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- # There's currently an issue comparing tibbles so we do it col-by-col
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- test_by_col <- function (a , b ) {
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- for (i in union(names(a ), names(b ))) {
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- expect_equal(a [[i ]], b [[i ]])
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- }
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- }
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-
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- # ------------------------------------------------------------------------------
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-
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test_that(' adding a new model' , {
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set_new_model(" sponge" )
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@@ -21,7 +12,7 @@ test_that('adding a new model', {
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tibble(engine = character (0 ), mode = character (0 ))
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)
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- test_by_col (
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+ expect_equal (
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get_from_env(" sponge_pkgs" ),
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tibble(engine = character (0 ), pkg = list (), mode = character (0 ))
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)
@@ -30,19 +21,19 @@ expect_equal(
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get_from_env(" sponge_modes" ), " unknown"
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)
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- test_by_col (
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+ expect_equal (
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get_from_env(" sponge_args" ),
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dplyr :: tibble(engine = character (0 ), parsnip = character (0 ),
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original = character (0 ), func = vector(" list" ),
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has_submodel = logical (0 ))
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)
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- test_by_col (
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+ expect_equal (
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get_from_env(" sponge_fit" ),
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tibble(engine = character (0 ), mode = character (0 ), value = vector(" list" ))
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)
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- test_by_col (
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+ expect_equal (
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get_from_env(" sponge_predict" ),
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tibble(engine = character (0 ), mode = character (0 ),
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type = character (0 ), value = vector(" list" ))
@@ -71,7 +62,7 @@ test_that('adding a new mode', {
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test_that(' adding a new engine' , {
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set_model_engine(" sponge" , mode = " classification" , eng = " gum" )
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- test_by_col (
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+ expect_equal (
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get_from_env(" sponge" ),
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tibble(engine = " gum" , mode = " classification" )
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)
@@ -96,20 +87,20 @@ test_that('adding a new package', {
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expect_error(set_dependency(" sponge" , " gummies" , " trident" ))
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expect_error(set_dependency(" sponge" , " gum" , " trident" , mode = " regression" ))
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- test_by_col (
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+ expect_equal (
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get_from_env(" sponge_pkgs" ),
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tibble(engine = " gum" , pkg = list (" trident" ), mode = " classification" )
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)
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set_dependency(" sponge" , " gum" , " juicy-fruit" , mode = " classification" )
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- test_by_col (
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+ expect_equal (
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get_from_env(" sponge_pkgs" ),
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tibble(engine = " gum" ,
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pkg = list (c(" trident" , " juicy-fruit" )),
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mode = " classification" )
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)
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- test_by_col (
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+ expect_equal (
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get_dependency(" sponge" ),
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tibble(engine = " gum" ,
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pkg = list (c(" trident" , " juicy-fruit" )),
@@ -142,7 +133,7 @@ test_that('adding a new argument', {
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args <- get_from_env(" sponge_args" )
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expect_equal(sum(args $ parsnip == " modeling" ), 1 )
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- test_by_col (
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+ expect_equal (
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get_from_env(" sponge_args" ),
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tibble(engine = " gum" , parsnip = " modeling" , original = " modelling" ,
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func = list (list (pkg = " foo" , fun = " bar" )),
@@ -267,7 +258,7 @@ test_that('adding a new fit', {
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)
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fit_env_data <- get_from_env(" sponge_fit" )
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- test_by_col (
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+ expect_equal (
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fit_env_data [ 1 : 2 ],
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tibble(engine = " gum" , mode = " classification" )
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)
@@ -359,7 +350,7 @@ test_that('adding a new fit', {
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)
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)
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- test_by_col (
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+ expect_equal (
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get_fit(" sponge" )[, 1 : 2 ],
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tibble(engine = " gum" , mode = " classification" )
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)
@@ -391,7 +382,7 @@ test_that('adding a new predict method', {
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)
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pred_env_data <- get_from_env(" sponge_predict" )
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- test_by_col (
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+ expect_equal (
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pred_env_data [ 1 : 3 ],
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tibble(engine = " gum" , mode = " classification" , type = " class" )
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)
@@ -401,7 +392,7 @@ test_that('adding a new predict method', {
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class_vals
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)
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- test_by_col (
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+ expect_equal (
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get_pred_type(" sponge" , " class" )[ 1 : 3 ],
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tibble(engine = " gum" , mode = " classification" , type = " class" )
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)
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