我的 Shiny 应用程序中有一个交互式情节。在此图中，我可以将数据点标记为人工制品。部分数据绘制为折线图，部分绘制为误差线。
我使用以下ggplot代码:
ggplot(plotdat,
aes(x = time, y = value, color = type)) +
labs(title = "vitals from test") +
geom_errorbar(data = nibpdat,
aes(x = time,
ymin = dianibp,
ymax = sysnibp),
position = position_dodge(.1)) +
scale_color_manual(values = vitalpalette) +
geom_point() +
geom_line(data = plotdat %>% filter(!grepl("NIBP$", type))) +
geom_point(data = plotdat %>% filter(artefact),mapping = aes(x = time, y = value, color = type),
shape = 4, size = 2, stroke = 2) +
theme_bw()
当我在 Shiny 的应用程序之外测试这个图时，它起作用了。所有误差线均保持可见。但在 Shiny 的应用程序中，如果标记了 nibpdat 中的点(列 artefact)，则不会绘制误差条。
这是正态图(标记点是模拟的)
这是使用相同代码制作的 Shiny 图，标记了误差线的几个点。
ui.R
# load function
library(shiny)
require(dplyr)
require(ggplot2)
require(purrr)
require(tidyr)
cases <- c(1)
vitaltypes <- tribble(
~field, ~label, ~color,
"sysnibp", "systolic NIBP", "0000FF",
"meannibp", "mean NIBP", "0000FF",
"dianibp", "diastolic NIBP", "0000FF",
"sysabp", "systolic IBP", "730C5A",
"meanabp", "mean IBP", "E5BFDE",
"diaabp", "diastolic IBP", "730C5A",
"heartrate", "heartrate", "FF0000",
"saturation", "saturation", "42BEFF"
)
vitalpalette <- paste0("#",vitaltypes$color)
names(vitalpalette) <- vitaltypes$label
shinyUI(fluidPage(
titlePanel("Annotate your data now"),
sidebarLayout(
sidebarPanel(
selectInput(inputId = "case",
label = "Select case:",
choices = cases)
),
mainPanel(
plotOutput("VitalsPlot", click = "VitalsPlot_click"),
h2("Marked Artefacts"),
tableOutput("artefacts")
)
)
))
服务器.R:
shinyServer(function(input, output) {
vitals <- reactive({
structure(list(time = c(3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,
14, 15, 16, 17, 18, 19, 20, 21, 22, 3, 4, 5, 6, 7, 8, 9, 10,
11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 4, 7, 10, 12,
14, 16, 18, 21, 22, 23, 25, 26, 27, 29, 30, 31, 32, 34, 35, 36,
4, 7, 10, 12, 14, 16, 18, 21, 22, 23, 25, 26, 27, 29, 30, 31,
32, 34, 35, 36, 4, 7, 10, 12, 14, 16, 18, 21, 22, 23, 25, 26,
27, 29, 30, 31, 32, 34, 35, 36),
type = c("heartrate", "heartrate",
"heartrate", "heartrate", "heartrate", "heartrate", "heartrate",
"heartrate", "heartrate", "heartrate", "heartrate", "heartrate",
"heartrate", "heartrate", "heartrate", "heartrate", "heartrate",
"heartrate", "heartrate", "heartrate", "saturation", "saturation",
"saturation", "saturation", "saturation", "saturation", "saturation",
"saturation", "saturation", "saturation", "saturation", "saturation",
"saturation", "saturation", "saturation", "saturation", "saturation",
"saturation", "saturation", "saturation", "sysnibp", "sysnibp",
"sysnibp", "sysnibp", "sysnibp", "sysnibp", "sysnibp", "sysnibp",
"sysnibp", "sysnibp", "sysnibp", "sysnibp", "sysnibp", "sysnibp",
"sysnibp", "sysnibp", "sysnibp", "sysnibp", "sysnibp", "sysnibp",
"meannibp", "meannibp", "meannibp", "meannibp", "meannibp", "meannibp",
"meannibp", "meannibp", "meannibp", "meannibp", "meannibp", "meannibp",
"meannibp", "meannibp", "meannibp", "meannibp", "meannibp", "meannibp",
"meannibp", "meannibp", "dianibp", "dianibp", "dianibp", "dianibp",
"dianibp", "dianibp", "dianibp", "dianibp", "dianibp", "dianibp",
"dianibp", "dianibp", "dianibp", "dianibp", "dianibp", "dianibp",
"dianibp", "dianibp", "dianibp", "dianibp"),
value = c(97, 101,
92, 95, 85, 93, 87, 87, 87, 92, 93, 90, 88, 83, 82, 72, 68, 62,
