Test memory leak

memory-leak

# Packages -----------------------------------------------------------------
require(data.table, quietly = TRUE) 
require(future, quietly = TRUE)
## Require for data and nowcasting
# require(EpiNow, quietly = TRUE)
# require(NCoVUtils, quietly = TRUE)

## Required for forecasting
# require(future.apply, quietly = TRUE)
# require(fable, quietly = TRUE)
# require(fabletools, quietly = TRUE)
# require(feasts, quietly = TRUE)
# require(urca, quietly = TRUE)

# Get cases ---------------------------------------------------------------

NCoVUtils::reset_cache()

cases <- NCoVUtils::get_ecdc_cases()
cases <-  NCoVUtils::format_ecdc_data(cases) 
 

cases <- data.table::setDT(cases)[!is.na(region)][, 
            `:=`(local = cases, imported = 0)][, cases := NULL]

cases <- data.table::melt(cases, measure.vars = c("local", "imported"),
                          variable.name = "import_status",
                          value.name = "confirm")

## Remove regions with data issues
cases <- cases[!region %in% c("Faroe Islands", "Sao Tome and Principe", "Tajikistan")]
cases <- cases[1:2000]
# Get linelist ------------------------------------------------------------

linelist <- 
  data.table::fread("https://raw.githubusercontent.com/epiforecasts/NCoVUtils/master/data-raw/linelist.csv")


delays <- linelist[!is.na(date_onset_symptoms)][, 
                   .(report_delay = as.numeric(lubridate::dmy(date_confirmation) - 
                                                 as.Date(lubridate::dmy(date_onset_symptoms))))]

delays <- delays$report_delay

# Set up cores -----------------------------------------------------
if (!interactive()){
  options(future.fork.enable = TRUE)
}

future::plan("multiprocess",
             gc = TRUE, earlySignal = TRUE)

# Fit the reporting delay -------------------------------------------------

delay_defs <- EpiNow::get_dist_def(delays,
                                    bootstraps = 10, 
                                    samples = 50)

# Fit the incubation period -----------------------------------------------

## Mean delay
exp(EpiNow::covid_incubation_period[1, ]$mean)

## Get incubation defs
incubation_defs <- EpiNow::lognorm_dist_def(mean = EpiNow::covid_incubation_period[1, ]$mean,
                                            mean_sd = EpiNow::covid_incubation_period[1, ]$mean_sd,
                                            sd = EpiNow::covid_incubation_period[1, ]$sd,
                                            sd_sd = EpiNow::covid_incubation_period[1, ]$sd_sd,
                                            max_value = 30, samples = 50)


# future::plan("multiprocess", workers = future::availableCores(),
#              gc = TRUE, earlySignal = TRUE)
future::plan("sequential", earlySignal = TRUE, gc = TRUE)
# Run pipeline ----------------------------------------------------

EpiNow::regional_rt_pipeline(
  cases = cases,
  delay_defs = delay_defs,
  incubation_defs = incubation_defs,
  target_folder = "national",
  case_limit = 60,
  horizon = 14,
  nowcast_lag = 8,
  approx_delay = TRUE,
  report_forecast = TRUE, 
  forecast_model = function(...) {
    EpiSoon::fable_model(model = fabletools::combination_model(fable::RW(y ~ drift()), fable::ETS(y), 
                                                               fable::NAIVE(y),
                                                               cmbn_args = list(weights = "inv_var")), ...)
  }
)


future::plan("sequential")

# Summarise results -------------------------------------------------------

EpiNow::regional_summary(results_dir = "national",
                         summary_dir = "national-summary",
                         target_date = "latest",
                         region_scale = "Country",
                         csv_region_label = "country",
                         log_cases = TRUE)

Hi @adhusch - still a work in progress unfortunately though I think getting there. Any help with the code would be much appreciated at any time. Being new to valgrind I didn't find the output particularly helpful in identifying the code areas in R that were causing problems and I have not been able to find anything on how to do this - anything on this would be great.

New issue detailing progress: epiforecasts/covid#56