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Update snaps for new tibble
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@juliasilge
juliasilge committed Aug 2, 2022
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1 change: 1 addition & 0 deletions tests/testthat/_snaps/boot.md
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9 <split [54/23]> Bootstrap09
10 <split [54/22]> Bootstrap10
# ... with 15 more rows
# i Use `print(n = ...)` to see more rows

120 changes: 64 additions & 56 deletions tests/testthat/_snaps/make_groups.md
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analysis(rs$splits[[1]])
Output
# A tibble: 87 x 14
name height mass hair_color skin_color eye_color birth_year sex gender
<chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr>
1 Luke Sk~ 172 77 blond fair blue 19 male mascu~
2 C-3PO 167 75 <NA> gold yellow 112 none mascu~
3 Darth V~ 202 136 none white yellow 41.9 male mascu~
4 Leia Or~ 150 49 brown light brown 19 fema~ femin~
5 Leia Or~ 150 49 brown light brown 19 fema~ femin~
6 Leia Or~ 150 49 brown light brown 19 fema~ femin~
7 Beru Wh~ 165 75 brown light blue 47 fema~ femin~
8 Biggs D~ 183 84 black light brown 24 male mascu~
9 Biggs D~ 183 84 black light brown 24 male mascu~
10 Biggs D~ 183 84 black light brown 24 male mascu~
# ... with 77 more rows, and 5 more variables: homeworld <chr>, species <chr>,
# films <list>, vehicles <list>, starships <list>
name height mass hair_~1 skin_~2 eye_c~3 birth~4 sex gender homew~5
<chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr> <chr>
1 Luke Skywa~ 172 77 blond fair blue 19 male mascu~ Tatooi~
2 C-3PO 167 75 <NA> gold yellow 112 none mascu~ Tatooi~
3 Darth Vader 202 136 none white yellow 41.9 male mascu~ Tatooi~
4 Leia Organa 150 49 brown light brown 19 fema~ femin~ Aldera~
5 Leia Organa 150 49 brown light brown 19 fema~ femin~ Aldera~
6 Leia Organa 150 49 brown light brown 19 fema~ femin~ Aldera~
7 Beru White~ 165 75 brown light blue 47 fema~ femin~ Tatooi~
8 Biggs Dark~ 183 84 black light brown 24 male mascu~ Tatooi~
9 Biggs Dark~ 183 84 black light brown 24 male mascu~ Tatooi~
10 Biggs Dark~ 183 84 black light brown 24 male mascu~ Tatooi~
# ... with 77 more rows, 4 more variables: species <chr>, films <list>,
# vehicles <list>, starships <list>, and abbreviated variable names
# 1: hair_color, 2: skin_color, 3: eye_color, 4: birth_year, 5: homeworld
# i Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names

---

Code
analysis(rs$splits[[1]])
Output
# A tibble: 86 x 14
name height mass hair_color skin_color eye_color birth_year sex gender
<chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr>
1 Luke Sk~ 172 77 blond fair blue 19 male mascu~
2 C-3PO 167 75 <NA> gold yellow 112 none mascu~
3 R2-D2 96 32 <NA> white, bl~ red 33 none mascu~
4 Darth V~ 202 136 none white yellow 41.9 male mascu~
5 Leia Or~ 150 49 brown light brown 19 fema~ femin~
6 Owen La~ 178 120 brown, gr~ light blue 52 male mascu~
7 Beru Wh~ 165 75 brown light blue 47 fema~ femin~
8 R5-D4 97 32 <NA> white, red red NA none mascu~
9 Biggs D~ 183 84 black light brown 24 male mascu~
10 Obi-Wan~ 182 77 auburn, w~ fair blue-gray 57 male mascu~
# ... with 76 more rows, and 5 more variables: homeworld <chr>, species <chr>,
# films <list>, vehicles <list>, starships <list>
name height mass hair_~1 skin_~2 eye_c~3 birth~4 sex gender homew~5
<chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr> <chr>
1 Luke Skywa~ 172 77 blond fair blue 19 male mascu~ Tatooi~
2 C-3PO 167 75 <NA> gold yellow 112 none mascu~ Tatooi~
3 R2-D2 96 32 <NA> white,~ red 33 none mascu~ Naboo
4 Darth Vader 202 136 none white yellow 41.9 male mascu~ Tatooi~
5 Leia Organa 150 49 brown light brown 19 fema~ femin~ Aldera~
6 Owen Lars 178 120 brown,~ light blue 52 male mascu~ Tatooi~
7 Beru White~ 165 75 brown light blue 47 fema~ femin~ Tatooi~
8 R5-D4 97 32 <NA> white,~ red NA none mascu~ Tatooi~
9 Biggs Dark~ 183 84 black light brown 24 male mascu~ Tatooi~
10 Obi-Wan Ke~ 182 77 auburn~ fair blue-g~ 57 male mascu~ Stewjon
# ... with 76 more rows, 4 more variables: species <chr>, films <list>,
# vehicles <list>, starships <list>, and abbreviated variable names
# 1: hair_color, 2: skin_color, 3: eye_color, 4: birth_year, 5: homeworld
# i Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names

