Using a dedicated environment for globals (#24)

Based on suggestion from <https://stackoverflow.com/a/12605694/1169233>.

R/globals.R

@@ -1,11 +1,10 @@
-COUNTS <- array(0, dim = c(100, 100, 100))
-SUMCOUNTS <- array(0, dim = c(100, 100))
-PARTITION <- array(1, dim = 100)
-POP_LOGML <- array(1, dim = 100)
-LOGDIFF <- array(1, dim = c(100, 100))
-# If handling globas break, try other ideas from
-# https://stackoverflow.com/a/65252740/1169233
+baps.globals <- new.env(parent = emptyenv())
 
-utils::globalVariables(
-  c("PARTITION", "COUNTS", "SUMCOUNTS", "LOGDIFF", "POP_LOGML", "GAMMA_LN")
-)
+assign("COUNTS", array(0, dim = c(0, 0, 0)), envir = baps.globals)
+assign("SUMCOUNTS", array(0, dim = c(0, 0)), envir = baps.globals)
+assign("PARTITION", array(1, dim = 0), envir = baps.globals)
+assign("POP_LOGML", array(1, dim = 0), envir = baps.globals)
+assign("LOGDIFF", array(1, dim = c(0, 0)), envir = baps.globals)
+# If handling globas break, try other ideas from
+# https://stackoverflow.com/a/65252740/1169233 and
+# https://stackoverflow.com/questions/12598242/

R/indMix.R

@@ -4,7 +4,6 @@ indMix <- function(c, npops, counts = NULL, sumcounts = NULL, max_iter = 100L, d
   # Input npops is not used if called by greedyMix or greedyPopMix.
 
   logml <- 1
-  clearGlobalVars()
 
   noalle <- c$noalle
   rows <- c$rows
@@ -94,16 +93,16 @@ indMix <- function(c, npops, counts = NULL, sumcounts = NULL, max_iter = 100L, d
     counts <- sumcounts_counts_logml$counts
     logml <- sumcounts_counts_logml$logml
 
-    PARTITION <- zeros(ninds, 1)
+    assign("PARTITION", zeros(ninds, 1), baps.globals)
     for (i in seq_len(ninds)) {
       apu <- rows[i]
-      PARTITION[i] <- initialPartition[apu[1]]
+      baps.globals$PARTITION[i] <- initialPartition[apu[1]]
     }
 
-    COUNTS <- counts
-    SUMCOUNTS <- sumcounts
-    POP_LOGML <- computePopulationLogml(seq_len(npops), adjprior, priorTerm)
-    LOGDIFF <- repmat(-Inf, c(ninds, npops))
+    assign("COUNTS", counts, baps.globals)
+    assign("SUMCOUNTS", sumcounts, baps.globals)
+    assign("POP_LOGML", computePopulationLogml(seq_len(npops), adjprior, priorTerm), baps.globals)
+    assign("LOGDIFF", matrix(-Inf, nrow = ninds, ncol = npops), baps.globals)
 
     # PARHAAN MIXTURE-PARTITION ETSIMINEN
     nRoundTypes <- 7
@@ -147,7 +146,7 @@ indMix <- function(c, npops, counts = NULL, sumcounts = NULL, max_iter = 100L, d
           muutosNyt <- 0
 
           for (ind in inds) {
-            i1 <- PARTITION[ind]
+            i1 <- baps.globals$PARTITION[ind]
             muutokset_diffInCounts <- greedyMix_muutokset$new()
             muutokset_diffInCounts <- muutokset_diffInCounts$laskeMuutokset(
               ind, rows, data, adjprior, priorTerm

R/laskeMuutokset12345.R

@@ -343,10 +343,10 @@ greedyMix_muutokset <- R6Class(
     #' @param priorTerm priorTerm
     laskeMuutokset = function(ind, globalRows, data, adjprior, priorTerm) {
       npops <- size(COUNTS, 3)
-      muutokset <- LOGDIFF[ind, ]
+      muutokset <- baps.globals$LOGDIFF[ind, ]
 
