minor: small comment cleanup and test import changes (#184)

Author: dshemetov

R/forecasters/forecaster_flusion.R

@@ -62,7 +62,6 @@ flusion <- function(epi_data,
   args_list <- do.call(default_args_list, args_input)
   # if you want to hardcode particular predictors in a particular forecaster
   predictors <- c(outcome, extra_sources)
-  # TODO: Partial match quantile_level coming from here (on Dmitry's machine)
   c(args_list, predictors, trainer) %<-% sanitize_args_predictors_trainer(epi_data, outcome, predictors, trainer, args_list)
   # end of the copypasta
   # finally, any other pre-processing (e.g. smoothing) that isn't performed by

R/forecasters/forecaster_scaled_pop_seasonal.R

@@ -109,14 +109,14 @@ scaled_pop_seasonal <- function(epi_data,
   # end of the copypasta
 
   # whiten to get the sources on the same scale
-  # TODO Jank way to avoid having hhs_region get centered
   # finally, any other pre-processing (e.g. smoothing) that isn't performed by
   # epipredict
   if (drop_non_seasons) {
     season_data <- epi_data %>% drop_non_seasons()
   } else {
     season_data <- epi_data
   }
+  # TODO: Jank way to avoid having hhs_region get centered; this isn't very general
   learned_params <- calculate_whitening_params(season_data, setdiff(predictors, "hhs_region"), scale_method, center_method, nonlin_method)
   epi_data %<>% data_whitening(setdiff(predictors, "hhs_region"), learned_params, nonlin_method)
 

R/targets/covid_external_targets.R

@@ -32,6 +32,8 @@ create_covid_external_targets <- function() {
           # Filter to only forecasts we care about.
           filter(forecast_date %in% (forecast_dates + g_time_value_adjust)) %>%
           mutate(target_end_date = as.Date(forecast_date) + 7 * as.numeric(ahead)) %>%
+          # TODO: A very rough adjustment to get daily counts on the same scale
+          # as weekly counts.
           mutate(prediction = prediction * 7)
       }
     ),

R/targets/shared_utils.R

@@ -96,7 +96,6 @@ create_forecast_targets <- function() {
           # Push the Wednesday markers to Saturday, to match targets with truth data.
           mutate(forecast_date = forecast_date + g_time_value_adjust, target_end_date = target_end_date + g_time_value_adjust) %>%
           rename("model" = "id")
-        # browser()
         evaluate_predictions(forecasts = forecast_scaled, truth_data = hhs_evaluation_data) %>%
           rename("id" = "model")
       }

tests/testthat/test-daily-weekly-archive.R

@@ -1,4 +1,4 @@
-source(here::here("R", "load_all.R"))
+suppressPackageStartupMessages(source(here::here("R", "load_all.R")))
 
 # Works correctly if you have exactly one version where the previous Friday data
 # is the latest so it is ignored and the week before THAT is summed (10-27 to

tests/testthat/test-data-whitening.R

@@ -1,4 +1,4 @@
-source(here::here("R", "load_all.R"))
+suppressPackageStartupMessages(source(here::here("R", "load_all.R")))
 real_ex <- epidatasets::covid_case_death_rates %>%
   as_tibble() %>%
   mutate(source = "same") %>%

tests/testthat/test-forecaster-utils.R

@@ -1,4 +1,4 @@
-source(here::here("R", "load_all.R"))
+suppressPackageStartupMessages(source(here::here("R", "load_all.R")))
 
 test_that("sanitize_args_predictors_trainer", {
   epi_data <- epidatasets::covid_case_death_rates

tests/testthat/test-forecasters-basics.R

@@ -1,4 +1,4 @@
-source(here::here("R", "load_all.R"))
+suppressPackageStartupMessages(source(here::here("R", "load_all.R")))
 testthat::local_edition(3)
 # TODO better way to do this than copypasta
 forecasters <- list(

tests/testthat/test-forecasters-data.R

@@ -1,4 +1,4 @@
-source(here::here("R", "load_all.R"))
+suppressPackageStartupMessages(source(here::here("R", "load_all.R")))
 
 testthat::skip("Optional, long-running tests skipped.")
 

tests/testthat/test-latency_adjusting.R

@@ -1,4 +1,4 @@
-source(here::here("R", "load_all.R"))
+suppressPackageStartupMessages(source(here::here("R", "load_all.R")))
 
 test_that("extend_ahead", {
   # testing that POSIXct converts correctly (as well as basic types)

tests/testthat/test-step-training-window.R

@@ -1,4 +1,4 @@
-source(here::here("R", "load_all.R"))
+suppressPackageStartupMessages(source(here::here("R", "load_all.R")))
 
 data <- tribble(
   ~geo_value, ~time_value, ~version, ~value,

tests/testthat/test-transforms.R

@@ -1,4 +1,4 @@
-source(here::here("R", "load_all.R"))
+suppressPackageStartupMessages(source(here::here("R", "load_all.R")))
 
 n_days <- 20
 removed_date <- 10