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amyheatheramyheather
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fix(results): remove arrivals with start time -1 (have confirmed for all that this means the time to next arrival was sampled for that patient, but it meant their arrival time came after the simulation end)
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Lines changed: 83 additions & 26 deletions

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‎NAMESPACE‎

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Original file line numberDiff line numberDiff line change
@@ -13,6 +13,7 @@ export(create_rehab_trajectory)
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export(model)
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export(sample_routing)
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export(transform_to_lnorm)
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importFrom(dplyr,filter)
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importFrom(simmer,add_generator)
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importFrom(simmer,branch)
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importFrom(simmer,get_attribute)

‎R/model.R‎

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@@ -6,6 +6,7 @@
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#' may not wish to do if being set elsewhere - such as done in \code{runner()}).
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#' Default is TRUE.
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#'
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#' @importFrom dplyr filter
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#' @importFrom simmer get_mon_arrivals get_mon_resources simmer wrap
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#' @importFrom utils capture.output
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#'
@@ -27,6 +28,7 @@ model <- function(run_number, param, set_seed = TRUE) {
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param[["rehab_los_lnorm"]] <- transform_to_lnorm(param[["rehab_los"]])
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# Create simmer environment - set verbose to FALSE as using custom logs
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# (but can change to TRUE if want to see default simmer logs as well)
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env <- simmer("simulation", verbose = FALSE)
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# Add ASU and rehab direct admission patient generators
@@ -41,14 +43,12 @@ model <- function(run_number, param, set_seed = TRUE) {
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}
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# Add patient generator using the created trajectory
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sim_log <- capture.output(
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env <- add_patient_generator( # nolint
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env = env,
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trajectory = traj,
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unit = unit,
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patient_type = patient_type,
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param = param
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)
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env <- add_patient_generator(
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env = env,
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trajectory = traj,
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unit = unit,
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patient_type = patient_type,
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param = param
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)
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}
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}
@@ -75,12 +75,11 @@ model <- function(run_number, param, set_seed = TRUE) {
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}
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}
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# Extract the monitored arrivals and resources information from the simmer
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# environment object
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result <- list(
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arrivals = get_mon_arrivals(env, per_resource = TRUE, ongoing = TRUE),
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resources = get_mon_resources(env)
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)
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# Extract the monitored arrivals info from the simmer environment object.
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# Remove patients with start time of -1, as they are patients whose arrival
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# was sampled but falls after the end of the smiulation.
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result <- get_mon_arrivals(env, ongoing = TRUE) |>
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filter(.data[["start_time"]] != -1L)
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return(result)
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}

‎rmarkdown/analysis.Rmd‎

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@@ -11,13 +11,18 @@ output:
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```{r}
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# Load the package from the local directory
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devtools::load_all()
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```
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```{r}
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# nolint start: undesirable_function_linter
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# Load the package
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library(dplyr)
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library(simulation)
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# nolint end
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```
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```{r}
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param <- create_parameters(log_to_console = TRUE)
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model(run_number = 1L, param = param, set_seed = TRUE)
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result <- model(run_number = 1L, param = param, set_seed = TRUE)
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arrange(result, start_time)
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```

