我正在尝试开发一个闪亮的应用程序,它将在浏览器上安装基于地图的热图,并允许您更改热图上显示的变量。该地图是具有 GIS 形状文件的地理区域,然后选择的变量在地图上显示为热图。不幸的是,我有一个问题,变量没有正确传递ggplot()
,我的地图失败了。下面的 server.r 代码作为直接的 R 脚本成功运行,没有问题,但是当适应 Shiny 时它会失败。
ggplot()
server.r中的以下代码会出现此问题:
myplot1 <- myplot1 + aes(long, lat, group = group, fill = input$var) + ...
我收到一个错误:
eval 中的错误(expr,envir,enclos):找不到对象“输入”
这与fill = input$var
它无法识别input$var
从 ui.r 传递的内容有关。input$var
是在 ui.r 中选择的变量(var1、var2 等)以显示在热图上。这是我在代码中知道的唯一input$var
无法识别的实例。我print(str(input$var))
在此行之前使用过,它清楚地保存了所需变量的名称。如果我在(例如fill=var1
)中对其进行硬编码,则ggplot()
可以正常工作并且地图可以正确显示。
我也使用environment = environment()
过,ggplot()
但这会产生另一个错误:
错误:提供给连续刻度的离散值
我的解释是它正在寻找由变量描述的数据框,但它却获得了一个值。
我觉得这是我缺少的一些简单的东西——我应该声明或重新分配的东西。如果人们对此有任何见解、指导或反馈,我将不胜感激。非常感谢 !!
# server.R
library(shiny)
library(maps)
library(mapdata)
library(sp)
library(maptools)
library(scales)
library(RColorBrewer)
library(ggplot2)
library(rgeos)
library(plyr)
library(reshape)
library(mapproj)
library(rgdal)
library(grid)
library(gridExtra)
setwd("C:/Shiny")
# Step 1 Read/loading the target shapefile
gregion = readOGR(dsn="C:/Shiny", layer="duid")
# Step 2 Get row numbers from .dbf / explicitly identifies attribute rows by the .dbf offset.
gregion@data$id = rownames(gregion@data)
# Step 3 Makes centroid (point layer) from polygon "FORTIFY"
gregion.points = fortify(gregion, region="id")
# Step 4 Reading in .csv which will be joined to .dbf using "MERGE"
mydata <- read.csv("c:/Shiny/dataset.txt")
# Step 5 Joins the points to their corresponding attributes and finalizes the data preparation
gregion.df = join(gregion.points, gregion@data, by="id")
# Step 6 Merge makes an inner join of the shapefile's data frame and the .csv on a common item (usually the spatial key)
mygeomdata <- merge(gregion.df, mydata, by.x="UID", by.y="UID")
# Define server logic required to plot various variables as heatmap
# Step 7 Create map
shinyServer(function(input, output) {
# Compute the forumla text in a reactive expression since it is
# shared by the output$caption and output$mapPlot expressions
formulaText <- reactive({
paste("Variable:", input$var)
})
# Return the formula text for printing as a caption
output$caption <- renderText({
formulaText()
})
output$mapPlot <- renderPlot({
myplot1 <- ggplot(mygeomdata)
myplot1 <- myplot1 + aes(long, lat, group = group, fill = input$var) + labs(x = "Easting", y = "Northing") + scale_fill_gradient(low = "ghostwhite", high = "steelblue")
myplot1 <- myplot1 + geom_polygon()
myplot1 <- myplot1 + coord_equal()
print(myplot1)
})
})
#ui.R
library(shiny)
shinyUI(pageWithSidebar(
# Application title
headerPanel("Mapping"),
# Sidebar with controls to select the variable to plot
#
sidebarPanel(
selectInput("var", "Variable:",
list("Variable 1" = "var1",
"Variable 2" = "var2"))
),
# Show the caption and plot of the requested variable
mainPanel(
h3(textOutput("caption")),
plotOutput("mapPlot")
)
))
数据集的一个样本mydata <- read.csv("c:/Shiny/dataset.txt")
是:
UID var1 var2 var3 var4 var5 var6 var7
1 0 0.001 0 0 0 0 0
2 0 0 0 0 1 0 0
3 0 0 0 0 0 0 0
4 0 0 0 0 1 0 0
5 0 0 0 0 1 0 0
6 0 0 0 0 1 0 0
7 0 0 0 0 0 0 0
8 0 0.004 0.026 0 0 0 0
9 0.499 0.014 0 0.499 1 0 0.033
10 0.573 0.002 0.015 0.573 1 0 0.427
11 1 0.003 0.01 1 1 0 0
mygeomdata
具有以下结构:
$ UID : int 1 1 1 1 1 1 1 1 1 1 ...
$ long : num 393121 392895 392895 392840 392839 ...
$ lat : num 5501404 5502275 5502275 5502489 5502494 ...
$ order : int 1 2 3 4 5 6 7 8 9 10 ...
$ hole : logi FALSE FALSE FALSE FALSE FALSE FALSE ...
$ piece : Factor w/ 4 levels "1","2","3","4": 1 1 1 1 1 1 1 1 1 1 ...
$ group : Factor w/ 5693 levels "0.1","1.1","10.1",..: 1 1 1 1 1 1 1 1 1 1 ...
$ id : chr "0" "0" "0" "0" ...
$ DUID : Factor w/ 5656 levels "130023362","130023367",..: 1 1 1 1 1 1 1 1 1 1 ...
$ PC : Factor w/ 3617 levels "0","ZZZ0A3","ZZZ0A4",..: 3271 3271 3271 3271 3271 3271 3271 3271 3271 3271 ...
$ DUIDAREA : num 21687 21687 21687 21687 21687 ...
$ ELEV : num 14.8 14.8 14.8 14.8 14.8 ...
$ GroupUp : int 2 2 2 2 2 2 2 2 2 2 ...
$ GroupUpT : Factor w/ 2 levels "A","B": 2 2 2 2 2 2 2 2 2 2 ...
$ var1 : num 0 0 0 0 0 0 0 0 0 0 ...
$ var2 : num 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 ...
$ var3 : num 0 0 0 0 0 0 0 0 0 0 ...
$ var4 : num 0 0 0 0 0 0 0 0 0 0 ...
$ var5 : int 0 0 0 0 0 0 0 0 0 0 ...
$ var6 : num 0 0 0 0 0 0 0 0 0 0 ...
$ var7 : num 0 0 0 0 0 0 0 0 0 0 ...