describe_posterior fails with multivariate brms models that have weighted observations

[Koalha]

Describe the bug
describe_posterior fails with multivariate brms models that have weighted observations.

To Reproduce

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(brms)
#> Loading required package: Rcpp
#> Loading 'brms' package (version 2.22.0). 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(bayestestR)

## Simulate data
dd <- tibble(
  y_1 = sample(letters[1:3], size = 100, replace = TRUE),
  y_2 = sample(letters[1:3], size = 100, replace = TRUE))

## Make ordered
dd[1:2] <- dd |> lapply(\(x) x |> factor(ordered = TRUE, levels = letters[1:3]))

## Count unique observations
dd <- dd |> count(y_1,y_2)

## Ordered model
f1 <- bf(mvbind(y_1,y_2)|resp_weights(n) ~ 1, family = cumulative(link = "logit")) + set_rescor(FALSE)
m1 <- brm(f1, chains = 1, backend = "cmdstanr", data = dd,refresh = 0)
#> Start sampling
#> Running MCMC with 1 chain...
#> 
#> Chain 1 finished in 0.1 seconds.
#> Loading required package: rstan
#> Loading required package: StanHeaders
#> 
#> rstan version 2.32.6 (Stan version 2.32.2)
#> For execution on a local, multicore CPU with excess RAM we recommend calling
#> options(mc.cores = parallel::detectCores()).
#> To avoid recompilation of unchanged Stan programs, we recommend calling
#> rstan_options(auto_write = TRUE)
#> For within-chain threading using `reduce_sum()` or `map_rect()` Stan functions,
#> change `threads_per_chain` option:
#> rstan_options(threads_per_chain = 1)

## describe_posterior fails
m1 |> describe_posterior()
#> Warning in mapply(FUN = f, ..., SIMPLIFY = FALSE): longer argument not a
#> multiple of length of shorter
#> Warning in mapply(FUN = f, ..., SIMPLIFY = FALSE): longer argument not a
#> multiple of length of shorter
#> Error in fix.by(by.y, y): 'by' must specify a uniquely valid column

Expected behaviour
Expected behaviour is to report summaries of the posterior distrubution for these responses.

Specifiations (please complete the following information):

sessionInfo()
#> R version 4.4.2 (2024-10-31)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.2 LTS
#> 
#> Matrix products: default
#> BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.0 
#> LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=fi_FI.UTF-8        LC_COLLATE=en_US.UTF-8    
#>  [5] LC_MONETARY=fi_FI.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=fi_FI.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=fi_FI.UTF-8 LC_IDENTIFICATION=C       
#> 
#> time zone: Europe/Helsinki
#> tzcode source: system (glibc)
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] bayestestR_0.15.2 brms_2.22.0       Rcpp_1.0.14       dplyr_1.1.4      
#> 
#> loaded via a namespace (and not attached):
#>  [1] bridgesampling_1.1-2 tensorA_0.36.2.1     generics_0.1.3      
#>  [4] stringi_1.8.4        lattice_0.22-6       digest_0.6.37       
#>  [7] magrittr_2.0.3       evaluate_1.0.3       grid_4.4.2          
#> [10] mvtnorm_1.3-3        fastmap_1.2.0        Matrix_1.7-2        
#> [13] backports_1.5.0      Brobdingnag_1.2-9    scales_1.3.0        
#> [16] abind_1.4-8          cli_3.6.3            rlang_1.1.5         
#> [19] munsell_0.5.1        reprex_2.1.1.9000    withr_3.0.2         
#> [22] yaml_2.3.10          tools_4.4.2          parallel_4.4.2      
#> [25] rstantools_2.4.0     checkmate_2.3.2      coda_0.19-4.1       
#> [28] colorspace_2.1-1     ggplot2_3.5.1        vctrs_0.6.5         
#> [31] posterior_1.6.0      R6_2.5.1             matrixStats_1.5.0   
#> [34] lifecycle_1.0.4      stringr_1.5.1        fs_1.6.5            
#> [37] insight_1.0.2.9      pkgconfig_2.0.3      RcppParallel_5.1.10 
#> [40] pillar_1.10.1        gtable_0.3.6         loo_2.8.0           
#> [43] glue_1.8.0           xfun_0.50            tibble_3.2.1        
#> [46] tidyselect_1.2.1     rstudioapi_0.17.1    knitr_1.49          
#> [49] bayesplot_1.11.1     htmltools_0.5.8.1    nlme_3.1-167        
#> [52] rmarkdown_2.29       compiler_4.4.2       distributional_0.5.0