Merge branch 'issue-24' into develop

* issue-24:
  Updated NEWS.md (#24)
  Increment version number to 0.0.0.9030
  Added logml tests for #24
  Fixed calculation of distances
  Fixed calculation of logml
  Adjusted unit tests
  Fixed output
  Syntax fixes

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: rBAPS
 Title: Bayesian Analysis of Population Structure
-Version: 0.0.0.9029
+Version: 0.0.0.9030
 Date: 2020-11-09
 Authors@R:
     c(

NEWS.md

@@ -1,5 +1,7 @@
 # rBAPS (development version)
 
+* Fixed `greedyMix()` for BAPS and Genepop files.
+
 # rBAPS 0.0.0.9021
 
 * Added a `NEWS.md` file to track changes to the package.

R/greedyMix.R

@@ -80,7 +80,7 @@ greedyMix <- function(
   # Generating partition summary ===============================================
   ekat <- seq(1L, ninds * c[["rowsFromInd"]], c[["rowsFromInd"]])
   c[["rows"]] <- cbind(ekat, ekat + c[["rowsFromInd"]] - 1L)
-  logml_npops_partitionSummary <- indMixWrapper(c, npops, counts, sumcounts, max_iter, fixedK, verbose) # FIXME: not working for FASTA, GenePop
+  logml_npops_partitionSummary <- indMixWrapper(c, npops, counts, sumcounts, max_iter, fixedK, verbose) # FIXME: not working for FASTA
   logml <- logml_npops_partitionSummary[["logml"]]
   npops <- logml_npops_partitionSummary[["npops"]]
   partitionSummary <- logml_npops_partitionSummary[["partitionSummary"]]

R/kldiv2str.R

@@ -20,5 +20,5 @@ kldiv2str <- function(div, max_chars = 6L) {
     mjono[3] <- "."
     mjono[2] <- palautaYks(abs(div), suurinYks)
   }
-  return(mjono)
+  paste(mjono, collapse = "")
 }

R/laskeLoggis.R

@@ -2,8 +2,6 @@ laskeLoggis <- function(counts, sumcounts, adjprior) {
   npops <- size(counts, 3)
   replicated_adjprior <- array(adjprior, c(nrow(adjprior), ncol(adjprior), npops))
   sum1 <- sum(sum(sum(lgamma(counts + replicated_adjprior))))
-  sum3 <- sum(sum(lgamma(adjprior))) - sum(sum(lgamma(1 + sumcounts)))
-  logml2 <- sum1 - npops * sum3
-  loggis <- logml2
-  return(loggis)
+  sum2 <- npops * sum(sum(lgamma(adjprior))) + sum(sum(lgamma(1 + sumcounts)))
+  sum1 - sum2
 }

R/laskeMuutokset12345.R

@@ -423,7 +423,7 @@ greedyMix_muutokset <- R6Class(
       globals$SUMCOUNTS[i1, ] <- globals$SUMCOUNTS[i1, ] + diffInSumCounts
 
       if (i1 < npops) {
-        i2 <- c(1:(i1 - 1), (i1 + 1):npops)
+        i2 <- c(seq_len(i1 - 1), (i1 + 1):npops)
       } else {
         i2 <- 1:(i1 - 1)
       }
@@ -458,12 +458,12 @@ greedyMix_muutokset <- R6Class(
       muutokset <- zeros(npops2, npops)
 
       i1_logml <- globals$POP_LOGML[i1]
-      for (pop2 in 1:npops2) {
+      for (pop2 in seq_len(npops2)) {
         inds <- inds2[matlab2r::find(T2 == pop2)]
         ninds <- length(inds)
         if (ninds > 0) {
           rows <- list()
-          for (i in 1:ninds) {
+          for (i in seq_len(ninds)) {
             ind <- inds[i]
             lisa <- globalRows[ind, 1]:globalRows[ind, 2]
             rows <- c(rows, t(lisa))
@@ -480,7 +480,7 @@ greedyMix_muutokset <- R6Class(
           globals$SUMCOUNTS[i1, ] <- globals$SUMCOUNTS[i1, ] + diffInSumCounts
 
           if (i1 < npops) {
-            i2 <- c(1:(i1 - 1), (i1 + 1):npops)
+            i2 <- c(seq_len(i1 - 1), (i1 + 1):npops)
           } else {
             i2 <- 1:(i1 - 1)
           }

R/laskeOsaDist.R

@@ -11,7 +11,7 @@ laskeOsaDist <- function(inds2, dist, ninds) {
   ninds2 <- length(inds2)
   apu <- zeros(choose(ninds2, 2), 2)
   rivi <- 1
-  for (i in 1:(ninds2 - 1)) {
+  for (i in seq_len(ninds2 - 1)) {
     for (j in (i + 1):ninds2) {
       apu[rivi, 1] <- inds2[i]
       apu[rivi, 2] <- inds2[j]
@@ -20,6 +20,6 @@ laskeOsaDist <- function(inds2, dist, ninds) {
   }
   apu <- (apu[, 1] - 1) * ninds - apu[, 1] / 2 *
     (apu[, 1] - 1) + (apu[, 2] - apu[, 1])
-  dist2 <- dist(apu)
+  dist2 <- dist[apu]
   return(dist2)
 }

