如何测量ggplot2中多边形的面积? [英] How to measure the area of a polygon in ggplot2?
问题描述
大家好，我有许多样本，我想为每个样本绘制一个多边形来说明数据的形状.我的数据看起来像这样:
01 0.3170731702 0.1219512203 0.0975609804 0.0731707305 0.0731707306 0.0731707307 0.0731707308 0.0731707309 0.0487804910 0.04878049我可以使用radarchart轻松绘制雷达图，如下所示:
但我正在尝试测量结果形状的面积并将其用作数据形状的度量.这就是我奋斗的地方.
我尝试将结果图形保存为向量并使用那里的点，但看起来我无法将图表传递到向量中.然后我尝试使用 rgdal 包将我的图形导出为 shapefile 并使用那里的坐标:
coorddf <- SpatialPointsDataFrame(radarchart(as.data.frame(ttradar), pcol=rgb(0.2,0.5,0.5), pfcol=rgb(0.2,0.5,0.5, 0.2)), 数据 = 雷达图(as.data.frame(ttradar), pcol=rgb(0.2,0.5,0.5) , cglcol = "white", pfcol=rgb(0.2,0.5,0.5, 0.2))writeOGR(coorddf, dsn = '.', layer = 'mypoints', driver = "ESRI Shapefile")这不是一个好主意，因为我的数据没有可用作经纬度点的值..
有什么建议吗?
扩展
<小时><小时>如果你做了很多这些，值得看看 ggradar 包:http://www.ggplot2-exts.org/ggradar.html
由于我只是一次性完成，所以我使用了 Erwan Le Pennec 的极坐标修改:http://www.cmap.polytechnique.fr/~lepennec/R/Radar/RadarAndParallelPlots.html
coord_radar <- 函数 (theta = "x", start = 0, direction = 1){theta <- match.arg(theta, c("x", "y"))r <- if (theta == "x")你"否则x"ggproto("CoordRadar", CoordPolar, theta = theta, r = r, start = start,方向 = 符号(方向)，is_linear = 函数(坐标)真)}Hi everyone, I have a number of samples that I would like to draw a polygon for each of them to illustrate the shape of the data. My data look likes this:
01 0.31707317
02 0.12195122
03 0.09756098
04 0.07317073
05 0.07317073
06 0.07317073
07 0.07317073
08 0.07317073
09 0.04878049
10 0.04878049
I can easily draw a radar chart using radarchart, which looks like this:
But I am trying to measure the area of the results shape and use that as a measure of data shape. This is where I struggle.
I tried to save the resulting figure as a vector and use the points there but it looks like I can not pass the chart into a vector. Then I tried rgdal package to exprt my figure as a shapefile and use the coordinates there:
coorddf <- SpatialPointsDataFrame(radarchart(as.data.frame(ttradar), pcol=rgb(0.2,0.5,0.5) , pfcol=rgb(0.2,0.5,0.5, 0.2))
, data = radarchart(as.data.frame(ttradar), pcol=rgb(0.2,0.5,0.5) , cglcol = "white", pfcol=rgb(0.2,0.5,0.5, 0.2))
writeOGR(coorddf, dsn = '.', layer = 'mypoints', driver = "ESRI Shapefile")
Which was not a good idea because my data does not have values that can be used as lat and long points..
Any suggestions?
