Running 'testthat.R' [191s/185s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > library(testthat)
  > library(caretEnsemble)
  > 
  > test_check("caretEnsemble")
   ----------- FAILURE REPORT -------------- 
   --- failure: the condition has length > 1 ---
   --- srcref --- 
  : 
   --- package (from environment) --- 
  caretEnsemble
   --- call from context --- 
  predict.caretList(models)
   --- call from argument --- 
  if (class(preds) != "matrix" & class(preds) != "data.frame") {
      if (class(preds) == "character" | class(preds) == "factor") {
          preds <- as.character(preds)
      }
      preds <- as.matrix(t(preds))
  }
   --- R stacktrace ---
  where 1: predict.caretList(models)
  where 2: predict(models)
  where 3: eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
  where 4: withCallingHandlers(code, warning = function(condition) {
      out$push(condition)
      maybe_restart("muffleWarning")
  })
  where 5: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), 
      ...)
  where 6: quasi_capture(enquo(object), label, capture_warnings)
  where 7 at testthat/test-caretList.R#109: expect_warning(p1 <- predict(models))
  where 8: eval(code, test_env)
  where 9: eval(code, test_env)
  where 10: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 11: doTryCatch(return(expr), name, parentenv, handler)
  where 12: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 13: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 14: doTryCatch(return(expr), name, parentenv, handler)
  where 15: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 16: tryCatchList(expr, classes, parentenv, handlers)
  where 17: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 18: test_code(desc, code, env = parent.frame())
  where 19 at testthat/test-caretList.R#94: test_that("caretList predictions", {
      skip_if_not_installed("randomForest")
      skip_if_not_installed("nnet")
      skip_if_not_installed("plyr")
      expect_warning({
          models <- caretList(iris[, 1:2], iris[, 5], tuneLength = 1, 
              verbose = FALSE, methodList = "rf", tuneList = list(nnet = caretModelSpec(method = "nnet", 
                  trace = FALSE)), trControl = trainControl(method = "cv", 
                  number = 2, savePredictions = "final", classProbs = FALSE))
      })
      expect_warning(p1 <- predict(models))
      p2 <- predict(models, newdata = iris[100, c(1:2)])
      p3 <- predict(models, newdata = iris[110, c(1:2)])
      expect_is(p1, "matrix")
      expect_is(p1[, 1], "character")
      expect_is(p1[, 2], "character")
      expect_equal(names(models), colnames(p1))
      expect_is(p2, "matrix")
      expect_is(p2[, 1], "character")
      expect_is(p2[, 2], "character")
      expect_equal(names(models), colnames(p2))
      expect_is(p3, "matrix")
      expect_is(p3[, 1], "character")
      expect_is(p3[, 2], "character")
      expect_equal(names(models), colnames(p3))
      expect_warning({
          models <- caretList(iris[, 1:2], iris[, 5], tuneLength = 1, 
              verbose = FALSE, methodList = "rf", tuneList = list(nnet = caretModelSpec(method = "nnet", 
                  trace = FALSE)), trControl = trainControl(method = "cv", 
                  number = 2, savePredictions = "final", classProbs = TRUE))
      })
      expect_warning(p2 <- predict(models))
      p3 <- predict(models, newdata = iris[100, c(1:2)])
      expect_is(p2, "matrix")
      expect_is(p2[, 1], "numeric")
      expect_is(p2[, 2], "numeric")
      expect_is(p3, "matrix")
      expect_is(p3[, 1], "numeric")
      expect_is(p3[, 2], "numeric")
      expect_equal(names(models), colnames(p3))
      models[[1]]$modelType <- "Bogus"
      expect_error(expect_warning(predict(models)))
  })
  where 20: eval(code, test_env)
  where 21: eval(code, test_env)
  where 22: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 23: doTryCatch(return(expr), name, parentenv, handler)
  where 24: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 25: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 26: doTryCatch(return(expr), name, parentenv, handler)
  where 27: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 28: tryCatchList(expr, classes, parentenv, handlers)
  where 29: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 30: test_code(NULL, exprs, env)
  where 31: source_file(path, new.env(parent = env), chdir = TRUE, wrap = wrap)
  where 32: force(code)
  where 33: doWithOneRestart(return(expr), restart)
  where 34: withOneRestart(expr, restarts[[1L]])
  where 35: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 36: with_reporter(reporter = reporter, start_end_reporter = start_end_reporter, 
      {
          reporter$start_file(basename(path))
          lister$start_file(basename(path))
          source_file(path, new.env(parent = env), chdir = TRUE, 
              wrap = wrap)
          reporter$.end_context()
          reporter$end_file()
      })
  where 37: FUN(X[[i]], ...)
  where 38: lapply(paths, test_file, env = env, reporter = current_reporter, 
      start_end_reporter = FALSE, load_helpers = FALSE, wrap = wrap)
  where 39: force(code)
  where 40: doWithOneRestart(return(expr), restart)
  where 41: withOneRestart(expr, restarts[[1L]])
  where 42: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 43: with_reporter(reporter = current_reporter, results <- lapply(paths, 
      test_file, env = env, reporter = current_reporter, start_end_reporter = FALSE, 
      load_helpers = FALSE, wrap = wrap))
  where 44: test_files(paths, reporter = reporter, env = env, stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 45: test_dir(path = test_path, reporter = reporter, env = env, filter = filter, 
      ..., stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, 
      wrap = wrap)
  where 46: test_package_dir(package = package, test_path = test_path, filter = filter, 
      reporter = reporter, ..., stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 47: test_check("caretEnsemble")
  
   --- value of length: 2 type: logical ---
  [1] FALSE  TRUE
   --- function from context --- 
  function (object, newdata = NULL, ..., verbose = FALSE) 
  {
      if (is.null(newdata)) {
          warning("Predicting without new data is not well supported.  Attempting to predict on the training data.")
          newdata <- object[[1]]$trainingData
          if (is.null(newdata)) {
              stop("Could not find training data in the first model in the ensemble.")
          }
      }
      if (verbose == TRUE) {
          pboptions(type = "txt", char = "*")
      }
      else if (verbose == FALSE) {
          pboptions(type = "none")
      }
      preds <- pbsapply(object, function(x) {
          type <- x$modelType
          if (type == "Classification") {
              if (x$control$classProbs) {
                  caret::predict.train(x, type = "prob", newdata = newdata, 
                    ...)[, 2]
              }
              else {
                  caret::predict.train(x, type = "raw", newdata = newdata, 
                    ...)
              }
          }
          else if (type == "Regression") {
              caret::predict.train(x, type = "raw", newdata = newdata, 
                  ...)
          }
          else {
              stop(paste("Unknown model type:", type))
          }
      })
      if (class(preds) != "matrix" & class(preds) != "data.frame") {
          if (class(preds) == "character" | class(preds) == "factor") {
              preds <- as.character(preds)
          }
          preds <- as.matrix(t(preds))
      }
      colnames(preds) <- make.names(sapply(object, function(x) x$method), 
          unique = TRUE)
      return(preds)
  }
  <bytecode: 0xcf92048>
  <environment: namespace:caretEnsemble>
   --- function search by body ---
  Function predict.caretList in namespace caretEnsemble has this body.
   ----------- END OF FAILURE REPORT -------------- 
  -- 1. Error: caretList predictions (@test-caretList.R#109)  --------------------
  the condition has length > 1
  Backtrace:
   1. testthat::expect_warning(p1 <- predict(models))
   7. caretEnsemble:::predict.caretList(models)
  
