与ggmap的世界地图

Question

我正在使用ggmap并希望有一个以澳大利亚为中心的世界地图,我可以轻松地绘制地理编码点.与其他一些映射包相比,ggmap似乎更容易使用.然而,当我使用下面的代码通过地图时,它会出错.

gc <- geocode('australia')
center <- as.numeric(gc) 
> map <- get_map(location = center, source="google", maptype="terrain", zoom=0)
Error: zoom must be a whole number between 1 and 21

从get_map帮助:"缩放:地图缩放,从0(全世界)到21(建筑物)的整数,默认值10(城市).openstreetmaps限制缩放18,雄蕊地图的限制取决于地图类型. 'auto'自动确定边界框规格的缩放,默认为中心/缩放规格为10."

将缩放更改为1对于get_map而言不是错误,而是用于绘制该地图

map <- get_map(location = center, source="google", maptype="terrain", zoom=1)
ggmap(map)

Warning messages:
1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf
3: In min(x) : no non-missing arguments to min; returning Inf
4: In max(x) : no non-missing arguments to max; returning -Inf

看起来经度没有被拉过来.最后,缩放为2确实有效,但没有通过整个世界的地图

所以,我的问题是如何使用get_map来获取世界地图？

会话信息:

sessionInfo()R版本2.15.0(2012-03-30)平台:i386-pc-mingw32/i386(32位)

locale:
[1] LC_COLLATE=English_United Kingdom.1252 
[2] LC_CTYPE=English_United Kingdom.1252   
[3] LC_MONETARY=English_United Kingdom.1252
[4] LC_NUMERIC=C                           
[5] LC_TIME=English_United Kingdom.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] mapproj_1.1-8.3 maps_2.2-6      rgdal_0.7-12    sp_0.9-99      
[5] ggmap_2.1       ggplot2_0.9.1  

loaded via a namespace (and not attached):
[1] colorspace_1.1-1   dichromat_1.2-4    digest_0.5.2       grid_2.15.0       
[5] labeling_0.1       lattice_0.20-6     MASS_7.3-17        memoise_0.1       
[9] munsell_0.3        plyr_1.7.1         png_0.1-4          proto_0.3-9.2     
[13] RColorBrewer_1.0-5 reshape2_1.2.1     RgoogleMaps_1.2.0  rjson_0.2.8       
[17] scales_0.2.1       stringr_0.6        tools_2.15.0 

Answer 1

编辑:更新为ggplot2 v 0.9.3

我尝试过类似的东西,但收效甚微.但是,有许多方法可以从map包中居中世界地图:请参阅此处,此处和此处.使用后者的代码,这是一个将世界地图置于经度160中心的示例,geocode()绘制使用ggplot2绘制的世界地图上的CRAN镜像位置(使用ggmap包中的函数获得的坐标),以及新西兰(使用geom_polygon)的颜色.将地图置于经度160的中心,使地图左侧的非洲全部和地图右侧的格陵兰大部分地区保持不变.

library(maps)
library(plyr)
library(ggplot2)
library(sp)
library(ggmap)

# Get some points to plot - CRAN Mirrors
Mirrors = getCRANmirrors(all = FALSE, local.only = FALSE)

Mirrors$Place = paste(Mirrors$City, ", ", Mirrors$Country, sep = "")    # Be patient
tmp = geocode(Mirrors$Place)
Mirrors = cbind(Mirrors, tmp)

###################################################################################################
# Recentre worldmap (and Mirrors coordinates) on longitude 160
### Code by Claudia Engel  March 19, 2012, www.stanford.edu/~cengel/blog

### Recenter ####
center <- 160 # positive values only

# shift coordinates to recenter CRAN Mirrors
Mirrors$long.recenter <- ifelse(Mirrors$lon < center - 180 , Mirrors$lon + 360, Mirrors$lon)

# shift coordinates to recenter worldmap
worldmap <- map_data ("world")
worldmap$long.recenter <- ifelse(worldmap$long < center - 180 , worldmap$long + 360, worldmap$long)

