title: SIR: Multiple Runs with Plotting¶

SIR: Multiple Runs with Plotting¶

Extends the multiple-run SIR example with post-processing resources for R-based visualization of replicate results.

Try It Live¶

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#include "epiworld.hpp"

using namespace epiworld;

int main() {

int total_replicates = 100;
    int pop_size         = 5000;

epimodels::ModelSIR<> sir(
        "a virus", // Name of the virus
        0.01,      // Initial prevalence
        0.9,       // Infectiousness
        0.3        // Recovery rate
    );

// Adding a bernoulli graph as step 0
    sir.agents_from_adjlist(
        rgraph_smallworld(pop_size, 5, .01, false, sir)
    );

// Function to record each replicate results 
    std::vector< std::vector< int > > results(total_replicates);
    std::vector< std::string > labels;

auto record =
        [&results,&labels](size_t iternum, epiworld::Model<> * m)
        {

if (iternum == 0u)
                m->get_db().get_today_total(nullptr, &results[iternum]);
            else
                m->get_db().get_today_total(&labels, &results[iternum]);

return;

};

// Running
    sir.run_multiple(
        60,
        total_replicates, // How many experiments
        123,
        record,           // Function to call after each experiment
        true,             // Whether to reset the population
        true              // Whether to print a progress bar
    );

sir.print();

// How long did it took?
    sir.get_elapsed();

// Writing the results to the disk
    std::ofstream fn("02b-sir-multiple-runs.csv", std::ios_base::out);
    fn << "run_id";
    for (epiworld_fast_uint s = 0u; s < labels.size(); ++s)
        fn << "," << labels[s];

fn << "\n";

for (int r = 0; r < total_replicates; ++r)
    {
        fn << r;
        for (epiworld_fast_uint s = 0u; s < labels.size(); ++s)
            fn << "," << results[r][s];

fn << "\n";

}

return 0;
}

Output