   ----------- FAILURE REPORT -------------- 
   --- failure: the condition has length > 1 ---
   --- srcref --- 
  : 
   --- package (from environment) --- 
  caretEnsemble
   --- call from context --- 
  predict.caretList(object$models, newdata = newdata)
   --- call from argument --- 
  if (class(preds) != "matrix" & class(preds) != "data.frame") {
      if (class(preds) == "character" | class(preds) == "factor") {
          preds <- as.character(preds)
      }
      preds <- as.matrix(t(preds))
  }
   --- R stacktrace ---
  where 1: predict.caretList(object$models, newdata = newdata)
  where 2: predict(object$models, newdata = newdata)
  where 3: predict.caretStack(ens.reg, newdata = X.reg)
  where 4: predict(ens.reg, newdata = X.reg)
  where 5: eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
  where 6: withCallingHandlers(code, warning = function(condition) {
      out$push(condition)
      maybe_restart("muffleWarning")
  })
  where 7: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), 
      ...)
  where 8: quasi_capture(enquo(object), label, capture_warnings)
  where 9 at testthat/test-caretStack.R#23: expect_warning(pred.reg <- predict(ens.reg, newdata = X.reg))
  where 10: eval(code, test_env)
  where 11: eval(code, test_env)
  where 12: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 13: doTryCatch(return(expr), name, parentenv, handler)
  where 14: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 15: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 16: doTryCatch(return(expr), name, parentenv, handler)
  where 17: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 18: tryCatchList(expr, classes, parentenv, handlers)
  where 19: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 20: test_code(desc, code, env = parent.frame())
  where 21 at testthat/test-caretStack.R#14: test_that("We can stack regression models", {
      set.seed(96367)
      ens.reg <- caretStack(models.reg, method = "lm", preProcess = "pca", 
          trControl = trainControl(number = 2, allowParallel = FALSE))
      expect_that(ens.reg, is_a("caretStack"))
      expect_is(summary(ens.reg), "summary.lm")
      sink <- capture.output(print(ens.reg))
      expect_warning(pred.reg <- predict(ens.reg, newdata = X.reg))
      expect_true(is.numeric(pred.reg))
      expect_true(length(pred.reg) == 150)
  })
  where 22: eval(code, test_env)
  where 23: eval(code, test_env)
  where 24: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 25: doTryCatch(return(expr), name, parentenv, handler)
  where 26: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 27: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 28: doTryCatch(return(expr), name, parentenv, handler)
  where 29: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 30: tryCatchList(expr, classes, parentenv, handlers)
  where 31: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 32: test_code(NULL, exprs, env)
  where 33: source_file(path, new.env(parent = env), chdir = TRUE, wrap = wrap)
  where 34: force(code)
  where 35: doWithOneRestart(return(expr), restart)
  where 36: withOneRestart(expr, restarts[[1L]])
  where 37: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 38: with_reporter(reporter = reporter, start_end_reporter = start_end_reporter, 
      {
          reporter$start_file(basename(path))
          lister$start_file(basename(path))
          source_file(path, new.env(parent = env), chdir = TRUE, 
              wrap = wrap)
          reporter$.end_context()
          reporter$end_file()
      })
  where 39: FUN(X[[i]], ...)
  where 40: lapply(paths, test_file, env = env, reporter = current_reporter, 
      start_end_reporter = FALSE, load_helpers = FALSE, wrap = wrap)
  where 41: force(code)
  where 42: doWithOneRestart(return(expr), restart)
  where 43: withOneRestart(expr, restarts[[1L]])
  where 44: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 45: with_reporter(reporter = current_reporter, results <- lapply(paths, 
      test_file, env = env, reporter = current_reporter, start_end_reporter = FALSE, 
      load_helpers = FALSE, wrap = wrap))
  where 46: test_files(paths, reporter = reporter, env = env, stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 47: test_dir(path = test_path, reporter = reporter, env = env, filter = filter, 
      ..., stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, 
      wrap = wrap)
  where 48: test_package_dir(package = package, test_path = test_path, filter = filter, 
      reporter = reporter, ..., stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 49: test_check("caretEnsemble")
  
   --- value of length: 2 type: logical ---
  [1] FALSE  TRUE
   --- function from context --- 
  function (object, newdata = NULL, ..., verbose = FALSE) 
  {
      if (is.null(newdata)) {
          warning("Predicting without new data is not well supported.  Attempting to predict on the training data.")
          newdata <- object[[1]]$trainingData
          if (is.null(newdata)) {
              stop("Could not find training data in the first model in the ensemble.")
          }
      }
      if (verbose == TRUE) {
          pboptions(type = "txt", char = "*")
      }
      else if (verbose == FALSE) {
          pboptions(type = "none")
      }
      preds <- pbsapply(object, function(x) {
          type <- x$modelType
          if (type == "Classification") {
              if (x$control$classProbs) {
                  caret::predict.train(x, type = "prob", newdata = newdata, 
                    ...)[, 2]
              }
              else {
                  caret::predict.train(x, type = "raw", newdata = newdata, 
                    ...)
              }
          }
          else if (type == "Regression") {
              caret::predict.train(x, type = "raw", newdata = newdata, 
                  ...)
          }
          else {
              stop(paste("Unknown model type:", type))
          }
      })
      if (class(preds) != "matrix" & class(preds) != "data.frame") {
          if (class(preds) == "character" | class(preds) == "factor") {
              preds <- as.character(preds)
          }
          preds <- as.matrix(t(preds))
      }
      colnames(preds) <- make.names(sapply(object, function(x) x$method), 
          unique = TRUE)
      return(preds)
  }
  <bytecode: 0xcf92048>
  <environment: namespace:caretEnsemble>
   --- function search by body ---
  Function predict.caretList in namespace caretEnsemble has this body.
   ----------- END OF FAILURE REPORT -------------- 
  -- 2. Error: We can stack regression models (@test-caretStack.R#23)  -----------
  the condition has length > 1
  Backtrace:
   1. testthat::expect_warning(pred.reg <- predict(ens.reg, newdata = X.reg))
   7. caretEnsemble:::predict.caretStack(ens.reg, newdata = X.reg)
   9. caretEnsemble:::predict.caretList(object$models, newdata = newdata)
  
   ----------- FAILURE REPORT -------------- 
   --- failure: the condition has length > 1 ---
   --- srcref --- 
  : 
   --- package (from environment) --- 
  caretEnsemble
   --- call from context --- 
  predict.caretList(object$models, newdata = newdata)
   --- call from argument --- 
  if (class(preds) != "matrix" & class(preds) != "data.frame") {
      if (class(preds) == "character" | class(preds) == "factor") {
          preds <- as.character(preds)
      }
      preds <- as.matrix(t(preds))
  }
   --- R stacktrace ---
  where 1: predict.caretList(object$models, newdata = newdata)
  where 2: predict(object$models, newdata = newdata)
  where 3: predict.caretStack(ens.class, X.class, type = "prob")
  where 4: predict(ens.class, X.class, type = "prob")
  where 5: eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
  where 6: withCallingHandlers(code, warning = function(condition) {
      out$push(condition)
      maybe_restart("muffleWarning")
  })
  where 7: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), 
      ...)
  where 8: quasi_capture(enquo(object), label, capture_warnings)
  where 9 at testthat/test-caretStack.R#36: expect_warning(pred.class <- predict(ens.class, X.class, type = "prob"))
  where 10: eval(code, test_env)
  where 11: eval(code, test_env)
  where 12: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 13: doTryCatch(return(expr), name, parentenv, handler)
  where 14: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 15: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 16: doTryCatch(return(expr), name, parentenv, handler)
  where 17: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 18: tryCatchList(expr, classes, parentenv, handlers)
  where 19: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 20: test_code(desc, code, env = parent.frame())
  where 21 at testthat/test-caretStack.R#28: test_that("We can stack classification models", {
      set.seed(42)
      ens.class <- caretStack(models.class, method = "glm", trControl = trainControl(number = 2, 
          allowParallel = FALSE))
      expect_that(ens.class, is_a("caretStack"))
      expect_is(summary(ens.class), "summary.glm")
      sink <- capture.output(print(ens.class))
      expect_warning(pred.class <- predict(ens.class, X.class, 
          type = "prob"))
      expect_true(is.numeric(pred.class))
      expect_true(length(pred.class) == 150)
      expect_warning(raw.class <- predict(ens.class, X.class, type = "raw"))
      expect_true(is.factor(raw.class))
      expect_true(length(raw.class) == 150)
  })
  where 22: eval(code, test_env)
  where 23: eval(code, test_env)
  where 24: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 25: doTryCatch(return(expr), name, parentenv, handler)
  where 26: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 27: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 28: doTryCatch(return(expr), name, parentenv, handler)
  where 29: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 30: tryCatchList(expr, classes, parentenv, handlers)
  where 31: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 32: test_code(NULL, exprs, env)
  where 33: source_file(path, new.env(parent = env), chdir = TRUE, wrap = wrap)
  where 34: force(code)
  where 35: doWithOneRestart(return(expr), restart)
  where 36: withOneRestart(expr, restarts[[1L]])
  where 37: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 38: with_reporter(reporter = reporter, start_end_reporter = start_end_reporter, 
      {
          reporter$start_file(basename(path))
          lister$start_file(basename(path))
          source_file(path, new.env(parent = env), chdir = TRUE, 
              wrap = wrap)
          reporter$.end_context()
          reporter$end_file()
      })
  where 39: FUN(X[[i]], ...)
  where 40: lapply(paths, test_file, env = env, reporter = current_reporter, 
      start_end_reporter = FALSE, load_helpers = FALSE, wrap = wrap)
  where 41: force(code)
  where 42: doWithOneRestart(return(expr), restart)
  where 43: withOneRestart(expr, restarts[[1L]])
  where 44: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 45: with_reporter(reporter = current_reporter, results <- lapply(paths, 
      test_file, env = env, reporter = current_reporter, start_end_reporter = FALSE, 
      load_helpers = FALSE, wrap = wrap))
  where 46: test_files(paths, reporter = reporter, env = env, stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 47: test_dir(path = test_path, reporter = reporter, env = env, filter = filter, 
      ..., stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, 
      wrap = wrap)
  where 48: test_package_dir(package = package, test_path = test_path, filter = filter, 
      reporter = reporter, ..., stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 49: test_check("caretEnsemble")
  
