将极坐标图作为单独的对象添加到ggplot/ggmap中? [英] Adding polar bar plot as separate object into ggplot/ggmap?

问题描述

下面我有一个代码，用于在ggplot中为基于象限的值(从纬度和经度的中心点开始的半径)生成一个简单的极线图，如下所示:

I have a code below for generating a simple polar bar plot in ggplot for quadrant-based values (wind radii from a central point of latitude & longitude), which looks like this:

我想将这些极坐标图提取到SpatialPolygons对象中，因此我可以在类似于以下的地图上将它们绘制为多边形:

I want to extract these polar plots to a SpatialPolygons object, so I can plot them as polygons on a map similar to this:

是否有任何方法可以将类似ggplot的对象提取到SpatialPolygons，shapefile或某种数据框，以便在具有ggplot/ggmap的地图上进行绘制?即使是进一步探索的建议也将是有用的.预先感谢.

Is there any method to extract ggplot objects like this to a SpatialPolygons, shapefile, or some kind of dataframe for plotting on a map with ggplot/ggmap? Even a suggestion to explore further would be useful. Thanks in advance.

我的数据框:

winds <- data.frame(WindField = c(34, 50, 64, 34, 50, 64, 34, 50, 64, 34, 50, 64), 
                    Quadrant = c("NE", "NE", "NE", "SE", "SE", "SE", 
                                 "SW", "SW", "SW", "NW", "NW", "NW"), 
                    Radius = c(222, 93, 37, 139, 46, 37, 74, 19, 9, 222, 93, 37)) 

quads <- c("NE", "SE", "SW", "NW")

我的ggplot代码:

My ggplot code:

ggplot() + 
    geom_col(data = winds,
             aes(x = factor(Quadrant, levels = quads),
                 y = Radius,
                 fill = factor(WindField),
                 group = factor(Quadrant, levels = quads)),
             stat = "identity", position = "identity", width = 1, color = 'black') +
    scale_fill_manual(values = c("yellow", "orange", "red")) +
    guides(fill = guide_legend(title = "Wind [kt]")) +
    coord_polar() +
    theme_bw() +
    theme(plot.title = element_text(size = 16), 
          plot.subtitle = element_text(size = 12),
          axis.title = element_text(size = 14),
          axis.text.y = element_text(size = 12, face = 'bold'),
          axis.text.x = element_text(size = 14, face = 'bold'),
          legend.text = element_text(size = 13), 
          legend.title = element_text(size = 13),
          panel.border = element_blank(), 
          legend.position = "bottom") +
    labs(y = "Radius [km]", x='Quadrant') 

推荐答案

我认为shapefile在ggplot中不能很好地发挥作用，但是您可以将绘图(即ggplot对象)转换为grob对象&使用annotation_custom()将它们添加到地图上.

I don't think shapefiles play very well with ggplot, but you can convert the plots (which are ggplot objects) into grob objects & add them to the map using annotation_custom().

这里是一个示例，假设您希望使用包含所有必要信息的单个数据框源文件绘制多个条形图.

Here's an example, assuming you wish to plot multiple bar plots using a single data frame source file that contains all the necessary information.

第0步:生成数据

set.seed(123)
df <- data.frame(
  plot.ID = rep(1:2, each = 12),
  WindField = rep(c(34, 50, 64), times = 8),
  Quadrant = rep(rep(c("NE", "SE", "SW", "NW"), each = 3), times = 2),
  Radius = rpois(24, lambda = 50) * 
    rep(c(5, 2, 1), times = 8) * # ensure radii decreases as WindField increases
    c(rep(sample(1:4), each = 3), # ensure each quadrant looks visually distinct
      rep(sample(5:8), each = 3)) # & looks different between plots
)

# convert Quadrant / WindField to factors
df$Quadrant = factor(df$Quadrant, levels = c("NE", "SE", "SW", "NW"))
df$WindField = factor(df$WindField)

# add position for each plot (using Florida for illustration)
# note maximum radius of the largest plot
df <- left_join(df,
                 data.frame(plot.ID = 1:2,
                            lon = c(-82, -80),
                            lat = c(29, 26)),
                 by = "plot.ID") %>%
  mutate(max.Radius = max(Radius))

> head(df)
  plot.ID WindField Quadrant Radius lon lat max.Radius
1       1        34       NE    460 -82  29       1920
2       1        50       NE    232 -82  29       1920
3       1        64       NE     76 -82  29       1920
4       1        34       SE   1000 -82  29       1920
5       1        50       SE    496 -82  29       1920
6       1        64       SE    212 -82  29       1920

在正常图上验证图的外观:

Verify what the plots would look like, on a normal plot:

ggplot(df,
       aes(x = Quadrant, y = Radius, fill = WindField)) +
  geom_col(position = "identity", width = 1, color = "black") +
  scale_fill_manual(values = c("yellow", "orange", "red")) +
  coord_polar() +
  facet_grid(~plot.ID) +
  theme_void()

第1步:为每个位置创建单独的极坐标图，转换为grob对象，&指定他们的位置

Step 1: Create separate polar bar plot for each location, convert to grob object, & specify their positions

df.grobs <- df %>%
  group_by(plot.ID, lon, lat, max.Radius) %>%
  do(subplots = ggplot(.,
                       aes(x = Quadrant, y = Radius, fill = WindField)) +
       geom_col(position = "identity", width = 1, color = "black",
                alpha = 0.5,            # increase transparency to see map underneath
                show.legend = FALSE) +  # don't show legend for individual grobs
       scale_y_continuous(limits = c(0, unique(.$max.Radius))) + 
       scale_fill_manual(values = c("yellow", "orange", "red")) +
       coord_polar() +
       theme_void()) %>%
  mutate(subgrobs = list(annotation_custom(ggplotGrob(subplots),
                                           x = lon - 1,      # change from 1 to other 
                                           y = lat - 1,      # values if necessary,
                                           xmax = lon + 1,   # depending on the map's
                                           ymax = lat + 1))) # resolution.

第2步:创建地图

library(ggmap)

p <- get_map("Florida", zoom = 7) %>% 
  ggmap() + 
  coord_fixed()

第3步:将地图与条形图小样列表结合起来

Step 3: Combine map with the list of bar plot grobs

p + df.grobs$subgrobs

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