66, 83, 98.3, 98, 98.3, 98, 98.9, 98.5, 99.8, 99.2, 99, 99.4,
98.8, 98.7, 99, 94.7, 98, 98.5, 95.9, 98.1, 99.1, 98.2, 142,
132, 126, 128, 136, 107, 107, 108, 121, 87, 102, 107, 100, 112,
115, 114, 110, 102, 103, 105, 93, 86, 86, 86, 70, 70, 82, 76,
76, 51, 57, 62, 66, 63, 70, 75, 65, 64, 71, 65, 71, 64, 72, 74,
57, 55, 74, 61, 59, 32, 31, 55, 50, 47, 48, 58, 48, 48, 61, 50
), case = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1)),
class = c("tbl_df",
"tbl", "data.frame"), .Names = c("time", "type", "value", "case"
), row.names = c(NA, -100L))
})
observe({
n <- nrow(vitals())
artefacts$numberofvitals <- n
artefacts$status <- rep(FALSE,n)
})
artefacts <- reactiveValues(
numberofvitals = 1,
status = rep(FALSE, 1)
)
observeEvent(input$VitalsPlot_click, {
res <- nearPoints(vitals(), input$VitalsPlot_click, allRows = TRUE)[1:artefacts$numberofvitals,]
artefacts$status <- xor(artefacts$status, res$selected_)
})
output$VitalsPlot <- renderPlot({
plotvitals <- vitals()
plotvitals$artefact <- artefacts$status
plotdat <- plotvitals %>% mutate(type = factor(match(type, vitaltypes$field),
levels = seq_len(nrow(vitaltypes)),
labels = vitaltypes$label))
nibpdat <- plotvitals %>% filter(grepl("nibp$",type)) %>%
spread(type, value) %>%
mutate(type = factor(match("meannibp", vitaltypes$field),
levels = seq_len(nrow(vitaltypes)),
labels = vitaltypes$label),
value = meannibp,
artefact = FALSE)
plotid <- "test"
ggplot(plotdat,
aes(x = time, y = value, color = type)) +
labs(title = paste0("vitals from ",plotid)) +
geom_errorbar(data = nibpdat,
aes(x = time,
ymin = dianibp,
ymax = sysnibp),
position = position_dodge(.1)) +
scale_color_manual(values = vitalpalette) +
geom_point() +
geom_line(data = plotdat %>% filter(!grepl("NIBP$", type))) +
geom_point(data = plotdat %>% filter(artefact),mapping = aes(x = time, y = value, color = type),
shape = 4, size = 2, stroke = 2) +
theme_bw()
})
output$artefacts <- renderTable({
vitals()[artefacts$status,] %>%
arrange(type, time) %>%
group_by(type) %>%
mutate(vital = if_else(row_number()==1,unlist(vitaltypes[match(type, vitaltypes$field),"label"]),""),
time = floor(time)) %>%
ungroup() %>%
select(vital, time, value)
})
})
来自sessionInfo()的输出
R version 3.4.1 (2017-06-30)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1
Matrix products: default
locale:
[1] LC_COLLATE=Dutch_Netherlands.1252 LC_CTYPE=Dutch_Netherlands.1252 LC_MONETARY=Dutch_Netherlands.1252
[4] LC_NUMERIC=C LC_TIME=Dutch_Netherlands.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] compiler_3.4.1 tools_3.4.1
最佳答案
此示例 Shiny 应用程序中出现以下问题:
单击某个点时，artefact$status 中的值 artefact 将从 TRUE 更改为 FALSE。
在下面的代码中，数据被分散，但由于现在属于在一起的三个值之一具有不同的字段 artefact 值，因此生成了两个单独的行。因此，使用 geom_errorbar() 至少缺少一种美感(y、ymax 或 ymin)。
nibpdat <- plotvitals %>% filter(grepl("nibp$",type)) %>%
spread(type, value) %>%
mutate(type = factor(match("meannibp", vitaltypes$field),
levels = seq_len(nrow(vitaltypes)),
labels = vitaltypes$label),
value = meannibp,
artefact = FALSE)
应更改为:
nibpdat <- plotvitals %>% filter(grepl("nibp$",type)) %>%
select(-artefact) %>%
spread(type, plotvalue) %>%
mutate(type = factor(match("meannibp", vitaltypes$field),
levels = seq_len(nrow(vitaltypes)),
labels = vitaltypes$label),
plotvalue = meannibp,
artefact = FALSE)
关于r - Shiny 的交互式 ggplot 缺少误差线，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/54575624/