R 在Shiny中使用ggplot时，如何保留绘图布局特征？
当绘制一个简单的ggplot时，画布的大小将扩展，以使绘图的高度适当，允许变量之间有一定的间距。例如，如果我有10个变量需要在一个绘图上显示，则所有变量都会很好地绘图： 是时候做些有光泽的事情了！让我们看看是否可以将此绘图嵌入选项卡面板 我们开始： 看起来很棒，但现在我的水平部分都挤在一起，就像一包热狗。水平几何图形段之间没有空格 这个问题一直困扰着我 我觉得ggplot有自己的大脑，当涉及到画布尺寸时，这很好，但我无法撬开头骨来适当控制它将如何绘制自己 引用， …获得一致的画布和所有其他尺寸的关键是直接控制图形输出设备 我完全同意他的观点，并使用了他的优秀建议，但由于我们使用的是Shiny，因此无法控制这一点 接下来，我尝试使用中的值R 在Shiny中使用ggplot时，如何保留绘图布局特征？,r,canvas,ggplot2,shiny,R,Canvas,Ggplot2,Shiny,当绘制一个简单的ggplot时，画布的大小将扩展，以使绘图的高度适当，允许变量之间有一定的间距。例如，如果我有10个变量需要在一个绘图上显示，则所有变量都会很好地绘图： 是时候做些有光泽的事情了！让我们看看是否可以将此绘图嵌入选项卡面板 我们开始： 看起来很棒，但现在我的水平部分都挤在一起，就像一包热狗。水平几何图形段之间没有空格 这个问题一直困扰着我 我觉得ggplot有自己的大脑，当涉及到画布尺寸时，这很好，但我无法撬开头骨来适当控制它将如何绘制自己 引用， …获得一致的画布和所有其他尺寸
p <- p + theme(plot.margin=unit(c(0,0,0,0), "cm")
p <- p + panel.margin=unit(c(0,0,0,0), "cm"))
面板边距并不能真正控制图形设备的大小。尝试在renderPlot中设置高度和宽度，并上下缩放，直到它们看起来合适为止。@Gregor:太接近了！！这通过在右边给我一个滚动条来帮助我，但这并没有真正扩大空间：
library("shiny")
library("ggplot2")
DF_for_plotting <- structure(list(col1 = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0), col2 = c(100,
100, 61.9433678425096, 10.7823906941804, 4.18175346165306, 3.24251454697229,
6.68573373055455, 14.945119260922, 18.9296271776082, 11.0742379220636
), col3 = c(100, 100, 100, 12.8418470680653, 5.31239161296286,
4.42025167250118, 10.699998838647, 27.5067118056336, 20.6360723198699,
13.1476876837599), col4 = c(100, 100, 100, 100, 100, 100, 100,
100, 100, 100)), .Names = c("col1", "col2", "col3", "col4"), row.names = c("one",
"two", "three", "four", "five", "six", "seven", "eight", "nine",
"ten"), class = "data.frame")
hex=c("#CC0000", "#90BD31", "#178CCB")
textsize <- c(9)
number_of_variables <- 5
p <- ggplot()
p <- p + scale_y_discrete(breaks = seq(10), labels = c("one", "two", "three", "four", "five"))
breaks=c(0, 25, 50, 75, 100)
break_labels=c("0%", "25%", "50%", "75%", "100%")
p <- p + scale_x_continuous(breaks = breaks, labels=break_labels, name=percent_correct)
### inner loop
for (varnum in seq(1:number_of_variables)){ #<-- we are already in the Tab. Now we need to make all three segments for all three variables for this tab
p <- p + geom_segment(data=DF_for_plotting, aes_q(x=DF_for_plotting$col1[varnum], xend=DF_for_plotting$col2[varnum]-0.001, y=varnum, yend=varnum, colour='impaired'), size=textsize*2.5) +
geom_segment(data=DF_for_plotting, aes_q(x=DF_for_plotting$col2[varnum], xend=DF_for_plotting$col3[varnum]-0.001, y=varnum, yend=varnum, colour='normal'), size=textsize*2.5) +
geom_segment(data=DF_for_plotting, aes_q(x=DF_for_plotting$col3[varnum], xend=DF_for_plotting$col4[varnum]-0.001, y=varnum, yend=varnum, colour='optimal'), size=textsize*2.5)
p <- p + scale_color_manual(values=c(impaired=hex[1], normal=hex[2], optimal=hex[3], white='#ffffff'), name="Function Key")
}
p
shinyUI(fluidPage(theme='test.css',
fluidRow(
column(2,
fluidRow(
h3("Select Customer:"),
wellPanel(class="info", numericInput(inputId="num", label="Select ID:", value=NaN),
