From 10dea9e8837fa051c39f0dbef2129ef60e96c6c8 Mon Sep 17 00:00:00 2001
From: philchalmers <rphilip.chalmers@gmail.com>
Date: Mon, 2 Dec 2024 11:59:20 -0500
Subject: [PATCH] make SimResults output consistent

---
 DESCRIPTION     |  2 +-
 NEWS.md         |  3 +++
 R/SimResults.R  | 17 +++++++++++++----
 man/SimSolve.Rd | 14 ++++++--------
 4 files changed, 23 insertions(+), 13 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index d76cead9..28e1ccb3 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: SimDesign
 Title: Structure for Organizing Monte Carlo Simulation Designs
-Version: 2.17.4
+Version: 2.17.5
 Authors@R: c(person("Phil", "Chalmers", email = "rphilip.chalmers@gmail.com", role = c("aut", "cre"),
                     comment = c(ORCID="0000-0001-5332-2810")),
              person("Matthew", "Sigal", role = c("ctb")),
diff --git a/NEWS.md b/NEWS.md
index c8494d21..6c484169 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -2,6 +2,9 @@
 
 ## Changes in SimDesign 2.18
 
+- `SimResults()` now gives the same output behavior when `store_results` or 
+  `save_results` are used (see issue #45)
+
 - Use of `SimSolve(..., wait.time)` now automatically sets the `maxiter` to 
   3000 to avoid early terminations
 
diff --git a/R/SimResults.R b/R/SimResults.R
index 93a461db..bbb34b24 100644
--- a/R/SimResults.R
+++ b/R/SimResults.R
@@ -86,11 +86,20 @@ SimResults <- function(obj, which, prefix = "results-row", wd = getwd()){
     file_nums <- gsub(paste0(prefix, '-'), '', file_nums)
     file_nums <- as.numeric(gsub('.rds', '', file_nums))
     files <- data.frame(file_nums, files, stringsAsFactors = FALSE)
-    ret <- vector('list', length(which))
+    stored_Results_list <- vector('list', length(which))
     for(i in seq_len(length(which))){
         pick <- which(files$file_num == which[i])
-        ret[[i]] <- readRDS(files$files[pick])
+        stored_Results_list[[i]] <- readRDS(files$files[pick])
     }
-    if(length(which) == 1L) ret <- ret[[1]]
-    ret
+    design <- SimExtract(obj, 'design')
+    if(is(stored_Results_list[[1L]]$results, 'data.frame') ||
+       is(stored_Results_list[[1L]]$results, 'matrix')){
+        for(i in seq_len(length(stored_Results_list)))
+            stored_Results_list[[i]] <- cbind(design[i,],
+                                              stored_Results_list[[i]]$results, row.names=NULL)
+        stored_Results_list <- dplyr::bind_rows(stored_Results_list)
+        stored_Results_list$ID <- NULL
+        stored_Results_list <- dplyr::as_tibble(stored_Results_list)
+    }
+    stored_Results_list
 }
diff --git a/man/SimSolve.Rd b/man/SimSolve.Rd
index 7dcb780b..c71d8274 100644
--- a/man/SimSolve.Rd
+++ b/man/SimSolve.Rd
@@ -370,19 +370,17 @@ pwr.t.test(d=.8, n=N[3])
 # Solutions involving more iterations will be more accurate,
 # and therefore it is recommended to run the ProBABLI root-solver as long
 # the analyst can tolerate if the most accurate estimates are desired.
-# Below executes the simulation for 5 minutes for each condition
+# Below executes the simulation for 2 minutes per condition
 
-solved_5min <- SimSolve(design=Design, b=.8, interval=c(10, 500),
+solved_2min <- SimSolve(design=Design[1, ], b=.8, interval=c(10, 500),
                 generate=Generate, analyse=Analyse, summarise=Summarise,
-                wait.time="5")
-solved_5min
-summary(solved_5min)
+                wait.time="2")
+solved_2min
+summary(solved_2min)
 
 # use estimated N results to see how close power was
-N <- solved_5min$N
+N <- solved_2min$N
 pwr.t.test(d=.2, n=N[1])
-pwr.t.test(d=.5, n=N[2])
-pwr.t.test(d=.8, n=N[3])
 
 
 #------------------------------------------------