Version 1.4.2 accepted on CRAN.

gaballench · Jun 4, 2024 · 53a1e7f · 53a1e7f
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,20 +1,22 @@
 Package: tbea
-Title: Tools for Pre- And Post-Processing in Bayesian Evolutionary Analyses
+Title: Pre- And Post-Processing in Bayesian Evolutionary Analyses
 Version: 1.4.2
 Authors@R: c(person("Gustavo A.", "Ballen", email = "gustavo.a.ballen@gmail.com", role = c("aut", "cre")), 
  person("Sandra", "Reinales", email = "spreinalesl@gmail.com", role = c("aut")))
-Description: Package for Bayesian inference in phylogenetics and evolution.
- It provides functions for prior specification in divergence time
- estimation using fossils as well as other kinds of data. The package
+Description: Functions are provided for prior specification in divergence time
+ estimation using fossils as well as other kinds of data. It
  provides tools for interacting with the input and output of Bayesian
- platforms in evolutionary biology such as BEAST2, MrBayes, RevBayes,
- or MCMCTree.
- The package implements a way to measure similarity between probability
- density functions in the context of comparisons between prior and
+ platforms in evolutionary biology such as 'BEAST2', 'MrBayes', 'RevBayes',
+ or 'MCMCTree'.
+ It Implements a simple measure similarity between probability
+ density functions for comparing prior and
  posterior Bayesian densities, as well as code for calculating the
- combination of distributions using conflation. Tools for estimating the
- origination time in collections of distributions using x-intercept and
- stratigraphic intervals are also available.
+ combination of distributions using conflation of Hill (2008). Functions for estimating the
+ origination time in collections of distributions using the x-intercept (e.g., Draper and Smith, 1998) and
+ stratigraphic intervals (Marshall 2010) are also available.
+ Hill, T. 2008. "Conflations of probability distributions". Transactions of the American Mathematical Society, 363:3351-3372. <doi:10.48550/arXiv.0808.1808>,
+ Draper, N. R. and Smith, H. 1998. "Applied Regression Analysis". 1--706. Wiley Interscience, New York. <DOI:10.1002/9781118625590>,
+ Marshall, C. R. 2010. "Using confidence intervals to quantify the uncertainty in the end-points of stratigraphic ranges". Quantitative Methods in Paleobiology, 291--316. <DOI:10.1017/S1089332600001911>.
 Depends: R (>= 3.5.0)
 Imports: ape, Rfit, boot, graphics, stats, utils, coda
 License: file LICENSE

diff --git a/R/conflate.R b/R/conflate.R
@@ -16,13 +16,7 @@
 #' conflated PDF on the sequence of x values determined by
 #' a number n of equidistant points between from and to.
 #' @examples
-#' \dontrun{
-#' conflate(c("density_fun(x, 'dnorm', mean=0, sd=1)",
-#' "density_fun(x, 'dnorm', mean=3, sd=1)"),
-#' from=-4, to=4, n=101, add=TRUE, plot=TRUE)
-#' curve(density_fun(x, 'dnorm', mean=0, sd=1), add=TRUE, col="red")
-#' curve(density_fun(x, 'dnorm', mean=3, sd=1), add=TRUE, col="blue")
-#' 
+#' \donttest{
 #' conflated_normals <- conflate(c("density_fun(x, 'dnorm', mean=0, sd=1)",
 #' "density_fun(x, 'dnorm', mean=3, sd=1)"),
 #' from=-4, to=4, n=101, plot=FALSE)
@@ -60,7 +54,7 @@ conflate <- function(pdfs, plot = TRUE, from, to, n, add = FALSE) {
 #' See the documentation for each individual distribution to call their parameters
 #' adequately. Argument names and values should be used.
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' c("density_fun(x, 'dnorm', mean=0, sd=1)",
 #' "density_fun(x, 'dnorm', mean=-1, sd=1)",
 #' "density_fun(x, 'dnorm', mean=1, sd=1)")
@@ -93,7 +87,7 @@ density_fun <- function(x, dist, ...) {
 #' with densities / int(densities) in an appropriate
 #' interval from--to
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' conflated <- .str_conflate("density_fun(x, 'dnorm', mean=0, sd=1)", "density_fun(x, 'dnorm', mean=3, sd=1)", from = -1, to = 1)
 #' }
 #' 
@@ -122,7 +116,7 @@ density_fun <- function(x, dist, ...) {
 #' conflation but it is also useful for calculating a series
 #' of x values of the conflated PDF from a sequence of x values
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' conflated <- .str_conflate("density_fun(x, 'dnorm', mean=0, sd=1)", "density_fun(x, 'dnorm', mean=3, sd=1)", from = -1, to = 1)
 #' }
 #' 

