paste0(tempdir() -> file.path(tempdir()

Docma-TU · Sep 3, 2018 · a282d31 · a282d31
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,8 +1,8 @@
 Package: tosca
 Type: Package
 Title: Tools for Statistical Content Analysis
-Version: 0.1-0
-Date: 2018-08-31
+Version: 0.1-1
+Date: 2018-09-03
 Authors@R: c(person("Lars", "Koppers", email="koppers@statistik.tu-dortmund.de", role=c("aut", "cre"), comment = c(ORCID = "0000-0002-1642-9616")),
 	     person("Jonas", "Rieger", email="riegerjonas@gmx.de", role=c("aut")),
 	     person("Karin", "Boczek", email="karin.boczek@tu-dortmund.de", role=c("ctb"), comment = c(ORCID = "0000-0003-1516-4094")),

diff --git a/R/LDAgen.R b/R/LDAgen.R
@@ -47,7 +47,7 @@
 #' @export LDAgen
 LDAgen <- function(documents, K = 100L, vocab, num.iterations = 200L,
   burnin = 70L, alpha = NULL, eta = NULL, seed = NULL,
-  folder = paste0(tempdir(),"/lda-result"), num.words = 50L, LDA = TRUE, count = FALSE){
+  folder = file.path(tempdir(),"lda-result"), num.words = 50L, LDA = TRUE, count = FALSE){
     if(is.null(alpha)) alpha <- 1/K
     if(is.null(eta)) eta <- 1/K
     if(is.null(seed)) seed <- sample(1:10^8,1)

diff --git a/man/LDAgen.Rd b/man/LDAgen.Rd
diff --git a/tests/testthat/test_LDAgen.R b/tests/testthat/test_LDAgen.R
@@ -8,7 +8,7 @@ load("data/LDAdoc_compare.RData")
 
 csvTest <- read.csv("data/test-k3i20b70s24602alpha0.33eta0.33_orig.csv")
 counttest <- LDAgen(documents=LDAdoc, K = 3L, vocab=wordlist$words, num.iterations = 20L, burnin = 70L, seed=24602, num.words = 10L, LDA = TRUE, count=TRUE)
-csvTest2 <- read.csv(paste0(tempdir(),"/lda-result-k3i20b70s24602alpha0.33eta0.33.csv"))
+csvTest2 <- read.csv(file.path(tempdir(),"lda-result-k3i20b70s24602alpha0.33eta0.33.csv"))
 expect_equal(csvTest, csvTest2)
 
 expect_equal(lda1, LDAgen(documents=LDAdoc, K = 3L, vocab=wordlist$words, num.iterations = 20L, burnin = 70L, seed=24601, folder=tempdir(), num.words = 10L, LDA = TRUE))

diff --git a/tests/testthat/test_clusterTopics.R b/tests/testthat/test_clusterTopics.R
@@ -10,6 +10,6 @@ load("data/test-k3i20b70s24601alpha0.33eta0.33.RData")
 
 load("data/clusterTopics.RData")
 
-expect_equal(cT, clusterTopics(ldaresult=result, file=paste0(tempdir(),"/abc.pdf"), method = "average", width=30, height=15))
-expect_equal(cT2, clusterTopics(ldaresult=result, file=paste0(tempdir(),"/abc.pdf"), method = "single", width=30, height=15))
+expect_equal(cT, clusterTopics(ldaresult=result, file=file.path(tempdir(),"abc.pdf"), method = "average", width=30, height=15))
+expect_equal(cT2, clusterTopics(ldaresult=result, file=file.path(tempdir(),"abc.pdf"), method = "single", width=30, height=15))
 })
diff --git a/tests/testthat/test_plotHeat.R b/tests/testthat/test_plotHeat.R
@@ -22,16 +22,16 @@ test_that("plotHeat", {
 
   obj <- textmeta(text = text, meta = meta)
 
