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materials/tutorial_03/data/US_county_cancer_data.csv
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library(digest) | ||
library(testthat) | ||
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test_1.1 <- function() { | ||
test_that('Did not assign answer to an object called "crabs_vs_width_scatterplot"', { | ||
expect_true(exists("crabs_vs_width_scatterplot")) | ||
}) | ||
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test_that("Solution should be a ggplot object", { | ||
expect_true(is.ggplot(crabs_vs_width_scatterplot)) | ||
}) | ||
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properties <- c(crabs_vs_width_scatterplot$layers[[1]]$mapping, crabs_vs_width_scatterplot$mapping) | ||
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test_that("Plot should have width on the x-axis", { | ||
expect_true("width" == rlang::get_expr(properties$x)) | ||
}) | ||
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test_that("Plot does not have the correct layers", { | ||
expect_true("GeomPoint" %in% class(crabs_vs_width_scatterplot$layers[[1]]$geom)) | ||
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# Remove if not needed: | ||
# expect_true("GeomVline" %in% class(crabs_vs_width_scatterplot$layers[[2]]$geom)) | ||
}) | ||
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test_that("Plot does not use the correct data", { | ||
expect_equal(digest(nrow(crabs_vs_width_scatterplot$data)), "8c2afe893b01f3a8c63e1aef3b5aad9e") | ||
expect_equal(digest(round(sum(crabs_vs_width_scatterplot$data$width))), "17a701ffb51e7429bcd57678dd80b402") | ||
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# If width is not known: | ||
# expect_equal(digest(round(sum(pull(crabs_vs_width_scatterplot$data, rlang::get_expr(properties$x))))), "HASH_HERE") | ||
}) | ||
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test_that("x-axis label should be descriptive and human readable", { | ||
expect_false(crabs_vs_width_scatterplot$labels$x == toString(rlang::get_expr(properties$x))) | ||
}) | ||
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test_that("Plot should have a title", { | ||
expect_true("title" %in% names(crabs_vs_width_scatterplot$labels)) | ||
}) | ||
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print("Success!") | ||
} | ||
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test_1.2 <- function() { | ||
test_that('Did not assign answer to an object called "crabs_group_avg_width"', { | ||
expect_true(exists("crabs_group_avg_width")) | ||
}) | ||
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test_that("Solution should be a data frame", { | ||
expect_true("data.frame" %in% class(crabs_group_avg_width)) | ||
}) | ||
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expected_colnames <- c("width_intervals", "mean_n_males") | ||
given_colnames <- colnames(crabs_group_avg_width) | ||
test_that("Data frame does not have the correct columns", { | ||
expect_equal(length(setdiff( | ||
union(expected_colnames, given_colnames), | ||
intersect(expected_colnames, given_colnames) | ||
)), 0) | ||
}) | ||
|
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test_that("Data frame does not contain the correct number of rows", { | ||
expect_equal(digest(as.integer(nrow(crabs_group_avg_width))), "71db8a6cad03244e6e50f0ad8bc95a65") | ||
}) | ||
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test_that("Data frame does not contain the correct data", { | ||
expect_equal(digest(as.integer(sum(crabs_group_avg_width$mean_n_males) * 10e4)), "12273d78c0faff1ea67c8f8e9c42edd0") | ||
}) | ||
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print("Success!") | ||
} | ||
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test_1.3 <- function() { | ||
test_that('Did not assign answer to an object called "crabs_avg_width_scatterplot"', { | ||
expect_true(exists("crabs_avg_width_scatterplot")) | ||
}) | ||
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||
test_that("Solution should be a ggplot object", { | ||
expect_true(is.ggplot(crabs_avg_width_scatterplot)) | ||
}) | ||
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properties <- c(crabs_avg_width_scatterplot$layers[[1]]$mapping, crabs_avg_width_scatterplot$mapping) | ||
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test_that("Plot should have width_intervals on the x-axis", { | ||
expect_true("width_intervals" == rlang::get_expr(properties$x)) | ||
}) | ||
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test_that("Plot does not have the correct layers", { | ||
expect_true("GeomPoint" %in% class(crabs_avg_width_scatterplot$layers[[1]]$geom)) | ||
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# Remove if not needed: | ||
# expect_true("GeomVline" %in% class(crabs_avg_width_scatterplot$layers[[2]]$geom)) | ||
}) | ||
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||
test_that("Plot does not use the correct data", { | ||
expect_equal(digest(nrow(crabs_avg_width_scatterplot$data)), "71db8a6cad03244e6e50f0ad8bc95a65") | ||
expect_equal(digest(round(sum(crabs_avg_width_scatterplot$data$mean_n_males))), "e1d9279a9999b2d3bb972ab3267b49c7") | ||
