Merge pull request #520 from tidymodels/all-snapshots

All snapshots

R/aaa-metrics.R

@@ -270,6 +270,7 @@ metric_set <- function(...) {
   )) {
     make_survival_metric_function(fns)
   } else {
+    # should not be reachable
     cli::cli_abort(
       "{.fn validate_function_class} should have errored on unknown classes.",
       .internal = TRUE
@@ -345,6 +346,7 @@ get_quo_label <- function(quo) {
   out <- as_label(quo)
 
   if (length(out) != 1L) {
+    # should not be reachable
     cli::cli_abort(
       "{.code as_label(quo)} resulted in a character vector of length >1.",
       .internal = TRUE
@@ -573,7 +575,9 @@ make_survival_metric_function <- function(fns) {
 
 validate_not_empty <- function(x, call = caller_env()) {
   if (is_empty(x)) {
-    cli::cli_abort("At least 1 function supplied to `...`.", call = call)
+    cli::cli_abort(
+      "At least 1 function must be supplied to {.code ...}.", call = call
+    )
   }
 }
 

R/class-mcc.R

@@ -161,6 +161,7 @@ mcc_multiclass_impl <- function(C) {
 
 check_mcc_data <- function(data) {
   if (!is.double(data) && !is.matrix(data)) {
+    # should not be reachable
     cli::cli_abort(
       "{.arg data} should be a double matrix at this point.",
       .internal = TRUE

R/misc.R

@@ -3,10 +3,6 @@
 # Column name extractors
 
 pos_val <- function(xtab, event_level) {
-  if (!all(dim(xtab) == 2)) {
-    cli::cli_abort("Only relevant for 2x2 tables.")
-  }
-
   if (is_event_first(event_level)) {
     colnames(xtab)[[1]]
   } else {
@@ -15,10 +11,6 @@ pos_val <- function(xtab, event_level) {
 }
 
 neg_val <- function(xtab, event_level) {
-  if (!all(dim(xtab) == 2)) {
-    cli::cli_abort("Only relevant for 2x2 tables.")
-  }
-
   if (is_event_first(event_level)) {
     colnames(xtab)[[2]]
   } else {
@@ -196,13 +188,15 @@ yardstick_cov <- function(truth,
 
   size <- vec_size(truth)
   if (size != vec_size(estimate)) {
+    # should be unreachable
     cli::cli_abort(
       "{.arg truth} ({vec_size(truth)}) and
       {.arg estimate} ({vec_size(estimate)}) must be the same size.",
       .internal = TRUE
     )
   }
   if (size != vec_size(case_weights)) {
+    # should be unreachable
     cli::cli_abort(
       "{.arg truth} ({vec_size(truth)}) and
       {.arg case_weights} ({vec_size(case_weights)}) must be the same size.",
@@ -250,13 +244,15 @@ yardstick_cor <- function(truth,
 
   size <- vec_size(truth)
   if (size != vec_size(estimate)) {
+    # should be unreachable
     cli::cli_abort(
       "{.arg truth} ({vec_size(truth)}) and
       {.arg estimate} ({vec_size(estimate)}) must be the same size.",
       .internal = TRUE
     )
   }
   if (size != vec_size(case_weights)) {
+    # should be unreachable
     cli::cli_abort(
       "{.arg truth} ({vec_size(truth)}) and
       {.arg case_weights} ({vec_size(case_weights)}) must be the same size.",
@@ -489,13 +485,15 @@ yardstick_truth_table <- function(truth, ..., case_weights = NULL) {
   abort_if_class_pred(truth)
 
   if (!is.factor(truth)) {
+    # should be unreachable
     cli::cli_abort("{.arg truth} must be a factor.", .internal = TRUE)
   }
 
   levels <- levels(truth)
   n_levels <- length(levels)
 
   if (n_levels < 2) {
+    # should be unreachable
     cli::cli_abort(
       "{.arg truth} must have at least 2 factor levels.",
       .internal = TRUE

R/prob-binary-thresholds.R

@@ -16,31 +16,36 @@ binary_threshold_curve <- function(truth,
   case_weights <- vec_cast(case_weights, to = double())
 
   if (!is.factor(truth)) {
+    # should be unreachable
     cli::cli_abort(
       "{.arg truth} must be a factor, not {.obj_type_friendly {truth}}.",
       .internal = TRUE
     )
   }
   if (length(levels(truth)) != 2L) {
+    # should be unreachable
     cli::cli_abort(
       "{.arg truth} must have two levels, not {length(levels(truth))}.",
       .internal = TRUE
     )
   }
   if (!is.numeric(estimate)) {
+    # should be unreachable
     cli::cli_abort(
       "{.arg estimate} must be numeric vector, not {.obj_type_friendly {estimate}}.",
       .internal = TRUE
     )
   }
   if (length(truth) != length(estimate)) {
+    # should be unreachable
     cli::cli_abort(
       "{.arg truth} ({length(truth)}) and
       {.arg estimate} ({length(estimate)}) must be the same length.",
       .internal = TRUE
     )
   }
   if (length(truth) != length(case_weights)) {
+    # should be unreachable
     cli::cli_abort(
       "{.arg truth} ({length(truth)}) and
       {.arg case_weights} ({length(case_weights)}) must be the same length.",

R/prob-helpers.R

@@ -11,6 +11,7 @@ auc <- function(x, y, na_rm = TRUE) {
   }
 
   if (is.unsorted(x, na.rm = TRUE, strictly = FALSE)) {
+    # should not be reachable
     cli::cli_abort(
       "{.arg x} must already be in weakly increasing order.",
       .internal = TRUE

R/prob-roc_auc.R

@@ -163,6 +163,7 @@ roc_auc_estimator_impl <- function(truth,
     roc_auc_binary(truth, estimate, event_level, case_weights)
   } else if (estimator == "hand_till") {
     if (!is.null(case_weights)) {
+      # should be unreachable
       cli::cli_abort(
         "{.arg case_weights} should be `NULL` at this point for hand-till.",
         .internal = TRUE

R/template.R

@@ -721,6 +721,7 @@ prob_estimate_convert <- function(estimate) {
   n_estimate <- ncol(estimate)
 
   if (n_estimate == 0L) {
+    # should be unreachable
     cli::cli_abort(
       "{.arg estimate} should have errored during tidy-selection.",
       .internal = TRUE
@@ -780,7 +781,8 @@ yardstick_eval_select <- function(expr,
 
   if (length(out) != 1L) {
     cli::cli_abort(
-      "{.arg arg} must select exactly 1 column from `data`, not {length(out)}.",
+      "{.arg {arg}} must select exactly 1 column from {.arg data}, 
+      not {length(out)}.",
       call = error_call
     )
   }

tests/testthat/_snaps/aaa-metrics.md

@@ -155,3 +155,11 @@
       ! Can't select columns that don't exist.
       x Column `weight` doesn't exist.
 
+# metric_set() errors on empty input
+
+    Code
+      metric_set()
+    Condition
+      Error in `metric_set()`:
+      ! At least 1 function must be supplied to `...`.
+

tests/testthat/_snaps/conf_mat.md

@@ -128,3 +128,11 @@
       ! Can't select columns that don't exist.
       x Column `not_predicted` doesn't exist.
 
+# conf_mat() error on 1-level factor truth
+
+    Code
+      conf_mat(table(1, 1))
+    Condition
+      Error in `conf_mat()`:
+      ! There must be at least 2 factors levels in the `data`.
+

tests/testthat/_snaps/estimator-helpers.md

@@ -0,0 +1,8 @@
+# get_weights() errors with wrong estimator
+
+    Code
+      get_weights(mtcars, "wrong")
+    Condition
+      Error in `get_weights()`:
+      ! `estimator` type "wrong" is unknown.
+

tests/testthat/_snaps/event-level.md

@@ -18,3 +18,11 @@
       i Please use the metric function argument `event_level` instead.
       i The global option is being ignored entirely.
 
+# validate_event_level() works
+
+    Code
+      recall(two_class_example, truth, predicted, event_level = "wrong")
+    Condition
+      Error in `recall()`:
+      ! `event_level` must be "first" or "second".
+

tests/testthat/_snaps/misc.md

@@ -152,3 +152,11 @@
       Error in `weighted_quantile()`:
       ! `probabilities` can't have missing values.
 
+# work with class_pred input
+
+    Code
+      accuracy_vec(fct_truth, cp_estimate)
+    Condition
+      Error in `as_factor_from_class_pred()`:
+      ! A <class_pred> input was detected, but the probably package isn't installed. Install probably to be able to convert <class_pred> to <factor>.
+

tests/testthat/_snaps/num-mase.md

@@ -38,3 +38,11 @@
       Error in `mase_vec()`:
       ! `mae_train` must be a number or `NULL`, not the string "x".
 
+# mase() errors if m is larger than number of observations
+
+    Code
+      mase(mtcars, mpg, disp, m = 100)
+    Condition
+      Error in `mase()`:
+      ! `truth` (32) must have a length greater than `m` (100) to compute the out-of-sample naive mean absolute error.
+

tests/testthat/_snaps/prob-gain_curve.md

@@ -6,6 +6,15 @@
       Error in `gain_curve()`:
       ! `truth` should be a factor, not a a number.
 
+# na_rm = FALSE errors if missing values are present
+
+    Code
+      gain_curve_vec(df$truth, df$Class1, na_rm = FALSE)
+    Condition
+      Error in `gain_curve_vec()`:
+      x Missing values were detected and `na_ra = FALSE`.
+      i Not able to perform calculations.
+
 # errors with class_pred input
 
     Code

tests/testthat/_snaps/prob-pr_curve.md

@@ -14,3 +14,12 @@
       Error in `pr_curve_vec()`:
       ! `truth` should not a <class_pred> object.
 
+# na_rm = FALSE errors if missing values are present
+
+    Code
+      pr_curve_vec(df$truth, df$Class1, na_rm = FALSE)
+    Condition
+      Error in `pr_curve_vec()`:
+      x Missing values were detected and `na_ra = FALSE`.
+      i Not able to perform calculations.
+

tests/testthat/_snaps/template.md

@@ -1,3 +1,19 @@
+# errors are thrown truth or estimate selects more than 1 column
+
+    Code
+      rmse(mtcars, mpg, tidyselect::starts_with("d"))
+    Condition
+      Error in `rmse()`:
+      ! `estimate` must select exactly 1 column from `data`, not 2.
+
+---
+
+    Code
+      rmse(mtcars, tidyselect::starts_with("d"), mpg)
+    Condition
+      Error in `rmse()`:
+      ! `truth` must select exactly 1 column from `data`, not 2.
+
 # numeric_metric_summarizer()'s errors when wrong things are passes
 
     Code

tests/testthat/_snaps/validation.md

@@ -249,6 +249,14 @@
       Error:
       ! `estimate` should be a list, not a a double vector.
 
+---
+
+    Code
+      validate_surv_truth_list_estimate(lung_surv$surv_obj[1:5, ], lung_surv$.pred)
+    Condition
+      Error:
+      ! `truth` (5) and `estimate` (228) must be the same length.
+
 ---
 
     Code

tests/testthat/test-aaa-metrics.R

@@ -521,3 +521,10 @@ test_that("metric_tweak and metric_set plays nicely together (#351)", {
     ref
   )
 })
+
+test_that("metric_set() errors on empty input", {
+  expect_snapshot(
+    error = TRUE,
+    metric_set()
+  )
+})

tests/testthat/test-conf_mat.R

@@ -290,3 +290,10 @@ test_that("conf_mat()'s errors when wrong things are passes", {
     )
   )
 })
+
+test_that("conf_mat() error on 1-level factor truth", {
+  expect_snapshot(
+    error = TRUE,
+    conf_mat(table(1, 1))
+  )
+})

tests/testthat/test-estimator-helpers.R

@@ -0,0 +1,6 @@
+test_that("get_weights() errors with wrong estimator", {
+  expect_snapshot(
+    error = TRUE,
+    get_weights(mtcars, "wrong")
+  )
+})

tests/testthat/test-event-level.R

@@ -17,3 +17,11 @@ test_that("`yardstick_event_level()` ignores option - FALSE, with a warning", {
   expect_snapshot(out <- yardstick_event_level())
   expect_identical(out, "first")
 })
+
+test_that("validate_event_level() works", {
+  expect_snapshot(
+    error = TRUE,
+    recall(two_class_example, truth, predicted, event_level = "wrong")
+  )
+})
+

tests/testthat/test-misc.R

@@ -350,3 +350,28 @@ test_that("`probabilities` must be in [0, 1]", {
 test_that("`probabilities` can't be missing", {
   expect_snapshot(error = TRUE, weighted_quantile(1, 1, NA))
 })
+
+test_that("work with class_pred input", {
+  skip_if_not_installed("probably")
+
+  cp_truth <- probably::as_class_pred(two_class_example$truth, which = 1)
+  cp_estimate <- probably::as_class_pred(two_class_example$predicted, which = 2)
+
+  fct_truth <- two_class_example$truth
+  fct_truth[1] <- NA
+
+  fct_estimate <- two_class_example$predicted
+  fct_estimate[2] <- NA
+
+  local_mocked_bindings(
+    .package = "rlang",
+    detect_installed = function(pkg, ...) {
+      FALSE
+    }
+  )
+
+  expect_snapshot(
+    error = TRUE,
+    accuracy_vec(fct_truth, cp_estimate)
+  )
+})