Use progressr instead of dplyr for progress

Resolves #184
Ref #192

DESCRIPTION

@@ -34,7 +34,8 @@ Imports:
     R6,
     utils,
     vctrs (>= 0.2.2),
-    distributional
+    distributional,
+    progressr
 Suggests:
     covr,
     crayon,

R/model.R

@@ -69,6 +69,7 @@ Check that specified model(s) are model definitions.", nm[which(!is_mdl)[1]]))
   num_key <- n_keys(.data)
   num_mdl <- length(models)
   num_est <- num_mdl * num_key
+  p <- progressr::progressor(num_est)
 
   kv <- key_vars(.data)
   .data <- nest_keys(.data, "lst_data")
@@ -85,30 +86,29 @@ Check that specified model(s) are model definitions.", nm[which(!is_mdl)[1]]))
     }
   }
 
+  estimate_progress <- function(dt, mdl){
+    out <- estimate(dt, mdl)
+    p()
+    out
+  }
+
   if(is_attached("package:future")){
     require_package("future.apply")
     eval_models <- function(models, lst_data){
       out <- future.apply::future_mapply(
         rep(lst_data, length(models)),
         rep(models, each = length(lst_data)),
-        FUN = estimate,
+        FUN = estimate_progress,
         SIMPLIFY = FALSE,
         future.globals = FALSE
       )
       unname(split(out, rep(seq_len(num_mdl), each = num_key)))
     }
   }
   else{
-    pb <- if(num_est > 1) dplyr::progress_estimated(num_est, min_time = 5) else NULL
     eval_models <- function(models, lst_data){
       map(models, function(model){
-        map(lst_data, function(dt, mdl){
-          out <- estimate(dt, mdl)
-          if(!is.null(pb)){
-            pb$tick()$print()
-          }
-          out
-        }, model)
+        map(lst_data, estimate_progress, model)
       })
     }
   }