tests/testthat/_snaps/add-functions.md

In gavinsimpson/gratia: Graceful 'ggplot'-Based Graphics and Other Functions for GAMs Fitted Using 'mgcv'

add_fitted_samples works

Code
  print(fs)
Output
  # A tibble: 600 x 13
         y    x0     x1    x2    x3     f    f0    f1    f2    f3  .row .draw
     <dbl> <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <int>
   1 10.1  0.786 0.709  0.119 0.975 10.1  1.25   4.13  4.73     0     1     1
   2 10.1  0.786 0.709  0.119 0.975 10.1  1.25   4.13  4.73     0     1     2
   3 13.5  0.252 0.0412 0.153 0.541  9.33 1.43   1.09  6.82     0     2     1
   4 13.5  0.252 0.0412 0.153 0.541  9.33 1.43   1.09  6.82     0     2     2
   5  6.61 0.699 0.245  0.110 0.975  7.38 1.62   1.63  4.13     0     3     1
   6  6.61 0.699 0.245  0.110 0.975  7.38 1.62   1.63  4.13     0     3     2
   7  7.09 0.184 0.160  0.681 0.861  5.58 1.10   1.38  3.11     0     4     1
   8  7.09 0.184 0.160  0.681 0.861  5.58 1.10   1.38  3.11     0     4     2
   9  7.88 0.960 0.0939 0.676 0.252  4.62 0.253  1.21  3.16     0     5     1
  10  7.88 0.960 0.0939 0.676 0.252  4.62 0.253  1.21  3.16     0     5     2
  # i 590 more rows
  # i 1 more variable: .fitted <dbl>

add_predicted_samples works

Code
  print(ps)
Output
  # A tibble: 600 x 13
         y    x0     x1    x2    x3     f    f0    f1    f2    f3  .row .draw
     <dbl> <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <int>
   1 10.1  0.786 0.709  0.119 0.975 10.1  1.25   4.13  4.73     0     1     1
   2 10.1  0.786 0.709  0.119 0.975 10.1  1.25   4.13  4.73     0     1     2
   3 13.5  0.252 0.0412 0.153 0.541  9.33 1.43   1.09  6.82     0     2     1
   4 13.5  0.252 0.0412 0.153 0.541  9.33 1.43   1.09  6.82     0     2     2
   5  6.61 0.699 0.245  0.110 0.975  7.38 1.62   1.63  4.13     0     3     1
   6  6.61 0.699 0.245  0.110 0.975  7.38 1.62   1.63  4.13     0     3     2
   7  7.09 0.184 0.160  0.681 0.861  5.58 1.10   1.38  3.11     0     4     1
   8  7.09 0.184 0.160  0.681 0.861  5.58 1.10   1.38  3.11     0     4     2
   9  7.88 0.960 0.0939 0.676 0.252  4.62 0.253  1.21  3.16     0     5     1
  10  7.88 0.960 0.0939 0.676 0.252  4.62 0.253  1.21  3.16     0     5     2
  # i 590 more rows
  # i 1 more variable: .response <dbl>

add_posterior_samples works

Code
  print(ps)
Output
  # A tibble: 600 x 13
         y    x0     x1    x2    x3     f    f0    f1    f2    f3  .row .draw
     <dbl> <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <int>
   1 10.1  0.786 0.709  0.119 0.975 10.1  1.25   4.13  4.73     0     1     1
   2 10.1  0.786 0.709  0.119 0.975 10.1  1.25   4.13  4.73     0     1     2
   3 13.5  0.252 0.0412 0.153 0.541  9.33 1.43   1.09  6.82     0     2     1
   4 13.5  0.252 0.0412 0.153 0.541  9.33 1.43   1.09  6.82     0     2     2
   5  6.61 0.699 0.245  0.110 0.975  7.38 1.62   1.63  4.13     0     3     1
   6  6.61 0.699 0.245  0.110 0.975  7.38 1.62   1.63  4.13     0     3     2
   7  7.09 0.184 0.160  0.681 0.861  5.58 1.10   1.38  3.11     0     4     1
   8  7.09 0.184 0.160  0.681 0.861  5.58 1.10   1.38  3.11     0     4     2
   9  7.88 0.960 0.0939 0.676 0.252  4.62 0.253  1.21  3.16     0     5     1
  10  7.88 0.960 0.0939 0.676 0.252  4.62 0.253  1.21  3.16     0     5     2
  # i 590 more rows
  # i 1 more variable: .response <dbl>

