lissyrtools: Tools for LISSY Jobs

library(lissyrtools)
library(testthat)
library(ggplot2)
# library(purrr)  # Make sure to load purrr
#
# # Test for plot_lorenz_curve
# test_that("plot_lorenz_curve returns a ggplot object", {
#   dataset1 <- data.frame(dhi = c(1, 2, 3, 4, 5))
#   dataset2 <- data.frame(dhi = c(2, 3, 4, 5, 6))
#   result <- plot_lorenz_curve(list(dataset1, dataset2), "dhi")
#   expect_is(result, "ggplot")
# })
#
# # Test for plot_indicator
# test_that("plot_indicator returns a ggplot object", {
#   dataset1 <- data.frame(dhi = c(1, 2, 3, 4, 5))
#   dataset2 <- data.frame(dhi = c(2, 3, 4, 5, 6))
#   result <- plot_indicator(list(dataset1, dataset2), "dhi", "mean")
#   expect_is(result, "ggplot")
# })
#
# test_that("plot_indicator throws an error for unsupported indicators", {
#   dataset1 <- data.frame(dhi = c(1, 2, 3, 4, 5))
#   dataset2 <- data.frame(dhi = c(2, 3, 4, 5, 6))
#   expect_error(plot_indicator(list(dataset1, dataset2), "dhi", "unsupported_indicator"))
# })


# plot_indicator ----------------------------------------------------------

# Sample data for testing
sample_lissy_files <- list(
    us2010ih = data.frame(dhi = rnorm(100), hwgt = 1),
    us2011ih = data.frame(dhi = rnorm(100), hwgt = 1),
    ca2010ih = data.frame(dhi = rnorm(100), hwgt = 1),
    ca2011ih = data.frame(dhi = rnorm(100), hwgt = 1)
)

test_that("plot_indicator returns a ggplot2 plot for valid inputs", {
    plot <- plot_indicator(lissy_files = sample_lissy_files, variable = "dhi", indicator = "mean")
    expect_true(is.ggplot(plot))
})

test_that("plot_indicator throws an error for invalid lissy_files names", {
    invalid_files <- list(
        invalid_namei = data.frame(dhi = rnorm(100))
    )
    expect_error(plot_indicator(invalid_files, "dhi", "mean"))
})

test_that("plot_indicator throws an error for invalid type values", {
    expect_error(plot_indicator(sample_lissy_files, "dhi", "mean", type = "invalid_type"))
})

test_that("plot_indicator throws an error for invalid indicator values", {
    expect_error(plot_indicator(sample_lissy_files, "dhi", "invalid_indicator"))
})

test_that("plot_indicator handles NA values based on the na.rm parameter", {
    files_with_na <- list(
        us2010ih = data.frame(dhi = c(NA, rnorm(99)))
    )
    expect_error(
        plot_indicator(lissy_files = files_with_na, variable = "dhi", indicator = "mean"),
        "None of the indicators computed had valid values. Did you forget to pass na.rm = TRUE?"
    )
    expect_silent(plot_indicator(files_with_na, "dhi", "mean", na.rm = TRUE))
})

test_that("plot_indicator handles an empty list of lissy_files", {
    expect_error(plot_indicator(list(), "dhi", "mean"))
})

test_that("plot_indicator handles missing parameters correctly", {
    expect_silent(plot_indicator(sample_lissy_files, "dhi", "mean"))
})


# decide_plot_type --------------------------------------------------------
# Test for a data frame with multiple countries and multiple years
results_df1 <- data.frame(
    file = c("us2010h", "us2011h", "ca2010h", "ca2011h"),
    country = c("US", "US", "CA", "CA"),
    year = c(2010, 2011, 2010, 2011),
    value = c(1, 2, 3, 4)
)
expected_output1 <- "line"
test_that("decide_plot_type() returns the correct plot type for a data frame with multiple countries and multiple years", {
    expect_equal(decide_plot_type(results_df1), expected_output1)
})

# Test for a data frame with multiple years and only one country
results_df2 <- data.frame(
    file = c("us2010h", "us2011h"),
    country = c("US", "US"),
    year = c(2010, 2011),
    value = c(1, 2)
)
expected_output2 <- "line"
test_that("decide_plot_type() returns the correct plot type for a data frame with multiple years and only one country", {
    expect_equal(decide_plot_type(results_df2), expected_output2)
})

# Test for a data frame with only one year and multiple countries
results_df3 <- data.frame(
    file = c("us2010h", "ca2010h", "mx2010h"),
    country = c("US", "CA", "MX"),
    year = c(2010, 2010, 2010),
    value = c(1, 2, 3)
)
expected_output3 <- "bar"
test_that("decide_plot_type() returns the correct plot type for a data frame with only one year and multiple countries", {
    expect_equal(decide_plot_type(results_df3), expected_output3)
})

# Test for a data frame with only one year and only one country
results_df4 <- data.frame(
    file = c("us2010h"),
    country = c("US"),
    year = c(2010),
    value = c(1)
)
expected_output4 <- "bar"
test_that("decide_plot_type() returns the correct plot type for a data frame with only one year and only one country", {
    expect_equal(decide_plot_type(results_df4), expected_output4)
})



# plot_line ---------------------------------------------------------------
results_df <- data.frame(
    country = c("us", "us", "us", "us", "ca", "ca", "ca", "ca"),
    file = c("us2010h", "us2011h", "us2012h", "us2013h", "ca2010h", "ca2011h", "ca2012h", "ca2013h"),
    year = c(2010L, 2011L, 2012L, 2013L, 2010L, 2011L, 2012L, 2013L),
    value = c(1, 2, 3, 4, 3, 4, 5, 6)
)

# Test that the function returns a ggplot object
test_that("plot_line returns a ggplot object", {
    expect_s3_class(plot_line(results_df), "ggplot")
})

# Test that the function plots the correct x-axis values
test_that("plot_line plots the correct x-axis values", {
    p <- plot_line(results_df)
    expect_equal(sort(unique(results_df$year)), sort(unique(p$data[["year"]])))
})

# Test that the function plots the correct y-axis values
test_that("plot_line plots the correct y-axis values", {
    p <- plot_line(results_df)
    expect_equal(sort(unique(results_df$value)), sort(unique(p$data[["value"]])))
})


# plot_bar ----------------------------------------------------------------

# Create a test data frame
results_df <- data.frame(
    file = c("us2010h", "us2011h", "ca2010h", "ca2011h"),
    country = c("us", "us", "ca", "ca"),
    year = c(2010, 2011, 2010, 2011),
    value = c(1, 2, 3, 4)
)

# Test that the function returns a ggplot object
test_that("plot_bar returns a ggplot object", {
    expect_s3_class(plot_bar(results_df), "ggplot")
})

test_that("plot_line plots the correct x-axis values", {
    p <- plot_line(results_df)
    expect_equal(sort(unique(results_df$year)), sort(unique(p$data[["year"]])))
})

# Test that the function plots the correct y-axis values
test_that("plot_line plots the correct y-axis values", {
    p <- plot_line(results_df)
    expect_equal(sort(unique(results_df$value)), sort(unique(p$data[["value"]])))
})