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# If width_intervals is not known: | ||
# expect_equal(digest(round(sum(pull(crabs_avg_width_scatterplot$data, rlang::get_expr(properties$x))))), "HASH_HERE") | ||
}) | ||
|
||
test_that("x-axis label should be descriptive and human readable", { | ||
expect_false(crabs_avg_width_scatterplot$labels$x == toString(rlang::get_expr(properties$x))) | ||
}) | ||
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||
test_that("Plot should have a title", { | ||
expect_true("title" %in% names(crabs_avg_width_scatterplot$labels)) | ||
}) | ||
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print("Success!") | ||
} | ||
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test_1.4 <- function() { | ||
test_that('Did not assign answer to an object called "answer1.4"', { | ||
expect_true(exists("answer1.4")) | ||
}) | ||
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test_that('Solution should be a single character ("A", "B", or "C")', { | ||
expect_match(answer1.4, "a|b|c", ignore.case = TRUE) | ||
}) | ||
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answer_hash <- digest(tolower(answer1.4)) | ||
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test_that("Solution is incorrect", { | ||
expect_equal(answer_hash, "127a2ec00989b9f7faf671ed470be7f8") | ||
}) | ||
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print("Success!") | ||
} | ||
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test_1.5 <- function() { | ||
test_that('Did not assign answer to an object called "crabs_vs_width_scatterplot"', { | ||
expect_true(exists("crabs_vs_width_scatterplot")) | ||
}) | ||
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test_that("Solution should be a ggplot object", { | ||
expect_true(is.ggplot(crabs_vs_width_scatterplot)) | ||
}) | ||
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properties <- c(crabs_vs_width_scatterplot$layers[[1]]$mapping, crabs_vs_width_scatterplot$mapping) | ||
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test_that("Plot should have width on the x-axis", { | ||
expect_true("width" == rlang::get_expr(properties$x)) | ||
}) | ||
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||
test_that("Plot does not have the correct layers", { | ||
expect_true("GeomPoint" %in% class(crabs_vs_width_scatterplot$layers[[1]]$geom)) | ||
}) | ||
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||
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||
test_that("Plot does not use the correct data", { | ||
expect_equal(digest(nrow(crabs_vs_width_scatterplot$data)), "8c2afe893b01f3a8c63e1aef3b5aad9e") | ||
expect_equal(digest(round(sum(crabs_vs_width_scatterplot$data$width))), "17a701ffb51e7429bcd57678dd80b402") | ||
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# If width is not known: | ||
# expect_equal(digest(round(sum(pull(crabs_vs_width_scatterplot$data, rlang::get_expr(properties$x))))), "HASH_HERE") | ||
}) | ||
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||
test_that("x-axis label should be descriptive and human readable", { | ||
expect_false(crabs_vs_width_scatterplot$labels$x == toString(rlang::get_expr(properties$x))) | ||
}) | ||
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test_that("Plot should have a title", { | ||
expect_true("title" %in% names(crabs_vs_width_scatterplot$labels)) | ||
}) | ||
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print("Success!") | ||
} | ||
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test_1.6 <- function() { | ||
test_that('Did not assign answer to an object called "crabs_poisson_model"', { | ||
expect_true(exists("crabs_poisson_model")) | ||
}) | ||
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test_that("Solution should be a glm object", { | ||
expect_true("glm" %in% class(crabs_poisson_model)) | ||
}) | ||
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test_that("Data frame does not contain the correct data", { | ||
expect_equal(digest(as.integer(sum(crabs_poisson_model$residuals) * 10e4)), "5ab35ebc157c4f75476569c445d5a1cc") | ||
}) | ||
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print("Success!") | ||
} | ||
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test_1.7 <- function() { | ||
test_that('Did not assign answer to an object called "crabs_poisson_model_results"', { | ||
expect_true(exists("crabs_poisson_model_results")) | ||
}) | ||
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test_that("Solution should be a data frame", { | ||
expect_true("data.frame" %in% class(crabs_poisson_model_results)) | ||
}) | ||
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expected_colnames <- c('term','estimate','std.error','statistic','p.value','conf.low','conf.high') | ||
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given_colnames <- colnames(crabs_poisson_model_results) | ||
test_that("Data frame does not have the correct columns", { | ||
expect_equal(length(setdiff( | ||
union(expected_colnames, given_colnames), | ||
intersect(expected_colnames, given_colnames) | ||
)), 0) | ||
}) | ||
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test_that("Data frame does not contain the correct number of rows", { | ||
