geo_exclusions 9-24, don't forecast wy

Author: dsweber2

scripts/covid_geo_exclusions.csv

@@ -11,6 +11,7 @@ forecast_date,forecaster,geo_value,weight
 2024-10-01, climate_base, all, 2
 2024-10-01, climate_geo_agged, all, 0
 2024-10-01, climate_quantile_extrapolated, all, 0
+2024-10-01, climate_linear, hi, 0.0001
 ##################
 # Sept 17
 ##################

scripts/covid_hosp_prod.R

@@ -12,10 +12,11 @@ set_targets_config()
 g_aheads <- -1:3
 g_submission_directory <- Sys.getenv("COVID_SUBMISSION_DIRECTORY", "cache")
 g_insufficient_data_geos <- c("as", "mp", "vi", "gu")
+g_insufficient_data_geos_nssp <- c(g_insufficient_data_geos, "wy")
 g_time_value_adjust <- 3
 g_fetch_args <- epidatr::fetch_args_list(return_empty = FALSE, timeout_seconds = 400)
 g_disease <- "covid"
-g_external_object_name <- glue::glue("2024/2024-2025_{g_disease}_hosp_forecasts.parquet")
+g_external_object_name <- glue::glue("exploration/2024-2025_{g_disease}_hosp_forecasts.parquet")
 # date to cut the truth data off at, so we don't have too much of the past
 g_truth_data_date <- "2023-09-01"
 # Whether we're running in backtest mode.
@@ -275,7 +276,7 @@ forecast_targets <- tar_map(
           geo_value = ifelse(geo_value == "usa", "us", geo_value),
           time_value = floor_date(time_value, "week", week_start = 7) + 3
         ) %>%
-        filter(geo_value %nin% g_insufficient_data_geos)
+        filter(geo_value %nin% g_insufficient_data_geos_nssp)
 
       if (!grepl("latest", id)) {
         nhsn_data %<>%