How to measure the polygon area in ggplot2?

Question

Hi everyone, I have some samples that I would like to draw a polygon for each of them to illustrate the shape of the data. My data looks like 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'm trying to measure the area of ​​the results form and use it as a measure of the data form. I'm scared here.

I tried to save the resulting shape as a vector and use the dots there, but it looks like I cannot pass the diagram to the vector. Then I tried the rgdal package to express my shape 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")

This is not a good idea, because my data does not have values ​​that can be used as lat and long points.

Any suggestions?

Answer 1

@G5W :

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)) 

, 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

: , default = value[1], , NA, , , . , 1/n * 2pi. , , :

areas %>% summarise(total = sum(area))

       total
1 0.02954661

---

.

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()

---

---

, ggradar: http://www.ggplot2-exts.org/ggradar.html

, 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)
}

Answer 2

. . , V1 V2 .

, v1 * v2 * sin (pi/5)/2. v2 * v3 * sin (pi/5)/2. .