---

Code
analysis(rs$splits[[1]])
Output
# A tibble: 65 x 14
name height mass hair_color skin_color eye_color birth_year sex gender
<chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr>
1 C-3PO 167 75 <NA> gold yellow 112 none mascu~
2 R2-D2 96 32 <NA> white, bl~ red 33 none mascu~
3 Leia Or~ 150 49 brown light brown 19 fema~ femin~
4 Owen La~ 178 120 brown, gr~ light blue 52 male mascu~
5 Beru Wh~ 165 75 brown light blue 47 fema~ femin~
6 R5-D4 97 32 <NA> white, red red NA none mascu~
7 Biggs D~ 183 84 black light brown 24 male mascu~
8 Obi-Wan~ 182 77 auburn, w~ fair blue-gray 57 male mascu~
9 Anakin ~ 188 84 blond fair blue 41.9 male mascu~
10 Greedo 173 74 <NA> green black 44 male mascu~
# ... with 55 more rows, and 5 more variables: homeworld <chr>, species <chr>,
# films <list>, vehicles <list>, starships <list>
name height mass hair_~1 skin_~2 eye_c~3 birth~4 sex gender homew~5
<chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr> <chr>
1 C-3PO 167 75 <NA> gold yellow 112 none mascu~ Tatooi~
2 R2-D2 96 32 <NA> white,~ red 33 none mascu~ Naboo
3 Leia Organa 150 49 brown light brown 19 fema~ femin~ Aldera~
4 Owen Lars 178 120 brown,~ light blue 52 male mascu~ Tatooi~
5 Beru White~ 165 75 brown light blue 47 fema~ femin~ Tatooi~
6 R5-D4 97 32 <NA> white,~ red NA none mascu~ Tatooi~
7 Biggs Dark~ 183 84 black light brown 24 male mascu~ Tatooi~
8 Obi-Wan Ke~ 182 77 auburn~ fair blue-g~ 57 male mascu~ Stewjon
9 Anakin Sky~ 188 84 blond fair blue 41.9 male mascu~ Tatooi~
10 Greedo 173 74 <NA> green black 44 male mascu~ Rodia
# ... with 55 more rows, 4 more variables: species <chr>, films <list>,
# vehicles <list>, starships <list>, and abbreviated variable names
# 1: hair_color, 2: skin_color, 3: eye_color, 4: birth_year, 5: homeworld
# i Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names

