tests_tutorial_07.R

library(testthat)
library(digest)
library(rlang)

# Round double to precise integer
#
# `int_round` works to create an integer corresponding to a number that is 
# tested up to a particular decimal point of precision. This is useful when 
# there is a need to compare a numeric value using hashes.
#
# @param x Double vector of length one.
# @param digits Double vector of length one to specify decimal point of precision. Negative numbers can be used to specifying significant digits > 0.1.
#
# @return Integer vector of length one corresponding to a particular decimal point of precision.
#
# @examples
# # to get an integer up to two decimals of precision from 234.56789
# int_round(234.56789, 2)
#
# to get an integer rounded to the hundred digit from 234.56789
# int_round(234.56789, -2)
int_round <- function(x, digits){
    x = x*10^digits
    xint = as.integer(x)
    xint1 = xint + 1L
    if (abs(xint - x) < abs(xint1 - x)){
        return(xint)
    }
    else {
        return(xint1)
    }
}


test_1.0 <- function(){
    test_that('Solution is incorrect', {
        expect_true(exists('answer1.0'))
        expect_equal(digest(answer1.0), 'c1f86f7430df7ddb256980ea6a3b57a4') # we hid the answer to the test here so you can't see it, but we can still run the test
    })
    print("Success!")
}        

test_1.1 <- function(){
    test_that('Solution is incorrect', {
        expect_true(exists('answer1.1'))
        expect_equal(digest(answer1.1), '475bf9280aab63a82af60791302736f6') # we hid the answer to the test here so you can't see it, but we can still run the test
    })
    print("Success!")
}    

test_2.0 <- function(){
    test_that('number_of_rows does not exist', {
        expect_true(exists('number_of_rows'))
    })
    test_that('The number of rows is incorrect', {
        expect_equal(digest(int_round(number_of_rows, 0)), 'a58969729b9f8713e03743154dfa7b57') # we hid the answer to the test here so you can't see it, but we can still run the test
    })
    print("Success!")
}

test_2.1 <- function(){
    test_that('Solution is incorrect', {
        expect_equal(int_round(nrow(counts), 0), 10)
        expect_equal(digest(int_round(sum(as.integer(counts$y)), 2)), 'ae80db6ce6693e364a09f88dd4e3d553')
        expect_equal(dim(counts), c(10, 2))
        expect_equal(digest(int_round(sum(as.integer(counts$n)), 2)), '9ecacdf4df8df05e2501eb3f18bd13ab')
    })
    print("Success!")
}

test_2.2 <- function(){
    test_that('answer2.2 does not exist', {
        expect_true(exists('answer2.2'))
    })
    test_that('Solution is incorrect', {
        expect_equal(digest(answer2.2), 'd2a90307aac5ae8d0ef58e2fe730d38b')
    })
    print("Success!")
}

test_2.4 <- function(){
    test_that('Did not create an object called label_102', {
        expect_true(exists('label_102'))
    })
    test_that('label_102 is not a tibble', {
        expect_true('tbl' %in% class(label_102))
    })
    test_that('y is not a factor', {
        expect_true('factor' %in% class(label_102$y))
    })
    test_that('Solution is incorrect', {
        expect_equal(digest(int_round(as.integer(label_102[[1]]), 2)), '069c0949cc402f30063b90e9a31f87e1') # we hid the answer to the test here so you can't see it, but we can still run the test
    })
    print("Success!")
}

test_3.0 <- function(){
    test_that('testing_set does not exist', {
        expect_true(exists('testing_set'))
    })
    test_that('testing_set does not contain the correct data', {
        expect_equal(dim(testing_set), c(600, 786))
        expect_equal(digest(int_round(sum(as.integer(testing_set$y)), 2)), '733395e0768b9479c1feffa0b067fcdd')
    })
    test_that('training_set does not exist', {
        expect_true(exists('training_set'))
    })
    test_that('training_set does not contain the correct data',{
        expect_equal(dim(training_set), c(600, 785))
        expect_equal(digest(int_round(sum(as.integer(training_set$y)), 2)), '4eb0b7cdd24a983324274d66e0860365')
    })
    print("Success!")
}

test_3.2 <- function(){
    properties <- c(cross_val_plot$layers[[1]]$mapping, cross_val_plot$mapping)
    labels <- cross_val_plot$labels
    test_that('Did not create an object named cross_val_plot',{
        expect_true(exists('cross_val_plot'))
    })
    test_that('cross_val_plot is not a lineplot', {
        expect_true('GeomPoint' %in% class(cross_val_plot$layers[[1]]$geom))
        expect_true('GeomLine' %in% class(cross_val_plot$layers[[2]]$geom))
    })
    test_that('neighbors should be on the x-axis.', {
        expect_true("neighbors" == rlang::get_expr(properties$x))
        })
    test_that('mean should be on the y-axis.', {
        expect_true("mean" == rlang::get_expr(properties$y))
        })
    test_that('cross_val_plot does not contain the correct data.', {
        expect_equal(digest(int_round(sum(cross_val_plot$data$mean), 2)), '088459b2025cd3f9cbf1451f8c2c1636')
        expect_equal(digest(int_round(sum(cross_val_plot$data$n), 2)), '189e2f1b2fbb3743811990e9708c226a')
    })
    test_that('cross_val_plot should only contain accuracy.', {
        expect_true('accuracy' %in% unique(cross_val_plot$data$.metric))
    })
    print("Success!")
}

test_3.3 <- function(){
    test_that('Did not create an object named answer3.3', {
        expect_true(exists('answer3.3'))
    })
    test_that('Solution is incorrect', {
        expect_equal(digest(answer3.3), '75f1160e72554f4270c809f041c7a776')
    })
    print("Success!")
}

test_4.1 <- function(){
    test_that('Did not create an object named mnist_predictions', {
        expect_true(exists('mnist_predictions'))
    })
    test_that('mnist_predictions does not contain the correct data', {
        expect_equal(digest(int_round(sum(as.integer(mnist_predictions$.pred_class)), 2)), 'ad1b496bd820958116aa67cdb147352b')
        expect_equal(digest(int_round(sum(as.integer(mnist_predictions$y)), 2)), '733395e0768b9479c1feffa0b067fcdd')
    })
    test_that('Did not create an objected named mnist_conf_mat', {
        expect_true(exists('mnist_conf_mat'))
    })
    test_that('mnist_conf_mat is not a confusion matrix', {
        expect_true('conf_mat' %in% class(mnist_conf_mat))
    })
    test_that('mnist_conf_mat contains the incorrect data', {
        expect_equal(digest(int_round(sum(as.integer(mnist_conf_mat$table)), 2)), '9ecacdf4df8df05e2501eb3f18bd13ab')
    })
    test_that('Did not create an objected named mnist_metrics', {
        expect_true(exists('mnist_metrics'))
    })
    test_that('mnist_metrics is not a data frame', {
        expect_true('tbl_df' %in% class(mnist_metrics))
    })
    test_that('mnist_metrics contains the incorrect data', {
        expect_equal(digest(int_round(sum(as.integer(mnist_metrics$.estimate)), 2)), '1473d70e5646a26de3c52aa1abd85b1f')
    })
    
    
    
    print("Success!")
}

test_4.4 <- function(){
    test_that('Did not create an object named answer4.4', {
        expect_true(exists('answer4.4'))
    })
    test_that('Solution is incorrect', {
        expect_equal(digest(answer4.4), '05ca18b596514af73f6880309a21b5dd')
    })
    print("Success!")
}