【560】Leaflet for R 绘图

　　写在前面：由于对于 folium 比较了解了，而且可以正常实现功能，本来认为学习 R 应该不会太难，毕竟都是一样的东西，但是学起来却很麻烦，主要是网上的一些糟糕的教程，将一些简单的实现弄得很复杂，然后就是用 R 特有的那些诡异的符号，其实有正常的符号可以用，而且很友好，为啥非得搞一堆%%%%%%%来做甚，最终在某大佬的帮助下，拿到了他学生的一段代码，结果就感觉容易好多，自己也在此基础上进行了相应的扩展。

参考：官方文档

参考：第三方底图数据

参考：R语言在线地图神器：Leaflet for R包（一）

参考：Package ‘leaflet’ - 语法说明

R 没有 Python 那样简单方便的数组，因此在准备的时候需要通过 data.frame 来实现
Python 里面的 polygon 以及 polyline 都是可以通过直接赋值二维数组（list）
R 里面则不是这样，需要对于 lng 和 lat 单独赋值一个向量（c）
因此最简洁的办法就是通过 data.frame，然后通过 $ 可以获取指定的列信息，从而可以直接赋值

　　参考代码如下

library(leaflet)
library(sp) 
 
m = leaflet()
m = addProviderTiles(m,providers$Esri.WorldGrayCanvas)
 
# 单点，直接加入坐标即可
m = addMarkers(m, lng=116.486635, lat=40.00777, popup='Wangjing')
 
# 多边形，需要所有的点，可以填充颜色
 
df1 = data.frame(
    longitude = c(116.485635, 116.488035, 116.487635, 116.487645), 
    latitude = c(40.00777, 40.00697, 40.00877, 40.00977))
 
m = addPolygons(m,
                lng = df1$longitude,
                lat = df1$latitude,
                weight = 2)
 
# 折线，需要所有的点，只有颜色
df2 = data.frame(
    longitude = c(116.485635, 116.488035, 116.487635), 
    latitude = c(40.00677, 40.00597, 40.00777))
 
m = addPolylines(m, 
                 lng = df2$longitude, 
                 lat = df2$latitude,
                 color = 'red', 
                 weight = 2)
 
# 圆圈显示
m = addCircles(m, 
               lng = 116.485635, 
               lat = 40.00677, 
               radius = 50,
               color = 'purple',
               fillColor = 'purple',
               fillOpacity = 0.5)
 
 
m = addCircleMarkers(m,
                     lng = 116.488035,
                     lat = 40.00597,
                     radius = 20,
                     popup = 'Park',
                     color = '#3186cc',
                     fill = TRUE,
                     fillColor = '#3186cc')
 
# 显示点集（Markers）
m = addMarkers(m,
               lng = df3$longitude,
               lat = df3$latitude)
 
 
# 显示点集（Circles）
 
m = addCircles(m,
               lng = df1$longitude,
               lat = df1$latitude,
               radius = 1,
               color = 'red')
 
m

　　效果如下

　　加载国外地图会出现偏移的情况，需要进行相应的调整，可以直接读取 csv 文件进行显示

library(leaflet)
 
# 偏移值
d_lng = 0.006094
d_lat = 0.001381
 
# 设置默认的路径，不然读不进来文件
setwd("/Users/libingnan/Documents/Python/R")
 
# 文件读取并且调整偏移值
data = read.csv("wj_aoi.csv", encoding="UTF-8")
data$lng = data$lng - d_lng
data$lat = data$lat - d_lat
 
m = leaflet()
m = addProviderTiles(m,providers$Esri.WorldGrayCanvas)
m = addPolygons(m,
                lng = data$lng,
                lat = data$lat,
                weight = 2)
m  # Print the map

　　显示效果如下（左边为 csv 数据格式，中间为代码显示效果，右边为没有进行偏移调整的效果）：

　　相关参考说明：

#+++++++画散点图等展示数据的图+++++++
#install.packages("ggplot2")#如果还没安装过这个包可以安装
library(ggplot2)
data=data.frame(x=c(1:18),y=sin(c(1:18)/6*pi)+1.2)#数据一定要用data.frame储存
#pdf("1.pdf",width=2,height=1.5)#保存为pdf格式
ggplot(data,aes(x=x,y=y))+
  geom_line()+geom_point(size=3)+#点和线，可以换成其他图表类型，相关代码在网上有很多
  theme(panel.grid.major=element_blank(),panel.grid.minor=element_blank(),panel.background=element_blank(),
        axis.line=element_line(colour="black"))+
  scale_x_continuous(expand=c(0,0))+
  scale_y_continuous(expand=c(0,0))+
  xlab("t")+ylab("Demand level")
#dev.off()#保存为pdf格式
 