diff --git a/R/crossplot.R b/R/crossplot.R
@@ -49,10 +49,6 @@
 #' 
 #' @examples
 #' \dontrun{
-#' write.table(x=data.frame(par1=rnorm(1000), par2=rnorm(1000), par3=rnorm(1000),
-#' par4=rnorm(1000), par5=rnorm(1000)), file="log1.tsv", row.names=FALSE)
-#' write.table(x=data.frame(par1=rnorm(1000), par2=rnorm(1000), par3=rnorm(1000),
-#' par4=rnorm(1000, mean=5), par5=rnorm(1000)), file="log2.tsv", row.names=FALSE)
 #' crossplot(log1Path="log1.tsv", log2Path="log2.tsv", skip.char="#",
 #' pattern="par", cols=NULL, bar.lty=1, bar.lwd=1,
 #' identity.lty=2, identity.lwd=1,

diff --git a/R/measureSimil.R b/R/measureSimil.R
@@ -18,7 +18,7 @@
 #'
 #' @details Similarity is measured as the overlapping portion between two densities. It has a value between 0 and 1. The values of the vector rawData determine the behavior of the function and therefore attention must be paid to their consistence with the nature of arguments d1 and d2. Despite the function was designed in order to allow to quantify similarity between the posterior and the prior, this can be used to quantify any overlap between two given densities and for any other purpose.
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' # Set seed and colors to use in plots in the order: Prior, posterior, and intersection
 #' set.seed(1985)
 #' colors <- c("red", "blue", "lightgray")

diff --git a/R/stratCI.R b/R/stratCI.R
@@ -246,7 +246,7 @@ stratCI <- function(times, method, nparams, C, endpoint, confidence, quantile) {
  if(output >= 1) {
  return(output)
  } else {
- print("Impossible to calculate lower bound")
+ message("Impossible to calculate lower bound\n")
  }
 }
 

diff --git a/R/summaryBrlen.R b/R/summaryBrlen.R
@@ -13,16 +13,18 @@
 #' first enclosed in a list
 #' 
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' set.seed(1)
+#' library(ape)
 #' trl <- ape::rmtree(10, 4)
 #' tpf <- topoFreq(unroot(trl), output="trees")
 #' sumtrees <- summaryBrlen(tpf$trees, method = "median")
+#' oldpar <- par(no.readonly = TRUE)
 #' par(mfrow=c(1,3))
 #' plot(sumtrees[[1]], type="unrooted", show.node.label=FALSE, cex=1.5)
 #' plot(sumtrees[[2]], type="unrooted", show.node.label=FALSE, cex=1.5)
 #' plot(sumtrees[[3]], type="unrooted", show.node.label=FALSE, cex=1.5)
-#' par(mfrow=c(1,1))
+#' par(oldpar)
 #' }
 #' 
 #' @export

