Question

我有一个代码，用于在ggplot中为基于象限的值（来自纬度和经度的中心点的风半径）生成一个简单的极坐标图，如下所示：

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

是否有任何方法可以将像这样的ggplot对象提取到SpatialPolygons，shapefile或某种数据框，以便在地图上使用ggplot / ggmap进行绘图？即使是进一步探索的建议也是有用的。提前谢谢。

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：

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')

Answer 1

我不认为shapefile与ggplot的效果非常好，但你可以将这些图（它们是ggplot对象）转换为grob对象＆amp;使用annotation_custom()将其添加到地图中。

以下是一个示例，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。

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

在正常图上验证图表的样子：

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，＆amp;指定他们的职位

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：将地图与条形图凹凸列表结合起来

p + df.grobs$subgrobs

将极坐标图作为单独的对象添加到ggplot / ggmap中？

1 个答案: