1- # There's currently an issue comparing tibbles so we do it col-by-col
2- test_by_col <- function (a , b ) {
3- for (i in union(names(a ), names(b ))) {
4- expect_equal(a [[i ]], b [[i ]])
5- }
6- }
7-
8- # ------------------------------------------------------------------------------
9-
101test_that(' adding a new model' , {
112 set_new_model(" sponge" )
123
@@ -21,7 +12,7 @@ test_that('adding a new model', {
2112 tibble(engine = character (0 ), mode = character (0 ))
2213 )
2314
24- test_by_col (
15+ expect_equal (
2516 get_from_env(" sponge_pkgs" ),
2617 tibble(engine = character (0 ), pkg = list (), mode = character (0 ))
2718)
@@ -30,19 +21,19 @@ expect_equal(
3021 get_from_env(" sponge_modes" ), " unknown"
3122)
3223
33- test_by_col (
24+ expect_equal (
3425 get_from_env(" sponge_args" ),
3526 dplyr :: tibble(engine = character (0 ), parsnip = character (0 ),
3627 original = character (0 ), func = vector(" list" ),
3728 has_submodel = logical (0 ))
3829)
3930
40- test_by_col (
31+ expect_equal (
4132 get_from_env(" sponge_fit" ),
4233 tibble(engine = character (0 ), mode = character (0 ), value = vector(" list" ))
4334)
4435
45- test_by_col (
36+ expect_equal (
4637 get_from_env(" sponge_predict" ),
4738 tibble(engine = character (0 ), mode = character (0 ),
4839 type = character (0 ), value = vector(" list" ))
@@ -71,7 +62,7 @@ test_that('adding a new mode', {
7162test_that(' adding a new engine' , {
7263 set_model_engine(" sponge" , mode = " classification" , eng = " gum" )
7364
74- test_by_col (
65+ expect_equal (
7566 get_from_env(" sponge" ),
7667 tibble(engine = " gum" , mode = " classification" )
7768 )
@@ -96,20 +87,20 @@ test_that('adding a new package', {
9687 expect_error(set_dependency(" sponge" , " gummies" , " trident" ))
9788 expect_error(set_dependency(" sponge" , " gum" , " trident" , mode = " regression" ))
9889
99- test_by_col (
90+ expect_equal (
10091 get_from_env(" sponge_pkgs" ),
10192 tibble(engine = " gum" , pkg = list (" trident" ), mode = " classification" )
10293 )
10394
10495 set_dependency(" sponge" , " gum" , " juicy-fruit" , mode = " classification" )
105- test_by_col (
96+ expect_equal (
10697 get_from_env(" sponge_pkgs" ),
10798 tibble(engine = " gum" ,
10899 pkg = list (c(" trident" , " juicy-fruit" )),
109100 mode = " classification" )
110101 )
111102
112- test_by_col (
103+ expect_equal (
113104 get_dependency(" sponge" ),
114105 tibble(engine = " gum" ,
115106 pkg = list (c(" trident" , " juicy-fruit" )),
@@ -142,7 +133,7 @@ test_that('adding a new argument', {
142133 args <- get_from_env(" sponge_args" )
143134 expect_equal(sum(args $ parsnip == " modeling" ), 1 )
144135
145- test_by_col (
136+ expect_equal (
146137 get_from_env(" sponge_args" ),
147138 tibble(engine = " gum" , parsnip = " modeling" , original = " modelling" ,
148139 func = list (list (pkg = " foo" , fun = " bar" )),
@@ -267,7 +258,7 @@ test_that('adding a new fit', {
267258 )
268259
269260 fit_env_data <- get_from_env(" sponge_fit" )
270- test_by_col (
261+ expect_equal (
271262 fit_env_data [ 1 : 2 ],
272263 tibble(engine = " gum" , mode = " classification" )
273264 )
@@ -359,7 +350,7 @@ test_that('adding a new fit', {
359350 )
360351 )
361352
362- test_by_col (
353+ expect_equal (
363354 get_fit(" sponge" )[, 1 : 2 ],
364355 tibble(engine = " gum" , mode = " classification" )
365356 )
@@ -391,7 +382,7 @@ test_that('adding a new predict method', {
391382 )
392383
393384 pred_env_data <- get_from_env(" sponge_predict" )
394- test_by_col (
385+ expect_equal (
395386 pred_env_data [ 1 : 3 ],
396387 tibble(engine = " gum" , mode = " classification" , type = " class" )
397388 )
@@ -401,7 +392,7 @@ test_that('adding a new predict method', {
401392 class_vals
402393 )
403394
404- test_by_col (
395+ expect_equal (
405396 get_pred_type(" sponge" , " class" )[ 1 : 3 ],
406397 tibble(engine = " gum" , mode = " classification" , type = " class" )
407398 )
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