### Function to regroup split lines and polygons
# Takes dataframe, column with long and unique group variable, returns df with added column named group.regroup
RegroupElements <- function(df, longcol, idcol){
  g <- rep(1, length(df[,longcol]))
  if (diff(range(df[,longcol])) > 300) { # check if longitude within group differs more than 300 deg, ie if element was split
    d <- df[,longcol] > mean(range(df[,longcol])) # we use the mean to help us separate the extreme values
    g[!d] <- 1 # some marker for parts that stay in place (we cheat here a little, as we do not take into account concave polygons)
    g[d] <- 2 # parts that are moved
  }
  g <- paste(df[, idcol], g, sep=".") # attach to id to create unique group variable for the dataset
  df$group.regroup <- g
  df
}

### Function to close regrouped polygons
# Takes dataframe, checks if 1st and last longitude value are the same, if not, inserts first as last and reassigns order variable
ClosePolygons <- function(df, longcol, ordercol){
  if (df[1,longcol] != df[nrow(df),longcol]) {
    tmp <- df[1,]
    df <- rbind(df,tmp)
  }
  o <- c(1: nrow(df)) # rassign the order variable
  df[,ordercol] <- o
  df
}

# now regroup
worldmap.rg <- ddply(worldmap, .(group), RegroupElements, "long.recenter", "group")

# close polys
worldmap.cp <- ddply(worldmap.rg, .(group.regroup), ClosePolygons, "long.recenter", "order") # use the new grouping var
#############################################################################

# Plot worldmap using data from worldmap.cp
windows(9.2, 4)
worldmap = ggplot(aes(x = long.recenter, y = lat), data = worldmap.cp) + 
  geom_polygon(aes(group = group.regroup), fill="#f9f9f9", colour = "grey65") + 
  scale_y_continuous(limits = c(-60, 85)) + 
  coord_equal() +  theme_bw() + 
  theme(legend.position = "none",
    panel.grid.major = element_blank(),
    panel.grid.minor = element_blank(),
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    #axis.text.x = element_blank(),
    axis.text.y = element_blank(),
    axis.ticks = element_blank(), 
    panel.border = element_rect(colour = "black"))

# Plot the CRAN Mirrors
worldmap = worldmap + geom_point(data = Mirrors, aes(long.recenter, lat),
   colour = "red", pch = 19, size = 3, alpha = .4)

# Colour New Zealand
# Take care of variable names in worldmap.cp
head(worldmap.cp)
worldmap + geom_polygon(data = subset(worldmap.cp, region == "New Zealand", select = c(long.recenter, lat, group.regroup)), 
          aes(x = long.recenter, y = lat, group = group.regroup), fill = "blue")

Answer 2

我最近得到了同样的错误,它归结为ggmap不喜欢在$\pm $ 80°以外的纬度.

但是,我必须单独下载我的图像,因为它太大而无法下载(使用OSM); 这不是你的问题,但我会为未来的读者记录下来.

这是我解决它的方式:

• 通过BigMap单独下载墨卡托投影图像
• 纬度需要一些关注:我得到了相同的错误你显示纬度限制超出$\pm $ 80°当我预计一切都应该没问题,直到85°OSM覆盖),但我没有追踪它们因为我反正不不需要很高的纬度.
• 0°/ 0°中心对我的目的很好(我在欧洲:-)),但你可以切割图像,无论它对你有好处并自己包装cbind.只要确保你知道切割的经度.
• 然后设置图像的边界框
• 并分配适当的类

这是我做的:

require ("ggmap")
library ("png")

zoom <- 2
map <- readPNG (sprintf ("mapquest-world-%i.png", zoom))
map <- as.raster(apply(map, 2, rgb))

# cut map to what I really need
pxymin <- LonLat2XY (-180,73,zoom+8)$Y # zoom + 8 gives pixels in the big map
pxymax <- LonLat2XY (180,-60,zoom+8)$Y # this may or may not work with google
                                       # zoom values
map <- map [pxymin : pxymax,]

# set bounding box
attr(map, "bb") <- data.frame (ll.lat = XY2LonLat (0, pxymax + 1, zoom+8)$lat, 
                                  ll.lon = -180, 
                                  ur.lat = round (XY2LonLat (0, pxymin, zoom+8)$lat), 
                                  ur.lon = 180)
class(map) <- c("ggmap", "raster")

ggmap (map) + 
  geom_point (data = data.frame (lat = runif (10, min = -60 , max = 73), 
                                 lon = runif (10, min = -180, max = 180)))

结果:

编辑:我用你的谷歌地图玩了一下,但我没有得到正确的纬度.:-(