---

Code
analysis(rs$splits[[1]])
Output
# A tibble: 65 x 14
name height mass hair_color skin_color eye_color birth_year sex gender
<chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr>
1 C-3PO 167 75 <NA> gold yellow 112 none mascu~
2 Darth V~ 202 136 none white yellow 41.9 male mascu~
3 Leia Or~ 150 49 brown light brown 19 fema~ femin~
4 Owen La~ 178 120 brown, gr~ light blue 52 male mascu~
5 Beru Wh~ 165 75 brown light blue 47 fema~ femin~
6 R5-D4 97 32 <NA> white, red red NA none mascu~
7 Biggs D~ 183 84 black light brown 24 male mascu~
8 Obi-Wan~ 182 77 auburn, w~ fair blue-gray 57 male mascu~
9 Wilhuff~ 180 NA auburn, g~ fair blue 64 male mascu~
10 Chewbac~ 228 112 brown unknown blue 200 male mascu~
# ... with 55 more rows, and 5 more variables: homeworld <chr>, species <chr>,
# films <list>, vehicles <list>, starships <list>
name height mass hair_~1 skin_~2 eye_c~3 birth~4 sex gender homew~5
<chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr> <chr>
1 C-3PO 167 75 <NA> gold yellow 112 none mascu~ Tatooi~
2 Darth Vader 202 136 none white yellow 41.9 male mascu~ Tatooi~
3 Leia Organa 150 49 brown light brown 19 fema~ femin~ Aldera~
4 Owen Lars 178 120 brown,~ light blue 52 male mascu~ Tatooi~
5 Beru White~ 165 75 brown light blue 47 fema~ femin~ Tatooi~
6 R5-D4 97 32 <NA> white,~ red NA none mascu~ Tatooi~
7 Biggs Dark~ 183 84 black light brown 24 male mascu~ Tatooi~
8 Obi-Wan Ke~ 182 77 auburn~ fair blue-g~ 57 male mascu~ Stewjon
9 Wilhuff Ta~ 180 NA auburn~ fair blue 64 male mascu~ Eriadu
10 Chewbacca 228 112 brown unknown blue 200 male mascu~ Kashyy~
# ... with 55 more rows, 4 more variables: species <chr>, films <list>,
# vehicles <list>, starships <list>, and abbreviated variable names
# 1: hair_color, 2: skin_color, 3: eye_color, 4: birth_year, 5: homeworld
# i Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names

3 changes: 3 additions & 0 deletions tests/testthat/_snaps/mc.md
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9 <split [40/14]> Resample09
10 <split [40/14]> Resample10
# ... with 15 more rows
# i Use `print(n = ...)` to see more rows

# grouping - bad args

Expand Down Expand Up @@ -48,6 +49,7 @@
9 <split [36/18]> Resample09
10 <split [36/18]> Resample10
# ... with 15 more rows
# i Use `print(n = ...)` to see more rows

# grouping - printing with ...

Expand All @@ -61,4 +63,5 @@
1 <split [36/18]> Resample01
2 <split [36/18]> Resample02
# ... with 23 more rows
# i Use `print(n = ...)` to see more rows

27 changes: 3 additions & 24 deletions tests/testthat/_snaps/misc.md
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Error in `reverse_splits()`:
! Permutations cannot have their splits reversed

---

Code
reverse_splits(1)
Condition
Error in `reverse_splits()`:
! `x` must be either an `rsplit` or an `rset` object

---

Code
reverse_splits(permutes)
Condition
Error in `reverse_splits()`:
! Permutations cannot have their splits reversed

---

Code
reverse_splits(permutes$splits[[1]])
Condition
Error in `reverse_splits()`:
! Permutations cannot have their splits reversed

# reshuffle_rset is working

Code
Expand All @@ -69,6 +45,7 @@
9 <split [1/1]> Slice09
10 <split [1/1]> Slice10
# ... with 39 more rows
# i Use `print(n = ...)` to see more rows

---

Expand Down Expand Up @@ -113,6 +90,7 @@
9 <split [1/1]> Slice09
10 <split [1/1]> Slice10
# ... with 39 more rows
# i Use `print(n = ...)` to see more rows

---

Expand All @@ -137,6 +115,7 @@
9 <split [13/1]> Slice09
10 <split [14/1]> Slice10
# ... with 35 more rows
# i Use `print(n = ...)` to see more rows

---

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1 change: 1 addition & 0 deletions tests/testthat/_snaps/permutations.md
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9 <split [32/0]> Permutations09
10 <split [32/0]> Permutations10
# ... with 15 more rows
# i Use `print(n = ...)` to see more rows

1 change: 1 addition & 0 deletions tests/testthat/_snaps/vfold.md
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1 <split [36/18]> Resample1
2 <split [36/18]> Resample2
# ... with 1 more row
# i Use `print(n = ...)` to see more rows

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