Speed up vignettes, change copyright format for CRAN, remove donttest…

… in examples

LICENSE

@@ -1,21 +1,2 @@
-MIT License
-
-Copyright (c) 2019 Nickalus Redell
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
+YEAR: 2019
+COPYRIGHT HOLDER: Nickalus Redell

LICENSE.md

@@ -1,21 +1,2 @@
-# MIT License
-
-Copyright (c) 2019 Nickalus Redell
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
+YEAR: 2019
+COPYRIGHT HOLDER: Nickalus Redell

R/examples/example_create_lagged_df.R

@@ -1,4 +1,3 @@
-\donttest{
 # Sampled Seatbelts data from the R package datasets.
 data("data_seatbelts", package = "forecastML")
 #------------------------------------------------------------------------------
@@ -26,4 +25,3 @@ data_train <- create_lagged_df(data_seatbelts, type = "train", outcome_cols = 1,
                                lookback_control = lookback, horizon = horizons)
 head(data_train[[length(horizons)]])
 #------------------------------------------------------------------------------
-}

R/examples/example_create_windows.R

@@ -1,4 +1,3 @@
-\donttest{
 # Sampled Seatbelts data from the R package datasets.
 data("data_seatbelts", package = "forecastML")
 
@@ -10,4 +9,3 @@ data_train <- create_lagged_df(data_seatbelts, type = "train", outcome_cols = 1,
                                lookback = lookback, horizon = horizons)
 
 create_windows(data_train, window_length = 12)
-}

R/examples/example_fill_gaps.R

@@ -1,20 +1,17 @@
-\donttest{
+# NOAA buoy dataset with gaps in data collection
+data("data_buoy_gaps", package = "forecastML")
 
-  # NOAA buoy dataset with gaps in data collection
-  data("data_buoy_gaps", package = "forecastML")
+data_buoy_no_gaps <- fill_gaps(data_buoy_gaps, date_col = 1, frequency = '1 day',
+                               groups = 'buoy_id', static_features = c('lat', 'lon'))
 
-  data_buoy_no_gaps <- fill_gaps(data_buoy_gaps, date_col = 1, frequency = '1 day',
-                                 groups = 'buoy_id', static_features = c('lat', 'lon'))
+# The returned data.frame has the same number of columns but the time-series
+# are now evenly spaced at 1 day apart. Additionally, the unchanging grouping
+# columns and static features columns have been filled in for the newly created dataset rows.
+dim(data_buoy_gaps)
+dim(data_buoy_no_gaps)
 
-  # The returned data.frame has the same number of columns but the time-series
-  # are now evenly spaced at 1 day apart. Additionally, the unchanging grouping
-  # columns and static features columns have been filled in for the newly created dataset rows.
-  dim(data_buoy_gaps)
-  dim(data_buoy_no_gaps)
-
-  # Running create_lagged_df() is the next step in the forecastML forecasting
-  # process. If there are long gaps in data collection, like in this buoy dataset,
-  # and the user-supplied modeling algorithm cannot handle missing outcomes data,
-  # the best option is to filter these rows out in the user-supplied modeling function
-  # for train_model()
-}
+# Running create_lagged_df() is the next step in the forecastML forecasting
+# process. If there are long gaps in data collection, like in this buoy dataset,
+# and the user-supplied modeling algorithm cannot handle missing outcomes data,
+# the best option is to filter these rows out in the user-supplied modeling function
+# for train_model()

R/examples/example_plot_lagged_df.R

@@ -1,4 +1,3 @@
-\donttest{
 # Sampled Seatbelts data from the R package datasets.
 data("data_seatbelts", package = "forecastML")
 #------------------------------------------------------------------------------
@@ -17,5 +16,3 @@ lookback <- list(c(3, 6, 9, 12), c(4:12), c(6:15), c(8))
 data_train <- create_lagged_df(data_seatbelts, type = "train", outcome_cols = 1,
                                lookback_control = lookback, horizon = horizons)
 plot(data_train)
-#------------------------------------------------------------------------------
-}

R/examples/example_plot_windows.R

@@ -1,4 +1,3 @@
-\donttest{
 # Sampled Seatbelts data from the R package datasets.
 data("data_seatbelts", package = "forecastML")
 
@@ -12,4 +11,3 @@ data_train <- create_lagged_df(data_seatbelts, type = "train", outcome_cols = 1,
 windows <- create_windows(data_train, window_length = 12)
 
 plot(windows, data_train)
-}

R/examples/example_predict_train_model.R

@@ -1,4 +1,3 @@
-\donttest{
 # Sampled Seatbelts data from the R package datasets.
 data("data_seatbelts", package = "forecastML")
 
@@ -57,4 +56,3 @@ data_forecast <- create_lagged_df(data_seatbelts, type = "forecast", outcome_col
 
 data_forecasts <- predict(model_results, prediction_function = list(prediction_function),
                           data = data_forecast)
-}

R/examples/example_return_error.R

@@ -1,4 +1,3 @@
-\donttest{
 # Sampled Seatbelts data from the R package datasets.
 data("data_seatbelts", package = "forecastML")
 
@@ -53,4 +52,3 @@ data_valid <- predict(model_results, prediction_function = list(prediction_funct
 
 # Forecast error metrics for validation datasets.
 data_error <- return_error(data_valid)
-}

R/examples/example_return_hyper.R

@@ -1,4 +1,3 @@
-\donttest{
 # Sampled Seatbelts data from the R package datasets.
 data("data_seatbelts", package = "forecastML")
 
@@ -70,4 +69,3 @@ data_hyper <- return_hyper(model_results, hyper_function)
 
 plot(data_hyper, data_valid, data_error, type = "stability",
      horizons = c(1, 12))
-}

R/examples/example_train_model.R

@@ -1,4 +1,3 @@
-\donttest{
 # Sampled Seatbelts data from the R package datasets.
 data("data_seatbelts", package = "forecastML")
 
@@ -35,4 +34,3 @@ model_results <- train_model(data_train, windows, model_name = "LASSO", model_fu
 # View the results for the model (a) trained on the first horizon
 # and (b) to be assessed on the first outer-loop validation window.
 model_results$horizon_1$window_1$model
-}

vignettes/custom_functions.Rmd

@@ -1,6 +1,6 @@
 ---
 title: "Customizing Wrapper Functions"
-author: "Nickalus Redell, nickalusredell@gmail.com"
+author: "Nickalus Redell"
 date: "`r lubridate::today()`"
 output: rmarkdown::html_vignette
 vignette: >