Updating tests

.travis.yml

@@ -1,46 +1,62 @@
-# Sample .travis.yml for R projects from https://github.com/craigcitro/r-travis
-
-language: c
+language: r
+warnings_are_errors: false
+sudo: required
 
 env:
    global:
-     - WARNINGS_ARE_ERRORS=1
-     - R_BUILD_ARGS=" "
-     - R_CHECK_ARGS="--as-cran"
-     - BOOTSTRAP_LATEX="1"
+     - CRAN: http://cran.rstudio.com
+     - R_BUILD_ARGS="--no-build-vignettes --no-manual --no-examples"
+     - R_CHECK_ARGS="--no-build-vignettes --no-manuall --no-examples --as-cran"
    matrix:
      - NOT_CRAN="true"
      - NOT_CRAN="false"
 
 before_install:
   - cd pkg/caret
-  - curl -OL http://raw.github.com/craigcitro/r-travis/master/scripts/travis-tool.sh
-  - chmod 755 ./travis-tool.sh
-  - ./travis-tool.sh bootstrap
-
-install:
-  - ./travis-tool.sh install_deps
-  - sudo add-apt-repository -y ppa:texlive-backports/ppa
+  - sudo add-apt-repository ppa:texlive-backports/ppa -y
   - sudo apt-get -qq update
-  - ./travis-tool.sh aptget_install texlive-base
-  - ./travis-tool.sh aptget_install biblatex
-  - ./travis-tool.sh aptget_install texlive-latex-base
-  - ./travis-tool.sh aptget_install texlive-latex-recommended
-  - ./travis-tool.sh aptget_install texlive-latex-extra
-  - ./travis-tool.sh aptget_install texlive-fonts-recommended
-  - ./travis-tool.sh aptget_install texlive-fonts-extra
-  - ./travis-tool.sh aptget_install texlive-science
-  - ./travis-tool.sh github_package jimhester/covr
-
-script: ./travis-tool.sh run_tests
 
-on_failure:
-  - ./travis-tool.sh dump_logs
-
-after_success:
-  - Rscript -e 'library(covr);coveralls()'
+apt_packages:
+  - texlive-base
+  - biblatex
+  - texlive-latex-base
+  - texlive-latex-recommended
+  - texlive-latex-extra
+  - texlive-fonts-recommended
+  - texlive-fonts-extra
+  - texlive-science
+
+r_packages:
+  - arm
+  - glmnet
+  - rpart
+  - C50
+  - ipred
+  - plyr
+  - earth
+  - kknn
+
+r_binary_packages:
+  - arm
+  - glmnet
+  - rpart
+  - C50
+  - ipred
+  - plyr
+  - earth
+  - kknn
+
+r_github_packages:
+  - jimhester/covr
 
 notifications:
   email:
     on_success: change
     on_failure: change
+
+after_script:
+  - Rscript -e 'library(devtools);test()'
+  - dump_logs
+
+after_success:
+  - Rscript -e 'library(covr);coveralls()'

pkg/caret/DESCRIPTION

@@ -46,8 +46,8 @@ Suggests:
     RANN,
     spls,
     subselect,
-    pamr, 
-    superpc, 
+    pamr,
+    superpc,
     Cubist,
     testthat (>= 0.9.1)
 License: GPL (>= 2)

pkg/caret/NAMESPACE

@@ -69,7 +69,7 @@ export(anovaScores,
        gafs_spCrossover,
        gafs_raMutation,
        gafs,
-       gafs.default, 
+       gafs.default,
        gafsControl,
        gamFormula,
        gamFuncs,
@@ -122,7 +122,7 @@ export(anovaScores,
        nullModel,
        nullModel.default,
        oneSE,
-       panel.calibration,       
+       panel.calibration,
        panel.lift,
        panel.lift2,
        panel.needle,
@@ -179,16 +179,16 @@ export(anovaScores,
        rfeControl,
        rfeIter,
        rfFuncs,
-       rfGA, 
+       rfGA,
        rfSA,
        rfSBF,
        rfStats,
        RMSE,
        safs_initial,
-       safs_perturb, 
+       safs_perturb,
        safs_prob,
        safs,
-       safs.default, 
+       safs.default,
        safsControl,
        sbf,
        sbf.default,
@@ -308,7 +308,7 @@ S3method(varImp, nnet)
 S3method(varImp, glmnet)
 S3method(varImp, gam)
 S3method(varImp, gafs)
-S3method(varImp, safs) 
+S3method(varImp, safs)
 