   --- value of length: 2 type: logical ---
  [1] FALSE  TRUE
   --- function from context --- 
  function (object, newdata = NULL, ..., verbose = FALSE) 
  {
      if (is.null(newdata)) {
          warning("Predicting without new data is not well supported.  Attempting to predict on the training data.")
          newdata <- object[[1]]$trainingData
          if (is.null(newdata)) {
              stop("Could not find training data in the first model in the ensemble.")
          }
      }
      if (verbose == TRUE) {
          pboptions(type = "txt", char = "*")
      }
      else if (verbose == FALSE) {
          pboptions(type = "none")
      }
      preds <- pbsapply(object, function(x) {
          type <- x$modelType
          if (type == "Classification") {
              if (x$control$classProbs) {
                  caret::predict.train(x, type = "prob", newdata = newdata, 
                    ...)[, 2]
              }
              else {
                  caret::predict.train(x, type = "raw", newdata = newdata, 
                    ...)
              }
          }
          else if (type == "Regression") {
              caret::predict.train(x, type = "raw", newdata = newdata, 
                  ...)
          }
          else {
              stop(paste("Unknown model type:", type))
          }
      })
      if (class(preds) != "matrix" & class(preds) != "data.frame") {
          if (class(preds) == "character" | class(preds) == "factor") {
              preds <- as.character(preds)
          }
          preds <- as.matrix(t(preds))
      }
      colnames(preds) <- make.names(sapply(object, function(x) x$method), 
          unique = TRUE)
      return(preds)
  }
  <bytecode: 0xcf92048>
  <environment: namespace:caretEnsemble>
   --- function search by body ---
  Function predict.caretList in namespace caretEnsemble has this body.
   ----------- END OF FAILURE REPORT -------------- 
  -- 3. Error: We can stack classification models (@test-caretStack.R#36)  -------
  the condition has length > 1
  Backtrace:
   1. testthat::expect_warning(...)
   7. caretEnsemble:::predict.caretStack(ens.class, X.class, type = "prob")
   9. caretEnsemble:::predict.caretList(object$models, newdata = newdata)
  
   ----------- FAILURE REPORT -------------- 
   --- failure: the condition has length > 1 ---
   --- srcref --- 
  : 
   --- package (from environment) --- 
  caretEnsemble
   --- call from context --- 
  predict.caretList(object$models, newdata = newdata)
   --- call from argument --- 
  if (class(preds) != "matrix" & class(preds) != "data.frame") {
      if (class(preds) == "character" | class(preds) == "factor") {
          preds <- as.character(preds)
      }
      preds <- as.matrix(t(preds))
  }
   --- R stacktrace ---
  where 1: predict.caretList(object$models, newdata = newdata)
  where 2: predict(object$models, newdata = newdata)
  where 3: predict.caretStack(ens.class, X.class, type = "raw", se = TRUE)
  where 4: predict(ens.class, X.class, type = "raw", se = TRUE)
  where 5: eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
  where 6: withCallingHandlers(code, message = function(condition) {
      out$push(condition)
      maybe_restart("muffleMessage")
  })
  where 7: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), 
      ...)
  where 8: quasi_capture(enquo(object), label, capture_messages)
  where 9 at testthat/test-caretStack.R#64: expect_message(predict(ens.class, X.class, type = "raw", se = TRUE))
  where 10: eval(code, test_env)
  where 11: eval(code, test_env)
  where 12: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 13: doTryCatch(return(expr), name, parentenv, handler)
  where 14: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 15: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 16: doTryCatch(return(expr), name, parentenv, handler)
  where 17: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 18: tryCatchList(expr, classes, parentenv, handlers)
  where 19: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 20: test_code(desc, code, env = parent.frame())
  where 21 at testthat/test-caretStack.R#59: test_that("Failure to calculate se occurs gracefully", {
      ens.class <- caretStack(models.class, method = "glm", trControl = trainControl(number = 2, 
          allowParallel = FALSE))
      expect_message(predict(ens.class, X.class, type = "raw", 
          se = TRUE))
      expect_warning(expect_is(predict(ens.class, X.class, type = "raw"), 
          "factor"))
      expect_warning(expect_is(predict(ens.class, X.class, type = "raw", 
          se = TRUE), "factor"))
      expect_warning({
          expect_identical(predict(ens.class, X.class, type = "raw", 
              se = TRUE), predict(ens.class, X.class, type = "raw"))
      })
      ens.reg <- caretStack(models.reg, method = "lm", preProcess = "pca", 
          trControl = trainControl(number = 2, allowParallel = FALSE))
      expect_warning(pred <- predict(ens.reg, X.reg, se = TRUE))
      expect_warning(expect_is(predict(ens.reg, X.reg, se = TRUE), 
          "data.frame"))
      expect_warning(expect_is(predict(ens.class, X.class, type = "prob", 
          se = TRUE), "data.frame"))
      expect_warning(expect_is(predict(ens.class, X.class, type = "prob", 
          se = TRUE, return_weights = TRUE), "data.frame"))
      expect_warning(expect_identical(colnames(predict(ens.class, 
          X.class, type = "prob", se = TRUE)), c("fit", "lwr", 
          "upr")))
      expect_warning(expect_false(identical(predict(ens.class, 
          X.class, type = "raw", return_weights = TRUE), predict(ens.class, 
          X.class, type = "raw", return_weights = FALSE))))
      expect_warning(expect_false(identical(predict(ens.class, 
          X.class, type = "prob", se = TRUE, level = 0.8), predict(ens.class, 
          X.class, type = "prob", se = TRUE, return_weights = FALSE))))
      expect_warning(expect_true(identical(predict(ens.class, X.class, 
          type = "prob", level = 0.8), predict(ens.class, X.class, 
          type = "prob", return_weights = FALSE))))
  })
  where 22: eval(code, test_env)
  where 23: eval(code, test_env)
  where 24: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 25: doTryCatch(return(expr), name, parentenv, handler)
  where 26: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 27: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 28: doTryCatch(return(expr), name, parentenv, handler)
  where 29: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 30: tryCatchList(expr, classes, parentenv, handlers)
  where 31: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 32: test_code(NULL, exprs, env)
  where 33: source_file(path, new.env(parent = env), chdir = TRUE, wrap = wrap)
  where 34: force(code)
  where 35: doWithOneRestart(return(expr), restart)
  where 36: withOneRestart(expr, restarts[[1L]])
  where 37: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 38: with_reporter(reporter = reporter, start_end_reporter = start_end_reporter, 
      {
          reporter$start_file(basename(path))
          lister$start_file(basename(path))
          source_file(path, new.env(parent = env), chdir = TRUE, 
              wrap = wrap)
          reporter$.end_context()
          reporter$end_file()
      })
  where 39: FUN(X[[i]], ...)
  where 40: lapply(paths, test_file, env = env, reporter = current_reporter, 
      start_end_reporter = FALSE, load_helpers = FALSE, wrap = wrap)
  where 41: force(code)
  where 42: doWithOneRestart(return(expr), restart)
  where 43: withOneRestart(expr, restarts[[1L]])
  where 44: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 45: with_reporter(reporter = current_reporter, results <- lapply(paths, 
      test_file, env = env, reporter = current_reporter, start_end_reporter = FALSE, 
      load_helpers = FALSE, wrap = wrap))
  where 46: test_files(paths, reporter = reporter, env = env, stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 47: test_dir(path = test_path, reporter = reporter, env = env, filter = filter, 
      ..., stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, 
      wrap = wrap)
  where 48: test_package_dir(package = package, test_path = test_path, filter = filter, 
      reporter = reporter, ..., stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 49: test_check("caretEnsemble")
  
   --- value of length: 2 type: logical ---
  [1] FALSE  TRUE
   --- function from context --- 
  function (object, newdata = NULL, ..., verbose = FALSE) 
  {
      if (is.null(newdata)) {
          warning("Predicting without new data is not well supported.  Attempting to predict on the training data.")
          newdata <- object[[1]]$trainingData
          if (is.null(newdata)) {
              stop("Could not find training data in the first model in the ensemble.")
          }
      }
      if (verbose == TRUE) {
          pboptions(type = "txt", char = "*")
      }
      else if (verbose == FALSE) {
          pboptions(type = "none")
      }
      preds <- pbsapply(object, function(x) {
          type <- x$modelType
          if (type == "Classification") {
              if (x$control$classProbs) {
                  caret::predict.train(x, type = "prob", newdata = newdata, 
                    ...)[, 2]
              }
              else {
                  caret::predict.train(x, type = "raw", newdata = newdata, 
                    ...)
              }
          }
          else if (type == "Regression") {
              caret::predict.train(x, type = "raw", newdata = newdata, 
                  ...)
          }
          else {
              stop(paste("Unknown model type:", type))
          }
      })
      if (class(preds) != "matrix" & class(preds) != "data.frame") {
          if (class(preds) == "character" | class(preds) == "factor") {
              preds <- as.character(preds)
          }
          preds <- as.matrix(t(preds))
      }
      colnames(preds) <- make.names(sapply(object, function(x) x$method), 
          unique = TRUE)
      return(preds)
  }
  <bytecode: 0xcf92048>
  <environment: namespace:caretEnsemble>
   --- function search by body ---
  Function predict.caretList in namespace caretEnsemble has this body.
   ----------- END OF FAILURE REPORT -------------- 
  -- 4. Error: Failure to calculate se occurs gracefully (@test-caretStack.R#64)  
  the condition has length > 1
  Backtrace:
   1. testthat::expect_message(...)
   7. caretEnsemble:::predict.caretStack(...)
   9. caretEnsemble:::predict.caretList(object$models, newdata = newdata)
  
