r语言 - 传单 - 欧洲空间网络图和距离岛屿移除

Question

>我可能有与传单相关的非常复杂的问题，我正在尝试绘制欧洲的多个国家(从 GADM 下载的数据(，然后为国家创建一个网络矩阵，但是法国包含岛屿，并且由于某些原因计算权重矩阵工作，但是在创建它的数据帧时，它会创建大炮(当法国被丢弃data6它工作时(

有没有办法从法国数据中删除该岛，或者是否有寻呼机页面，可以在其中获得并轻松绘制国家/地区，如我的示例？

此外，当法国被丢弃并在传单中创建地图时，有一条奇怪的水平线，可以以某种方式擦除吗？

这里的例子(看起来很长，但那是因为许多国家的地理数据(

library(leaflet)
library(ggplot2)
library(sf)
library(spdep)
library(leaflet.minicharts)
library(leafletCN)
# Regions of each country selected
URL <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_DEU_1_sp.rds"
data <- readRDS(url(URL))
URL2 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_CZE_1_sp.rds"
data2 <- readRDS(url(URL2))
URL3 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_POL_1_sp.rds"
data3 <- readRDS(url(URL3))
URL4 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_SVK_1_sp.rds"
data4 <- readRDS(url(URL4))
URL5 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_AUT_1_sp.rds"
data5 <- readRDS(url(URL5))
URL6 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_FRA_1_sp.rds"
data6 <- readRDS(url(URL6))
URL7 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_HUN_1_sp.rds"
data7 <- readRDS(url(URL7))
URL8 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_BEL_1_sp.rds"
data8 <- readRDS(url(URL8))
URL9 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_NLD_1_sp.rds"
data9 <- readRDS(url(URL9))
URL10 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_CHE_1_sp.rds"
data10 <- readRDS(url(URL10))
# Country borders of all countries
B_URL <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_DEU_0_sp.rds"
Bdata <- readRDS(url(B_URL))
B_URL2 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_CZE_0_sp.rds"
Bdata2 <- readRDS(url(B_URL2))
B_URL3 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_POL_0_sp.rds"
Bdata3 <- readRDS(url(B_URL3))
B_URL4 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_SVK_0_sp.rds"
Bdata4 <- readRDS(url(B_URL4))
B_URL5 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_AUT_0_sp.rds"
Bdata5 <- readRDS(url(B_URL5))
B_URL6 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_FRA_0_sp.rds"
Bdata6 <- readRDS(url(B_URL6))
B_URL7 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_HUN_0_sp.rds"
Bdata7 <- readRDS(url(B_URL7))
B_URL8 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_BEL_0_sp.rds"
Bdata8 <- readRDS(url(B_URL8))
B_URL9 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_NLD_0_sp.rds"
Bdata9 <- readRDS(url(B_URL9))
B_URL10 <- "https://biogeo.ucdavis.edu/data/gadm3.6/Rsp/gadm36_CHE_0_sp.rds"
Bdata10 <- readRDS(url(B_URL10))

# Trying to perform network base on QUEEN AND ROOK
A <- rbind(data, data2, data3, data4, data5,data6, data7, data8, data9, data10)
queen_data <- poly2nb(A, queen = F)
queen_data <- nb2listw(queen_data, style = "W", zero.policy = TRUE)
# Creating dataframe for plot purposes
data_df <- data.frame(coordinates(A))
colnames(data_df) <- c("long", "lat")
n = length(attributes(queen_data$neighbours)$region.id)
DA = data.frame(
from = rep(1:n,sapply(queen_data$neighbours,length)),
to = unlist(queen_data$neighbours),
weight = unlist(queen_data$weights)
)
DA = cbind(DA, data_df[DA$from,], data_df[DA$to,])
colnames(DA)[4:7] = c("long","lat","long_to","lat_to")

leaflet() %>% addProviderTiles("CartoDB.Positron") %>% 
addPolygons(data=data, weight = 1, fill = F, color = "red") %>% 
addPolygons(data=data2, weight = 1, fill = F, color = "red") %>% 
addPolygons(data=data3, weight = 1, fill = F, color = "red") %>% 
addPolygons(data=data4, weight = 1, fill = F, color = "red") %>% 
addPolygons(data=data5, weight = 1, fill = F, color = "red") %>% 
addPolygons(data=data7, weight = 1, fill = F, color = "red") %>%  
addPolygons(data=data8, weight = 1, fill = F, color = "red") %>%  
addPolygons(data=data9, weight = 1, fill = F, color = "red") %>%  
addPolygons(data=data10, weight = 1, fill = F, color = "red") %>%  
addPolygons(data=Bdata, weight = 3, fill = F, color = "black") %>% 
addPolygons(data=Bdata2, weight = 3, fill = F, color = "black") %>% 
addPolygons(data=Bdata3, weight = 3, fill = F, color = "black") %>% 
addPolygons(data=Bdata4, weight = 3, fill = F, color = "black") %>% 
addPolygons(data=Bdata5, weight = 3, fill = F, color = "black") %>%
addPolygons(data=Bdata6, weight = 3, fill = F, color = "black") %>%
addPolygons(data=Bdata7, weight = 3, fill = F, color = "black") %>%
addPolygons(data=Bdata8, weight = 3, fill = F, color = "black") %>%
addPolygons(data=Bdata9, weight = 3, fill = F, color = "black") %>%
addPolygons(data=Bdata10, weight = 3, fill = F, color = "black") %>%
addCircles(lng = data_df$long, lat = data_df$lat, weight = 9) %>% 
#addCircles(lng = data_df2$long, lat = data_df2$lat) %>% 
addFlows(lng0 = DA$long, lat0 = DA$lat,lng1 = DA$long_to, lat1 = DA$lat_to,
dir = 0, maxThickness= 0.85)

Answer 1

我想出了机械解决方案，我们将机械地强制data.frame具有相同的行数，但是这种方法并不好。

A <- rbind(data, data2, data3, data4, data5, data6, data7, data8, data9, data10)
queen_data <- poly2nb(A, queen = T)
queen_data <- nb2listw(queen_data, zero.policy = T)
plot(A)
plot(queen_data, coordinates(A), add = T, col = "red")
# Creating dataframe for plot purposes
data_df <- data.frame(coordinates(A))
colnames(data_df) <- c("long", "lat")
n = length(attributes(queen_data$neighbours)$region.id)
weights = unlist(queen_data$weights)
data_df[DA$from,] %>% dim()
da_to = data_df[DA$to,]
da_to[709, c(1, 2)] = NA
weight[709] = NA
DA = data.frame(
from = rep(1:n,sapply(queen_data$neighbours,length)),
to = unlist(queen_data$neighbours),
weight = weight
)
DA = cbind(DA, data_df[DA$from,], da_to)
colnames(DA)[4:7] = c("long","lat","long_to","lat_to")

最终绘图应看起来像plot(A) plot(queen_data, coordinates(A), add = T, col = "red")，并且在绘制此DA数据帧时leaflet它不一样，因此不正确。