Edited examples, references

Edited examples, references for `import_inputs` and `run_fredi`

FrEDI/R/import_inputs.R

@@ -79,17 +79,20 @@
 #' popInputFile  <- scenariosPath |> file.path("State ICLUS Population.csv")
 #'
 #' ### Import inputs
-#' example_inputsList <- import_inputs(
-#'   slrfile  = slrInputFile,
-#'   popfile  = popInputFile,
-#'   temptype = "global"
-#' )
+#' example_inputsList <- import_inputs(slrfile=slrInputFile, popfile=popInputFile, popArea="state")
 #'
 #' ### Use imports with FREDI:
 #' df_x <- run_fredi(inputsList=example_inputsList)
 #'
 #' @references Environmental Protection Agency (EPA). 2021. Technical Documentation on The Framework for Evaluating Damages and Impacts (FrEDI). Technical Report EPA 430-R-21-004, EPA, Washington, DC. Available at <https://epa.gov/cira/FrEDI/>.
 #'
+#' United Nations. 2015. World population prospects: The 2015 revision. New York: United Nations, Department of Economic and Social Affairs, Population Division.
+#'
+#' U.S. Census Bureau. 2021. State Population Totals and Components of Change: 2010--2019. Available at <https://www.census.gov/data/tables/time-series/demo/popest/2010s-state-total.html>.
+#'
+#' U.S. Census Bureau. 2023. State Population Totals and Components of Change: 2020--2023. Available at <https://www.census.gov/data/tables/time-series/demo/popest/2020s-state-total.html>.
+#'
+#' U.S. Census Bureau. 2023. 2023 National Population Projections Tables: Main Series. Available at <https://www.census.gov/data/tables/2023/demo/popproj/2023-summary-tables.html>.
 #'
 #' @export
 #' @md

FrEDI/R/run_fredi.R

@@ -125,7 +125,9 @@
 #' popScenario |> glimpse()
 #'
 #' ### Subset climate scenario
-#' temps1 <- gcamScenarios |> filter(scenario=="ECS_3.0_ref_0") |> select(year, temp_C)
+#' temps1 <- gcamScenarios |> filter(scenario=="Hector_GCAM_v5.3_ECS_3.0_ref")
+#' temps1 <- temps1 |> mutate(temp_C = temp_C_global |> convertTemps(from="global"))
+#' temps1 <- temps1 |> select(year, temp_C)
 #'
 #' ### Run custom scenario
 #' run2 <- run_fredi(inputsList=list(tempInput=temps1, popInput=popScenario))
@@ -142,10 +144,7 @@
 #' popInputFile  <- scenariosPath |> file.path("State ICLUS Population.csv")
 #'
 #' ### Import inputs
-#' x_inputs <- import_inputs(
-#'   slrfile  = slrInputFile,
-#'   popfile  = popInputFile
-#' )
+#' x_inputs <- import_inputs(slrfile=slrInputFile, popfile=popInputFile, popArea="state")
 #'
 #' ### Run custom scenarios
 #' run3 <- run_fredi(inputsList=x_inputs)
@@ -157,7 +156,7 @@
 #' run4 <- run_fredi(sectorList="ATS Temperature-Related Mortality", aggLevels="none", elasticity=1)
 #'
 #' ### Set end year for analysis to 2110 -- messages user and returns a null value since default scenarios only have values out to 2100
-#' run5 <- run_fredi(maxYear=2100)
+#' run5 <- run_fredi(maxYear=2110)
 #'
 #' ### Set end year for analysis to 2300 -- messages user and returns a null value since default scenarios only have values out to 2100)
 #' run6 <- run_fredi(thru2300=TRUE)