   ----------- FAILURE REPORT -------------- 
   --- failure: the condition has length > 1 ---
   --- srcref --- 
  : 
   --- package (from environment) --- 
  caretEnsemble
   --- call from context --- 
  predict.caretList(object$models, newdata = newdata)
   --- call from argument --- 
  if (class(preds) != "matrix" & class(preds) != "data.frame") {
      if (class(preds) == "character" | class(preds) == "factor") {
          preds <- as.character(preds)
      }
      preds <- as.matrix(t(preds))
  }
   --- R stacktrace ---
  where 1: predict.caretList(object$models, newdata = newdata)
  where 2: predict(object$models, newdata = newdata)
  where 3: predict.caretStack(object, type = "prob")
  where 4: predict(object, type = "prob")
  where 5: residuals.caretEnsemble(ens)
  where 6: residuals(ens)
  where 7: eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
  where 8: withCallingHandlers(code, warning = function(condition) {
      out$push(condition)
      maybe_restart("muffleWarning")
  })
  where 9: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), 
      ...)
  where 10: quasi_capture(enquo(object), label, capture_warnings)
  where 11 at testthat/test-ensemble.R#43: expect_warning(r <- residuals(ens))
  where 12: eval(code, test_env)
  where 13: eval(code, test_env)
  where 14: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 15: doTryCatch(return(expr), name, parentenv, handler)
  where 16: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 17: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 18: doTryCatch(return(expr), name, parentenv, handler)
  where 19: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 20: tryCatchList(expr, classes, parentenv, handlers)
  where 21: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 22: test_code(desc, code, env = parent.frame())
  where 23 at testthat/test-ensemble.R#41: test_that("We can extract resdiuals from caretEnsemble objects", 
      {
          ens <- caretEnsemble(models.class)
          expect_warning(r <- residuals(ens))
          expect_is(r, "numeric")
          expect_equal(length(r), 150)
          ens <- caretEnsemble(models.reg)
          expect_warning(r <- residuals(ens))
          expect_is(r, "numeric")
          expect_equal(length(r), 150)
      })
  where 24: eval(code, test_env)
  where 25: eval(code, test_env)
  where 26: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 27: doTryCatch(return(expr), name, parentenv, handler)
  where 28: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 29: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 30: doTryCatch(return(expr), name, parentenv, handler)
  where 31: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 32: tryCatchList(expr, classes, parentenv, handlers)
  where 33: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 34: test_code(NULL, exprs, env)
  where 35: source_file(path, new.env(parent = env), chdir = TRUE, wrap = wrap)
  where 36: force(code)
  where 37: doWithOneRestart(return(expr), restart)
  where 38: withOneRestart(expr, restarts[[1L]])
  where 39: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 40: with_reporter(reporter = reporter, start_end_reporter = start_end_reporter, 
      {
          reporter$start_file(basename(path))
          lister$start_file(basename(path))
          source_file(path, new.env(parent = env), chdir = TRUE, 
              wrap = wrap)
          reporter$.end_context()
          reporter$end_file()
      })
  where 41: FUN(X[[i]], ...)
  where 42: lapply(paths, test_file, env = env, reporter = current_reporter, 
      start_end_reporter = FALSE, load_helpers = FALSE, wrap = wrap)
  where 43: force(code)
  where 44: doWithOneRestart(return(expr), restart)
  where 45: withOneRestart(expr, restarts[[1L]])
  where 46: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 47: with_reporter(reporter = current_reporter, results <- lapply(paths, 
      test_file, env = env, reporter = current_reporter, start_end_reporter = FALSE, 
      load_helpers = FALSE, wrap = wrap))
  where 48: test_files(paths, reporter = reporter, env = env, stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 49: test_dir(path = test_path, reporter = reporter, env = env, filter = filter, 
      ..., stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, 
      wrap = wrap)
  where 50: test_package_dir(package = package, test_path = test_path, filter = filter, 
      reporter = reporter, ..., stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 51: test_check("caretEnsemble")
  
   --- value of length: 2 type: logical ---
  [1] FALSE  TRUE
   --- function from context --- 
  function (object, newdata = NULL, ..., verbose = FALSE) 
  {
      if (is.null(newdata)) {
          warning("Predicting without new data is not well supported.  Attempting to predict on the training data.")
          newdata <- object[[1]]$trainingData
          if (is.null(newdata)) {
              stop("Could not find training data in the first model in the ensemble.")
          }
      }
      if (verbose == TRUE) {
          pboptions(type = "txt", char = "*")
      }
      else if (verbose == FALSE) {
          pboptions(type = "none")
      }
      preds <- pbsapply(object, function(x) {
          type <- x$modelType
          if (type == "Classification") {
              if (x$control$classProbs) {
                  caret::predict.train(x, type = "prob", newdata = newdata, 
                    ...)[, 2]
              }
              else {
                  caret::predict.train(x, type = "raw", newdata = newdata, 
                    ...)
              }
          }
          else if (type == "Regression") {
              caret::predict.train(x, type = "raw", newdata = newdata, 
                  ...)
          }
          else {
              stop(paste("Unknown model type:", type))
          }
      })
      if (class(preds) != "matrix" & class(preds) != "data.frame") {
          if (class(preds) == "character" | class(preds) == "factor") {
              preds <- as.character(preds)
          }
          preds <- as.matrix(t(preds))
      }
      colnames(preds) <- make.names(sapply(object, function(x) x$method), 
          unique = TRUE)
      return(preds)
  }
  <bytecode: 0xcf92048>
  <environment: namespace:caretEnsemble>
   --- function search by body ---
  Function predict.caretList in namespace caretEnsemble has this body.
   ----------- END OF FAILURE REPORT -------------- 
  -- 5. Error: We can extract resdiuals from caretEnsemble objects (@test-ensemble
  the condition has length > 1
  Backtrace:
    1. testthat::expect_warning(r <- residuals(ens))
    7. caretEnsemble:::residuals.caretEnsemble(ens)
    9. caretEnsemble:::predict.caretStack(object, type = "prob")
   11. caretEnsemble:::predict.caretList(object$models, newdata = newdata)
  
   ----------- FAILURE REPORT -------------- 
   --- failure: the condition has length > 1 ---
   --- srcref --- 
  : 
   --- package (from environment) --- 
  caretEnsemble
   --- call from context --- 
  predict.caretList(object$models, newdata = newdata)
   --- call from argument --- 
  if (class(preds) != "matrix" & class(preds) != "data.frame") {
      if (class(preds) == "character" | class(preds) == "factor") {
          preds <- as.character(preds)
      }
      preds <- as.matrix(t(preds))
  }
   --- R stacktrace ---
  where 1: predict.caretList(object$models, newdata = newdata)
  where 2: predict(object$models, newdata = newdata)
  where 3: predict.caretStack(ens.reg)
  where 4: predict(ens.reg)
  where 5: eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
  where 6: withCallingHandlers(code, warning = function(condition) {
      out$push(condition)
      maybe_restart("muffleWarning")
  })
  where 7: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), 
      ...)
  where 8: quasi_capture(enquo(object), label, capture_warnings)
  where 9 at testthat/test-ensemble.R#79: expect_warning(pred.reg <- predict(ens.reg))
  where 10: eval(code, test_env)
  where 11: eval(code, test_env)
  where 12: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 13: doTryCatch(return(expr), name, parentenv, handler)
  where 14: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 15: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 16: doTryCatch(return(expr), name, parentenv, handler)
  where 17: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 18: tryCatchList(expr, classes, parentenv, handlers)
  where 19: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 20: test_code(desc, code, env = parent.frame())
  where 21 at testthat/test-ensemble.R#76: test_that("We can ensemble regression models", {
      ens.reg <- caretEnsemble(models.reg, trControl = trainControl(number = 2))
      expect_that(ens.reg, is_a("caretEnsemble"))
      expect_warning(pred.reg <- predict(ens.reg))
      expect_warning(pred.reg2 <- predict(ens.reg, se = TRUE))
      expect_true(all(pred.reg == pred.reg2$fit))
      expect_warning(expect_error(predict(ens.reg, return_weights = "BOGUS")))
      expect_true(is.numeric(pred.reg))
      expect_true(length(pred.reg) == 150)
      ens.class <- caretEnsemble(models.class, trControl = trainControl(number = 2))
      expect_that(ens.class, is_a("caretEnsemble"))
      expect_warning(pred.class <- predict(ens.class, type = "prob"))
      expect_true(is.numeric(pred.class))
      expect_true(length(pred.class) == 150)
      expect_warning(p1 <- predict(ens.reg, return_weights = TRUE, 
          se = FALSE))
      expect_is(attr(p1, which = "weights"), "numeric")
      expect_is(p1, "numeric")
      expect_warning(p2 <- predict(ens.reg, return_weights = TRUE, 
          se = TRUE))
      expect_is(attr(p2, which = "weights"), "numeric")
      expect_is(p2, "data.frame")
      expect_equal(ncol(p2), 3)
      expect_identical(names(p2), c("fit", "lwr", "upr"))
      expect_warning(p3 <- predict(ens.reg, return_weights = FALSE, 
          se = FALSE))
      expect_is(p3, "numeric")
      expect_true(all(p1 == p3))
      expect_false(identical(p1, p3))
      expect_true(all(p2$fit == p1))
      expect_true(all(p2$fit == p3))
      expect_null(attr(p3, which = "weights"))
  })
  where 22: eval(code, test_env)
  where 23: eval(code, test_env)
  where 24: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 25: doTryCatch(return(expr), name, parentenv, handler)
  where 26: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 27: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 28: doTryCatch(return(expr), name, parentenv, handler)
  where 29: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 30: tryCatchList(expr, classes, parentenv, handlers)
  where 31: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 32: test_code(NULL, exprs, env)
  where 33: source_file(path, new.env(parent = env), chdir = TRUE, wrap = wrap)
  where 34: force(code)
  where 35: doWithOneRestart(return(expr), restart)
  where 36: withOneRestart(expr, restarts[[1L]])
  where 37: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 38: with_reporter(reporter = reporter, start_end_reporter = start_end_reporter, 
      {
          reporter$start_file(basename(path))
          lister$start_file(basename(path))
          source_file(path, new.env(parent = env), chdir = TRUE, 
              wrap = wrap)
          reporter$.end_context()
          reporter$end_file()
      })
  where 39: FUN(X[[i]], ...)
  where 40: lapply(paths, test_file, env = env, reporter = current_reporter, 
      start_end_reporter = FALSE, load_helpers = FALSE, wrap = wrap)
  where 41: force(code)
  where 42: doWithOneRestart(return(expr), restart)
  where 43: withOneRestart(expr, restarts[[1L]])
  where 44: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 45: with_reporter(reporter = current_reporter, results <- lapply(paths, 
      test_file, env = env, reporter = current_reporter, start_end_reporter = FALSE, 
      load_helpers = FALSE, wrap = wrap))
  where 46: test_files(paths, reporter = reporter, env = env, stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 47: test_dir(path = test_path, reporter = reporter, env = env, filter = filter, 
      ..., stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, 
      wrap = wrap)
  where 48: test_package_dir(package = package, test_path = test_path, filter = filter, 
      reporter = reporter, ..., stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 49: test_check("caretEnsemble")
  
