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[英]How to write a ggplot '+'-pipeable function that can refer to the input plot
[英]How to write a test for a ggplot plot
我有很多生成繪圖的函數,通常使用ggplot2。 現在,我正在生成情節並測試基礎數據。 但我想知道是否有合理的方法來測試該圖包含我期望的圖層/選項或圖形元素是否符合預期。
例如:
library(ggplot2)
library(scales) # for percent()
library(testthat)
df <- data.frame(
Response = LETTERS[1:5],
Proportion = c(0.1,0.2,0.1,0.2,0.4)
)
#' @export plot_fun
plot_fun <- function(df) {
p1 <- ggplot(df, aes(Response, Proportion)) +
geom_bar(stat='identity') +
scale_y_continuous(labels = percent)
return(p1)
}
test_that("Plot returns ggplot object",{
p <- plot_fun(df)
expect_is(p,"ggplot")
})
test_that("Plot uses correct data", {
p <- plot_fun(df)
expect_that(df, equals(p$data))
})
這就是我被困住的地方
test_that("Plot layers match expectations",{
p <- plot_fun(df)
expect_that(...,...)
})
test_that("Scale is labelled percent",{
p <- plot_fun(df)
expect_that(...,...)
})
也許有更直接的方法?
這似乎是你的目標,雖然繪制參數和內容的具體要求當然會有所不同。 但是對於你在這些測試之上精心設計的例子應該全部通過:
## Load the proto library for accessing sub-components of the ggplot2
## plot objects:
library(proto)
test_that("Plot layers match expectations",{
p <- plot_fun(df)
expect_is(p$layers[[1]], "proto")
expect_identical(p$layers[[1]]$geom$objname, "bar")
expect_identical(p$layers[[1]]$stat$objname, "identity")
})
test_that("Scale is labelled 'Proportion'",{
p <- plot_fun(df)
expect_identical(p$labels$y, "Proportion")
})
test_that("Scale range is NULL",{
p <- plot_fun(df)
expect_null(p$scales$scales[[1]]$range$range)
})
這個問題及其答案為其他表征ggplot
對象的方法提供了一個很好的起點,以防你有其他想要測試的東西。
值得注意的是, vdiffr軟件包是為比較圖而設計的。 一個很好的功能是它與testthat軟件包集成 - 它實際上用於在ggplot2中進行測試 - 它有一個RStudio的插件來幫助管理你的測試套件。
除了現有答案之外,我還發現有用的是測試是否可以實際打印圖表。
library(ggplot2)
library(scales) # for percent()
library(testthat)
# First, 'correct' data frame
df <- data.frame(
Response = LETTERS[1:5],
Proportion = c(0.1,0.2,0.1,0.2,0.4)
)
# Second data frame where column has 'wrong' name that does not match aes()
df2 <- data.frame(
x = LETTERS[1:5],
Proportion = c(0.1,0.2,0.1,0.2,0.4)
)
plot_fun <- function(df) {
p1 <- ggplot(df, aes(Response, Proportion)) +
geom_bar(stat='identity') +
scale_y_continuous(labels = percent)
return(p1)
}
# All tests succeed
test_that("Scale is labelled 'Proportion'",{
p <- plot_fun(df)
expect_true(is.ggplot(p))
expect_identical(p$labels$y, "Proportion")
p <- plot_fun(df2)
expect_true(is.ggplot(p))
expect_identical(p$labels$y, "Proportion")
})
# Second test with data frame df2 fails
test_that("Printing ggplot object actually works",{
p <- plot_fun(df)
expect_error(print(p), NA)
p <- plot_fun(df2)
expect_error(print(p), NA)
})
#> Error: Test failed: 'Printing ggplot object actually works'
#> * `print(p)` threw an error.
#> Message: object 'Response' not found
#> Class: simpleError/error/condition
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