if(show_age_slider=='Yes'){textOutput("")},
if(show_edu_slider=='Yes'){textOutput("")},
if(show_gender_buttons=='Yes'){textOutput("")}
))),
#do.call will call the navbarPage function with the arguments in the tabs list
shinyUI(fluidRow(
column(12,
"",
do.call(navbarPage,tabs)
))))))
library("shiny")
library("ggplot2")
DF_for_plotting <- structure(list(col1 = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0), col2 = c(100,
100, 61.9433678425096, 10.7823906941804, 4.18175346165306, 3.24251454697229,
6.68573373055455, 14.945119260922, 18.9296271776082, 11.0742379220636
), col3 = c(100, 100, 100, 12.8418470680653, 5.31239161296286,
4.42025167250118, 10.699998838647, 27.5067118056336, 20.6360723198699,
13.1476876837599), col4 = c(100, 100, 100, 100, 100, 100, 100,
100, 100, 100)), .Names = c("col1", "col2", "col3", "col4"), row.names = c("one",
"two", "three", "four", "five", "six", "seven", "eight", "nine",
"ten"), class = "data.frame")
hex=c("#CC0000", "#90BD31", "#178CCB")
textsize=c(8)
############## shiny server starts here: #######################################################################
shinyServer(function(input, output) {
# begin the observe() block
observe(
lapply(seq(1:number_of_tabs),function(i) output[[paste0("plot",i)]] <- renderPlot({ #<-- lapply will fill up each tab and create one ggplot
plotindex <<- 0
list_of_ggplots <<- list() #although we only have one tab, we could easily extend to having multiple tabs
p <- ggplot()
breaks=c(0, 25, 50, 75, 100, 115, 130)
break_labels=c("0%", "25%", "50%", "75%", "100%")
number_of_variables <- 10
### inner loop
for (varnum in seq(1:number_of_variables)){ #<-- We need to make all three segments for all three variables for this tab
p <- p + scale_y_discrete(breaks = seq(10), labels = c("one", "two", "three", "four", "five", "six", "seven", "eight", "nine", "ten"))
p <- p + geom_segment(data=DF_for_plotting, aes_q(x=DF_for_plotting$col1[varnum], xend=DF_for_plotting$col2[varnum]-0.001, y=varnum, yend=varnum, colour='impaired'), size=textsize*2.5) +
geom_segment(data=DF_for_plotting, aes_q(x=DF_for_plotting$col2[varnum], xend=DF_for_plotting$col3[varnum]-0.001, y=varnum, yend=varnum, colour='normal'), size=textsize*2.5) +
geom_segment(data=DF_for_plotting, aes_q(x=DF_for_plotting$col3[varnum], xend=DF_for_plotting$col4[varnum]-0.001, y=varnum, yend=varnum, colour='optimal'), size=textsize*2.5)
p <- p + scale_color_manual(values=c(impaired=hex[1], normal=hex[2], optimal=hex[3], white='#ffffff'), name="Function Key")
# p <- p + theme(plot.margin=unit(c(0,0,0,0), "cm"))
# p <- p + theme(panel.margin=unit(c(0,0,0,0), "cm"))
list_of_ggplots[["to_UI"]] <<- p # this is strange but true; apparently any arbitrary key works for inserting the plot into the list_of_ggplots
}
print(list_of_ggplots) #<-- to send out to UI
})
)
) #<-- end of observe function
} #<-- end of brace in shinyserver function
) #<-- end the shinyserver function