‎rmarkdown/analysis.md‎

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@@ -1,7 +1,7 @@
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analysis
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================
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Amy Heather
4-
2025-07-01
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2025-07-02
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``` r
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# Load the package from the local directory
@@ -11,13 +11,30 @@ devtools::load_all()
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## ℹ Loading simulation
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``` r
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# nolint start: undesirable_function_linter
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# Load the package
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library(dplyr)
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```
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##
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## Attaching package: 'dplyr'
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## The following objects are masked from 'package:stats':
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##
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## filter, lag
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## The following objects are masked from 'package:base':
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##
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## intersect, setdiff, setequal, union
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``` r
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library(simulation)
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# nolint end
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```
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``` r
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param <- create_parameters(log_to_console = TRUE)
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model(run_number = 1L, param = param, set_seed = TRUE)
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result <- model(run_number = 1L, param = param, set_seed = TRUE)
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```
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## [1] "Parameters:"
@@ -174,11 +191,46 @@ model(run_number = 1L, param = param, set_seed = TRUE)
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## [152] "19.8821: asu_stroke19: 🎯 Planned ASU -> 3 (other)"
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## [153] "19.8821: asu_stroke19: ⏳ ASU length of stay: 1.819"
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## $arrivals
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## [1] name start_time end_time activity_time resource
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## <0 rows> (or 0-length row.names)
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##
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## $resources
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## [1] resource time server queue capacity queue_size system
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## [8] limit
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## <0 rows> (or 0-length row.names)
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``` r
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arrange(result, start_time)
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```
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## name start_time end_time activity_time finished replication
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## 1 asu_other0 0.4473448 2.676165 2.2288198 TRUE 1
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## 2 asu_neuro0 0.5245442 4.171772 3.6472278 TRUE 1
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## 3 asu_stroke0 0.9062182 1.422308 0.5160899 TRUE 1
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## 4 asu_stroke1 1.1893125 5.509324 4.3200113 TRUE 1
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## 5 asu_other1 1.2902898 6.502389 5.2120987 TRUE 1
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## 6 asu_stroke2 1.9750085 12.640820 10.6658111 TRUE 1
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## 7 asu_stroke3 2.6540471 7.370079 4.7160317 TRUE 1
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## 8 asu_other2 2.7220399 6.960086 4.2380463 TRUE 1
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## 9 asu_neuro1 3.2678517 3.867813 0.5999612 TRUE 1
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## 10 asu_other3 5.9118414 9.356139 3.4442981 TRUE 1
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## 11 asu_other4 6.5630745 9.901922 3.3388479 TRUE 1
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## 12 asu_neuro2 6.7174941 NA NA FALSE 1
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## 13 asu_stroke4 7.4047666 11.548437 4.1436706 TRUE 1
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## 14 asu_stroke5 7.7291507 10.492783 2.7636327 TRUE 1
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## 15 asu_other5 8.9680111 9.644429 0.6764179 TRUE 1
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## 16 asu_stroke6 9.2809003 10.249020 0.9681194 TRUE 1
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## 17 rehab_stroke0 9.5062960 NA NA FALSE 1
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## 18 asu_stroke7 9.9287833 18.114076 8.1852931 TRUE 1
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## 19 asu_stroke8 10.0363922 NA NA FALSE 1
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## 20 asu_stroke9 10.3331093 10.844631 0.5115214 TRUE 1
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## 21 asu_neuro3 10.6050662 14.143857 3.5387909 TRUE 1
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## 22 asu_tia0 10.9892778 12.129621 1.1403433 TRUE 1
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## 23 asu_neuro4 13.5331919 NA NA FALSE 1
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## 24 asu_stroke10 13.6095765 16.845102 3.2355256 TRUE 1
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## 25 asu_neuro5 13.7205915 15.051997 1.3314053 TRUE 1
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## 26 asu_stroke11 13.8532754 NA NA FALSE 1
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## 27 asu_other6 13.8727452 15.859368 1.9866225 TRUE 1
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## 28 asu_stroke12 13.9904583 15.084152 1.0936941 TRUE 1
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## 29 rehab_stroke1 14.0813875 NA NA FALSE 1
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## 30 asu_stroke13 15.8908936 18.801468 2.9105743 TRUE 1
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## 31 asu_neuro6 16.6529204 NA NA FALSE 1
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## 32 asu_stroke14 17.1432238 NA NA FALSE 1
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## 33 asu_stroke15 18.1849052 NA NA FALSE 1
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## 34 asu_stroke16 18.3422720 NA NA FALSE 1
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## 35 asu_stroke17 18.8504573 NA NA FALSE 1
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## 36 asu_other7 19.7390660 NA NA FALSE 1
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## 37 asu_stroke18 19.8417499 NA NA FALSE 1
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## 38 asu_stroke19 19.8820623 NA NA FALSE 1

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