expect_equal(digest(as.integer(nrow(crabs_poisson_model_results))), "dd4ad37ee474732a009111e3456e7ed7") | ||
}) | ||
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test_that("Data frame does not contain the correct data", { | ||
expect_equal(digest(as.integer(sum(crabs_poisson_model_results$conf.low) * 10e6)), "79cef645627327fe2632a29728949fa8") | ||
expect_equal(digest(as.integer(sum(crabs_poisson_model_results$conf.high) * 10e6)), "b2f64ff96ebb309861a640e306397224") | ||
expect_equal(digest(as.integer(sum(crabs_poisson_model_results$statistic) * 10e6)), "09ad422316ee480535d0735aedfb2543") | ||
}) | ||
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print("Success!") | ||
} | ||
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test_1.8 <- function() { | ||
test_that('Did not assign answer to an object called "crabs_poisson_model_results"', { | ||
expect_true(exists("crabs_poisson_model_results")) | ||
}) | ||
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test_that("Solution should be a data frame", { | ||
expect_true("data.frame" %in% class(crabs_poisson_model_results)) | ||
}) | ||
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expected_colnames <- c('term','estimate','std.error','statistic','p.value','conf.low','conf.high', 'exp.estimate', 'exp.conf.low', 'exp.conf.high') | ||
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given_colnames <- colnames(crabs_poisson_model_results) | ||
test_that("Data frame does not have the correct columns", { | ||
expect_equal(length(setdiff( | ||
union(expected_colnames, given_colnames), | ||
intersect(expected_colnames, given_colnames) | ||
)), 0) | ||
}) | ||
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test_that("Data frame does not contain the correct number of rows", { | ||
expect_equal(digest(as.integer(nrow(crabs_poisson_model_results))), "dd4ad37ee474732a009111e3456e7ed7") | ||
}) | ||
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test_that("Data frame does not contain the correct data", { | ||
expect_equal(digest(as.integer(sum(crabs_poisson_model_results$exp.estimate) * 10e6)), "dd50342cffd6d0cde245787cbdd97021") | ||
expect_equal(digest(as.integer(sum(crabs_poisson_model_results$exp.conf.low) * 10e6)), "5aa9e6879f68968bdb958bdc1a4cdf32") | ||
expect_equal(digest(as.integer(sum(crabs_poisson_model_results$exp.conf.high) * 10e6)), "b6866c669fd240e038b16d7e35b90592") | ||
}) | ||
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print("Success!") | ||
} | ||
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test_1.9 <- function() { | ||
test_that('Did not assign answer to an object called "answer1.9"', { | ||
expect_true(exists("answer1.9")) | ||
}) | ||
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answer_hash <- digest(tolower(answer1.9)) | ||
test_that("Solution is incorrect", { | ||
expect_equal(answer_hash, "fd4d64bc84d8d1ac10b94c23bda1a016") | ||
}) | ||
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print("Success!") | ||
} | ||
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test_1.10 <- function() { | ||
test_that('Did not assign answer to an object called "answer1.10"', { | ||
expect_true(exists("answer1.10")) | ||
}) | ||
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test_that('Solution should be a single character ("A", "B", "C", or "D")', { | ||
expect_match(answer1.10, "a|b|c|d", ignore.case = TRUE) | ||
}) | ||
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answer_hash <- digest(tolower(answer1.10)) | ||
test_that("Solution is incorrect", { | ||
expect_equal(answer_hash, "6e7a8c1c098e8817e3df3fd1b21149d1") | ||
}) | ||
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print("Success!") | ||
} | ||
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test_1.11 <- function() { | ||
test_that('Did not assign answer to an object called "answer1.11"', { | ||
expect_true(exists("answer1.11")) | ||
}) | ||
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test_that('Solution should be a single character ("A", "B", "C", or "D")', { | ||
expect_match(answer1.11, "a|b|c|d", ignore.case = TRUE) | ||
}) | ||
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answer_hash <- digest(tolower(answer1.11)) | ||
test_that("Solution is incorrect", { | ||
expect_equal(answer_hash, "ddf100612805359cd81fdc5ce3b9fbba") | ||
}) | ||
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print("Success!") | ||
} | ||
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test_1.12 <- function() { | ||
test_that('Did not assign answer to an object called "answer1.12"', { | ||
expect_true(exists("answer1.12")) | ||
}) | ||
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answer_as_numeric <- as.numeric(answer1.12) | ||
test_that("Solution should be a number", { | ||
expect_false(is.na(answer_as_numeric)) | ||
}) | ||
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test_that("Solution is incorrect", { | ||
expect_equal(digest(as.integer(answer_as_numeric * 10e6)), "07660fdc17d69e9b645c10b4a1f810be") | ||
}) | ||
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print("Success!") | ||
} |
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