stupid git didn't catch all my diff on last commit

.travis.yml

@@ -4,11 +4,11 @@ warnings_are_errors: TRUE
 
 before_install:
 - sudo apt-get install libgmp3-dev
-- export RGL_USE_NULL=TRUE 
+- export RGL_USE_NULL=TRUE
 
 script:
 - R CMD build .
 - travis_wait 45 R CMD check *tar.gz --as-cran
-  
+
 after_success:
   -  travis_wait 45 Rscript -e 'covr::codecov()'

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: TreEvo
 Type: Package
 Title: Using ABC to Understand Trait Evolution
-Version: 0.4.6
-Date: 2018-01-17
+Version: 0.5.0
+Date: 2018-01-14
 Authors@R: c(person("Brian", "O'Meara", role=c("aut"), email="[email protected]"),
     person("Barb", "Banbury", role=c("aut")),
     person("David","Bapst", role=c("aut", "cre"), email="[email protected]"))
@@ -29,7 +29,7 @@ Suggests:
     doMC,
     doParallel,
     gpclib,
-    rgl, 
+    rgl,
     testthat,
     paleotree,
     knitr,

README.md

@@ -1,7 +1,7 @@
 ## TreEvo
 # R Package for Estimating Trait Evolution Parameter using Approximate Bayesian Computation.
 
-TreEvo (case-sensitive) is an R Package for doing phylogenetic comparative method analyses of trait evolution, with a flexible framework for users to define their own novel models of trait evolution, involving both 'intrinsic' and 'extrinsic' factors (respective to the evolving lineage). 
+TreEvo (case-sensitive) is an R Package for doing phylogenetic comparative method analyses of trait evolution, with a flexible framework for users to define their own novel models of trait evolution, involving both 'intrinsic' and 'extrinsic' factors (respective to the evolving lineage).
 
 Currently, TreEvo is adapted only for univariate, continuous traits.
 
@@ -17,7 +17,7 @@ You can install the latest stable development version using the R function insta
 
 More experimental, less stable versions can be found on other branches of this github repo.
 
-The current build status is indicated here: 
+The current build status is indicated here:
 	[![Build Status](https://travis-ci.org/bomeara/treevo.svg)](https://travis-ci.org/bomeara/treevo) [![codecov](https://codecov.io/gh/bomeara/treevo/branch/master/graph/badge.svg)](https://codecov.io/gh/bomeara/treevo)
 
 You can see a version of help created with  at http://bomeara.github.io/treevo/reference/index.html

tests/testthat/test_boxcoxTransformation.R

@@ -2,27 +2,27 @@ test_that("boxcoxTransformation works", {
   set.seed(1)
   simPhy <- rcoal(5)
   simPhy$edge.length <- simPhy$edge.length * 20
-  
+
   #expect_warning(
   simDataParallel <- parallelSimulateWithPriors(
     nrepSim = 2,
-    multicore = FALSE, 
-	coreLimit = 1, 
+    multicore = FALSE,
+	coreLimit = 1,
 	phy = simPhy,
-    intrinsicFn = brownianIntrinsic, 
+    intrinsicFn = brownianIntrinsic,
 	extrinsicFn = nullExtrinsic,
-    startingPriorsFns = "normal", 
-	startingPriorsValues = matrix(c(mean(simChar[,1]), sd(simChar[, 1]))), 
+    startingPriorsFns = "normal",
+	startingPriorsValues = matrix(c(mean(simChar[,1]), sd(simChar[, 1]))),
 	intrinsicPriorsFns = c("exponential"),
-    intrinsicPriorsValues = matrix(c(10, 10), nrow = 2, byrow = FALSE), 
+    intrinsicPriorsValues = matrix(c(10, 10), nrow = 2, byrow = FALSE),
 	extrinsicPriorsFns = c("fixed"),
-    extrinsicPriorsValues = matrix(c(0, 0), nrow = 2, byrow = FALSE), 
-	generation.time = 100000, 
+    extrinsicPriorsValues = matrix(c(0, 0), nrow = 2, byrow = FALSE),
+	generation.time = 100000,
 	checkpointFile = NULL,
-    checkpointFreq = 24, 
-	verbose = FALSE, 
+    checkpointFreq = 24,
+	verbose = FALSE,
 	freevector = NULL,
-    taxon.df = NULL 
+    taxon.df = NULL
 	#,niter.brown = 25, niter.lambda = 25,
     #niter.delta = 25, niter.OU = 25, niter.white = 25
 	)
@@ -34,7 +34,7 @@ test_that("boxcoxTransformation works", {
   boxTranMat <- boxcoxTransformationMatrix(summaryValuesMatrix = summaryValuesMat)
   #
   result<-boxcoxTransformation(
-	summaryValuesVector = summaryValuesMat[,1], 
+	summaryValuesVector = summaryValuesMat[,1],
 	boxcoxAddition = boxTranMat$boxcoxAddition,
     boxcoxLambda = boxTranMat$boxcoxLambda)
 })

