Add r_calc functions

R0estimation/r_calc.R

@@ -0,0 +1,86 @@
+#' Combine dataframes together by column
+#'
+#' @param region
+#' @param country
+#' @details 
+#'
+#' @examples
+#' r_calc_epinow('Scotland')
+#'
+#' @export r_calc_epinow 
+r_calc_epinow <- function(region, country = 'all countries'){
+  require(EpiNow, quietly = TRUE)
+  require(NCoVUtils, quietly = TRUE)
+  require(furrr, quietly = TRUE)
+  require(future, quietly = TRUE)
+  require(dplyr, quietly = TRUE)
+  require(tidyr, quietly = TRUE)
+  require(magrittr, quietly = TRUE)
+  require(forecastHybrid, quietly = TRUE)
+  require(data.table, quietly = TRUE)
+
+  epinow_codeloc = 'C:/Users/12SDa/davenpor/davenpor/Private_Projects/Covid/EpiNowForecast/'
+  save_dir <- paste0(epinow_codeloc, region)   
+  delay_loc = paste0(epinow_codeloc, 'Delay_Files/delays_', region, '.rds')
+  delay_defs <- readRDS(delay_loc)
+
+  NCoVUtils::reset_cache()
+  cases <- NCoVUtils::get_uk_regional_cases(geography = country)
+
+  regional_cases = as.data.table(filter(cases, region == region))
+  regional_cases = data.table::setDT(regional_cases)
+  regional_cases <- regional_cases[, `:=`(confirm = as.integer(cases), import_status = "local")][,
+                                                                                             cases := NULL]
+  rt_pipeline(cases = london_cases,
+              delay_defs = delay_defs,
+              target_date = max(regional_cases$date),
+              target_folder = save_dir)
+
+  knitr::include_graphics(paste0(target_dir, "/latest/rt_cases_plot.png"))
+}
+
+#' Combine dataframes together by column
+#'
+#' @param cases
+#' @details this function can combine dataframes which have different numbers of rows,
+#' replacing undefined rows with NAs.
+#'
+#' @examples
+#' h1 = data.frame(matrix(1:6,2))
+#' h2 = data.frame(matrix(1:3,1))
+#' cbinddf(h1,h2)
+#'
+#' @export county_r
+county_r <- function(county){
+  require(EpiNow, quietly = TRUE)
+  require(NCoVUtils, quietly = TRUE)
+  require(furrr, quietly = TRUE)
+  require(future, quietly = TRUE)
+  require(dplyr, quietly = TRUE)
+  require(tidyr, quietly = TRUE)
+  require(magrittr, quietly = TRUE)
+  require(forecastHybrid, quietly = TRUE)
+  require(data.table, quietly = TRUE)
+
+  gitrep_loc = 'C:/Users/12SDa/davenpor/davenpor/Other_Toolboxes/COVID19CCT/'
+  code_loc = paste0(gitrep_loc,'R0calcutations/')
+  save_dir <- paste0(code_loc, 'Counties/',region)   
+  delay_loc = paste0(code_loc, 'delays.rds')
+  delay_defs <- readRDS(delay_loc)
+
+  cases = load(paste0(code_loc, 'covid_data.csv'))
+  names(us_cases)[1] = c('County')
+  ndates = length(us_cases) - 1;
+  names(us_cases)[2:length(us_cases)] = as.character(seq(1,ndates))
+
+  county_cases = as.data.table(filter(cases, region == region))
+  county_cases = data.table::setDT(county_cases)
+  county_cases <- county_cases[, `:=`(confirm = as.integer(cases), import_status = "local")][,cases := NULL]
+
+  rt_pipeline(cases = london_cases,
+              delay_defs = delay_defs,
+              target_date = max(regional_cases$date),
+              target_folder = save_dir)
+
+  knitr::include_graphics(paste0(target_dir, "/latest/rt_cases_plot.png"))
+}