Class notes CS1001

8. Warm-up interval




Coding:

# Load necessary libraries

library(dplyr)

library(tibble)



# Define the initial state of the system

initial_state <- list(

current_time = 0,

events = data.frame(time = numeric(), event = character(), stringsAsFactors = FALSE),

event_log = tibble(time = numeric(), event = character()),

warm_up_time = 0, # Time before data collection starts

data_collected = tibble(time = numeric(), data = numeric())

)



# Function to schedule an event

schedule_event <- function(state, event_time, event_description) {

new_event <- data.frame(time = event_time, event = event_description, stringsAsFactors = FALSE)

state$events <- bind_rows(state$events, new_event) %>%

arrange(time) # Keep events sorted

return(state)

}



# Function to process the next event

process_event <- function(state) {

if (nrow(state$events) == 0) {

return(state) # No more events to process

, }



# Get the next event

next_event <- state$events[1, ]



# Update current time

state$current_time <- next_event$time



# Log the event

state$event_log <- bind_rows(state$event_log, tibble(time = state$current_time, event =
next_event$event))



# Collect data after warm-up period

if (state$current_time >= state$warm_up_time) {

# Example of data collection (e.g., random data)

data_value <- rnorm(1) # Random data for illustration

state$data_collected <- bind_rows(state$data_collected, tibble(time = state$current_time, data =
data_value))

}



# Remove the processed event

state$events <- state$events[-1, ]



return(state)

}



# Initialize the system state

state <- initial_state

state$warm_up_time <- 5 # Set the warm-up period