Merge pull request #7 from SABS-R3-Epidemiology/full_functionality

Full functionality

R/simulation_epigeopop.r

@@ -0,0 +1,89 @@
+source("R/wrapper.R")
+# Example usage:
+# Run complete simulation
+run_complete_simulation <- function(country="Andorra",
+                                    output_file = "output.csv",
+                                    sir_plot_file = "SIR_plot.png",
+                                    rt_plot_file = "Rt_plot.png",
+                                    si_plot_file = "SerialInterval_plot.png",
+                                    simulation_duration = 60,
+                                    initial_infected = 100) { 
+  output_dir <- paste0("data/", country, "/simulation_outputs")
+
+  # Initialize environment
+  pe <- initialize_simulation_env()
+
+  # User-defined variables
+  input_dir <- paste0("data/", country, "/inputs")
+  config_parameters <- paste0("data/", country, "_parameters.json")
+  seed <- 42
+
+  pe <- configure_parameters(pe, input_dir, config_parameters)
+
+  sim_params <- list(
+    simulation_start_time = as.integer(0),
+    simulation_end_time = as.integer(simulation_duration),
+    simulation_seed = TRUE,
+    initial_infected_number = as.integer(initial_infected),
+    initial_infect_cell = FALSE,
+    include_waning = TRUE
+  )
+
+  file_params <- list(
+    output_file = output_file,
+    output_dir = output_dir,
+    spatial_output = TRUE,
+    age_stratified = TRUE
+  )
+
+  dem_file_params <- list(
+    output_dir = output_dir,
+    spatial_output = TRUE,
+    age_output = TRUE
+  )
+
+  inf_history_params <- list(
+    output_dir = output_dir,
+    status_output = TRUE,
+    infectiousness_output = TRUE,
+    compress = FALSE,
+    secondary_infections_output = TRUE,
+    generation_time_output = TRUE,
+    serial_interval_output = TRUE
+  )
+
+
+  # Use Andorra population data
+  population <- create_epigeopop_population(pe, 
+  paste0("data/", country, "/inputs/", country, 
+  "_microcells.csv"))
+
+  # Run simulation
+  sim <- run_geopop_sim(pe, sim_params, 
+  file_params, dem_file_params, population, 
+  inf_history_params, seed)
+
+  # Process data
+  df_long <- process_simulation_data(file.path(output_dir, output_file))
+
+  print(colnames(df_long))
+  print(df_long)
+
+  # Generate SIR plot
+  sir_plot <- create_sir_plot(df_long, display = TRUE)
+  save_sir_plot(sir_plot, file.path(output_dir, sir_plot_file))
+
+  # Generate Rt plot
+  rt_plot <- plot_rt_curves(file.path(output_dir, "secondary_infections.csv"), 
+  location = file.path(output_dir, rt_plot_file))
+
+  # Generate Serial Interval plot
+  si_plot <- create_serial_interval_plot(file.path(output_dir, 
+  "serial_intervals.csv"), display = TRUE, 
+  location = file.path(output_dir, si_plot_file))
+
+  return(list(simulation = sim, data = df_long, 
+  sir_plot = sir_plot, rt_plot = rt_plot, si_plot = si_plot))
+}
+
+results <- run_complete_simulation()

R/simulation_toy.r

@@ -0,0 +1,97 @@
+source("R/wrapper.R")
+# Example usage:
+# Run complete simulation
+run_complete_simulation <- function(output_dir="data/toy/simulation_outputs",
+                                    output_file = "output.csv",
+                                    sir_plot_file = "SIR_plot.png",
+                                    rt_plot_file = "Rt_plot.png",
+                                    si_plot_file = "SerialInterval_plot.png",
+                                    use_toy_example = TRUE,
+                                    simulation_duration = 60,
+                                    initial_infected = 10) {
+  # Initialize environment
+  pe <- initialize_simulation_env()
+
+  # User-defined variables
+  input_dir <- ""
+  config_parameters <- "data/toy/simple_parameters.json"
+  seed <- 42
+
+  pe <- configure_parameters(pe, input_dir, config_parameters)
+
+  # Create all parameter sets
+  pop_params <- list(
+    population_size = as.integer(100),
+    cell_number = as.integer(2),
+    microcell_number = as.integer(2),
+    household_number = as.integer(5),
+    place_number = as.integer(2)
+  )
+
+  sim_params <- list(
+    simulation_start_time = as.integer(0),
+    simulation_end_time = as.integer(simulation_duration),
+    simulation_seed = TRUE,
+    initial_infected_number = as.integer(initial_infected),
+    initial_infect_cell = TRUE,
+    include_waning = TRUE
+  )
+
+  file_params <- list(
+    output_file = output_file,
+    output_dir = output_dir,
+    spatial_output = FALSE,
+    age_stratified = FALSE
+  )
+
+  dem_file_params <- list(
+    output_dir = output_dir,
+    spatial_output = FALSE,
+    age_output = FALSE
+  )
+
+  inf_history_params <- list(
+    output_dir = output_dir,
+    status_output = TRUE,
+    infectiousness_output = TRUE,
+    compress = FALSE,
+    secondary_infections_output = TRUE,
+    generation_time_output = TRUE,
+    serial_interval_output = TRUE
+  )
+
+  # Select population creation function
+  population_creation_function <- if (use_toy_example) create_toy_population else create_epigeopop_population
+   # nolint: line_length_linter.
+  population <- population_creation_function(pe, if (use_toy_example) pop_params else "data/epigeopop.csv")
+
+  # Run simulation
+  sim <- run_simulation(pe, sim_params, file_params, 
+  dem_file_params, population, inf_history_params, seed)
+
+  # Process data
+  df_long <- process_simulation_data(file.path(output_dir, output_file))
+
+  print(colnames(df_long))
+  print(df_long)
+
+  # Generate SIR plot
+  sir_plot <- create_sir_plot(df_long, display = TRUE)
+  save_sir_plot(sir_plot, file.path(output_dir, sir_plot_file))
+
+
+  # Generate Rt plot
+  rt_plot <- plot_rt_curves(file.path(output_dir,
+   "secondary_infections.csv"), 
+   location = file.path(output_dir, rt_plot_file))
+
+  # Generate Serial Interval plot
+  si_plot <- create_serial_interval_plot(file.path(output_dir,
+   "serial_intervals.csv"), display = TRUE, 
+   location = file.path(output_dir, si_plot_file))
+
+  return(list(simulation = sim, data = df_long,
+   sir_plot = sir_plot, rt_plot = "", si_plot = ""))
+}
+
+results <- run_complete_simulation()