Return all tskit statistics as numerical vectors (not 1D arrays)

NEWS.md

@@ -16,6 +16,8 @@
 
 - Avoid the unnecessary `array` type of _tskit_ results returned via reticulate. Numeric vectors (columns of data frames with numerical results) obtained in this way are simple R numeric vector ([#c690334](https://github.com/bodkan/slendr/commit/c690334)).
 
+- One-way and multi-way statistics results are now returned as simple numerical vectors. Previously, results were returned as a type `array` despite "looking" as vectors (this is how values are returned to R from the reticulate-Python layer), which caused unnecessary annoyances and type-conversions on the R side of things and was not even intended ([#e1d178e](https://github.com/bodkan/slendr/commit/e1d178e)).
+
 # slendr 0.3.0
 
 -   SLiM 4.0 is now required for running simulations with the `slim()` engine. If you want to run _slendr_ simulations with SLiM (spatial or non-spatial), you will need to upgrade you SLiM installation. SLiM 3.7.1 version is no longer supported as the upcoming new _slendr_ spatial features will depend on SLiM 4.x and maintaining two functionally identical yet syntactically different back ends is not feasible (PR [#104](https://github.com/bodkan/slendr/pull/104)).

R/tree-sequences.R

@@ -1667,6 +1667,8 @@ multiway_stat <- function(ts, stat = c("fst", "divergence"),
   if (is.matrix(values))
     values <- split(values, col(values))
 
+  if (!is.list(values)) values <- as.numeric(values) # convert 1D arrays to simple vectors
+
   if (is.null(names(sample_sets)))
     set_names <- paste0("set_", seq_len(n_sets))
   else
@@ -1677,7 +1679,7 @@ multiway_stat <- function(ts, stat = c("fst", "divergence"),
     as.data.frame(t(matrix(set)), stringsAsFactors = FALSE)
   }) %>%
     dplyr::as_tibble() %>%
-    dplyr::mutate(stat = as.numeric(values))
+    dplyr::mutate(stat = values)
 
   result
 }
@@ -1786,6 +1788,8 @@ oneway_stat <- function(ts, stat, sample_sets, mode, windows, span_normalise = N
   if (is.matrix(values))
     values <- split(values, col(values))
 
+  if (!is.list(values)) values <- as.numeric(values) # convert 1D arrays to simple vectors
+
   if (all(sapply(sample_sets, length) == 1))
     set_names <- unlist(sample_sets)
   else if (is.null(names(sample_sets)))
@@ -1794,7 +1798,7 @@ oneway_stat <- function(ts, stat, sample_sets, mode, windows, span_normalise = N
     set_names <- names(sample_sets)
 
   result <- dplyr::tibble(set = set_names)
-  result[[stat]] <- as.numeric(values)
+  result[[stat]] <- values
   result
 }