在更改要在 R Shiny 中绘制的变量时，防止绘图选择的迹线重置
Prevent plotly selected traces from resetting when changing the variable to be plotted in R Shiny
我正在尝试制作一个闪亮的应用程序，它由一个侧边栏面板和一个绘图组成。在面板中，我有 select 应该绘制哪个 ID 的单选按钮。我还有多个变量，用户可以使用 plotly legend 关闭和打开这些变量。
我希望应用程序首次打开时该图为空。为此，我在情节中使用 visible = "legendonly" 。但是，当在侧边栏面板中更改 ID 时，我想保留用户已经激活的痕迹（通过在图例中单击它们）；但是，由于每次都会重新生成 plotly，因此它再次使用 visible = "legendonly" 选项并导致 plot 重置。
当侧边栏面板中的不同选项被 selected 时，是否有办法保留痕迹（仅那些已经 selected 的痕迹？
请参阅下面的可重现示例；请注意，我在本地将此示例设为 运行。您需要将数据和包分别加载到您的 R 会话中。数据可以在问题底部找到。
library(shiny)
library(plotly)
library(lubridate)
### Read mdata into your R session
# UI
uix <- shinyUI(pageWithSidebar(
headerPanel("Data"),
sidebarPanel(
radioButtons('vars', 'ID',
c("1", "2")),
helpText('Select an ID.')
),
mainPanel(
h4("Plot"),
plotlyOutput("myPlot")
)
)
)
# SERVER
serverx <- function(input, output) {
#load("Data/mdata.RData") #comment out this part and load data locally
# a large table, reative to input$show_vars
output$uteTable = renderDataTable({
ute[, input$show_vars, drop = FALSE]
})
output$myPlot = renderPlotly(
{
p <- plot_ly() %>%
layout(title = "Title", xaxis = list(tickformat = "%b %Y", title = "Date"),
yaxis = list(title = "Y"))
## Add the IDs selected in input$vars
for (item in input$vars) {
mdata %>%
mutate(Date = make_date(Year, Month, 15)) %>%
filter(ID == item) -> foo
p <- add_lines(p, data = foo, x = ~Date, y = ~Value, color = ~Variable, visible = "legendonly",
evaluate = TRUE)
p <- p %>% layout(showlegend = TRUE,
legend = list(orientation = "v", # show entries horizontally
xanchor = "center", # use center of legend as anchor
x = 100, y=1))
}
print(p)
})
}
shinyApp(uix, serverx)
由 reprex package (v0.3.0)
于 2020 年 6 月 12 日创建
问题：改成ID == 2后，是否可以保留Var1痕迹？
想法： 我觉得如果能把visible = 'legendonly改成TRUE就可以了在应用程序部署之后，因此它仅适用于情节的第一个示例。可能，我也需要将 evaluate 更改为 FALSE。
数据：
mdata <- structure(list(Year = c(2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L), Month = c(1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L,
5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L,
9L, 9L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L,
12L), Variable = c("Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2"), ID = c(1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,
2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2,
1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2), Value = c(187.797761979167,
6.34656438541666, 202.288468333333, 9.2249309375, 130.620451458333,
4.61060465625, 169.033213020833, 7.5226940625, 290.015582677083,
10.8697671666667, 178.527960520833, 7.6340359375, 234.53493728125,
8.32400878125, 173.827054583333, 7.54521947916667, 164.359205635417,
5.55496292708333, 151.75458625, 6.361610625, 190.124467760417,
6.45046077083333, 191.377006770833, 8.04720916666667, 170.714612604167,
5.98860073958333, 210.827157916667, 9.46311385416667, 145.784868927083,
5.16647911458333, 159.9545675, 6.7466725, 147.442681895833, 5.43921594791667,
153.057018958333, 6.39029208333333, 165.6476956875, 5.63139815625,
197.179256875, 8.73210604166667, 148.1879651875, 5.58784840625,
176.859451354167, 7.65670020833333, 186.215496677083, 7.12404453125,
219.104379791667, 9.39468864583333)), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -48L), groups = structure(list(
Year = 2015L, .rows = list(1:48)), row.names = c(NA, -1L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE))
我能想到的是在 select 要绘制的变量中添加一个复选框，而不是在图例中关闭和打开它们。使用此方法，而不是使用 visible = legendonly，我保留没有默认值的复选框 selected。此外，当用户更改 ID 时，变量保持不变，因此会为下一个 ID 绘制。见下文；
library(shiny)
library(plotly)
library(lubridate)
### Read mdata into your R session
# UI
uix <- shinyUI(pageWithSidebar(
headerPanel("Data"),
sidebarPanel(
radioButtons('vars', 'ID',
c("1", "2")),
checkboxGroupInput('varp', 'Variable',
c("Var1", "Var2")),
helpText('Select an ID and Variables to be plotted.')