R/writeMixtureInfo.R

@@ -65,9 +65,9 @@ writeMixtureInfo <- function(
   }
 
   cluster_count <- length(unique(globals$PARTITION))
-  if (verbose) cat("Best Partition: ")
+  if (verbose) cat("\nBest Partition:\n")
   if (fid != -1) {
-    append(fid, c("Best Partition: ", "\n"))
+    append(fid, c("\nBest Partition:", "\n"))
   }
   for (m in 1:cluster_count) {
     indsInM <- matlab2r::find(globals$PARTITION == m)
@@ -116,7 +116,7 @@ writeMixtureInfo <- function(
       cat("\n")
       cat(
         "Changes in log(marginal likelihood)",
-        " if indvidual i is moved to group j:\n"
+        "if indvidual i is moved to group j:\n"
       )
     }
     if (fid != -1) {
@@ -163,24 +163,24 @@ writeMixtureInfo <- function(
       muutokset <- changesInLogml[, ind]
       if (names) {
         nimi <- as.character(popnames[ind])
-        rivi <- c(blanks(maxSize - length(nimi)), nimi, ":\n")
+        rivi <- c(blanks(maxSize - length(nimi)), nimi, ":")
       } else {
-        rivi <- c("\n", blanks(4 - floor(log10(ind))), ownNum2Str(ind), ":\n")
+        rivi <- c("\n", blanks(4 - floor(log10(ind))), ownNum2Str(ind), ":")
       }
       for (j in 1:npops) {
-        rivi <- c(rivi, logml2String(omaRound(muutokset[j]), ""))
+        rivi <- c(rivi, "  ", logml2String(omaRound(muutokset[j])))
       }
       if (verbose) cat(rivi, sep = "")
       if (fid != -1) {
         append(fid, rivi)
         append(fid, "\n")
       }
     }
-    if (verbose) cat("\n\nKL-divergence matrix in PHYLIP format: ")
+    if (verbose) cat("\n\nKL-divergence matrix in PHYLIP format:\n")
 
     dist_mat <- zeros(npops, npops)
     if (fid != -1) {
-      append(fid, "  KL-divergence matrix in PHYLIP format: ")
+      append(fid, "  KL-divergence matrix in PHYLIP format:\n")
     }
 
     globals$COUNTS <- globals$COUNTS[seq_len(nrow(adjprior)), seq_len(ncol(adjprior)), , drop = FALSE]
@@ -196,7 +196,10 @@ writeMixtureInfo <- function(
     prior[1, nollia] <- 1
     for (pop1 in 1:npops) {
       squeezed_COUNTS_prior <- squeeze(globals$COUNTS[, , pop1]) + prior
-      d[, , pop1] <- squeezed_COUNTS_prior / sum(squeezed_COUNTS_prior)
+      repmat_squeezed_COUNTS_prior <- matlab2r::repmat(
+        colSums(squeezed_COUNTS_prior), c(maxnoalle, 1L)
+      )
+      d[, , pop1] <- squeezed_COUNTS_prior / repmat_squeezed_COUNTS_prior
     }
     ekarivi <- as.character(npops)
     if (verbose) cat(ekarivi)
@@ -223,9 +226,9 @@ writeMixtureInfo <- function(
 
     dist_mat <- dist_mat + t(dist_mat) # make it symmetric
     for (pop1 in 1:npops) {
-      rivi <- c("\nCluster_", as.character(pop1), "\n")
+      rivi <- c("\nCluster_", as.character(pop1), " ")
       for (pop2 in 1:npops) {
-        rivi <- c(rivi, kldiv2str(dist_mat[pop1, pop2], 4L))
+        rivi <- c(rivi, kldiv2str(dist_mat[pop1, pop2]))
       }
       if (verbose) cat(rivi, sep = "")
       if (fid != -1) {

tests/testthat/test-greedyMix.R

@@ -65,13 +65,20 @@ test_that("greedyMix() fails successfully", {
 })
 
 test_that("greedyMix() works when it should", {
+  tol <- 1e-4
   baps_file <- file.path(path_inst, "BAPS_clustering_diploid.txt")
-  genepop_file <- file.path(path_inst, "GenePop.txt")
-  fasta_file <- file.path(path_inst, "FASTA_clustering_haploid.fasta")
   greedy_baps <- greedyMix(baps_file, "BAPS")
-  expect_error(greedy_genepop <- greedyMix(genepop_file, "GenePop")) # TEMP: fails
   expect_type(greedy_baps, "list")
   expect_length(greedy_baps, 10L)
+  expect_equal(greedy_baps[['logml']], -78.10151, tolerance = tol)
+
+  genepop_file <- file.path(path_inst, "GenePop.txt")
+  greedy_genepop <- greedyMix(genepop_file, "GenePop")
+  expect_type(greedy_genepop, "list")
+  expect_length(greedy_genepop, 10L)
+  expect_equal(greedy_genepop[['logml']], -10.76224, tolerance = tol)
+
+  fasta_file <- file.path(path_inst, "FASTA_clustering_haploid.fasta")
 })
 
 context("Linkage")