 S3method(densityplot, train)
 S3method(histogram,   train)
@@ -346,7 +346,7 @@ S3method(plot,  prcomp.resamples)
 S3method(plot,  lift)
 S3method(plot,  calibration)
 S3method(plot,  gafs)
-S3method(plot,  safs) 
+S3method(plot,  safs)
 
 S3method(confusionMatrix,  train)
 S3method(confusionMatrix,  rfe)
@@ -387,7 +387,7 @@ S3method(print, lift)
 S3method(print, calibration)
 S3method(print, expoTrans)
 S3method(print, gafs)
-S3method(print, safs) 
+S3method(print, safs)
 
 S3method(predict, plsda)
 S3method(predict, splsda)
@@ -410,7 +410,7 @@ S3method(predict, dummyVars)
 S3method(predict, BoxCoxTrans)
 S3method(predict, expoTrans)
 S3method(predict, gafs)
-S3method(predict, safs) 
+S3method(predict, safs)
 
 S3method(summary, bagEarth)
 S3method(summary, bagFDA)
@@ -428,7 +428,7 @@ S3method(predictors, default)
 S3method(predictors, rfe)
 S3method(predictors, sbf)
 S3method(predictors, gafs)
-S3method(predictors, safs) 
+S3method(predictors, safs)
 
 S3method(confusionMatrix, table)
 
@@ -455,7 +455,7 @@ S3method(summary, diff.resamples)
 S3method(update, train)
 S3method(update, rfe)
 S3method(update, gafs)
-S3method(update, safs) 
+S3method(update, safs)
 
 S3method(fitted, train)
 S3method(residuals, train)
@@ -471,7 +471,7 @@ S3method(oob_pred, sbf)
 S3method(oob_pred, list)
 
 S3method(gafs, default)
-S3method(safs, default) 
+S3method(safs, default)
 
 S3method(trim, train)
 

pkg/caret/R/trim.R

@@ -6,14 +6,14 @@ trim.train <- function(object, ...) {
                 "perfNames", "maxmimize", "times")
   for(i in removals)
     if(i %in% names(object)) object[i] <- NULL
-  c_removals <- c('method', 'number', 'repeats', 'p', 'initialWindow', 
-                  'horizon', 'fixedWindow', 'verboseIter', 'returnData', 
-                  'returnResamp', 'savePredictions', 'summaryFunction', 
-                  'selectionFunction', 'index', 'indexOut', 'timingSamps', 
+  c_removals <- c('method', 'number', 'repeats', 'p', 'initialWindow',
+                  'horizon', 'fixedWindow', 'verboseIter', 'returnData',
+                  'returnResamp', 'savePredictions', 'summaryFunction',
+                  'selectionFunction', 'index', 'indexOut', 'timingSamps',
                   'trim', 'yLimits')
   for(i in c_removals)
-    if(i %in% names(object$control)) object$control[i] <- NULL  
+    if(i %in% names(object$control)) object$control[i] <- NULL
   if(!is.null(object$modelInfo$trim))
     object$finalModel <- object$modelInfo$trim(object$finalModel)
   object
-}
+}

pkg/caret/tests/testthat/test_confusionMatrix.R

@@ -4,15 +4,15 @@ set.seed(442)
 