   --- value of length: 2 type: logical ---
  [1] FALSE  TRUE
   --- function from context --- 
  function (object, newdata = NULL, ..., verbose = FALSE) 
  {
      if (is.null(newdata)) {
          warning("Predicting without new data is not well supported.  Attempting to predict on the training data.")
          newdata <- object[[1]]$trainingData
          if (is.null(newdata)) {
              stop("Could not find training data in the first model in the ensemble.")
          }
      }
      if (verbose == TRUE) {
          pboptions(type = "txt", char = "*")
      }
      else if (verbose == FALSE) {
          pboptions(type = "none")
      }
      preds <- pbsapply(object, function(x) {
          type <- x$modelType
          if (type == "Classification") {
              if (x$control$classProbs) {
                  caret::predict.train(x, type = "prob", newdata = newdata, 
                    ...)[, 2]
              }
              else {
                  caret::predict.train(x, type = "raw", newdata = newdata, 
                    ...)
              }
          }
          else if (type == "Regression") {
              caret::predict.train(x, type = "raw", newdata = newdata, 
                  ...)
          }
          else {
              stop(paste("Unknown model type:", type))
          }
      })
      if (class(preds) != "matrix" & class(preds) != "data.frame") {
          if (class(preds) == "character" | class(preds) == "factor") {
              preds <- as.character(preds)
          }
          preds <- as.matrix(t(preds))
      }
      colnames(preds) <- make.names(sapply(object, function(x) x$method), 
          unique = TRUE)
      return(preds)
  }
  <bytecode: 0xcf92048>
  <environment: namespace:caretEnsemble>
   --- function search by body ---
  Function predict.caretList in namespace caretEnsemble has this body.
   ----------- END OF FAILURE REPORT -------------- 
  -- 6. Error: We can ensemble regression models (@test-ensemble.R#79)  ----------
  the condition has length > 1
  Backtrace:
   1. testthat::expect_warning(pred.reg <- predict(ens.reg))
   7. caretEnsemble:::predict.caretStack(ens.reg)
   9. caretEnsemble:::predict.caretList(object$models, newdata = newdata)
  
   ----------- FAILURE REPORT -------------- 
   --- failure: the condition has length > 1 ---
   --- srcref --- 
  : 
   --- package (from environment) --- 
  caretEnsemble
   --- call from context --- 
  predict.caretList(object$models, newdata = newdata)
   --- call from argument --- 
  if (class(preds) != "matrix" & class(preds) != "data.frame") {
      if (class(preds) == "character" | class(preds) == "factor") {
          preds <- as.character(preds)
      }
      preds <- as.matrix(t(preds))
  }
   --- R stacktrace ---
  where 1: predict.caretList(object$models, newdata = newdata)
  where 2: predict(object$models, newdata = newdata)
  where 3: predict.caretStack(ens.reg)
  where 4: predict(ens.reg)
  where 5: eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
  where 6: withCallingHandlers(code, warning = function(condition) {
      out$push(condition)
      maybe_restart("muffleWarning")
  })
  where 7: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), 
      ...)
  where 8: quasi_capture(enquo(object), label, capture_warnings)
  where 9 at testthat/test-ensemble.R#160: expect_warning(pred.reg <- predict(ens.reg))
  where 10: eval(code, test_env)
  where 11: eval(code, test_env)
  where 12: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 13: doTryCatch(return(expr), name, parentenv, handler)
  where 14: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 15: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 16: doTryCatch(return(expr), name, parentenv, handler)
  where 17: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 18: tryCatchList(expr, classes, parentenv, handlers)
  where 19: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 20: test_code(desc, code, env = parent.frame())
  where 21 at testthat/test-ensemble.R#156: test_that("It works for regression models", {
      set.seed(1234)
      ens.reg <- caretEnsemble(models.reg, trControl = trainControl(number = 2))
      expect_is(ens.reg, "caretEnsemble")
      expect_warning(pred.reg <- predict(ens.reg))
      newPreds1 <- as.data.frame(X.reg)
      expect_warning(pred.regb <- predict(ens.reg, newdata = newPreds1))
      expect_warning(pred.regc <- predict(ens.reg, newdata = newPreds1[2, 
          ]))
      expect_identical(pred.reg, pred.regb)
      expect_less_than(abs(4.740135 - pred.regc), 0.01)
      expect_is(pred.reg, "numeric")
      expect_is(pred.regb, "numeric")
      expect_is(pred.regc, "numeric")
      expect_equal(length(pred.regc), 1)
  })
  where 22: eval(code, test_env)
  where 23: eval(code, test_env)
  where 24: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 25: doTryCatch(return(expr), name, parentenv, handler)
  where 26: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 27: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 28: doTryCatch(return(expr), name, parentenv, handler)
  where 29: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 30: tryCatchList(expr, classes, parentenv, handlers)
  where 31: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 32: test_code(NULL, exprs, env)
  where 33: source_file(path, new.env(parent = env), chdir = TRUE, wrap = wrap)
  where 34: force(code)
  where 35: doWithOneRestart(return(expr), restart)
  where 36: withOneRestart(expr, restarts[[1L]])
  where 37: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 38: with_reporter(reporter = reporter, start_end_reporter = start_end_reporter, 
      {
          reporter$start_file(basename(path))
          lister$start_file(basename(path))
          source_file(path, new.env(parent = env), chdir = TRUE, 
              wrap = wrap)
          reporter$.end_context()
          reporter$end_file()
      })
  where 39: FUN(X[[i]], ...)
  where 40: lapply(paths, test_file, env = env, reporter = current_reporter, 
      start_end_reporter = FALSE, load_helpers = FALSE, wrap = wrap)
  where 41: force(code)
  where 42: doWithOneRestart(return(expr), restart)
  where 43: withOneRestart(expr, restarts[[1L]])
  where 44: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 45: with_reporter(reporter = current_reporter, results <- lapply(paths, 
      test_file, env = env, reporter = current_reporter, start_end_reporter = FALSE, 
      load_helpers = FALSE, wrap = wrap))
  where 46: test_files(paths, reporter = reporter, env = env, stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 47: test_dir(path = test_path, reporter = reporter, env = env, filter = filter, 
      ..., stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, 
      wrap = wrap)
  where 48: test_package_dir(package = package, test_path = test_path, filter = filter, 
      reporter = reporter, ..., stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 49: test_check("caretEnsemble")
  
   --- value of length: 2 type: logical ---
  [1] FALSE  TRUE
   --- function from context --- 
  function (object, newdata = NULL, ..., verbose = FALSE) 
  {
      if (is.null(newdata)) {
          warning("Predicting without new data is not well supported.  Attempting to predict on the training data.")
          newdata <- object[[1]]$trainingData
          if (is.null(newdata)) {
              stop("Could not find training data in the first model in the ensemble.")
          }
      }
      if (verbose == TRUE) {
          pboptions(type = "txt", char = "*")
      }
      else if (verbose == FALSE) {
          pboptions(type = "none")
      }
      preds <- pbsapply(object, function(x) {
          type <- x$modelType
          if (type == "Classification") {
              if (x$control$classProbs) {
                  caret::predict.train(x, type = "prob", newdata = newdata, 
                    ...)[, 2]
              }
              else {
                  caret::predict.train(x, type = "raw", newdata = newdata, 
                    ...)
              }
          }
          else if (type == "Regression") {
              caret::predict.train(x, type = "raw", newdata = newdata, 
                  ...)
          }
          else {
              stop(paste("Unknown model type:", type))
          }
      })
      if (class(preds) != "matrix" & class(preds) != "data.frame") {
          if (class(preds) == "character" | class(preds) == "factor") {
              preds <- as.character(preds)
          }
          preds <- as.matrix(t(preds))
      }
      colnames(preds) <- make.names(sapply(object, function(x) x$method), 
          unique = TRUE)
      return(preds)
  }
  <bytecode: 0xcf92048>
  <environment: namespace:caretEnsemble>
   --- function search by body ---
  Function predict.caretList in namespace caretEnsemble has this body.
   ----------- END OF FAILURE REPORT -------------- 
  -- 7. Error: It works for regression models (@test-ensemble.R#160)  ------------
  the condition has length > 1
  Backtrace:
   1. testthat::expect_warning(pred.reg <- predict(ens.reg))
   7. caretEnsemble:::predict.caretStack(ens.reg)
   9. caretEnsemble:::predict.caretList(object$models, newdata = newdata)
  
