Fix race condition on file write in diversity analysis

Will not override file if diversity indices or lower bound estimates
files are found to prevent race conditions when compared samples are
loading these files

R/diversityAnalysis.R

@@ -980,39 +980,45 @@
                      file.path(diversityOut, ind.fname))
 
     lapply(seq_along(estimateTypes), function(i) {
-        fileName <- names(estimateTypes)[[i]]
-        fileNameSansExt <- tools::file_path_sans_ext(fileName)
-        functor <- estimateTypes[[i]]
+        if (!file.exists(outputFiles[[i]])) {
+            fileName <- names(estimateTypes)[[i]]
+            fileNameSansExt <- tools::file_path_sans_ext(fileName)
+            functor <- estimateTypes[[i]]
+
+            files <-
+                .listFilesInOrder(path = diversityDirectories,
+                                  pattern = paste0(fileNameSansExt,
+                                                   "\\.tsv(\\.gz)?$"))
+
+            if (length(files) != length(sampleNames)) {
+                # if even one of the tsv file doesn't exist
+                # (which means we haven't generated it, or if it was deleted,
+                # we re-generate them)
+                message(paste("Calculating",
+                              sub("_", " ", fileNameSansExt, fixed = TRUE),
+                              "for", paste(sampleNames, collapse = ", ")))
+                df.ests <- lapply(dataframes, functor)
+            } else {
+                # the rare occasion when all individual samples have already been
+                # analyzed and the TSVs are all available, we only need to reload
+                # them rather than re-computing the values
+                message(paste("Loading precomputed",
+                              sub("_", " ", fileNameSansExt, fixed = TRUE),
+                              "from",
+                              paste(sampleNames, collapse = ", ")))
+                df.ests <- lapply(files, read.table, header = TRUE)
+            }
+            stopifnot(length(diversityDirectories) == length(sampleNames) &&
+                          length(df.ests) == length(sampleNames))
+
+            dfs <- do.call("rbind", Map(cbind, df.ests, sample = sampleNames))
+            write.table(dfs, file = outputFiles[[i]],
+                        sep = "\t", quote = FALSE,
+                        row.names = FALSE)
 
-        files <-
-            .listFilesInOrder(path = diversityDirectories,
-                              pattern = paste0(fileNameSansExt,
-                                               "\\.tsv(\\.gz)?$"))
-
-        if (length(files) != length(sampleNames)) {
-            # if even one of the tsv file doesn't exist
-            # (which means we haven't generated it, or if it was deleted,
-            # we re-generate them)
-            message(paste("Calculating",
-                          sub("_", " ", fileNameSansExt, fixed = TRUE),
-                          "for", paste(sampleNames, collapse = ", ")))
-            df.ests <- lapply(dataframes, functor)
         } else {
-            # the rare occasion when all individual samples have already been
-            # analyzed and the TSVs are all available, we only need to reload
-            # them rather than re-computing the values
-            message(paste("Loading precomputed",
-                          sub("_", " ", fileNameSansExt, fixed = TRUE),
-                          "from",
-                          paste(sampleNames, collapse = ", ")))
-            df.ests <- lapply(files, read.table, header = TRUE)
+            message(paste0("Found ", names(estimateTypes)[[i]],
+                           ", skipping ..."))
         }
-        stopifnot(length(diversityDirectories) == length(sampleNames) &&
-                      length(df.ests) == length(sampleNames))
-
-        dfs <- do.call("rbind", Map(cbind, df.ests, sample = sampleNames))
-        write.table(dfs, file = outputFiles[[i]],
-                    sep = "\t", quote = FALSE,
-                    row.names = FALSE)
     })
 }