To expand on @G5W's excellent point:
library(dplyr)
library(ggplot2)
df <- structure(
list(
V1 = 1:10,
V2 = c(
0.31707317,
0.12195122,
0.09756098,
0.07317073,
0.07317073,
0.07317073,
0.07317073,
0.07317073,
0.04878049,
0.04878049
)
),
.Names = c("V1", "V2"),
class = "data.frame",
row.names = c(NA, -10L))
You can calculate each triangle from its neighbor to the right using dplyr::lead:
areas <- df %>%
setNames(c("variable", "value")) %>%
mutate(nextval = lead(value, default = value[1]),
angle = (1/10) * (2*pi),
# change 1/n to number of variables
area = value*nextval*sin(angle)/2)
variable value nextval angle area 1 1 0.31707317 0.12195122 0.6283185 0.0113640813 2 2 0.12195122 0.09756098 0.6283185 0.0034966406 3 3 0.09756098 0.07317073 0.6283185 0.0020979843 4 4 0.07317073 0.07317073 0.6283185 0.0015734881 5 5 0.07317073 0.07317073 0.6283185 0.0015734881 6 6 0.07317073 0.07317073 0.6283185 0.0015734881 7 7 0.07317073 0.07317073 0.6283185 0.0015734881 8 8 0.07317073 0.04878049 0.6283185 0.0010489921 9 9 0.04878049 0.04878049 0.6283185 0.0006993281 10 10 0.04878049 0.31707317 0.6283185 0.0045456327
A couple things: notice that I used the default = value[1] to make sure that the NA that would be caused at the end to wrap around to using the first value instead. Also you need to use angles in radians, so that's just 1/n * 2pi. Now that we have all the triangle areas, we can add them:
areas %>% summarise(total = sum(area))
total 1 0.02954661
This approach is easily extended to multiple groups to compare.
df <- expand.grid(var = 1:8, grp = c("a", "b")) %>%
mutate(value = runif(length(var), 0.25, 1)) %>%
group_by(grp) %>%
mutate(nextval = lead(value, default = value[1]),
angle = (1/8)*(2*pi),
area = value*nextval*sin(angle)/2) %>%
mutate(total = sum(area))
# A tibble: 16 x 7 # Groups: grp [2] var grp value nextval angle area total <int> <fctr> <dbl> <dbl> <dbl> <dbl> <dbl> 1 1 a 0.3101167 0.6831233 0.7853982 0.07489956 0.5689067 2 2 a 0.6831233 0.4166692 0.7853982 0.10063417 0.5689067 3 3 a 0.4166692 0.4756976 0.7853982 0.07007730 0.5689067 4 4 a 0.4756976 0.3426595 0.7853982 0.05763002 0.5689067 5 5 a 0.3426595 0.3107870 0.7853982 0.03765135 0.5689067 6 6 a 0.3107870 0.3001208 0.7853982 0.03297721 0.5689067 7 7 a 0.3001208 0.9039894 0.7853982 0.09592115 0.5689067 8 8 a 0.9039894 0.3101167 0.7853982 0.09911594 0.5689067 9 1 b 0.9888119 0.3481213 0.7853982 0.12170243 1.1749789 10 2 b 0.3481213 0.8513316 0.7853982 0.10478143 1.1749789 11 3 b 0.8513316 0.9928401 0.7853982 0.29883611 1.1749789 12 4 b 0.9928401 0.6372992 0.7853982 0.22370605 1.1749789 13 5 b 0.6372992 0.8303906 0.7853982 0.18710303 1.1749789 14 6 b 0.8303906 0.3607232 0.7853982 0.10590379 1.1749789 15 7 b 0.3607232 0.2786354 0.7853982 0.03553575 1.1749789 16 8 b 0.2786354 0.9888119 0.7853982 0.09741033 1.1749789
df %>%
ggplot(aes(var, value)) +
geom_polygon() +
geom_text(aes(0,0, label = round(total, 2)), color = "white") +
facet_grid(~grp) +
scale_y_continuous("", limits = c(0, 1), expand = c(0,0)) +
scale_x_continuous("", breaks = 1:8, expand = c(0,0)) +
theme_minimal() +
coord_radar()
If you're doing a lot of these, it's worth looking at the ggradar package: http://www.ggplot2-exts.org/ggradar.html
Since I was just doing this one-off, I used a polar coordinate modification from Erwan Le Pennec: http://www.cmap.polytechnique.fr/~lepennec/R/Radar/RadarAndParallelPlots.html
coord_radar <- function (theta = "x", start = 0, direction = 1)
{
theta <- match.arg(theta, c("x", "y"))
r <- if (theta == "x")
"y"
else "x"
ggproto("CoordRadar", CoordPolar, theta = theta, r = r, start = start,
direction = sign(direction),
is_linear = function(coord) TRUE)
}
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