Running ‘testthat.R’ [31m/31m]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > 
  > # Machine Learning
  > library(tidymodels)
  ── Attaching packages ────────────────────────────────────── tidymodels 0.1.2 ──
  ✔ broom     0.7.5      ✔ recipes   0.1.15
  ✔ dials     0.0.9      ✔ rsample   0.0.9 
  ✔ dplyr     1.0.5      ✔ tibble    3.1.0 
  ✔ ggplot2   3.3.3      ✔ tidyr     1.1.3 
  ✔ infer     0.5.4      ✔ tune      0.1.3 
  ✔ modeldata 0.1.0      ✔ workflows 0.2.2 
  ✔ parsnip   0.1.5      ✔ yardstick 0.0.7 
  ✔ purrr     0.3.4      
  ── Conflicts ───────────────────────────────────────── tidymodels_conflicts() ──
  ✖ purrr::discard() masks scales::discard()
  ✖ dplyr::filter()  masks stats::filter()
  ✖ purrr::is_null() masks testthat::is_null()
  ✖ dplyr::lag()     masks stats::lag()
  ✖ tidyr::matches() masks rsample::matches(), dplyr::matches(), testthat::matches()
  ✖ recipes::step()  masks stats::step()
  > library(modeltime)
  > library(modeltime.ensemble)
  Loading required package: modeltime.resample
  > library(modeltime.resample)
  > 
  > library(xgboost)
  
  Attaching package: 'xgboost'
  
  The following object is masked from 'package:dplyr':
  
      slice
  
  > 
  > # Core Packages
  > library(tidyverse)
  ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
  ✔ readr   1.4.0     ✔ forcats 0.5.1
  ✔ stringr 1.4.0     
  ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
  ✖ readr::col_factor() masks scales::col_factor()
  ✖ purrr::discard()    masks scales::discard()
  ✖ dplyr::filter()     masks stats::filter()
  ✖ stringr::fixed()    masks recipes::fixed()
  ✖ purrr::is_null()    masks testthat::is_null()
  ✖ dplyr::lag()        masks stats::lag()
  ✖ tidyr::matches()    masks rsample::matches(), dplyr::matches(), testthat::matches()
  ✖ xgboost::slice()    masks dplyr::slice()
  ✖ readr::spec()       masks yardstick::spec()
  > library(timetk)
  > library(lubridate)
  
  Attaching package: 'lubridate'
  
  The following objects are masked from 'package:base':
  
      date, intersect, setdiff, union
  
  > 
  > test_check("modeltime.ensemble")
  ── Modeltime Ensemble ───────────────────────────────────────────
  Ensemble of 3 Models (MEDIAN)
  
  # Modeltime Table
  # A tibble: 3 x 3
    .model_id .model     .model_desc            
        <int> <list>     <chr>                  
  1         1 <workflow> ARIMA(0,1,1)(0,1,1)[12]
  2         2 <workflow> PROPHET                
  3         3 <workflow> GLMNET                 
  ── Fitting Non-Tunable Model Specification ──────────────────────
  
  # A tibble: 4 x 3
    .model_id  rmse .model_desc            
    <chr>     <dbl> <chr>                  
  1 1          579. ARIMA(0,1,1)(0,1,1)[12]
  2 2          381. PROPHET                
  3 3          558. GLMNET                 
  4 ensemble   128. ENSEMBLE (MODEL SPEC)  
  
  ── Final Model ──────────────────────────────────────────────────
  
  ══ Workflow [trained] ══════════════════════════════════════════════════════════
  Preprocessor: Recipe
  Model: linear_reg()
  
  ── Preprocessor ────────────────────────────────────────────────────────────────
  0 Recipe Steps
  
  ── Model ───────────────────────────────────────────────────────────────────────
  
  Call:
  stats::lm(formula = ..y ~ ., data = data)
  
  Coefficients:
  (Intercept)  .model_id_1  .model_id_2  .model_id_3  
   -2637.2266       0.5754      -0.1919       0.8550  
  
  
  1.522 sec elapsed
  
  ── Modeltime Ensemble ───────────────────────────────────────────
  Ensemble of 3 Models (LM STACK)
  
  # Modeltime Table
  # A tibble: 3 x 3
    .model_id .model     .model_desc            
        <int> <list>     <chr>                  
  1         1 <workflow> ARIMA(0,1,1)(0,1,1)[12]
  2         2 <workflow> PROPHET                
  3         3 <workflow> GLMNET                 
  ── Modeltime Ensemble ───────────────────────────────────────────
  Ensemble of 3 Models (GLMNET STACK)
  
  # Modeltime Table
  # A tibble: 3 x 3
    .model_id .model     .model_desc            
        <int> <list>     <chr>                  
  1         1 <workflow> ARIMA(0,1,1)(0,1,1)[12]
  2         2 <workflow> PROPHET                
  3         3 <workflow> GLMNET                 
  ── Modeltime Ensemble ───────────────────────────────────────────
  Ensemble of 3 Models (WEIGHTED)
  
  # Modeltime Table
  # A tibble: 3 x 4
    .model_id .model     .model_desc             .loadings
        <int> <list>     <chr>                       <dbl>
  1         1 <workflow> ARIMA(0,1,1)(0,1,1)[12]     0.5  
  2         2 <workflow> PROPHET                     0.333
  3         3 <workflow> GLMNET                      0.167