library(testthat)
library(data.table)
library(DTwrappers2)

# Convert iris to a data.table once before the tests begin
data("iris")
setDT(iris)  # Convert to data.table

describe("dt.mean.numerics functionality", {

  it("computes mean values correctly with filter and grouping", {
    mean_values <- dt.mean.numerics(
      dt.name = "iris",
      the.filter = "Sepal.Length > 4 & Sepal.Length < 6",
      grouping.variables = "Species"
    )

    # Convert the expected Species column to a factor to match the actual results
    expected_means <- data.table(
      Species = factor(c("setosa", "versicolor", "virginica")),
      Sepal.Length = c(5.006000, 5.53076923 , 5.64285714),
      Sepal.Width = c(3.428000, 2.67307692, 2.71428571),
      Petal.Length = c(1.462000, 3.9692308 , 4.9714286),
      Petal.Width = c(0.246000, 1.23846154  , 1.95714286)
    )

    # Set the sorted attribute for the expected_means to match mean_values
    setattr(expected_means, 'sorted', 'Species')

    # Check if the computed mean values match the expected values
    expect_equal(mean_values, expected_means, info = "Computed means should match expected means")
  })

})