-  res1 <- plotHeat(object = obj, ldaresult = lda, ldaID = ldaID, file = paste0(tempdir(),"/abc.pdf"))
+  res1 <- plotHeat(object = obj, ldaresult = lda, ldaID = ldaID, file = file.path(tempdir(),"abc.pdf"))
   expect_equal(dim(res1), c(3, 4))
   res2 <- plotHeat(object = obj, ldaresult = lda, ldaID = ldaID, unit = "month",
-    file = paste0(tempdir(),"/abc.pdf"))
+    file = file.path(tempdir(),"abc.pdf"))
   expect_true(all(res2$date == seq(min(res2$date), max(res2$date), "month")))
-  res3 <- plotHeat(object = obj, ldaresult = lda, ldaID = ldaID, file = paste0(tempdir(),"/abc.pdf"),
+  res3 <- plotHeat(object = obj, ldaresult = lda, ldaID = ldaID, file = file.path(tempdir(),"abc.pdf"),
     norm = TRUE)
   expect_equal(dim(res3), c(3, 4))
   res4 <- plotHeat(object = textmeta(meta = obj$meta), ldaresult = lda,
-    ldaID = ldaID, file = paste0(tempdir(),"/abc.pdf"))
+    ldaID = ldaID, file = file.path(tempdir(),"abc.pdf"))
   expect_equal(dim(res4), c(3, 4))
   expect_true(all(res4$date == seq(min(res4$date), max(res4$date), "year")))
   expect_true(all(res3$date == seq(min(res3$date), max(res3$date), "year")))

diff --git a/tests/testthat/test_plotTopic.R b/tests/testthat/test_plotTopic.R
@@ -34,7 +34,7 @@ test_that("plotTopic", {
   res5 <- plotTopic(object = obj, ldaresult = lda, ldaID = ldaID, rel = TRUE)
   expect_true(all(res5$date == res1$date), all(colnames(res1) == colnames(res5)),
     all(res5[, -1] <= 1))
-  res6 <- plotTopic(object = obj, ldaresult = lda, ldaID = ldaID, file = paste0(tempdir(),"/abc.pdf"))
+  res6 <- plotTopic(object = obj, ldaresult = lda, ldaID = ldaID, file = file.path(tempdir(),"abc.pdf"))
   expect_equal(res1, res6)
   res7 <- plotTopic(object = obj, ldaresult = lda, ldaID = ldaID, curves = "smooth")
   expect_equal(res1, res7)

diff --git a/tests/testthat/test_plotTopicWord.R b/tests/testthat/test_plotTopicWord.R
@@ -40,7 +40,7 @@ test_that("plotTopicWord", {
   expect_true(all(res5$date == res1$date), all(colnames(res1) == colnames(res5)),
     all(res5[, -1] <= 1))
   res6 <- plotTopicWord(object = obj, docs = LDAdoc, ldaresult = lda,
-    ldaID = ldaID, file = paste0(tempdir(),"/abc.pdf"))
+    ldaID = ldaID, file = file.path(tempdir(),"abc.pdf"))
   expect_equal(res1, res6)
   res7 <- plotTopicWord(object = obj, docs = LDAdoc, ldaresult = lda,
     ldaID = ldaID, curves = "smooth")

diff --git a/tests/testthat/test_plotWordSub.R b/tests/testthat/test_plotWordSub.R
@@ -65,7 +65,7 @@ test_that("plotWordSub", {
   expect_true(all(res5$date == res1$date), all(colnames(res1) == colnames(res5)),
     all(res5[, -1] <= 1))
   res6 <- plotWordSub(object = obj, ldaresult = lda, ldaID = ldaID,
-    file = paste0(tempdir(),"/abc.pdf"), search = search)
+    file = file.path(tempdir(),"abc.pdf"), search = search)
   expect_equal(res1, res6)
   res7 <- plotWordSub(object = obj, ldaresult = lda, ldaID = ldaID,
     curves = "smooth", search = search)