tests/testthat/test_doRun.R

@@ -38,21 +38,21 @@ test_that("doRun_rej works", {
 	set.seed(1)
    expect_warning(
    resultsRej <- doRun_rej(
-	phy = simPhy, 
+	phy = simPhy,
 	traits = simChar,
-    intrinsicFn = brownianIntrinsic, 
+    intrinsicFn = brownianIntrinsic,
 	extrinsicFn = nullExtrinsic,
-    startingPriorsFns = "normal", 
-	startingPriorsValues = matrix(c(mean(simChar[,1]), sd(simChar[, 1]))), 
+    startingPriorsFns = "normal",
+	startingPriorsValues = matrix(c(mean(simChar[,1]), sd(simChar[, 1]))),
 	intrinsicPriorsFns = c("exponential"),
     intrinsicPriorsValues = matrix(c(10, 10), nrow = 2,byrow = FALSE),
 	extrinsicPriorsFns = c("fixed"),
-    extrinsicPriorsValues = matrix(c(0, 0), nrow = 2,byrow = FALSE), 
-	StartSims = 10, 
+    extrinsicPriorsValues = matrix(c(0, 0), nrow = 2,byrow = FALSE),
+	StartSims = 10,
 	generation.time=1000000,
 	jobName = "examplerun_rej",
-    abcTolerance = 0.05, 
-	multicore = FALSE, 
+    abcTolerance = 0.05,
+	multicore = FALSE,
 	coreLimit = 1)
 	)
 	expect_is(resultsRej, "list")

tests/testthat/test_doSimulation.R

@@ -2,13 +2,13 @@ test_that("doSimulation works", {
   set.seed(1)
   tree <- rcoal(5)
   tree$edge.length <- tree$edge.length * 20
-  
+
   char <- doSimulation(
-	phy = tree, 
+	phy = tree,
 	intrinsicFn = brownianIntrinsic,
-    extrinsicFn = nullExtrinsic, 
+    extrinsicFn = nullExtrinsic,
 	startingValues = c(10),
-    intrinsicValues = c(0.01), 
+    intrinsicValues = c(0.01),
 	extrinsicValues = c(0),
 	generation.time=1000000,
 	saveHistory = FALSE
@@ -17,11 +17,11 @@ test_that("doSimulation works", {
 	expect_equal(dim(char)[1], Ntip(tree))
 
   char <- doSimulation(
-	phy = tree, 
+	phy = tree,
 	intrinsicFn = boundaryMinIntrinsic,
     extrinsicFn = ExponentiallyDecayingPushExtrinsic,
-    startingValues = c(10), 
-	intrinsicValues = c(0.05,10, 0.01), 
+    startingValues = c(10),
+	intrinsicValues = c(0.05,10, 0.01),
 	extrinsicValues = c(0, 0.1, 0.25),
 	generation.time=1000000,
 	saveHistory = FALSE
@@ -37,28 +37,28 @@ test_that("doSimulationForPlotting works", {
   tree$edge.length <- tree$edge.length * 20
 
   char <- doSimulationForPlotting(
-	phy = tree, 
+	phy = tree,
 	intrinsicFn = brownianIntrinsic,
-    extrinsicFn = nullExtrinsic, 
+    extrinsicFn = nullExtrinsic,
 	startingValues = c(10),
-    intrinsicValues = c(0.01), 
+    intrinsicValues = c(0.01),
 	extrinsicValues = c(0),
 	generation.time=1000000,
-    plot = FALSE, 
+    plot = FALSE,
 	saveHistory = FALSE
 	)
 	expect_equal(class(char[,1]), "integer")
 	expect_equal(dim(char)[1], Ntip(tree))
 
   char <- doSimulationForPlotting(
-	phy = tree, 
+	phy = tree,
 	intrinsicFn = boundaryMinIntrinsic,
     extrinsicFn = ExponentiallyDecayingPushExtrinsic,
-    startingValues = c(10), 
-	intrinsicValues = c(0.05,10, 0.01), 
+    startingValues = c(10),
+	intrinsicValues = c(0.05,10, 0.01),
 	extrinsicValues = c(0, 0.1, 0.25),
 	generation.time=1000000,
-    plot = TRUE, 
+    plot = TRUE,
 	saveHistory = FALSE
 	)
 	expect_equal(class(char[,1]), "integer")
@@ -75,12 +75,12 @@ test_that("doSimulationWithPossibleExtinction works", {
   expect_warning(
   charDoSim <- doSimulationWithPossibleExtinction(
 	phy = tree,
-    intrinsicFn = brownianIntrinsic, 
+    intrinsicFn = brownianIntrinsic,
 	extrinsicFn = nullExtrinsic,
-    startingValues = c(10), 
+    startingValues = c(10),
 	intrinsicValues = c(0.01),
 	generation.time=1000000,
-    extrinsicValues = c(0), 
+    extrinsicValues = c(0),
 	saveHistory = FALSE
 	)
 	)