add_smooth_samples works

Code
  print(ss)
Output
  # A tibble: 2,400 x 15
         y    x0     x1    x2    x3     f    f0    f1    f2    f3  .row .smooth
     <dbl> <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <chr>  
   1  10.1 0.786 0.709  0.119 0.975 10.1   1.25  4.13  4.73     0     1 s(x0)  
   2  10.1 0.786 0.709  0.119 0.975 10.1   1.25  4.13  4.73     0     1 s(x0)  
   3  10.1 0.786 0.709  0.119 0.975 10.1   1.25  4.13  4.73     0     1 s(x1)  
   4  10.1 0.786 0.709  0.119 0.975 10.1   1.25  4.13  4.73     0     1 s(x1)  
   5  10.1 0.786 0.709  0.119 0.975 10.1   1.25  4.13  4.73     0     1 s(x2)  
   6  10.1 0.786 0.709  0.119 0.975 10.1   1.25  4.13  4.73     0     1 s(x2)  
   7  10.1 0.786 0.709  0.119 0.975 10.1   1.25  4.13  4.73     0     1 s(x3)  
   8  10.1 0.786 0.709  0.119 0.975 10.1   1.25  4.13  4.73     0     1 s(x3)  
   9  13.5 0.252 0.0412 0.153 0.541  9.33  1.43  1.09  6.82     0     2 s(x0)  
  10  13.5 0.252 0.0412 0.153 0.541  9.33  1.43  1.09  6.82     0     2 s(x0)  
  # i 2,390 more rows
  # i 3 more variables: .term <chr>, .draw <int>, .value <dbl>

add_smooth_samples works for selected smooth

Code
  print(ss)
Output
  # A tibble: 600 x 15
         y    x0     x1    x2    x3     f    f0    f1    f2    f3  .row .smooth
     <dbl> <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <chr>  
   1 10.1  0.786 0.709  0.119 0.975 10.1  1.25   4.13  4.73     0     1 s(x2)  
   2 10.1  0.786 0.709  0.119 0.975 10.1  1.25   4.13  4.73     0     1 s(x2)  
   3 13.5  0.252 0.0412 0.153 0.541  9.33 1.43   1.09  6.82     0     2 s(x2)  
   4 13.5  0.252 0.0412 0.153 0.541  9.33 1.43   1.09  6.82     0     2 s(x2)  
   5  6.61 0.699 0.245  0.110 0.975  7.38 1.62   1.63  4.13     0     3 s(x2)  
   6  6.61 0.699 0.245  0.110 0.975  7.38 1.62   1.63  4.13     0     3 s(x2)  
   7  7.09 0.184 0.160  0.681 0.861  5.58 1.10   1.38  3.11     0     4 s(x2)  
   8  7.09 0.184 0.160  0.681 0.861  5.58 1.10   1.38  3.11     0     4 s(x2)  
   9  7.88 0.960 0.0939 0.676 0.252  4.62 0.253  1.21  3.16     0     5 s(x2)  
  10  7.88 0.960 0.0939 0.676 0.252  4.62 0.253  1.21  3.16     0     5 s(x2)  
  # i 590 more rows
  # i 3 more variables: .term <chr>, .draw <int>, .value <dbl>

gavinsimpson/gratia documentation built on May 4, 2024, 8:13 a.m.