   ----------- FAILURE REPORT -------------- 
   --- failure: the condition has length > 1 ---
   --- srcref --- 
  : 
   --- package (from environment) --- 
  caretEnsemble
   --- call from context --- 
  predict.caretList(object$models, newdata = newdata)
   --- call from argument --- 
  if (class(preds) != "matrix" & class(preds) != "data.frame") {
      if (class(preds) == "character" | class(preds) == "factor") {
          preds <- as.character(preds)
      }
      preds <- as.matrix(t(preds))
  }
   --- R stacktrace ---
  where 1: predict.caretList(object$models, newdata = newdata)
  where 2: predict(object$models, newdata = newdata)
  where 3: predict.caretStack(ens.class, type = "prob")
  where 4: predict(ens.class, type = "prob")
  where 5: eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
  where 6: withCallingHandlers(code, warning = function(condition) {
      out$push(condition)
      maybe_restart("muffleWarning")
  })
  where 7: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), 
      ...)
  where 8: quasi_capture(enquo(object), label, capture_warnings)
  where 9 at testthat/test-ensemble.R#176: expect_warning(pred.class <- predict(ens.class, type = "prob"))
  where 10: eval(code, test_env)
  where 11: eval(code, test_env)
  where 12: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 13: doTryCatch(return(expr), name, parentenv, handler)
  where 14: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 15: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 16: doTryCatch(return(expr), name, parentenv, handler)
  where 17: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 18: tryCatchList(expr, classes, parentenv, handlers)
  where 19: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 20: test_code(desc, code, env = parent.frame())
  where 21 at testthat/test-ensemble.R#172: test_that("It works for classification models", {
      set.seed(1234)
      ens.class <- caretEnsemble(models.class, trControl = trainControl(number = 2))
      expect_that(ens.class, is_a("caretEnsemble"))
      expect_warning(pred.class <- predict(ens.class, type = "prob"))
      newPreds1 <- as.data.frame(X.class)
      expect_warning(pred.classb <- predict(ens.class, newdata = newPreds1, 
          type = "prob"))
      expect_warning(pred.classc <- predict(ens.class, newdata = newPreds1[2, 
          ], type = "prob"))
      expect_true(is.numeric(pred.class))
      expect_true(length(pred.class) == 150)
      expect_identical(pred.class, pred.classb)
      expect_less_than(abs(0.03727609 - pred.classc), 0.01)
      expect_is(pred.class, "numeric")
      expect_is(pred.classb, "numeric")
      expect_is(pred.classc, "numeric")
      expect_equal(length(pred.classc), 1)
  })
  where 22: eval(code, test_env)
  where 23: eval(code, test_env)
  where 24: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 25: doTryCatch(return(expr), name, parentenv, handler)
  where 26: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 27: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 28: doTryCatch(return(expr), name, parentenv, handler)
  where 29: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 30: tryCatchList(expr, classes, parentenv, handlers)
  where 31: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 32: test_code(NULL, exprs, env)
  where 33: source_file(path, new.env(parent = env), chdir = TRUE, wrap = wrap)
  where 34: force(code)
  where 35: doWithOneRestart(return(expr), restart)
  where 36: withOneRestart(expr, restarts[[1L]])
  where 37: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 38: with_reporter(reporter = reporter, start_end_reporter = start_end_reporter, 
      {
          reporter$start_file(basename(path))
          lister$start_file(basename(path))
          source_file(path, new.env(parent = env), chdir = TRUE, 
              wrap = wrap)
          reporter$.end_context()
          reporter$end_file()
      })
  where 39: FUN(X[[i]], ...)
  where 40: lapply(paths, test_file, env = env, reporter = current_reporter, 
      start_end_reporter = FALSE, load_helpers = FALSE, wrap = wrap)
  where 41: force(code)
  where 42: doWithOneRestart(return(expr), restart)
  where 43: withOneRestart(expr, restarts[[1L]])
  where 44: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 45: with_reporter(reporter = current_reporter, results <- lapply(paths, 
      test_file, env = env, reporter = current_reporter, start_end_reporter = FALSE, 
      load_helpers = FALSE, wrap = wrap))
  where 46: test_files(paths, reporter = reporter, env = env, stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 47: test_dir(path = test_path, reporter = reporter, env = env, filter = filter, 
      ..., stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, 
      wrap = wrap)
  where 48: test_package_dir(package = package, test_path = test_path, filter = filter, 
      reporter = reporter, ..., stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 49: test_check("caretEnsemble")
  
   --- value of length: 2 type: logical ---
  [1] FALSE  TRUE
   --- function from context --- 
  function (object, newdata = NULL, ..., verbose = FALSE) 
  {
      if (is.null(newdata)) {
          warning("Predicting without new data is not well supported.  Attempting to predict on the training data.")
          newdata <- object[[1]]$trainingData
          if (is.null(newdata)) {
              stop("Could not find training data in the first model in the ensemble.")
          }
      }
      if (verbose == TRUE) {
          pboptions(type = "txt", char = "*")
      }
      else if (verbose == FALSE) {
          pboptions(type = "none")
      }
      preds <- pbsapply(object, function(x) {
          type <- x$modelType
          if (type == "Classification") {
              if (x$control$classProbs) {
                  caret::predict.train(x, type = "prob", newdata = newdata, 
                    ...)[, 2]
              }
              else {
                  caret::predict.train(x, type = "raw", newdata = newdata, 
                    ...)
              }
          }
          else if (type == "Regression") {
              caret::predict.train(x, type = "raw", newdata = newdata, 
                  ...)
          }
          else {
              stop(paste("Unknown model type:", type))
          }
      })
      if (class(preds) != "matrix" & class(preds) != "data.frame") {
          if (class(preds) == "character" | class(preds) == "factor") {
              preds <- as.character(preds)
          }
          preds <- as.matrix(t(preds))
      }
      colnames(preds) <- make.names(sapply(object, function(x) x$method), 
          unique = TRUE)
      return(preds)
  }
  <bytecode: 0xcf92048>
  <environment: namespace:caretEnsemble>
   --- function search by body ---
  Function predict.caretList in namespace caretEnsemble has this body.
   ----------- END OF FAILURE REPORT -------------- 
  -- 8. Error: It works for classification models (@test-ensemble.R#176)  --------
  the condition has length > 1
  Backtrace:
   1. testthat::expect_warning(pred.class <- predict(ens.class, type = "prob"))
   7. caretEnsemble:::predict.caretStack(ens.class, type = "prob")
   9. caretEnsemble:::predict.caretList(object$models, newdata = newdata)
  
   ----------- FAILURE REPORT -------------- 
   --- failure: the condition has length > 1 ---
   --- srcref --- 
  : 
   --- package (from environment) --- 
  caretEnsemble
   --- call from context --- 
  predict.caretList(models.reg, "reg", newdata = X.reg)
   --- call from argument --- 
  if (class(preds) != "matrix" & class(preds) != "data.frame") {
      if (class(preds) == "character" | class(preds) == "factor") {
          preds <- as.character(preds)
      }
      preds <- as.matrix(t(preds))
  }
   --- R stacktrace ---
  where 1: predict.caretList(models.reg, "reg", newdata = X.reg)
  where 2: predict(models.reg, "reg", newdata = X.reg)
  where 3: eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
  where 4: withCallingHandlers(code, warning = function(condition) {
      out$push(condition)
      maybe_restart("muffleWarning")
  })
  where 5: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), 
      ...)
  where 6: quasi_capture(enquo(object), label, capture_warnings)
  where 7 at testthat/test-helper_functions.R#63: expect_warning(out <- predict(models.reg, "reg", newdata = X.reg))
  where 8: eval(code, test_env)
  where 9: eval(code, test_env)
  where 10: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 11: doTryCatch(return(expr), name, parentenv, handler)
  where 12: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 13: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 14: doTryCatch(return(expr), name, parentenv, handler)
  where 15: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 16: tryCatchList(expr, classes, parentenv, handlers)
  where 17: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 18: test_code(desc, code, env = parent.frame())
  where 19 at testthat/test-helper_functions.R#62: test_that("We can predict", {
      expect_warning(out <- predict(models.reg, "reg", newdata = X.reg))
      expect_is(out, "matrix")
      expect_true(all(dim(out) == c(150, 4)))
      expect_true(all(colnames(out) == c("rf", "glm", "rpart", 
          "treebag")))
  })
  where 20: eval(code, test_env)
  where 21: eval(code, test_env)
  where 22: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 23: doTryCatch(return(expr), name, parentenv, handler)
  where 24: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 25: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 26: doTryCatch(return(expr), name, parentenv, handler)
  where 27: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 28: tryCatchList(expr, classes, parentenv, handlers)
  where 29: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 30: test_code(NULL, exprs, env)
  where 31: source_file(path, new.env(parent = env), chdir = TRUE, wrap = wrap)
  where 32: force(code)
  where 33: doWithOneRestart(return(expr), restart)
  where 34: withOneRestart(expr, restarts[[1L]])
  where 35: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 36: with_reporter(reporter = reporter, start_end_reporter = start_end_reporter, 
      {
          reporter$start_file(basename(path))
          lister$start_file(basename(path))
          source_file(path, new.env(parent = env), chdir = TRUE, 
              wrap = wrap)
          reporter$.end_context()
          reporter$end_file()
      })
  where 37: FUN(X[[i]], ...)
  where 38: lapply(paths, test_file, env = env, reporter = current_reporter, 
      start_end_reporter = FALSE, load_helpers = FALSE, wrap = wrap)
  where 39: force(code)
  where 40: doWithOneRestart(return(expr), restart)
  where 41: withOneRestart(expr, restarts[[1L]])
  where 42: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 43: with_reporter(reporter = current_reporter, results <- lapply(paths, 
      test_file, env = env, reporter = current_reporter, start_end_reporter = FALSE, 
      load_helpers = FALSE, wrap = wrap))
  where 44: test_files(paths, reporter = reporter, env = env, stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 45: test_dir(path = test_path, reporter = reporter, env = env, filter = filter, 
      ..., stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, 
      wrap = wrap)
  where 46: test_package_dir(package = package, test_path = test_path, filter = filter, 
      reporter = reporter, ..., stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 47: test_check("caretEnsemble")
  