tests/testthat/test_methodsPLS.R

@@ -3,54 +3,54 @@ test_that("methodsPLS works", {
   set.seed(1)
   simPhy <- rcoal(5)
   simPhy$edge.length <- simPhy$edge.length * 20
-  
+
   nSimulations <- 6
-  
+
   #expect_warning(
   simDataParallel <- parallelSimulateWithPriors(
     nrepSim = nSimulations,
-    multicore = FALSE, 
-	coreLimit = 1, 
+    multicore = FALSE,
+	coreLimit = 1,
 	phy = simPhy,
-    intrinsicFn = brownianIntrinsic, 
+    intrinsicFn = brownianIntrinsic,
 	extrinsicFn = nullExtrinsic,
-    startingPriorsFns = "normal", 
+    startingPriorsFns = "normal",
 	startingPriorsValues = matrix(c(mean(simChar[,
-      1]), sd(simChar[, 1]))), 
+      1]), sd(simChar[, 1]))),
 	intrinsicPriorsFns = c("exponential"),
     intrinsicPriorsValues = matrix(c(10, 10), nrow = 2,
-      byrow = FALSE), 
+      byrow = FALSE),
 	extrinsicPriorsFns = c("fixed"),
     extrinsicPriorsValues = matrix(c(0, 0), nrow = 2,
-      byrow = FALSE), 
-	generation.time = 100000, 
+      byrow = FALSE),
+	generation.time = 100000,
 	checkpointFile = NULL,
-    checkpointFreq = 24, 
-	verbose = FALSE, 
+    checkpointFreq = 24,
+	verbose = FALSE,
 	freevector = NULL,
-    taxon.df = NULL 
-	#,niter.brown = 25, 
+    taxon.df = NULL
+	#,niter.brown = 25,
 	#niter.lambda = 25,
-    #niter.delta = 25, 
-	#niter.OU = 25, 
+    #niter.delta = 25,
+	#niter.OU = 25,
 	#niter.white = 25
 	)
 	#)
 
   nParFree <- sum(attr(simDataParallel, "freevector"))
   trueFreeValuesMat <- simDataParallel[, 1:nParFree]
   summaryValuesMat <- simDataParallel[, -1:-nParFree]
-  
+
   expect_warning(
   PLSmodel <- returnPLSModel(
 	trueFreeValuesMatrix = trueFreeValuesMat,
-    summaryValuesMatrix = summaryValuesMat, 
+    summaryValuesMatrix = summaryValuesMat,
 	validation = "CV",
-    scale = TRUE, 
-	variance.cutoff = 95, 
+    scale = TRUE,
+	variance.cutoff = 95,
 	segments = nSimulations)
    )
-  
+
   PLSTransform(
     summaryValuesMatrix = summaryValuesMat,
     pls.model = PLSmodel

tests/testthat/test_plotting.R

@@ -4,10 +4,10 @@ test_that("plotABC_3D works", {
     data(simRunExample)
     plotABC_3D(
 		particleDataFrame = results$particleDataFrame,
-		parameter = 7, 
-		show.particles = "none", 
+		parameter = 7,
+		show.particles = "none",
 		plot.parent = FALSE,
-		realParam = FALSE, 
+		realParam = FALSE,
 		realParamValues = NA)
   }
 })
@@ -17,7 +17,7 @@ test_that("plotPosteriors works", {
 	data(simRunExample)
 	plotPosteriors(
 		particleDataFrame = results$particleDataFrame,
-		priorsMat = results$PriorMatrix, 
+		priorsMat = results$PriorMatrix,
 		realParam = TRUE,
 		realParamValues = c(ancState, genRate)
 		)
@@ -28,19 +28,19 @@ test_that("plotPosteriors correctly gives an error", {
 	data(simRunExample)
 	expect_error(
 		plotPosteriors(
-			results$particleDataFrame, 
-			results$PriorMatrix) 
+			results$particleDataFrame,
+			results$PriorMatrix)
 		,NA)
 })
 
 test_that("plotPriorPost works", {
 	set.seed(1)
   data(simRunExample)
   plotPrior(priorFn = "exponential", priorVariables = c(10))
-  
+
   plotPrior(priorFn = "normal", priorVariables = c(1,
     2))
-  
+
   plotPrior(priorFn = "gamma", priorVariables = c(2,
     0.2), plotQuants = FALSE, plotLegend = FALSE)
   priorKernal <- getUnivariatePriorCurve(priorFn = "normal",