),
mainPanel(
h4("Plot"),
plotlyOutput("myPlot")
)
)
)
# SERVER
serverx <- function(input, output) {
#load("Data/mdata.RData") #comment out this part and load data locally
# a large table, reative to input$show_vars
output$uteTable = renderDataTable({
ute[, input$show_vars, drop = FALSE]
})
output$myPlot = renderPlotly(
{
p <- plot_ly() %>%
layout(title = "Title", xaxis = list(tickformat = "%b %Y", title = "Date"),
yaxis = list(title = "Y"))
## Add the IDs selected in input$vars
for (item in input$vars) {
mdata %>%
mutate(Date = make_date(Year, Month, 15)) %>%
filter(ID == item,
Variable %in% input$varp)-> foo
p <- add_lines(p, data = foo, x = ~Date, y = ~Value, color = ~Variable, evaluate = TRUE)
p <- p %>% layout(showlegend = TRUE,
legend = list(orientation = "v", # show entries horizontally
xanchor = "center", # use center of legend as anchor
x = 100, y=1))
}
print(p)
})
}
shinyApp(uix, serverx)
以下使用 plotlyProxy 替换现有绘图对象（和轨迹）的数据，因此避免重新渲染绘图。这种方法比重新渲染更快。
library(shiny)
library(plotly)
library(lubridate)
# UI
uix <- shinyUI(pageWithSidebar(
headerPanel("Data"),
sidebarPanel(
radioButtons('myID', 'ID',
c("1", "2")),
helpText('Select an ID.')
),
mainPanel(
h4("Plot"),
plotlyOutput("myPlot")
)
)
)
# SERVER
serverx <- function(input, output, session) {
output$myPlot = renderPlotly({
p <- plot_ly() %>%
layout(title = "Title", xaxis = list(tickformat = "%b %Y", title = "Date"),
yaxis = list(title = "Y"))
mdata %>%
mutate(Date = make_date(Year, Month, 15)) %>%
filter(ID == 1) -> IDData
p <- add_lines(p, data = IDData, x = ~Date, y = ~Value,
color = ~Variable, visible = "legendonly")
p <- p %>% layout(showlegend = TRUE,
legend = list(orientation = "v", # show entries horizontally
xanchor = "center", # use center of legend as anchor
x = 100, y=1))
p
})
myPlotProxy <- plotlyProxy("myPlot", session)
observe({
mdata %>%
mutate(Date = make_date(Year, Month, 15)) %>%
filter(ID == input$myID) -> IDData
req(IDData)
uniqueVars <- unique(IDData$Variable)
for(i in seq_along(uniqueVars)){
IDData %>% filter(Variable == uniqueVars[i]) -> VarData
plotlyProxyInvoke(myPlotProxy, "restyle", list(x = list(VarData$Date),
y = list(VarData$Value)), list(i-1))
}
})
}
shinyApp(uix, serverx)
有关更多信息，请参阅 plotly book, plotly's function reference and this answer 中的“17.3.1 部分情节更新”一章。
数据：
### Read mdata into your R session
mdata <- structure(list(Year = c(2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L), Month = c(1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L,
5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L,
9L, 9L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L,
12L), Variable = c("Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2"), ID = c(1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,
2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2,
1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2), Value = c(187.797761979167,
6.34656438541666, 202.288468333333, 9.2249309375, 130.620451458333,
4.61060465625, 169.033213020833, 7.5226940625, 290.015582677083,
10.8697671666667, 178.527960520833, 7.6340359375, 234.53493728125,
8.32400878125, 173.827054583333, 7.54521947916667, 164.359205635417,
5.55496292708333, 151.75458625, 6.361610625, 190.124467760417,
6.45046077083333, 191.377006770833, 8.04720916666667, 170.714612604167,
5.98860073958333, 210.827157916667, 9.46311385416667, 145.784868927083,
5.16647911458333, 159.9545675, 6.7466725, 147.442681895833, 5.43921594791667,
153.057018958333, 6.39029208333333, 165.6476956875, 5.63139815625,
197.179256875, 8.73210604166667, 148.1879651875, 5.58784840625,
176.859451354167, 7.65670020833333, 186.215496677083, 7.12404453125,
219.104379791667, 9.39468864583333)), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -48L), groups = structure(list(
