Issue 17: Fixes to data.table assignment (#18)

* Add omitted assignments

* Correct typo (draw to draws) as suggested by seabbs

* Add Adam Howes as contributor

Former-commit-id: 4306d40
Former-commit-id: 922dc6b29c49be1c61ed9cb5f71a2ab986dbb470
Former-commit-id: f72c2ad343194371b9e2018e076c50c9c4fd9c3c [formerly 1308111]
Former-commit-id: 81aa52f128e208738eae6b827d75ec32a453858f

DESCRIPTION

@@ -10,7 +10,11 @@ Authors@R:
     person(given = "Sam Abbott",
            role = c("aut"),
            email = "contact@samabbott.co.uk",
-           comment = c(ORCID = "0000-0001-8057-8037")))
+           comment = c(ORCID = "0000-0001-8057-8037")),
+    person(given = "Adam Howes",
+           role = c("aut"),
+           email = "adamthowes@gmail.com",
+           comment = c(ORCID = "0000-0003-2386-4031")))
 Description: Understanding and accurately estimating epidemiological delay
     distributions is important for public health policy. These estimates
     directly influence epidemic situational awareness, control strategies, and resource allocation. In this package, we provide methods to address the key challenges in estimating these distributions, including truncation, interval censoring, and dynamical biases. Despite their importance, these issues are frequently overlooked, often resulting in biased conclusions.

R/fitting-and-postprocessing.R

@@ -204,7 +204,7 @@ primary_censoring_bias_correction <- function(draws) {
   draws <- data.table::copy(draws)
   draws[, mean := mean - runif(.N, min = 0, max = 1)]
   draws[, meanlog := log(mean^2 / sqrt(sd^2 + mean^2))]
-  draw[, sdlog := sqrt(log(1 + (sd^2 / mean^2)))]
+  draws[, sdlog := sqrt(log(1 + (sd^2 / mean^2)))]
 
   return(draws[])
 }

R/observe.R

@@ -82,7 +82,7 @@ pad_zero <- function(data, pad = 1e-3) {
 #' @export
 drop_zero <- function(data) {
   data <- data.table::copy(data)
-  data[delay_daily != 0]
+  data <- data[delay_daily != 0]
 
   return(data)
 }

R/plot-helpers.R

@@ -9,7 +9,7 @@ calculate_cohort_mean <- function(data, type = c("cohort", "cumulative"),
     mean = mean(delay_daily), n = .N),
     by = c("ptime_daily", by)]
 
-  out[order(rank(ptime_daily))]
+  out <- out[order(rank(ptime_daily))]
 
   if (type == "cumulative") {
     out[, mean := cumsum(mean * n) / cumsum(n), by = by]

R/preprocess.R

@@ -142,7 +142,7 @@ event_to_incidence <- function(data, by = c()) {
   dd <- data.table::copy(data)
 
   dd[, .(cases = .N), by = c("ptime_daily", by)]
-  dd[order(ptime_daily)]
+  dd <- dd[order(ptime_daily)]
 
   setnames(dd, old = c("ptime_daily"), new = c("time"))