tests/testthat/test-clean-factor_labels.R

In AntonioJBT/episcout: Quickly Clean, Explore and Visualise Large Epidemiological Datasets

context("episcout stats function tests")

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library(testthat)
library(dplyr)
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# Working directory for informal tests, should be from pkg/tests/testthat/:
# setwd("")
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# Set a test set:

# Define a sample dataframe:
sample_data_df <- data.frame(
    ORIGEN = c(1, 2, 99, 1),
    SECTOR = c(1, 2, 4, 5),
    stringsAsFactors = FALSE
    )

# Define a sample lookup dataframe:
sample_lookup_df <- data.frame(
    variable = c("ORIGEN", "ORIGEN", "ORIGEN", "SECTOR", "SECTOR", "SECTOR"),
    level = as.character(c(1, 2, 99, 1, 2, 4)),
    label = c("USMER", "FUERA DE USMER", "NO ESPECIFICADO", "CRUZ ROJA", "DIF", "IMSS"),
    stringsAsFactors = FALSE
    )
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print("Function being tested: epi_clean_label")

test_that("epi_clean_label correctly applies factor levels and labels", {
    # Apply the function to the sample data
    result_df <- epi_clean_label(sample_data_df, sample_lookup_df)

    # Test if the ORIGEN column is correctly transformed into a factor with the correct levels and labels
    expect_is(result_df$ORIGEN, "factor")
    expect_equal(levels(result_df$ORIGEN), c("USMER", "FUERA DE USMER", "NO ESPECIFICADO"))
    expect_equal(as.character(result_df$ORIGEN), c("USMER", "FUERA DE USMER", "NO ESPECIFICADO", "USMER"))

    # Test if the SECTOR column is correctly transformed into a factor with the correct levels and labels
    expect_is(result_df$SECTOR, "factor")
    expect_equal(levels(result_df$SECTOR), c("CRUZ ROJA", "DIF", "IMSS"))
    expect_equal(as.character(result_df$SECTOR), c("CRUZ ROJA", "DIF", "IMSS", NA))
})

# Additional test to check handling of missing levels
test_that("epi_clean_label handles missing levels correctly", {
    # Introduce a SECTOR level that isn't in the lookup (e.g., level 5)
    altered_data_df <- sample_data_df
    altered_data_df$SECTOR[4] <- 5  # Level not in lookup

    # Expected to handle this by introducing NA for missing level
    result_df <- epi_clean_label(altered_data_df, sample_lookup_df)
    expect_true(is.na(result_df$SECTOR[4]))
})
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