`ndraws` in `add_[epred|linpred|predicted]_draws()` does not work

[JohannesNE]

When I set ndraws in add_[epred|linpred|predicted]_draws() I still get all draws.

library(brms)
#> Loading required package: Rcpp
#> Loading 'brms' package (version 2.15.0). Useful instructions
#> can be found by typing help('brms'). A more detailed introduction
#> to the package is available through vignette('brms_overview').
#> 
#> Attaching package: 'brms'
#> The following object is masked from 'package:stats':
#> 
#>     ar
library(tidybayes)
#> 
#> Attaching package: 'tidybayes'
#> The following objects are masked from 'package:brms':
#> 
#>     dstudent_t, pstudent_t, qstudent_t, rstudent_t

m_mpg_am = brm(
  mpg ~ log(hp) * am, 
  data = mtcars, 
  family = lognormal
)
#> Compiling Stan program...

mtcars |>
  add_epred_draws(m_mpg_am, ndraws = 1)
#> # A tibble: 128,000 × 16
#> # Groups:   mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb, .row [32]
#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb  .row
#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
#>  1    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  2    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  3    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  4    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  5    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  6    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  7    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  8    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  9    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#> 10    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#> # … with 127,990 more rows, and 4 more variables: .chain <int>,
#> #   .iteration <int>, .draw <int>, .epred <dbl>

mtcars |>
  add_predicted_draws(m_mpg_am, ndraws = 1)
#> # A tibble: 128,000 × 16
#> # Groups:   mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb, .row [32]
#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb  .row
#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
#>  1    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  2    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  3    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  4    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  5    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  6    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  7    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  8    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  9    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#> 10    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#> # … with 127,990 more rows, and 4 more variables: .chain <int>,
#> #   .iteration <int>, .draw <int>, .prediction <dbl>

mtcars |>
  add_linpred_draws(m_mpg_am, ndraws = 1)
#> # A tibble: 128,000 × 16
#> # Groups:   mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb, .row [32]
#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb  .row
#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
#>  1    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  2    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  3    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  4    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  5    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  6    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  7    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  8    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#>  9    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#> 10    21     6   160   110   3.9  2.62  16.5     0     1     4     4     1
#> # … with 127,990 more rows, and 4 more variables: .chain <int>,
#> #   .iteration <int>, .draw <int>, .linpred <dbl>

sessionInfo()
#> R version 4.1.0 (2021-05-18)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Pop!_OS 21.10
#> 
#> Matrix products: default
#> BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/libmkl_rt.so
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_DK.UTF-8        LC_COLLATE=en_US.UTF-8    
#>  [5] LC_MONETARY=en_DK.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=en_DK.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=en_DK.UTF-8 LC_IDENTIFICATION=C       
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] tidybayes_3.0.2.9000 brms_2.15.0          Rcpp_1.0.8          
#> 
#> loaded via a namespace (and not attached):
#>   [1] TH.data_1.0-10       minqa_1.2.4          colorspace_2.0-3    
#>   [4] ellipsis_0.3.2       ggridges_0.5.3       rsconnect_0.8.24    
#>   [7] estimability_1.3     markdown_1.1         base64enc_0.1-3     
#>  [10] fs_1.5.2             farver_2.1.0         rstan_2.21.3        
#>  [13] svUnit_1.0.6         DT_0.17              fansi_1.0.3         
#>  [16] mvtnorm_1.1-2        bridgesampling_1.1-2 codetools_0.2-18    
#>  [19] splines_4.1.0        knitr_1.37           shinythemes_1.2.0   
#>  [22] bayesplot_1.8.1      projpred_2.0.2       nloptr_1.2.2.2      
#>  [25] ggdist_3.1.0         shiny_1.7.1          compiler_4.1.0      
#>  [28] emmeans_1.6.2-1      backports_1.4.1      assertthat_0.2.1    
#>  [31] Matrix_1.3-4         fastmap_1.1.0        cli_3.2.0           
#>  [34] later_1.2.0          htmltools_0.5.2      prettyunits_1.1.1   
#>  [37] tools_4.1.0          igraph_1.2.6         coda_0.19-4         
#>  [40] gtable_0.3.0         glue_1.6.2           posterior_1.2.0     
#>  [43] reshape2_1.4.4       dplyr_1.0.8          styler_1.5.1.9000   
#>  [46] vctrs_0.4.0          nlme_3.1-152         crosstalk_1.1.1     
#>  [49] tensorA_0.36.2       xfun_0.30            stringr_1.4.0       
#>  [52] ps_1.6.0             lme4_1.1-27.1        mime_0.12           
#>  [55] miniUI_0.1.1.1       lifecycle_1.0.1      gtools_3.9.2        
#>  [58] MASS_7.3-54          zoo_1.8-9            scales_1.1.1        
#>  [61] colourpicker_1.1.0   promises_1.2.0.1     Brobdingnag_1.2-6   
#>  [64] sandwich_3.0-1       parallel_4.1.0       inline_0.3.19       
#>  [67] shinystan_2.5.0      gamm4_0.2-6          yaml_2.3.5          
#>  [70] gridExtra_2.3        ggplot2_3.3.5        loo_2.4.1           
#>  [73] StanHeaders_2.21.0-7 stringi_1.7.6        highr_0.9           
#>  [76] dygraphs_1.1.1.6     checkmate_2.0.0      boot_1.3-28         
#>  [79] pkgbuild_1.3.1       rlang_1.0.2          pkgconfig_2.0.3     
#>  [82] matrixStats_0.61.0   distributional_0.3.0 evaluate_0.15       
#>  [85] lattice_0.20-44      purrr_0.3.4          rstantools_2.1.1    
#>  [88] htmlwidgets_1.5.4    tidyselect_1.1.2     processx_3.5.2      
#>  [91] plyr_1.8.6           magrittr_2.0.3       R6_2.5.1            
#>  [94] generics_0.1.2       multcomp_1.4-17      DBI_1.1.1           
#>  [97] pillar_1.7.0         withr_2.5.0          mgcv_1.8-36         
#> [100] xts_0.12.1           survival_3.2-11      abind_1.4-5         
#> [103] tibble_3.1.6         crayon_1.5.1         arrayhelpers_1.1-0  
#> [106] utf8_1.2.2           rmarkdown_2.12.2     grid_4.1.0          
#> [109] callr_3.7.0          threejs_0.3.3        reprex_2.0.0        
#> [112] digest_0.6.29        xtable_1.8-4         tidyr_1.2.0         
#> [115] httpuv_1.6.2         RcppParallel_5.1.5   stats4_4.1.0        
#> [118] munsell_0.5.0        shinyjs_2.0.0

^{Created on 2022-04-07 by the reprex package (v2.0.0)}

[mjskay]

Strange... it is working fine for me using both the CRAN and github versions of tidybayes, and you seem to be on the latest version of tidybayes. However, one thing I notice is that you are using brms 2.15 instead of the latest (2.16). If you update brms does it work?

[JohannesNE]

Hmm. It did not help updating brms to 2.16. It seems to be a problem with ndraws in epred_draws and nsamples in rstantools::posterior_epred. If I run

mtcars |>
  add_epred_draws(m_mpg_am, nsamples = 1)

I only get one draw (32 rows). I guess nsamples is simply passed on through ....

[mjskay]

Hmm that's bizarre, as the nsamples argument was renamed to ndraws in 2.16 so I don't think nsamples should work on 2.16. Are you sure the update was successful? Did you restart your R session?

[JohannesNE]

I did not restart the session :disappointed: It works! Thank you for the help, and I apologize for the inconvenience.

[mjskay]

No problem! Glad to help.