## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----------------------------------------------------------------------------- # Locate the example YAML configuration file yaml_file <- system.file("extdata", "example_config.yaml", package = "MetaRVM") print(yaml_file) ## ----results='hide'----------------------------------------------------------- # Load the metaRVM library library(MetaRVM) options(odin.verbose = FALSE) # Run the simulation sim_out <- metaRVM(yaml_file) ## ----------------------------------------------------------------------------- # Load configuration from YAML file config_obj <- MetaRVMConfig$new(yaml_file) # Examine the configuration config_obj ## ----------------------------------------------------------------------------- # List all available parameters param_names <- config_obj$list_parameters() head(param_names, 10) # Get a summary of parameter types and sizes param_summary <- config_obj$parameter_summary() head(param_summary, 10) ## ----------------------------------------------------------------------------- # Get demographic categories age_categories <- config_obj$get_age_categories() race_categories <- config_obj$get_race_categories() zones <- config_obj$get_zones() cat("Age categories:", paste(age_categories, collapse = ", "), "\n") cat("Race categories:", paste(race_categories, collapse = ", "), "\n") cat("Geographic zones:", paste(zones, collapse = ", "), "\n") ## ----------------------------------------------------------------------------- # Method 1: Direct from file path # sim_out <- metaRVM(config_file) # Method 2: From MetaRVMConfig object sim_out <- metaRVM(config_obj) # Method 3: From parsed configuration list config_list <- parse_config(yaml_file) sim_out <- metaRVM(config_list) ## ----------------------------------------------------------------------------- # Look at the structure of formatted results head(sim_out$results) # Check unique values for key variables cat("Disease states:", paste(unique(sim_out$results$disease_state), collapse = ", "), "\n") cat("Date range:", paste(range(sim_out$results$date), collapse = " to "), "\n") ## ----------------------------------------------------------------------------- # Subset by single criteria hospitalized_data <- sim_out$subset_data(disease_states = "H") hospitalized_data$results # Subset by multiple demographic categories elderly_data <- sim_out$subset_data( age = c("65+"), disease_states = c("H", "D") ) elderly_data$results # Specific date range peak_period <- sim_out$subset_data( date_range = c(as.Date("2023-10-01"), as.Date("2023-12-31")), disease_states = "H" ) peak_period$results ## ----------------------------------------------------------------------------- # Locate the example YAML configuration file with distributions yaml_file_dist <- system.file("extdata", "example_config_dist.yaml", package = "MetaRVM") ## ----results='hide', message=FALSE, warning=FALSE----------------------------- # Run the simulation with the new configuration sim_out_dist <- metaRVM(yaml_file_dist) ## ----fig.height = 4, fig.width = 8, fig.align = "center"---------------------- library(ggplot2) # Summarize hospitalizations by age group hospital_summary_dist <- sim_out_dist$summarize( group_by = c("age"), disease_states = "n_IsympH", stats = c("median", "quantile"), quantiles = c(0.05, 0.95) ) # Plot the summary hospital_summary_dist$plot() + ggtitle("Daily Hospitalizations by Age Group (with 90% confidence interval)") + theme_bw() ## ----fig.height = 6, fig.width = 8, fig.align = "center"---------------------- # Summary of hospitalizations by age and race group hospital_summary <- sim_out_dist$summarize( group_by = c("age", "race"), disease_states = "n_IsympH", stats = c("median", "quantile"), quantiles = c(0.05, 0.95) ) hospital_summary # visualize the summary hospital_summary$plot() + ggtitle("Daily Hospitalizations by Age and Race") + theme_bw() ## ----------------------------------------------------------------------------- # Locate the example YAML configuration file with subgroup parameters yaml_file_subgroup <- system.file("extdata", "example_config_subgroup_dist.yaml", package = "MetaRVM") ## ----results='hide', message = FALSE------------------------------------------ # Run the simulation with the subgroup configuration sim_out_subgroup <- metaRVM(yaml_file_subgroup) ## ----fig.height = 6, fig.width = 8, fig.align = "center"---------------------- # Summarize hospitalizations by age group hospital_summary_subgroup <- sim_out_subgroup$summarize( group_by = c("age"), disease_states = "H", stats = c("median", "quantile"), quantiles = c(0.025, 0.975) ) # Plot the summary hospital_summary_subgroup$plot() + ggtitle("Daily Hospitalizations by Age Group (Subgroup Parameters)") + theme_bw()