   --- value of length: 2 type: logical ---
  [1] FALSE  TRUE
   --- function from context --- 
  function (object, newdata = NULL, ..., verbose = FALSE) 
  {
      if (is.null(newdata)) {
          warning("Predicting without new data is not well supported.  Attempting to predict on the training data.")
          newdata <- object[[1]]$trainingData
          if (is.null(newdata)) {
              stop("Could not find training data in the first model in the ensemble.")
          }
      }
      if (verbose == TRUE) {
          pboptions(type = "txt", char = "*")
      }
      else if (verbose == FALSE) {
          pboptions(type = "none")
      }
      preds <- pbsapply(object, function(x) {
          type <- x$modelType
          if (type == "Classification") {
              if (x$control$classProbs) {
                  caret::predict.train(x, type = "prob", newdata = newdata, 
                    ...)[, 2]
              }
              else {
                  caret::predict.train(x, type = "raw", newdata = newdata, 
                    ...)
              }
          }
          else if (type == "Regression") {
              caret::predict.train(x, type = "raw", newdata = newdata, 
                  ...)
          }
          else {
              stop(paste("Unknown model type:", type))
          }
      })
      if (class(preds) != "matrix" & class(preds) != "data.frame") {
          if (class(preds) == "character" | class(preds) == "factor") {
              preds <- as.character(preds)
          }
          preds <- as.matrix(t(preds))
      }
      colnames(preds) <- make.names(sapply(object, function(x) x$method), 
          unique = TRUE)
      return(preds)
  }
  <bytecode: 0xcf92048>
  <environment: namespace:caretEnsemble>
   --- function search by body ---
  Function predict.caretList in namespace caretEnsemble has this body.
   ----------- END OF FAILURE REPORT -------------- 
  -- 9. Error: We can predict (@test-helper_functions.R#63)  ---------------------
  the condition has length > 1
  Backtrace:
   1. testthat::expect_warning(out <- predict(models.reg, "reg", newdata = X.reg))
   7. caretEnsemble:::predict.caretList(models.reg, "reg", newdata = X.reg)
  
   ----------- FAILURE REPORT -------------- 
   --- failure: the condition has length > 1 ---
   --- srcref --- 
  : 
   --- package (from environment) --- 
  caretEnsemble
   --- call from context --- 
  predict.caretList(models.class, "Classification", newdata = X.class)
   --- call from argument --- 
  if (class(preds) != "matrix" & class(preds) != "data.frame") {
      if (class(preds) == "character" | class(preds) == "factor") {
          preds <- as.character(preds)
      }
      preds <- as.matrix(t(preds))
  }
   --- R stacktrace ---
  where 1: predict.caretList(models.class, "Classification", newdata = X.class)
  where 2: predict(models.class, "Classification", newdata = X.class)
  where 3: eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
  where 4: withCallingHandlers(code, warning = function(condition) {
      out$push(condition)
      maybe_restart("muffleWarning")
  })
  where 5: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), 
      ...)
  where 6: quasi_capture(enquo(object), label, capture_warnings)
  where 7 at testthat/test-helper_functions.R#81: expect_warning(out <- predict(models.class, "Classification", 
      newdata = X.class))
  where 8: eval(code, test_env)
  where 9: eval(code, test_env)
  where 10: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 11: doTryCatch(return(expr), name, parentenv, handler)
  where 12: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 13: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 14: doTryCatch(return(expr), name, parentenv, handler)
  where 15: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 16: tryCatchList(expr, classes, parentenv, handlers)
  where 17: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 18: test_code(desc, code, env = parent.frame())
  where 19 at testthat/test-helper_functions.R#80: test_that("We can predict", {
      expect_warning(out <- predict(models.class, "Classification", 
          newdata = X.class))
      expect_is(out, "matrix")
      expect_true(all(dim(out) == c(150, 4)))
      expect_true(all(colnames(out) == c("rf", "glm", "rpart", 
          "treebag")))
      expect_warning(out2 <- predict(models.reg, "Regression", 
          newdata = X.reg))
      expect_true(all(dim(out2) == c(150, 4)))
      expect_true(all(colnames(out2) == c("rf", "glm", "rpart", 
          "treebag")))
  })
  where 20: eval(code, test_env)
  where 21: eval(code, test_env)
  where 22: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 23: doTryCatch(return(expr), name, parentenv, handler)
  where 24: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 25: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 26: doTryCatch(return(expr), name, parentenv, handler)
  where 27: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 28: tryCatchList(expr, classes, parentenv, handlers)
  where 29: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 30: test_code(NULL, exprs, env)
  where 31: source_file(path, new.env(parent = env), chdir = TRUE, wrap = wrap)
  where 32: force(code)
  where 33: doWithOneRestart(return(expr), restart)
  where 34: withOneRestart(expr, restarts[[1L]])
  where 35: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 36: with_reporter(reporter = reporter, start_end_reporter = start_end_reporter, 
      {
          reporter$start_file(basename(path))
          lister$start_file(basename(path))
          source_file(path, new.env(parent = env), chdir = TRUE, 
              wrap = wrap)
          reporter$.end_context()
          reporter$end_file()
      })
  where 37: FUN(X[[i]], ...)
  where 38: lapply(paths, test_file, env = env, reporter = current_reporter, 
      start_end_reporter = FALSE, load_helpers = FALSE, wrap = wrap)
  where 39: force(code)
  where 40: doWithOneRestart(return(expr), restart)
  where 41: withOneRestart(expr, restarts[[1L]])
  where 42: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 43: with_reporter(reporter = current_reporter, results <- lapply(paths, 
      test_file, env = env, reporter = current_reporter, start_end_reporter = FALSE, 
      load_helpers = FALSE, wrap = wrap))
  where 44: test_files(paths, reporter = reporter, env = env, stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 45: test_dir(path = test_path, reporter = reporter, env = env, filter = filter, 
      ..., stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, 
      wrap = wrap)
  where 46: test_package_dir(package = package, test_path = test_path, filter = filter, 
      reporter = reporter, ..., stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 47: test_check("caretEnsemble")
  
   --- value of length: 2 type: logical ---
  [1] FALSE  TRUE
   --- function from context --- 
  function (object, newdata = NULL, ..., verbose = FALSE) 
  {
      if (is.null(newdata)) {
          warning("Predicting without new data is not well supported.  Attempting to predict on the training data.")
          newdata <- object[[1]]$trainingData
          if (is.null(newdata)) {
              stop("Could not find training data in the first model in the ensemble.")
          }
      }
      if (verbose == TRUE) {
          pboptions(type = "txt", char = "*")
      }
      else if (verbose == FALSE) {
          pboptions(type = "none")
      }
      preds <- pbsapply(object, function(x) {
          type <- x$modelType
          if (type == "Classification") {
              if (x$control$classProbs) {
                  caret::predict.train(x, type = "prob", newdata = newdata, 
                    ...)[, 2]
              }
              else {
                  caret::predict.train(x, type = "raw", newdata = newdata, 
                    ...)
              }
          }
          else if (type == "Regression") {
              caret::predict.train(x, type = "raw", newdata = newdata, 
                  ...)
          }
          else {
              stop(paste("Unknown model type:", type))
          }
      })
      if (class(preds) != "matrix" & class(preds) != "data.frame") {
          if (class(preds) == "character" | class(preds) == "factor") {
              preds <- as.character(preds)
          }
          preds <- as.matrix(t(preds))
      }
      colnames(preds) <- make.names(sapply(object, function(x) x$method), 
          unique = TRUE)
      return(preds)
  }
  <bytecode: 0xcf92048>
  <environment: namespace:caretEnsemble>
   --- function search by body ---
  Function predict.caretList in namespace caretEnsemble has this body.
   ----------- END OF FAILURE REPORT -------------- 
  -- 10. Error: We can predict (@test-helper_functions.R#81)  --------------------
  the condition has length > 1
  Backtrace:
   1. testthat::expect_warning(...)
   7. caretEnsemble:::predict.caretList(...)
  