-      i1 <- PARTITION[ind]
-      i1_logml <- POP_LOGML[i1]
+      i1 <- baps.globals$PARTITION[ind]
+      i1_logml <- baps.globals$POP_LOGML[i1]
       muutokset[i1] <- 0
 
       if (is.null(dim(globalRows))) {
@@ -355,29 +355,30 @@ greedyMix_muutokset <- R6Class(
         rows <- globalRows[ind, 1]:globalRows[ind, 2]
       }
       diffInCounts <- computeDiffInCounts(
-        rows, size(COUNTS, 1), size(COUNTS, 2), data
       )
+        rows, size(baps.globals$COUNTS, 1), size(baps.globals$COUNTS, 2), data
       diffInSumCounts <- colSums(diffInCounts)
-      COUNTS[, , i1] <- COUNTS[, , i1] - diffInCounts
-      SUMCOUNTS[i1, ] <- SUMCOUNTS[i1, ] - diffInSumCounts
       new_i1_logml <- computePopulationLogml(i1, adjprior, priorTerm)
-      COUNTS[, , i1] <- COUNTS[, , i1] + diffInCounts
-      SUMCOUNTS[i1, ] <- SUMCOUNTS[i1, ] + diffInSumCounts
+      browser() # TEMP. Tip: browserText()
+      baps.globals$COUNTS[, , i1] <- baps.globals$COUNTS[, , i1] - diffInCounts
+      baps.globals$SUMCOUNTS[i1, ] <- baps.globals$SUMCOUNTS[i1, ] - diffInSumCounts
+      baps.globals$COUNTS[, , i1] <- baps.globals$COUNTS[, , i1] + diffInCounts
+      baps.globals$SUMCOUNTS[i1, ] <- baps.globals$SUMCOUNTS[i1, ] + diffInSumCounts
 
       i2 <- matlab2r::find(muutokset == -Inf) # Etsit��n populaatiot jotka muuttuneet viime kerran j�lkeen. (Searching for populations that have changed since the last time)
       i2 <- setdiff(i2, i1)
-      i2_logml <- POP_LOGML[i2]
+      i2_logml <- baps.globals$POP_LOGML[i2]
 
       ni2 <- length(i2)
 
-      COUNTS[, , i2] <- COUNTS[, , i2] + repmat(diffInCounts, c(1, 1, ni2))
-      SUMCOUNTS[i2, ] <- SUMCOUNTS[i2, ] + repmat(diffInSumCounts, c(ni2, 1))
       new_i2_logml <- computePopulationLogml(i2, adjprior, priorTerm)
-      COUNTS[, , i2] <- COUNTS[, , i2] - repmat(diffInCounts, c(1, 1, ni2))
-      SUMCOUNTS[i2, ] <- SUMCOUNTS[i2, ] - repmat(diffInSumCounts, c(ni2, 1))
+      baps.globals$COUNTS[, , i2] <- baps.globals$COUNTS[, , i2] + repmat(diffInCounts, c(1, 1, ni2))
+      baps.globals$SUMCOUNTS[i2, ] <- baps.globals$SUMCOUNTS[i2, ] + repmat(diffInSumCounts, c(ni2, 1))
+      baps.globals$COUNTS[, , i2] <- baps.globals$COUNTS[, , i2] - repmat(diffInCounts, c(1, 1, ni2))
+      baps.globals$SUMCOUNTS[i2, ] <- baps.globals$SUMCOUNTS[i2, ] - repmat(diffInSumCounts, c(ni2, 1))
 
       muutokset[i2] <- new_i1_logml - i1_logml + new_i2_logml - i2_logml
-      LOGDIFF[ind, ] <- muutokset
+      baps.globals$LOGDIFF[ind, ] <- muutokset
       return(list(muutokset = muutokset, diffInCounts = diffInCounts))
     },
     #' @param i1 i1