Year = 2015L, .rows = list(1:48)), row.names = c(NA, -1L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE))
我正在尝试制作一个闪亮的应用程序，它由一个侧边栏面板和一个绘图组成。在面板中，我有 select 应该绘制哪个 ID 的单选按钮。我还有多个变量，用户可以使用 plotly legend 关闭和打开这些变量。
我希望应用程序首次打开时该图为空。为此，我在情节中使用 visible = "legendonly" 。但是，当在侧边栏面板中更改 ID 时，我想保留用户已经激活的痕迹（通过在图例中单击它们）；但是，由于每次都会重新生成 plotly，因此它再次使用 visible = "legendonly" 选项并导致 plot 重置。
当侧边栏面板中的不同选项被 selected 时，是否有办法保留痕迹（仅那些已经 selected 的痕迹？
请参阅下面的可重现示例；请注意，我在本地将此示例设为 运行。您需要将数据和包分别加载到您的 R 会话中。数据可以在问题底部找到。
library(shiny)
library(plotly)
library(lubridate)
### Read mdata into your R session
# UI
uix <- shinyUI(pageWithSidebar(
headerPanel("Data"),
sidebarPanel(
radioButtons('vars', 'ID',
c("1", "2")),
helpText('Select an ID.')
),
mainPanel(
h4("Plot"),
plotlyOutput("myPlot")
)
)
)
# SERVER
serverx <- function(input, output) {
#load("Data/mdata.RData") #comment out this part and load data locally
# a large table, reative to input$show_vars
output$uteTable = renderDataTable({
ute[, input$show_vars, drop = FALSE]
})
output$myPlot = renderPlotly(
{
p <- plot_ly() %>%
layout(title = "Title", xaxis = list(tickformat = "%b %Y", title = "Date"),
yaxis = list(title = "Y"))
## Add the IDs selected in input$vars
for (item in input$vars) {
mdata %>%
mutate(Date = make_date(Year, Month, 15)) %>%
filter(ID == item) -> foo
p <- add_lines(p, data = foo, x = ~Date, y = ~Value, color = ~Variable, visible = "legendonly",
evaluate = TRUE)
p <- p %>% layout(showlegend = TRUE,
legend = list(orientation = "v", # show entries horizontally
xanchor = "center", # use center of legend as anchor
x = 100, y=1))
}
print(p)
})
}
shinyApp(uix, serverx)
由 reprex package (v0.3.0)
于 2020 年 6 月 12 日创建问题：改成ID == 2后，是否可以保留Var1痕迹？
想法： 我觉得如果能把visible = 'legendonly改成TRUE就可以了在应用程序部署之后，因此它仅适用于情节的第一个示例。可能，我也需要将 evaluate 更改为 FALSE。
数据：
mdata <- structure(list(Year = c(2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L), Month = c(1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L,
5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L,
9L, 9L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L,
12L), Variable = c("Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2"), ID = c(1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,
2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2,
1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2), Value = c(187.797761979167,
6.34656438541666, 202.288468333333, 9.2249309375, 130.620451458333,
4.61060465625, 169.033213020833, 7.5226940625, 290.015582677083,
10.8697671666667, 178.527960520833, 7.6340359375, 234.53493728125,
8.32400878125, 173.827054583333, 7.54521947916667, 164.359205635417,
5.55496292708333, 151.75458625, 6.361610625, 190.124467760417,
6.45046077083333, 191.377006770833, 8.04720916666667, 170.714612604167,
5.98860073958333, 210.827157916667, 9.46311385416667, 145.784868927083,
5.16647911458333, 159.9545675, 6.7466725, 147.442681895833, 5.43921594791667,
153.057018958333, 6.39029208333333, 165.6476956875, 5.63139815625,
197.179256875, 8.73210604166667, 148.1879651875, 5.58784840625,
176.859451354167, 7.65670020833333, 186.215496677083, 7.12404453125,
219.104379791667, 9.39468864583333)), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -48L), groups = structure(list(
Year = 2015L, .rows = list(1:48)), row.names = c(NA, -1L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE))
我能想到的是在 select 要绘制的变量中添加一个复选框，而不是在图例中关闭和打开它们。使用此方法，而不是使用 visible = legendonly，我保留没有默认值的复选框 selected。此外，当用户更改 ID 时，变量保持不变，因此会为下一个 ID 绘制。见下文；
library(shiny)
library(plotly)
library(lubridate)
### Read mdata into your R session
# UI
uix <- shinyUI(pageWithSidebar(
headerPanel("Data"),
sidebarPanel(
radioButtons('vars', 'ID',
c("1", "2")),
checkboxGroupInput('varp', 'Variable',
c("Var1", "Var2")),
helpText('Select an ID and Variables to be plotted.')
