README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README-"
)
```

# AirportSim

The goal of AirportSim is to demonstrate how queuecomputer can be used to quickly simulate a large scale system. In this case, an airport. 

## Installation

You can install AirportSim from github with:

```{r gh-installation, eval = FALSE}
# install.packages("devtools")
devtools::install_github("AnthonyEbert/AirportSim")
```

## Example

```{r example}

library(AirportSim)

# Input data
str(airport_list_1, 1)

# Run simulation
passenger_table <- do.call(AirportSimulate1, airport_list_1)

# Show output
passenger_table

system.time(do.call(AirportSimulate1, airport_list_1))

```

Voilla! Have a look at the source code in R/AirportSimulate1.R


```{r ggplot2}

library(ggplot2)
library(dplyr)

x <- c("arrive_ac", "arrive_imm", "arrive_bh", "arrive_cus", "depart_cus")

out2 <- 
  tidyr::gather(
    passenger_table %>% select(flight, arrive_ac, arrive_imm, arrive_bh, arrive_cus, depart_cus), 
    key = "key", 
    value = "value", 
    -flight
  ) %>% 
  mutate(key = factor(key, levels = x)) %>% 
  arrange(key) 

out2_grouped <- out2 %>% group_by(flight, key) %>% summarise(value = median(value), passengers = n())

p <- ggplot(out2) + aes(x = value, fill = factor(flight)) + stat_bin(position = "stack", bins = 200, col = NA) + ylab("Passenger/min") + xlab("Time of day")  +
  geom_linerange(mapping = aes(x = value, ymin = -5, ymax = 0, col = factor(flight)), data = out2_grouped) + 
  scale_x_continuous(labels = scales::trans_format( function(x){x}, function(x){substr(lubridate::as_datetime(x * 60 + 360 * 60), 12, 16)} ), breaks = (seq(0,5, by = 0.5))*60, expand = c(0, 0), limits = c(0, 200)) +
  geom_text(mapping = aes(x = value, y = ifelse((as.numeric(substr(flight, start = 7, stop = 12)) %% 2) == 0,-15,-10), label = flight), data = out2_grouped, size = 2) + theme_bw() + theme(legend.position = "none")

p + facet_wrap(~key, ncol = 1) 

```