使用 lapply 创建 ppp 对象（package spatstat）
Creating ppp objects with lapply (package spatstat)
我的最终目标是使用包 spatstat 计算数据帧列表的 Clark-Evans-Index (clarkevans.test)。
所以我有一个点数据列表：
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
和绘图坐标列表：
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
我创建了一个包含 owin 个对象的列表：
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
现在我想创建 ppp 个对象：
pattern.li <- lapply(points.li, function(x) {ppp(x$x.n, x$y.n, window=bound.li)})
导致：
Error in verifyclass(window, "owin") :
argument ‘window’ is not of class ‘owin’
我不知道问题出在使用 owin 对象列表还是我错误地使用了 lapply 和 ppp 函数，因为我需要在此处引用两个列表但不知道如何引用。任何提示如何解决这个问题？
(编辑) 我也试过了
mapply(function(x, y) {ppp(x$x.n, x$y.n, window=y)}, x=points.li, y=bound.li)
但这不是 return ppp 对象列表..
您正在将整个 owin 对象列表传递给 ppp 中的 window 参数。您可以使用 Map 来同时遍历两个列表。当您尝试 mapply 时，它会自动简化结果。您还可以将 SIMPLIFY=FALSE 参数用于 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
你最后的建议几乎奏效了。您只需要参数 SIMPLIFY = FALSE:
mapply(function(x, y) {ppp(x$x.n, x$y.n, window=y)}, x=points.li, y=bound.li, SIMPLIFY = FALSE)
或者，您可以调用函数 as.ppp，将 X 作为您的 data.frame 点坐标，将 W 作为您的 owin 对象：
mapply(as.ppp, X = points.li, W = bound.li, SIMPLIFY = FALSE)
我的最终目标是使用包 spatstat 计算数据帧列表的 Clark-Evans-Index (clarkevans.test)。
所以我有一个点数据列表：
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
和绘图坐标列表：
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
我创建了一个包含 owin 个对象的列表：
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
现在我想创建 ppp 个对象：
pattern.li <- lapply(points.li, function(x) {ppp(x$x.n, x$y.n, window=bound.li)})
导致：
Error in verifyclass(window, "owin") :
argument ‘window’ is not of class ‘owin’
我不知道问题出在使用 owin 对象列表还是我错误地使用了 lapply 和 ppp 函数，因为我需要在此处引用两个列表但不知道如何引用。任何提示如何解决这个问题？
(编辑) 我也试过了
mapply(function(x, y) {ppp(x$x.n, x$y.n, window=y)}, x=points.li, y=bound.li)
但这不是 return ppp 对象列表..
您正在将整个 owin 对象列表传递给 ppp 中的 window 参数。您可以使用 Map 来同时遍历两个列表。当您尝试 mapply 时，它会自动简化结果。您还可以将 SIMPLIFY=FALSE 参数用于 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
你最后的建议几乎奏效了。您只需要参数 SIMPLIFY = FALSE:
mapply(function(x, y) {ppp(x$x.n, x$y.n, window=y)}, x=points.li, y=bound.li, SIMPLIFY = FALSE)
或者，您可以调用函数 as.ppp，将 X 作为您的 data.frame 点坐标，将 W 作为您的 owin 对象：
mapply(as.ppp, X = points.li, W = bound.li, SIMPLIFY = FALSE)