Running 'testthat.R' [32s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > library(testthat)
  > 
  > test_check("EventDetectR")
  Loading required package: EventDetectR
  == Skipped tests ===============================================================
  * On CRAN (2)
  
  == Failed tests ================================================================
  -- Error (test-detectionQuality.R:7:19): confusionMatrix works -----------------
  Error: invalid value 0 for 'digits' argument
  Backtrace:
      x
   1. \-EventDetectR::detectEvents(...) test-detectionQuality.R:7:18
   2.   +-stats::predict(edModel, newData)
   3.   \-EventDetectR:::predict.UnivariateForecast(edModel, newData)
   4.     +-base::as.data.frame(forecast(object$modelList[[i]], h = dataLength))
   5.     \-forecast:::as.data.frame.forecast(...)
   6.       +-base::format(tx, nsmall = nd, digits = nd)
   7.       \-base::format.default(tx, nsmall = nd, digits = nd)
   8.         \-base::prettyNum(...)
  -- Failure (test-eventClassification.R:9:15): wrongInputs lead to errors -------
  `predict(m, newDataReal[, -1])` threw an error with unexpected message.
  Expected match: "Predictions dimensions do not match newData"
  Actual message: "invalid value 0 for 'digits' argument"
  Backtrace:
       x
    1. +-testthat::expect_error(predict(m, newDataReal[, -1]), regexp = "Predictions dimensions do not match newData") test-eventClassification.R:9:14
    2. | \-testthat:::quasi_capture(...)
    3. |   +-testthat:::.capture(...)
    4. |   | \-base::withCallingHandlers(...)
    5. |   \-rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    6. +-stats::predict(m, newDataReal[, -1])
    7. \-EventDetectR:::predict.UnivariateForecast(m, newDataReal[, -1])
    8.   +-base::as.data.frame(forecast(object$modelList[[i]], h = dataLength))
    9.   \-forecast:::as.data.frame.forecast(...)
   10.     +-base::format(tx, nsmall = nd, digits = nd)
   11.     \-base::format.default(tx, nsmall = nd, digits = nd)
   12.       \-base::prettyNum(...)
  -- Error (test-eventClassification.R:18:15): prediction works correct ----------
  Error: invalid value 0 for 'digits' argument
  Backtrace:
      x
   1. +-stats::predict(m) test-eventClassification.R:18:14
   2. \-EventDetectR:::predict.UnivariateForecast(m)
   3.   +-base::as.data.frame(forecast(object$modelList[[i]], h = dataLength))
   4.   \-forecast:::as.data.frame.forecast(...)
   5.     +-base::format(tx, nsmall = nd, digits = nd)
   6.     \-base::format.default(tx, nsmall = nd, digits = nd)
   7.       \-base::prettyNum(...)
  -- Error (test-eventClassification.R:49:15): print works -----------------------
  Error: invalid value 0 for 'digits' argument
  Backtrace:
      x
   1. \-EventDetectR::detectEvents(...) test-eventClassification.R:49:14
   2.   +-stats::predict(edModel, newData)
   3.   \-EventDetectR:::predict.UnivariateForecast(edModel, newData)
   4.     +-base::as.data.frame(forecast(object$modelList[[i]], h = dataLength))
   5.     \-forecast:::as.data.frame.forecast(...)
   6.       +-base::format(tx, nsmall = nd, digits = nd)
   7.       \-base::format.default(tx, nsmall = nd, digits = nd)
   8.         \-base::prettyNum(...)
  -- Error (test-plots.R:5:15): check plots --------------------------------------
  Error: invalid value 0 for 'digits' argument
  Backtrace:
      x
   1. \-EventDetectR::detectEvents(...) test-plots.R:5:14
   2.   +-stats::predict(edModel, newData)
   3.   \-EventDetectR:::predict.UnivariateForecast(edModel, newData)
   4.     +-base::as.data.frame(forecast(object$modelList[[i]], h = dataLength))
   5.     \-forecast:::as.data.frame.forecast(...)
   6.       +-base::format(tx, nsmall = nd, digits = nd)
   7.       \-base::format.default(tx, nsmall = nd, digits = nd)
   8.         \-base::prettyNum(...)
  
  [ FAIL 5 | WARN 3 | SKIP 2 | PASS 8 ]
  Error: Test failures
  Execution halted