 test_that("Confusion matrix works", {
   library(caret)
-  train <- twoClassSim(n = 1000, intercept = -8, linearVars = 3, 
+  train <- twoClassSim(n = 1000, intercept = -8, linearVars = 3,
                        noiseVars = 10, corrVars = 4, corrValue = 0.6)
-  
+
   ctrl <- trainControl(method = "cv", classProbs = TRUE)
-  
-  fullModel <- train(Class ~ ., data = train, 
-                     method = "knn", 
-                     preProc = c("center", "scale"), 
-                     tuneLength = 4, 
+
+  fullModel <- train(Class ~ ., data = train,
+                     method = "knn",
+                     preProc = c("center", "scale"),
+                     tuneLength = 4,
                      trControl = ctrl)
   dat <- train$Class
   ref <- predict(fullModel)
@@ -26,10 +26,10 @@ test_that("Confusion matrix works", {
   dat5 <- as.character(dat3)
   dat5[200] <- "Class4"
   dat5 <- factor(dat5, levels = c("Class1", "Class4"))
-  cm1 <- confusionMatrix(dat, ref)
-  cm2 <- confusionMatrix(dat2, ref2)
-  cm3 <- confusionMatrix(dat3, ref2)
-  cm4 <- confusionMatrix(dat4, ref2)
+  suppressWarnings(cm1 <- confusionMatrix(dat, ref))
+  suppressWarnings(cm2 <- confusionMatrix(dat2, ref2))
+  suppressWarnings(cm3 <- confusionMatrix(dat3, ref2))
+  suppressWarnings(cm4 <- confusionMatrix(dat4, ref2))
   expect_true(class(cm1) == "confusionMatrix")
   expect_true(class(cm2) == "confusionMatrix")
   expect_true(class(cm3) == "confusionMatrix")
@@ -42,4 +42,4 @@ test_that("Confusion matrix works", {
   expect_identical(cm4$overall, cm3$overall)
   expect_true(identical(cm1, cm2))
   expect_true(identical(cm3, cm4))
-})
+})

pkg/caret/tests/testthat/test_create_folds.R

@@ -0,0 +1,49 @@
+library(caret)
+context('Test Data Splitting Functions')
+
+test_that('createTimeSlices', {
+  set.seed(1)
+  y <- 1:10
+
+  s1 <- createTimeSlices(y, initialWindow=5, horizon=1, fixedWindow=TRUE)
+  expect_equal(length(s1$train), 5)
+  expect_equal(length(s1$test), 5)
+  expect_equal(s1$train$Training1, 1:5)
+  expect_equal(s1$train$Training2, 2:6)
+  expect_equal(s1$train$Training3, 3:7)
+  expect_equal(s1$train$Training4, 4:8)
+  expect_equal(s1$train$Training5, 5:9)
+  expect_equal(s1$test$Testing1, 6)
+  expect_equal(s1$test$Testing2, 7)
+  expect_equal(s1$test$Testing3, 8)
+  expect_equal(s1$test$Testing4, 9)
+  expect_equal(s1$test$Testing5, 10)
+
+  s2 <- createTimeSlices(y, initialWindow=5, horizon=1, fixedWindow=FALSE)
+  expect_equal(length(s2$train), 5)
+  expect_equal(length(s2$test), 5)
+  expect_equal(s2$train$Training1, 1:5)
+  expect_equal(s2$train$Training2, 1:6)
+  expect_equal(s2$train$Training3, 1:7)
+  expect_equal(s2$train$Training4, 1:8)
+  expect_equal(s2$train$Training5, 1:9)
+  expect_equal(s2$test$Testing1, 6)
+  expect_equal(s2$test$Testing2, 7)
+  expect_equal(s2$test$Testing3, 8)
+  expect_equal(s2$test$Testing4, 9)
+  expect_equal(s2$test$Testing5, 10)
+
+  s3 <- createTimeSlices(y, initialWindow=5, horizon=5, fixedWindow=TRUE)
+  expect_equal(length(s3$train), 1)
+  expect_equal(length(s3$test), 1)
+  expect_equal(s3$train$Training1, 1:5)
+  expect_equal(s3$test$Testing1, 6:10)
+
+  s4 <- createTimeSlices(y, initialWindow=5, horizon=5, fixedWindow=FALSE)
+  expect_equal(length(s3$train), 1)
+  expect_equal(length(s3$test), 1)
+  expect_equal(s3$train$Training1, 1:5)
+  expect_equal(s3$test$Testing1, 6:10)
+
+  expect_identical(s3, s4)
+})