40

我有很多生成绘图的函数，通常使用 ggplot2。现在，我正在生成绘图并测试基础数据。但我想知道是否有合理的方法来测试绘图是否包含我期望的图层/选项，或者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))

})

这就是我卡住的地方

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？

4

3 回答 3

26

这似乎是您的目标，尽管对绘图参数和内容的具体要求当然会有所不同。但是对于您在上面精心制作的示例，这些测试应该全部通过：

##  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)
})

如果您有其他想要测试的东西，这个问题及其答案提供了一个很好的起点来描述对象的其他特征。ggplot

于 2015-06-25T04:23:59.027 回答
10

值得注意的是vdiffr包是为比较图而设计的。一个不错的功能是它与 testthat 包集成——它实际上用于在 ggplot2 中进行测试——并且它有一个 RStudio 插件来帮助管理你的测试套件。

于 2017-07-08T21:20:51.510 回答
7

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
于 2018-01-23T11:51:43.183 回答