),
mainPanel(
h4("Plot"),
plotlyOutput("myPlot")
)
)
)
# SERVER
serverx <- function(input, output) {
#load("Data/mdata.RData") #comment out this part and load data locally
# a large table, reative to input$show_vars
output$uteTable = renderDataTable({
ute[, input$show_vars, drop = FALSE]
})
output$myPlot = renderPlotly(
{
p <- plot_ly() %>%
layout(title = "Title", xaxis = list(tickformat = "%b %Y", title = "Date"),
yaxis = list(title = "Y"))
## Add the IDs selected in input$vars
for (item in input$vars) {
mdata %>%
mutate(Date = make_date(Year, Month, 15)) %>%
filter(ID == item,
Variable %in% input$varp)-> foo
p <- add_lines(p, data = foo, x = ~Date, y = ~Value, color = ~Variable, evaluate = TRUE)
p <- p %>% layout(showlegend = TRUE,
legend = list(orientation = "v", # show entries horizontally
xanchor = "center", # use center of legend as anchor
x = 100, y=1))
}
print(p)
})
}
shinyApp(uix, serverx)
以下使用 plotlyProxy 替换现有绘图对象（和轨迹）的数据，因此避免重新渲染绘图。这种方法比重新渲染更快。
library(shiny)
library(plotly)
library(lubridate)
# UI
uix <- shinyUI(pageWithSidebar(
headerPanel("Data"),
sidebarPanel(
radioButtons('myID', 'ID',
c("1", "2")),
helpText('Select an ID.')
),
mainPanel(
h4("Plot"),
plotlyOutput("myPlot")
)
)
)
# SERVER
serverx <- function(input, output, session) {
output$myPlot = renderPlotly({
p <- plot_ly() %>%
layout(title = "Title", xaxis = list(tickformat = "%b %Y", title = "Date"),
yaxis = list(title = "Y"))
mdata %>%
mutate(Date = make_date(Year, Month, 15)) %>%
filter(ID == 1) -> IDData
p <- add_lines(p, data = IDData, x = ~Date, y = ~Value,
color = ~Variable, visible = "legendonly")
p <- p %>% layout(showlegend = TRUE,
legend = list(orientation = "v", # show entries horizontally
xanchor = "center", # use center of legend as anchor
x = 100, y=1))
p
})
myPlotProxy <- plotlyProxy("myPlot", session)
observe({
mdata %>%
mutate(Date = make_date(Year, Month, 15)) %>%
filter(ID == input$myID) -> IDData
req(IDData)
uniqueVars <- unique(IDData$Variable)
for(i in seq_along(uniqueVars)){
IDData %>% filter(Variable == uniqueVars[i]) -> VarData
plotlyProxyInvoke(myPlotProxy, "restyle", list(x = list(VarData$Date),
y = list(VarData$Value)), list(i-1))
}
})
}
shinyApp(uix, serverx)
有关更多信息，请参阅 plotly book, plotly's function reference and this answer 中的“17.3.1 部分情节更新”一章。
数据：
### Read mdata into your R session
mdata <- structure(list(Year = c(2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L), Month = c(1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L,
5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L,
9L, 9L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L,
12L), Variable = c("Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
"Var2", "Var2", "Var1", "Var1", "Var2", "Var2", "Var1", "Var1",
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