diff --git a/tests/testthat/test_plotWordpt.R b/tests/testthat/test_plotWordpt.R
@@ -40,7 +40,7 @@ test_that("plotWordpt", {
   expect_true(all(res5$date == res1$date), all(colnames(res1) == colnames(res5)),
     all(res5[, -1] <= 1))
   res6 <- plotWordpt(object = obj, docs = LDAdoc, ldaresult = lda,
-    ldaID = ldaID, file = paste0(tempdir(),"/abc.pdf"))
+    ldaID = ldaID, file = file.path(tempdir(),"abc.pdf"))
   expect_equal(res1, res6)
   res7 <- plotWordpt(object = obj, docs = LDAdoc, ldaresult = lda,
     ldaID = ldaID, curves = "smooth")

diff --git a/vignettes/Vignette.Rmd b/vignettes/Vignette.Rmd
@@ -356,7 +356,7 @@ pagesLDA <- LDAprep(text = corpusFiltered$text, vocab = words5)
 After receiving the words which appear at least six times in the whole filtered corpus, the function \texttt{LDAprep} is applied to the example corpus with \texttt{vocab = words5}. The object \texttt{pagesLDA} will be committed to the function which performs a latent Dirichlet allocation.
 
 ## Performing LDA - \texttt{LDAgen}
-The function that has to be applied first to the corpus prepared by \texttt{LDAprep} is \texttt{LDAgen}. The function offers the options \texttt{K} (\texttt{integer}, default: \texttt{K = 100L}) to set the number of topics, \texttt{vocab} (\texttt{character} vector) for specifying the words which are considered in the preparation of the corpus and several more e.g. number of iterations for the burnin (default: \texttt{burnin = 70}) and the number of iterations for the Gibbs sampler (default: \texttt{num.iterations = 200}). The result is saved in a \texttt{R} workspace, the first part of the results name can be specified by setting the option \texttt{folder} (default: \texttt{folder = paste0(tempdir(),"/lda-result")}). If you want to save your data permanent, you have to change the path in an non temporary one.
+The function that has to be applied first to the corpus prepared by \texttt{LDAprep} is \texttt{LDAgen}. The function offers the options \texttt{K} (\texttt{integer}, default: \texttt{K = 100L}) to set the number of topics, \texttt{vocab} (\texttt{character} vector) for specifying the words which are considered in the preparation of the corpus and several more e.g. number of iterations for the burnin (default: \texttt{burnin = 70}) and the number of iterations for the Gibbs sampler (default: \texttt{num.iterations = 200}). The result is saved in a \texttt{R} workspace, the first part of the results name can be specified by setting the option \texttt{folder} (default: \texttt{folder = file.path(tempdir(),"lda-result")}). If you want to save your data permanent, you have to change the path in an non temporary one.
 
 In the concrete example corpus the manipulated corpus \texttt{pagesLDA} is used for \texttt{documents}, the topic number is set to \texttt{K = 10} and for reproducibility a seed is set to \texttt{seed = 123}. The filename consists of the \texttt{folder} argument followed by the options of \texttt{K}, \texttt{num.iterations}, \texttt{burnin} and the \texttt{seed} of the LDA. The hyperparameter \texttt{alpha} and \texttt{eta} are set to $1/K$ by default.
 ```{r, eval = TRUE, include = FALSE}
@@ -366,7 +366,7 @@ load("lda-result-k10i200b70s123alpha0.1eta0.1.RData")
 
 ```{r, eval = FALSE}
 result <- LDAgen(documents = pagesLDA, K = 10L, vocab = words5, seed = 123)
-load(paste0(tempdir(),"/lda-result-k10i200b70s123alpha0.1eta0.1.RData"))
+load(file.path(tempdir(),"lda-result-k10i200b70s123alpha0.1eta0.1.RData"))
 ```
 
 For validation of the LDA result and further analysis, the result is loaded back to the workspace.