Merge pull request #1 from Lionel-Re/fix-issues-330

Closes mjskay#330 and partal Fix issues  mjskay#332
Comment for our approach:
Purpose: In our approach, we modified the gather_draws() function to handle NA values more effectively after gathering the variables. This change ensures that rows with missing values in the .value column are removed, allowing us to work with clean data.

Implementation: To achieve this, we used lapply() within the gather_draws() function. This function dynamically applies the filter() operation to each of the gathered variables, ensuring that rows containing NA values are excluded from each variable. The filtering happens automatically for each variable based on its respective values.

Specific Code Change: We added the following lines of code to filter out NA values in the .value column after gathering the data:

tidied = tidied %>% 
  filter(!is.na(.value))  # Filter out rows where .value is NA
This ensures that only rows with valid (non-NA) .value entries are retained for further analysis.

Reasoning: By applying this filter dynamically for each gathered variable, our solution became more flexible and could handle datasets where some variables might contain missing data. This approach removes the need for manually dealing with missing values for each variable, ensuring that the resulting data is clean and ready for analysis.

Outcome: After applying this change, the data returned by gather_draws() no longer contains rows with missing values in the .value column, making the data ready for the next steps in the analysis process.

library(tidybayes)
library(dplyr)
library(tidyr)
library(waldo)
my_tidy_draws <-expand_grid(.chain = 1:2, .iteration = 1:5) |>
mutate(.draw = tidybayes:::draw_from_chain_and_iteration_(.chain, .iteration)) |>
mutate(aa[1] = rnorm(n()), aa[2] = rnorm(n()), ab[1] = rnorm(n())) |>
tidy_draws()
gather_draws_explicit <- my_tidy_draws |> gather_draws(aa[i], ab[i])
gather_draws_regex <- my_tidy_draws |> gather_draws(a.*[i], regex = T)

Result
compare(gather_draws_explicit, gather_draws_regex)
✔ No differences

Author: Lionel-Re

NAMESPACE

@@ -475,6 +475,7 @@ importFrom(tidyr,separate)
 importFrom(tidyr,spread)
 importFrom(tidyr,unite)
 importFrom(tidyr,unnest_legacy)
+importFrom(tidyr,unnest)
 importFrom(tidyselect,all_of)
 importFrom(tidyselect,any_of)
 importFrom(tidyselect,one_of)

R/gather_draws.R

@@ -11,34 +11,40 @@
 #' @importFrom rlang enquos
 #' @export
 gather_draws = function(
-  model,
-  ...,
-  regex = FALSE,
-  sep = "[, ]",
-  ndraws = NULL,
-  seed = NULL,
-  draw_indices = c(".chain", ".iteration", ".draw"),
-  n
+    model,
+    ...,
+    regex = FALSE,
+    sep = "[, ]",
+    ndraws = NULL,
+    seed = NULL,
+    draw_indices = c(".chain", ".iteration", ".draw"),
+    n
 ) {
   ndraws = .Deprecated_argument_alias(ndraws, n)
-
+  
   draws = sample_draws_from_model_(model, ndraws, seed)
-
+  
   draw_indices = intersect(draw_indices, names(draws))
   tidysamples = lapply(enquos(...), function(variable_spec) {
-    gather_variables(
+    tidied = gather_variables(
       spread_draws_(draws, variable_spec, regex = regex, sep = sep, draw_indices = draw_indices),
       exclude = c(draw_indices, ".row")
     )
+    
+    # Drop NAs for the specific variable columns after gathering
+    tidied = tidied %>%
+      filter(!is.na(.value))  # Filter out rows where .value is NA
+    
+    return(tidied)
   })
-
+  
   #get the groups from all the samples --- when we bind them together,
   #the grouping information is not always retained, so we'll have to recreate
   #the full set of groups from all the data frames after we bind them
   groups_ = tidysamples %>%
     lapply(group_vars) %>%
     reduce_(union)
-
+  
   bind_rows(tidysamples) %>%
     group_by_at(groups_)
-}
+}