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No image snapshots #134

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Feb 21, 2024
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No image snapshots #134

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e1cf4c8
better testing
Feb 21, 2024
c754f16
tibble::tibble -> dplyr::tibble
Feb 21, 2024
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224 changes: 188 additions & 36 deletions tests/testthat/test-cal-plot.R
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Original file line number Diff line number Diff line change
Expand Up @@ -33,16 +33,36 @@ test_that("Binary breaks functions work with group argument", {
dplyr::mutate(id = dplyr::row_number() %% 2) %>%
cal_plot_breaks(Class, .pred_good, .by = id)

expect_s3_class(
res,
"ggplot"
expect_s3_class(res, "ggplot")

expect_equal(
res$data[0,],
dplyr::tibble(
id = factor(0, levels = paste(0:1)),
predicted_midpoint = double(), event_rate = double(), events = double(),
total = integer(), lower = double(), upper = double()
)
)

skip("wait to refactor plot tests")
expect_snapshot_plot(
"cal_plot_breaks-df-group",
print(res)
expect_equal(
rlang::expr_text(res$mapping$x),
"~predicted_midpoint"
)
expect_equal(
rlang::expr_text(res$mapping$colour),
"~id"
)
expect_equal(
rlang::expr_text(res$mapping$fill),
"~id"
)
expect_equal(
res$labels,
list(x = "Bin Midpoint", y = "Event Rate", colour = "id", fill = "id",
intercept = "intercept", slope = "slope", ymin = "lower",
ymax = "upper")
)
expect_equal(length(res$layers), 4)

expect_snapshot_error(
segment_logistic %>%
Expand Down Expand Up @@ -207,12 +227,36 @@ test_that("Binary logistic functions work with group argument", {
)
expect_true(has_facet(res))

skip("wait to refactor plot tests")
expect_snapshot_plot(
"cal_plot_logistic-df-group",
print(res)
expect_s3_class(res, "ggplot")

expect_equal(
res$data[0,],
dplyr::tibble(
id = factor(0, levels = paste(0:1)),
estimate = double(), prob = double(), lower = double(), upper = double()
)
)

expect_equal(
rlang::expr_text(res$mapping$x),
"~estimate"
)
expect_equal(
rlang::expr_text(res$mapping$colour),
"~id"
)
expect_equal(
rlang::expr_text(res$mapping$fill),
"~id"
)
expect_equal(
res$labels,
list(x = "Probability", y = "Predicted Event Rate", colour = "id",
fill = "id", intercept = "intercept", slope = "slope", ymin = "lower",
ymax = "upper")
)
expect_equal(length(res$layers), 3)

expect_snapshot_error(
segment_logistic %>%
dplyr::mutate(group1 = 1, group2 = 2) %>%
Expand Down Expand Up @@ -442,38 +486,146 @@ test_that("regression functions work", {

obj <- testthat_cal_reg()

expect_s3_class(
cal_plot_regression(boosting_predictions_oob, outcome, .pred),
"ggplot"
res <- cal_plot_regression(boosting_predictions_oob, outcome, .pred)
expect_s3_class(res, "ggplot")

expect_equal(
res$data[0,],
dplyr::tibble(outcome = numeric(0), .pred = numeric(0), id = character(0))
)

skip("wait to refactor plot tests")
expect_snapshot_plot(
"df-scat",
print(cal_plot_regression(boosting_predictions_oob, outcome, .pred))
expect_equal(
rlang::expr_text(res$mapping$x),
"~outcome"
)
# There are incredibly small differences for this particular plot between
# Intel Macs and those with Apple Silicon
skip("wait to refactor plot tests")
expect_snapshot_plot(
"df-scat-group",
print(cal_plot_regression(boosting_predictions_oob, outcome, .pred, .by = id))
expect_equal(
rlang::expr_text(res$mapping$y),
"~.pred"
)
skip("wait to refactor plot tests")
expect_snapshot_plot(
"rs-scat-group",
print(cal_plot_regression(obj))
expect_null(res$mapping$colour)
expect_null(res$mapping$fill)

expect_equal(
res$labels,
list(x = "Observed", y = "Predicted", colour = "colour", fill = "fill",
intercept = "intercept", slope = "slope")
)
skip("wait to refactor plot tests")
expect_snapshot_plot(
"rs-scat-group-opts",
print(cal_plot_regression(obj), alpha = 1 / 5, smooth = FALSE)
expect_equal(length(res$layers), 3)


res <- cal_plot_regression(boosting_predictions_oob, outcome, .pred, .by = id)
expect_s3_class(res, "ggplot")

expect_equal(
res$data[0,],
dplyr::tibble(outcome = numeric(0), .pred = numeric(0), id = character(0))
)

expect_equal(
rlang::expr_text(res$mapping$x),
"~outcome"
)
skip("wait to refactor plot tests")
expect_snapshot_plot(
"df-scat-lin",
print(cal_plot_regression(boosting_predictions_oob, outcome, .pred, smooth = FALSE))
expect_equal(
rlang::expr_text(res$mapping$y),
"~.pred"
)
expect_null(res$mapping$colour)
expect_null(res$mapping$fill)

expect_equal(
res$labels,
list(x = "Observed", y = "Predicted", colour = "colour", fill = "fill",
intercept = "intercept", slope = "slope")
)
expect_equal(length(res$layers), 3)


res <- cal_plot_regression(obj)
expect_s3_class(res, "ggplot")

expect_equal(
res$data[0,],
dplyr::tibble(.pred = numeric(0), .row = numeric(0),
predictor_01 = integer(0), outcome = numeric(0),
.config = character())
)

expect_equal(
rlang::expr_text(res$mapping$x),
"~outcome"
)
expect_equal(
rlang::expr_text(res$mapping$y),
"~.pred"
)
expect_null(res$mapping$colour)
expect_null(res$mapping$fill)

expect_equal(
res$labels,
list(x = "Observed", y = "Predicted", colour = "colour", fill = "fill",
intercept = "intercept", slope = "slope")
)
expect_equal(length(res$layers), 3)


res <- print(cal_plot_regression(obj), alpha = 1 / 5, smooth = FALSE)
expect_s3_class(res, "ggplot")

expect_equal(
res$data[0,],
dplyr::tibble(.pred = numeric(0), .row = numeric(0),
predictor_01 = integer(0), outcome = numeric(0),
.config = character())
)

expect_equal(
rlang::expr_text(res$mapping$x),
"~outcome"
)
expect_equal(
rlang::expr_text(res$mapping$y),
"~.pred"
)
expect_null(res$mapping$colour)
expect_null(res$mapping$fill)

expect_equal(
res$labels,
list(x = "Observed", y = "Predicted", colour = "colour", fill = "fill",
intercept = "intercept", slope = "slope")
)
expect_equal(length(res$layers), 3)


res <- cal_plot_regression(boosting_predictions_oob, outcome, .pred, smooth = FALSE)
expect_s3_class(res, "ggplot")

expect_equal(
res$data[0,],
dplyr::tibble(outcome = numeric(0), .pred = numeric(0),
id = character())
)

expect_equal(
rlang::expr_text(res$mapping$x),
"~outcome"
)
expect_equal(
rlang::expr_text(res$mapping$y),
"~.pred"
)
expect_null(res$mapping$colour)
expect_null(res$mapping$fill)

expect_equal(
res$labels,
list(x = "Observed", y = "Predicted", colour = "colour", fill = "fill",
intercept = "intercept", slope = "slope")
)
expect_equal(length(res$layers), 3)


})

test_that("regression plot function errors - grouped_df", {
Expand Down
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