51.95752, 24.976] x [-29.86011, 47.07341] units
[[2]]
window: polygonal boundary
enclosing rectangle: [-52.3069, 32.54833] x [-44.54848, 40.30675] units
And now I'd like to create the ppp
objects:
pattern.li <- lapply(points.li, function(x) {ppp(x$x.n, x$y.n, window=bound.li)})
resulting in:
Error in verifyclass(window, "owin") :
argument ‘window’ is not of class ‘owin’
I don't know if the problem is using a list of owin objects or my incorrect use of lapply with the ppp function as I need to refer to two lists here but don't know how. Any hint how to solve this?
(edit) I also tried
mapply(function(x, y) {ppp(x$x.n, x$y.n, window=y)}, x=points.li, y=bound.li)
but that does not return a list of ppp objects..
Upvotes: 3
Views: 874
Reputation: 28441
You are passing the whole list of owin
objects to the window
parameter in ppp
. You can use Map
instead to iterate over both lists simultaneously. When you attempted mapply
it automatically simplified the result. You can also use the SIMPLIFY=FALSE
argument for mapply
:
Map(function(x, y) {ppp(x$x.n, x$y.n, window=y)}, x=points.li, y=bound.li)
#[[1]]
#Planar point pattern: 10 points
#window: polygonal boundary
#enclosing rectangle: [-51.95752, 24.976] x [-29.86011, 47.07341] units
#
#[[2]]
#Planar point pattern: 10 points
#window: polygonal boundary
#enclosing rectangle: [-52.3069, 32.54833] x [-44.54848, 40.30675] units
Upvotes: 5
Reputation: 4507
Your last suggestion almost works. You just need the argument SIMPLIFY = FALSE
:
mapply(function(x, y) {ppp(x$x.n, x$y.n, window=y)}, x=points.li, y=bound.li, SIMPLIFY = FALSE)
Alternatively you can call the function as.ppp
with X
as your data.frame
of point coordinates and W
as your owin
object:
mapply(as.ppp, X = points.li, W = bound.li, SIMPLIFY = FALSE)
Upvotes: 3