如何为ggplot图编写测试

Question

我有很多生成绘图的函数,通常使用ggplot2.现在,我正在生成情节并测试基础数据.但我想知道是否有合理的方法来测试该图包含我期望的图层/选项或图形元素是否符合预期.

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))

})

这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(...,...)
})

也许有更直接的方法？

Answer 1

这似乎是你的目标,虽然绘制参数和内容的具体要求当然会有所不同.但是对于你在这些测试之上精心设计的例子应该全部通过:

##  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)
})

这个问题及其答案为其他表征ggplot对象的方法提供了一个很好的起点,以防你有其他想要测试的东西.

Answer 2

值得注意的是,vdiffr软件包是为比较图而设计的.一个很好的功能是它与testthat软件包集成 - 它实际上用于在ggplot2中进行测试 - 它有一个RStudio的插件来帮助管理你的测试套件.

Answer 3

除了现有答案之外，我还发现有用的是测试是否可以实际打印绘图。

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