   ----------- FAILURE REPORT -------------- 
   --- failure: the condition has length > 1 ---
   --- srcref --- 
  : 
   --- package (from environment) --- 
  caretEnsemble
   --- call from context --- 
  predict.caretList(models.class, "Classification", newdata = X.class)
   --- call from argument --- 
  if (class(preds) != "matrix" & class(preds) != "data.frame") {
      if (class(preds) == "character" | class(preds) == "factor") {
          preds <- as.character(preds)
      }
      preds <- as.matrix(t(preds))
  }
   --- R stacktrace ---
  where 1: predict.caretList(models.class, "Classification", newdata = X.class)
  where 2: predict(models.class, "Classification", newdata = X.class)
  where 3: eval_bare(expr, quo_get_env(quo))
  where 4: quasi_label(enquo(object), label, arg = "object")
  where 5: expect_is(predict(models.class, "Classification", newdata = X.class), 
      "matrix")
  where 6: eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
  where 7: withCallingHandlers(code, warning = function(condition) {
      out$push(condition)
      maybe_restart("muffleWarning")
  })
  where 8: .capture(act$val <- eval_bare(quo_get_expr(.quo), quo_get_env(.quo)), 
      ...)
  where 9: quasi_capture(enquo(object), label, capture_warnings)
  where 10: expect_warning({
      expect_is(predict(models.class, "Classification", newdata = X.class), 
          "matrix")
      out1 <- predict(models.class, "Classification", newdata = X.class)
      out2 <- predict(models.class, "Classification", verbose = TRUE, 
          newdata = X.class)
      expect_identical(out1, out2)
  })
  where 11: eval(expr, pf)
  where 12: eval(expr, pf)
  where 13: withVisible(eval(expr, pf))
  where 14: evalVis(expr)
  where 15 at testthat/test-helper_functions.R#91: capture.output({
      expect_warning({
          expect_is(predict(models.class, "Classification", newdata = X.class), 
              "matrix")
          out1 <- predict(models.class, "Classification", newdata = X.class)
          out2 <- predict(models.class, "Classification", verbose = TRUE, 
              newdata = X.class)
          expect_identical(out1, out2)
      })
      expect_warning({
          expect_is(predict(models.reg, "Regression", newdata = X.reg), 
              "matrix")
          out1 <- predict(models.reg, "Regression", newdata = X.reg)
          out2 <- predict(models.reg, "Regression", verbose = TRUE, 
              newdata = X.reg)
          expect_identical(out1, out2)
      })
  })
  where 16: eval(code, test_env)
  where 17: eval(code, test_env)
  where 18: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 19: doTryCatch(return(expr), name, parentenv, handler)
  where 20: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 21: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 22: doTryCatch(return(expr), name, parentenv, handler)
  where 23: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 24: tryCatchList(expr, classes, parentenv, handlers)
  where 25: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 26: test_code(desc, code, env = parent.frame())
  where 27 at testthat/test-helper_functions.R#90: test_that("predict results same regardless of verbose option", 
      {
          sink <- capture.output({
              expect_warning({
                  expect_is(predict(models.class, "Classification", 
                    newdata = X.class), "matrix")
                  out1 <- predict(models.class, "Classification", 
                    newdata = X.class)
                  out2 <- predict(models.class, "Classification", 
                    verbose = TRUE, newdata = X.class)
                  expect_identical(out1, out2)
              })
              expect_warning({
                  expect_is(predict(models.reg, "Regression", newdata = X.reg), 
                    "matrix")
                  out1 <- predict(models.reg, "Regression", newdata = X.reg)
                  out2 <- predict(models.reg, "Regression", verbose = TRUE, 
                    newdata = X.reg)
                  expect_identical(out1, out2)
              })
          })
      })
  where 28: eval(code, test_env)
  where 29: eval(code, test_env)
  where 30: withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error)
  where 31: doTryCatch(return(expr), name, parentenv, handler)
  where 32: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  where 33: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  where 34: doTryCatch(return(expr), name, parentenv, handler)
  where 35: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), 
      names[nh], parentenv, handlers[[nh]])
  where 36: tryCatchList(expr, classes, parentenv, handlers)
  where 37: tryCatch(withCallingHandlers({
      eval(code, test_env)
      if (!handled && !is.null(test)) {
          skip_empty()
      }
  }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, 
      message = handle_message, error = handle_error), error = handle_fatal, 
      skip = function(e) {
      })
  where 38: test_code(NULL, exprs, env)
  where 39: source_file(path, new.env(parent = env), chdir = TRUE, wrap = wrap)
  where 40: force(code)
  where 41: doWithOneRestart(return(expr), restart)
  where 42: withOneRestart(expr, restarts[[1L]])
  where 43: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 44: with_reporter(reporter = reporter, start_end_reporter = start_end_reporter, 
      {
          reporter$start_file(basename(path))
          lister$start_file(basename(path))
          source_file(path, new.env(parent = env), chdir = TRUE, 
              wrap = wrap)
          reporter$.end_context()
          reporter$end_file()
      })
  where 45: FUN(X[[i]], ...)
  where 46: lapply(paths, test_file, env = env, reporter = current_reporter, 
      start_end_reporter = FALSE, load_helpers = FALSE, wrap = wrap)
  where 47: force(code)
  where 48: doWithOneRestart(return(expr), restart)
  where 49: withOneRestart(expr, restarts[[1L]])
  where 50: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  where 51: with_reporter(reporter = current_reporter, results <- lapply(paths, 
      test_file, env = env, reporter = current_reporter, start_end_reporter = FALSE, 
      load_helpers = FALSE, wrap = wrap))
  where 52: test_files(paths, reporter = reporter, env = env, stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 53: test_dir(path = test_path, reporter = reporter, env = env, filter = filter, 
      ..., stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, 
      wrap = wrap)
  where 54: test_package_dir(package = package, test_path = test_path, filter = filter, 
      reporter = reporter, ..., stop_on_failure = stop_on_failure, 
      stop_on_warning = stop_on_warning, wrap = wrap)
  where 55: test_check("caretEnsemble")
  
   --- value of length: 2 type: logical ---
  [1] FALSE  TRUE
   --- function from context --- 
  function (object, newdata = NULL, ..., verbose = FALSE) 
  {
      if (is.null(newdata)) {
          warning("Predicting without new data is not well supported.  Attempting to predict on the training data.")
          newdata <- object[[1]]$trainingData
          if (is.null(newdata)) {
              stop("Could not find training data in the first model in the ensemble.")
          }
      }
      if (verbose == TRUE) {
          pboptions(type = "txt", char = "*")
      }
      else if (verbose == FALSE) {
          pboptions(type = "none")
      }
      preds <- pbsapply(object, function(x) {
          type <- x$modelType
          if (type == "Classification") {
              if (x$control$classProbs) {
                  caret::predict.train(x, type = "prob", newdata = newdata, 
                    ...)[, 2]
              }
              else {
                  caret::predict.train(x, type = "raw", newdata = newdata, 
                    ...)
              }
          }
          else if (type == "Regression") {
              caret::predict.train(x, type = "raw", newdata = newdata, 
                  ...)
          }
          else {
              stop(paste("Unknown model type:", type))
          }
      })
      if (class(preds) != "matrix" & class(preds) != "data.frame") {
          if (class(preds) == "character" | class(preds) == "factor") {
              preds <- as.character(preds)
          }
          preds <- as.matrix(t(preds))
      }
      colnames(preds) <- make.names(sapply(object, function(x) x$method), 
          unique = TRUE)
      return(preds)
  }
  <bytecode: 0xcf92048>
  <environment: namespace:caretEnsemble>
   --- function search by body ---
  Function predict.caretList in namespace caretEnsemble has this body.
   ----------- END OF FAILURE REPORT -------------- 
  -- 11. Error: predict results same regardless of verbose option  ---------------
  the condition has length > 1
  Backtrace:
    1. testthat::expect_warning(...)
   10. caretEnsemble:::predict.caretList(...)
  
  == testthat results  ===========================================================
  [ OK: 317 | SKIPPED: 29 | WARNINGS: 3 | FAILED: 11 ]
  1. Error: caretList predictions (@test-caretList.R#109) 
  2. Error: We can stack regression models (@test-caretStack.R#23) 
  3. Error: We can stack classification models (@test-caretStack.R#36) 
  4. Error: Failure to calculate se occurs gracefully (@test-caretStack.R#64) 
  5. Error: We can extract resdiuals from caretEnsemble objects (@test-ensemble.R#43) 
  6. Error: We can ensemble regression models (@test-ensemble.R#79) 
  7. Error: It works for regression models (@test-ensemble.R#160) 
  8. Error: It works for classification models (@test-ensemble.R#176) 
  9. Error: We can predict (@test-helper_functions.R#63) 
  1. ...
  
  Error: testthat unit tests failed
  Execution halted