#+++++++画在地图上展示点的图+++++++
library(leaflet)
nodedata=data.frame(longitude=c(-73.98055),latitude=c(40.76247))
m=leaflet()
ad=setView(m,lng=-73.98055,lat=40.76247,zoom=12)
ad=addProviderTiles(ad,providers$Esri.WorldGrayCanvas)#空白画布
ad=addCircleMarkers(ad,lng=nodedata$longitude,lat=nodedata$latitude,color="grey",radius=5)#加大点
addCircleMarkers(ad,lng=nodedata$longitude,lat=nodedata$latitude,color="black",radius=2)#这里没有ad=，与前面不一样
#用rstudio可以可视化该图，可以保存为png后截图，不能保存为pdf
 
#+++++++画图经验+++++++
#1. 论文中，一般简单黑白图就可以了，在只能展示复杂图的情况下，才需要花很多时间在调整画图上
#2. 如果需要多种颜色，颜色搭配也重要，可以参考网上已有的颜色搭配
#3. 以上是使用R画图的基础模板，重要参数都写出来了
#4. 如果不能用以上模板画出来的话，可以借用其他工具画图，应该也会很好用的

　　散点显示

library(leaflet)
 
# 设置默认的路径，不然读不进来文件
setwd("/Users/libingnan/Documents/Python/R")
 
m = leaflet()
# 加载 Google 地图
m = addTiles(m, "https://mt.google.com/vt/lyrs=m&x={x}&y={y}&z={z}")
 
data = read.csv(paste("./01-Example (points+polygons)/data/poly_df.csv"), 
                encoding="UTF-8")
# 外层边框
m = addPolygons(m,
                lng = data$lng,
                lat = data$lat,
                color = 'purple',
                opacity = 1,
                fillColor = "purple",
                fillOpacity = 0, 
                weight = 3)
 
# 点数据
# 存储点集的颜色信息
colors = c('#76EE00', '#1E90FF', '#FF1493', 'yellow')
 
# 遍历4个点集数据，data.frame
for (j in 0:3) {
  data1 = read.csv(paste("./01-Example (points+polygons)/data/addr_", j, ".csv", sep=""), 
                 encoding="UTF-8")
 
  for (i in 1:dim(data1)[1]) {
    # 外层圆
    m = addCircleMarkers(m,
                       lng = data1[i, 1],
                       lat = data1[i, 2],
                       color = '#333',
                       opacity = 1,
                       radius = 1.5)
    # 内层圆
    m = addCircleMarkers(m,
                       lng = data1[i, 1],
                       lat = data1[i, 2],
                       color = colors[j+1],
                       opacity = 1,
                       radius = 0.5)
  }
}
 
m  # Print the map

　　显示效果

　　三角网绘图

library(leaflet)
 
# 设置默认的路径，不然读不进来文件
setwd("/Users/libingnan/Documents/Python/R")
 
m = leaflet()
m = addTiles(m, "https://mt.google.com/vt/lyrs=m&x={x}&y={y}&z={z}")
 
ind = sample(1:90, 90, replace = FALSE)
 
for (i in 0:732) {
  data = read.csv(paste("/Users/libingnan/Documents/Python/04_Geohash_new_experiment/03_concave_hull_凹包_alpha_shape/data/tri_edges_", i, ".csv", sep = ""), 
                  encoding="UTF-8")
   
  m = addPolygons(m,
                  lng = data$lng,
                  lat = data$lat,
                  color = '#333',
                  opacity = 1,
                  fillColor = "blue",
                  fillOpacity = 0, 
                  weight = 1)
}
 
# concave2 (大三角形)
for (i in 8:8) {
  data = read.csv(paste("/Users/libingnan/Documents/Python/04_Geohash_new_experiment/03_concave_hull_凹包_alpha_shape/data/concave2_", i, ".csv", sep = ""), 
                  encoding="UTF-8")
   
  m = addPolygons(m,
                  lng = data$lng,
                  lat = data$lat,
                  color = 'blue',
                  opacity = 1,
                  fillColor = "blue",
                  fillOpacity = 0.2, 
                  weight = 2.5)
}
 
# concave3
data_concave1 = read.csv(paste("/Users/libingnan/Documents/Python/04_Geohash_new_experiment/03_concave_hull_凹包_alpha_shape/concave3_df.csv", sep = ""), 
                         encoding="UTF-8")
 
m = addPolygons(m,
                lng = data_concave1$lng,
                lat = data_concave1$lat,
                color = 'purple',
                opacity = 1,
                fillColor = "purple",
                fillOpacity = 0.2, 
                weight = 2.5)
 
# 点数据
data1 = read.csv(paste("/Users/libingnan/Documents/Python/04_Geohash_new_experiment/03_concave_hull_凹包_alpha_shape/pt_df.csv", sep = ""), 
                 encoding="UTF-8")
 
for (i in 1:375) {
   
  m = addCircleMarkers(m,
                       lng = data1[i, 1],
                       lat = data1[i, 2],
                       color = '#333',
                       opacity = 1,
                       radius = 1.5)
   
  m = addCircleMarkers(m,
                       lng = data1[i, 1],
                       lat = data1[i, 2],
                       color = 'orange',
                       opacity = 1,
                       radius = 0.5)
   
}
 
 
 
m  # Print the map