Running 'testthat.R' [11m]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > library(testthat)
  > library(finnts)
  Loading required package: modeltime
  > 
  > test_check("finnts")
  
  -- Prepping Data ---------------------------------------------------------------
  Joining with `by = join_by(Combo, Date)`
  
  -- Kicking off Finn Modeling Process -------------------------------------------
  
  -- Running Combo: M750 --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Creating Simple Model Averages ----------------------------------------------
  
  -- Final Finn Outputs ----------------------------------------------------------
  
  -- Selecting Best Model 
  Joining with `by = join_by(Combo, Model)`
  Joining with `by = join_by(Combo, Model)`
  Joining with `by = join_by(Combo, Model)`
  Joining with `by = join_by(Combo, Model)`
   [1] "First Dt Val M750"       "First Dt Val M750"      
   [3] "First Dt Val 16587"      "First Dt Val Historical"
   [5] "First Dt Val NA"         "First Dt Val 11000"     
   [7] "First Dt Val 11000"      "First Dt Val 11000"     
   [9] "First Dt Val 11000"      "First Dt Val 11000"     
  
  -- Prepping Data ---------------------------------------------------------------
  Since argument characters are not specified, the default labelling system is used.
  Joining with `by = join_by(Combo, Date)`
  
  -- Kicking off Finn Modeling Process -------------------------------------------
  
  -- Running Combo: A --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: A..AA --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: A..AB --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: A..AC --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: B --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: B..BA --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: B..BB --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: Total --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Creating Simple Model Averages ----------------------------------------------
  
  -- Final Finn Outputs ----------------------------------------------------------
  
  -- Selecting Best Model 
  
  -- Reconciling Hierarchical Forecast 
  Joining with `by = join_by(Combo, Model)`
  Joining with `by = join_by(Combo, Model)`
  Since argument characters are not specified, the default labelling system is used.
  Joining with `by = join_by(Date, Combo)`
  Joining with `by = join_by(Combo, Model)`
   [1] "First Dt Val B--BB"           "First Dt Val B"              
   [3] "First Dt Val BB"              "First Dt Val 11504"          
   [5] "First Dt Val Historical"      "First Dt Val NA"             
   [7] "First Dt Val 12.537166248181" "First Dt Val 12.537166248181"
   [9] "First Dt Val 12.537166248181" "First Dt Val 12.537166248181"
  [11] "First Dt Val 12.537166248181"
  
  -- Prepping Data ---------------------------------------------------------------
  Joining with `by = join_by(Combo, Date)`
  
  -- Kicking off Finn Modeling Process -------------------------------------------
  
  -- Running Combo: ACT..female --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: ACT..male --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: NSW..female --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: NSW..male --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: NT..female --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: NT..male --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: QLD..female --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: QLD..male --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: SA..female --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: SA..male --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: Sex.female --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: Sex.male --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: State.ACT --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: State.NSW --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: State.NT --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: State.QLD --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: State.SA --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: State.TAS --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: State.VIC --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: State.WA --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: TAS..female --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: TAS..male --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: Total --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: VIC..female --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: VIC..male --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: WA..female --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Running Combo: WA..male --
  
  -- Initial Feature Engineering 
  
  -- Individual Model Training 
  v Known model:meanf function:meanf
  v Known model:snaive function:snaive
  i Function being called: meanf
  v meanf
  i Function being called: snaive
  v snaive
  # Modeltime Table
  # A tibble: 2 x 3
    .model_id .model     .model_desc
        <int> <list>     <chr>      
  1         1 <workflow> snaive     
  2         2 <workflow> meanf      
  # Modeltime Table
  # A tibble: 0 x 3
  # ... with 3 variables: .model_id <int>, .model <list>, .model_desc <chr>
  
  -- Refitting Individual Models 
  Data is not ordered by the 'date_var'. Resamples will be arranged by `Date`.
  Overlapping Timestamps Detected. Processing overlapping time series together using sliding windows.
  Joining with `by = join_by(.id, .row)`
  
  -- Forecast Output 
  
  -- Creating Simple Model Averages ----------------------------------------------
  
  -- Final Finn Outputs ----------------------------------------------------------
  
  -- Selecting Best Model 
  
  -- Reconciling Hierarchical Forecast 
  Joining with `by = join_by(Combo, Model)`
  Joining with `by = join_by(Combo, Model)`
  Joining with `by = join_by(Date, Combo)`
  Joining with `by = join_by(Combo, Model)`
   [1] "First Dt Val WA--male"   "First Dt Val WA"        
   [3] "First Dt Val male"       "First Dt Val 12234"     
   [5] "First Dt Val Historical" "First Dt Val NA"        
   [7] "First Dt Val 54"         "First Dt Val 54"        
   [9] "First Dt Val 54"         "First Dt Val 54"        
  [11] "First Dt Val 54"        
  [ FAIL 2 | WARN 10 | SKIP 0 | PASS 111 ]
  
  == Failed tests ================================================================
  -- Failure ('test-forecast_time_series.R:195'): final forecast data rows are meaningful --
  nrow(future_frame) (`actual`) not equal to length(unique(inp_data_combos$Combo)) * forecast_horizon (`expected`).
  
    `actual`:  8
  `expected`: 15
  -- Failure ('test-forecast_time_series.R:294'): final forecast data rows are meaningful --
  nrow(future_frame) (`actual`) not equal to length(unique(inp_data_combos$Combo)) * forecast_horizon (`expected`).
  
    `actual`: 27
  `expected`: 48
  
  [ FAIL 2 | WARN 10 | SKIP 0 | PASS 111 ]
  Error: Test failures
  Execution halted