tests/testthat/_snaps/posterior-samples.md

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

smooth_samples works for a continuous by GAM

Code
  sm
Output
  # A tibble: 500 x 9
     .smooth .term    .type .by    .row .draw   .value       x2    x1
     <chr>   <chr>    <chr> <chr> <int> <int>    <dbl>    <dbl> <int>
   1 s(x2)   s(x2):x1 TPRS  x1        1     1  0.323   0.000206     1
   2 s(x2)   s(x2):x1 TPRS  x1        1     2 -0.955   0.000206     1
   3 s(x2)   s(x2):x1 TPRS  x1        1     3  0.154   0.000206     1
   4 s(x2)   s(x2):x1 TPRS  x1        1     4 -0.305   0.000206     1
   5 s(x2)   s(x2):x1 TPRS  x1        1     5  0.00806 0.000206     1
   6 s(x2)   s(x2):x1 TPRS  x1        2     1  0.497   0.0103       1
   7 s(x2)   s(x2):x1 TPRS  x1        2     2 -0.441   0.0103       1
   8 s(x2)   s(x2):x1 TPRS  x1        2     3  0.468   0.0103       1
   9 s(x2)   s(x2):x1 TPRS  x1        2     4  0.0415  0.0103       1
  10 s(x2)   s(x2):x1 TPRS  x1        2     5  0.302   0.0103       1
  # i 490 more rows

smooth_samples works for a simple GAM

Code
  sm
Output
  # A tibble: 500 x 8
     .smooth .term .type .by    .row .draw .value      x0
     <chr>   <chr> <chr> <chr> <int> <int>  <dbl>   <dbl>
   1 s(x0)   s(x0) TPRS  <NA>      1     1 -0.812 0.00162
   2 s(x0)   s(x0) TPRS  <NA>      1     2 -2.33  0.00162
   3 s(x0)   s(x0) TPRS  <NA>      1     3 -1.91  0.00162
   4 s(x0)   s(x0) TPRS  <NA>      1     4 -1.72  0.00162
   5 s(x0)   s(x0) TPRS  <NA>      1     5 -2.05  0.00162
   6 s(x0)   s(x0) TPRS  <NA>      2     1 -0.812 0.0117 
   7 s(x0)   s(x0) TPRS  <NA>      2     2 -2.21  0.0117 
   8 s(x0)   s(x0) TPRS  <NA>      2     3 -1.82  0.0117 
   9 s(x0)   s(x0) TPRS  <NA>      2     4 -1.64  0.0117 
  10 s(x0)   s(x0) TPRS  <NA>      2     5 -1.91  0.0117 
  # i 490 more rows

smooth_samples works for a simple GAM multi rng calls

Code
  sm
Output
  # A tibble: 500 x 8
     .smooth .term .type .by    .row .draw .value      x0
     <chr>   <chr> <chr> <chr> <int> <int>  <dbl>   <dbl>
   1 s(x0)   s(x0) TPRS  <NA>      1     1  -1.73 0.00162
   2 s(x0)   s(x0) TPRS  <NA>      1     2  -2.34 0.00162
   3 s(x0)   s(x0) TPRS  <NA>      1     3  -1.93 0.00162
   4 s(x0)   s(x0) TPRS  <NA>      1     4  -2.28 0.00162
   5 s(x0)   s(x0) TPRS  <NA>      1     5  -2.11 0.00162
   6 s(x0)   s(x0) TPRS  <NA>      2     1  -1.65 0.0117 
   7 s(x0)   s(x0) TPRS  <NA>      2     2  -2.21 0.0117 
   8 s(x0)   s(x0) TPRS  <NA>      2     3  -1.90 0.0117 
   9 s(x0)   s(x0) TPRS  <NA>      2     4  -2.20 0.0117 
  10 s(x0)   s(x0) TPRS  <NA>      2     5  -1.98 0.0117 
  # i 490 more rows

fitted_samples example output doesn't change

Code
  fs
Output
  # A tibble: 5,000 x 3
      .row .draw .fitted
     <int> <int>   <dbl>
   1     1     1    4.76
   2     2     1    5.70
   3     3     1    4.16
   4     4     1   11.0 
   5     5     1   11.1 
   6     6     1    4.47
   7     7     1    5.67
   8     8     1    6.86
   9     9     1    9.76
  10    10     1    7.39
  # i 4,990 more rows

smooth_samples example output doesn't change

Code
  samples
Output
  # A tibble: 1,000 x 8
     .smooth .term .type .by    .row .draw .value      x0
     <chr>   <chr> <chr> <chr> <int> <int>  <dbl>   <dbl>
   1 s(x0)   s(x0) TPRS  <NA>      1     1  -1.28 0.00131
   2 s(x0)   s(x0) TPRS  <NA>      1     2  -1.25 0.00131
   3 s(x0)   s(x0) TPRS  <NA>      1     3  -1.02 0.00131
   4 s(x0)   s(x0) TPRS  <NA>      1     4  -1.62 0.00131
   5 s(x0)   s(x0) TPRS  <NA>      1     5  -1.32 0.00131
   6 s(x0)   s(x0) TPRS  <NA>      2     1  -1.24 0.00633
   7 s(x0)   s(x0) TPRS  <NA>      2     2  -1.21 0.00633
   8 s(x0)   s(x0) TPRS  <NA>      2     3  -1.00 0.00633
   9 s(x0)   s(x0) TPRS  <NA>      2     4  -1.58 0.00633
  10 s(x0)   s(x0) TPRS  <NA>      2     5  -1.29 0.00633
  # i 990 more rows

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