diff --git a/R/table2nexus.R b/R/table2nexus.R
@@ -28,7 +28,7 @@
 #' @examples
 #' \dontrun{
 #' # this will return the matrix to the console rather than to a file
-#' table2nexus(path="../prototipos/morpho.csv", datatype="standard", header=FALSE, sep=",")
+#' table2nexus(path="morpho.csv", datatype="standard", header=FALSE, sep=",")
 #' }
 #' @export
 #' @importFrom utils read.delim

diff --git a/R/tnt2newick.R b/R/tnt2newick.R
@@ -19,19 +19,9 @@
 #' @details This function has been tested for cases where only one tree is in the original tnt tree file. Please be careful with files containing multiple trees.
 #' 
 #' @examples
-#' # create a file with multiple trees tree in TNT format to convert to newick format
-#' writeLines(
-#' text = c(
-#' "tread 'some comment'", 
-#' "(Taxon_A ((Taxon_B Taxon_C)(Taxon_D Taxon_E)))*", 
-#' "(Taxon_A (Taxon_B (Taxon_C (Taxon_D Taxon_E))))*", 
-#' "(Taxon_A (Taxon_C (Taxon_B (Taxon_D Taxon_E))));", 
-#' "proc-;"
-#' ),
-#' con = "someTrees.tre"
-#' )
+#' \dontrun{
 #' tnt2newick(file = "someTrees.tre", return = TRUE)
-#' file.remove("someTrees.tre")
+#' }
 #' @export
 
 tnt2newick <- function(file, output = NULL, string = NULL, return = FALSE, subsetting = FALSE, name.sep = NULL){

diff --git a/R/topoFreq.R b/R/topoFreq.R
@@ -20,6 +20,7 @@
 #' @examples
 #' # tests
 #' set.seed(1)
+#' library(ape)
 #' trl <- ape::rmtree(10, 4)
 #' tpf <- topoFreq(ape::unroot(trl), output="trees")
 #'

diff --git a/R/xintercept.R b/R/xintercept.R
@@ -39,7 +39,7 @@
 #' ages <- ages[complete.cases(ages)] # remove NAs
 #' ages <- ages[which(ages < 10)] # remove outliers
 #' 
-#' \dontrun{
+#' \donttest{
 #' # Draper-Smith, OLS
 #' draperSmithNormalX0 <- xintercept(x = ages, method = "Draper-Smith", alpha = 0.05, robust = FALSE)
 #' # Draper-Smith, Robust fit

diff --git a/man/conflate.Rd b/man/conflate.Rd
diff --git a/man/crossplot.Rd b/man/crossplot.Rd
diff --git a/man/density_fun.Rd b/man/density_fun.Rd
diff --git a/man/measureSimil.Rd b/man/measureSimil.Rd
diff --git a/man/summaryBrlen.Rd b/man/summaryBrlen.Rd
diff --git a/man/table2nexus.Rd b/man/table2nexus.Rd
diff --git a/man/tbea-package.Rd b/man/tbea-package.Rd
diff --git a/man/tnt2newick.Rd b/man/tnt2newick.Rd
diff --git a/man/topoFreq.Rd b/man/topoFreq.Rd
diff --git a/man/xintercept.Rd b/man/xintercept.Rd
diff --git a/tests/testthat/test-tnt2newick.R b/tests/testthat/test-tnt2newick.R
@@ -1,4 +1,5 @@
-# create some input tree and their expected outputs
+# create some input tree and their expected outputs in the tempdir()
+setwd(tempdir())
 
 # create a file with multiple trees in TNT format to convert to newick format
 writeLines(
@@ -53,6 +54,6 @@ test_that("number of name separators got completely replaced using name.sep", {
  sum(sapply(gregexpr(pattern = "--", text = tnt2newick(file = "someTrees.tre", output = NULL, string = NULL, return = TRUE, subsetting = FALSE, name.sep = c("_", "--")), fixed=TRUE), function(i) sum(i > 0))))
 })
 
-# clean tesating files
+# clean testing files
 file.remove(dir(pattern = ".tre$"))
 file.remove(dir(pattern = ".newick$"))