# Examples for the microsimulation package

## Table of Contents

- 1. Introduction
- 2. Tick-tock model
  - 2.1. R version
  - 2.2. C++ version
- 3. Illness-death model with costs and QALYs
  - 3.1. R version
  - 3.2. C++ version
  - 3.3. Benchmark comparing R and C++
- 4. Reporting using a data-frame
  - 4.1. R version
  - 4.2. C++ version
  - 4.3. Benchmark comparing R and C++
  - 4.4. C++ using an EventReport

## 1 Introduction

- Some examples in both R and C++.

## 2 Tick-tock model

- This simple model includes three states and three transitions:

### 2.1 R version

- In this implementation, we model only for the events, where the states are implied by the transitions. Note that there are no simulation attributes.
- Initially, a message is printed, and `"tick"` and `"stop"` events are scheduled.
- For each message or event:
  - A description of the event is printed
  - The response is defined in terms of `"tick"` → `"tock"`, `"tock"` → `"tick"` and `"stop"` → `clear()`.
- Finally, we print a message and return the final time.
- To run this, we set the seed, get a new class instance, and `run()` the class twice.

    library(microsimulation, quietly=TRUE)
    tick_tock =
        setRefClass("tick_tock",
                    contains="BaseDiscreteEventSimulation",
                    methods=list(
                        init = \() {
                            cat("Started\n")
                            scheduleAt(rexp(1,1), "tick")
                            scheduleAt(rexp(1,0.1), "stop")
                        },
                        handleMessage = \(msg) {
                            cat(sprintf("Time: %f; event: %s\n", now(), msg))
                            switch(msg,
                                   tick=scheduleAt(now()+rexp(1), "tock"),
                                   tock=scheduleAt(now()+rexp(1), "tick"),
                                   clear())
                        },
                        final = \() {cat("Finished\n"); now()} ))
    set.seed(12345)
    sim = new("tick_tock")
    replicate(2, sim$run())

    Attaching package: ‘microsimulation’

    The following object is masked from ‘package:Rcpp’:

        LdFlags
    Started
    Time: 0.441808; event: tick
    Time: 1.250275; event: tock
    Time: 1.268724; event: tick
    Time: 1.724134; event: tock
    Time: 1.748072; event: tick
    Time: 5.274728; event: stop
    Finished
    Started
    Time: 1.257961; event: tick
    Time: 3.075964; event: tock
    Time: 3.302451; event: tick
    Time: 3.749214; event: tock
    Time: 5.001675; event: tick
    Time: 5.398762; event: tock
    Time: 5.486878; event: tick
    Time: 7.209042; event: tock
    Time: 9.621881; event: stop
    Finished
    [1] 5.274728 9.621881

### 2.2 C++ version

- For the C++ code, we first show that the Rcpp and C++ code depends on the `microsimulation` package.
- For brevity, we use the `ssim` namespace.
- We define a class `tick_tock` that inherits from the `cProcess` class.
- We define a class field for the `finish_time`.
- We initialise the simulation using the `init()` function. In this case, we print out a message and schedule the `"tick"` and `"stop"` events.
- We handle each message or event by (a) printing a message for the event and (b) then schedule other events depending on the message `name`, which is a `std::string`.
- At the end of the process, we call the `stop()` method, which copies the final time to `finish_time` and print a message.
- We export the `call_tick_tock` function from C++ to C for calling from R. This function defines the `sim` process as an instance of `tick_tock`, inserts the process into the simulation using `create_process`, runs the simulation, clears the simulation queue, and returns `finish_time`.
- In R, we compile the function using the `sourceCpp` function, set the random seed, and call `call_tick_tock` function twice.
- The C++ model has the same output as the R version.

    library(microsimulation, quietly=TRUE)
    sourceCpp(code="
      // [[Rcpp::depends(microsimulation)]]
      #include <microsimulation.h>
      using namespace ssim;
      // define a process
      class tick_tock : public cProcess
      {
      public:
        double finish_time;
        // initialise the simulation
        void init() {
          Rprintf(\"Started\\n\");
          scheduleAt(R::rexp(1.0), \"tick\");
          scheduleAt(R::rexp(10.0), \"stop\");
        }
        // handle the messages
        void handleMessage(const cMessage* msg) {
          Rprintf(\"Time: %f; event: %s\\n\", now(), msg->name.c_str());
          msg->name == \"tick\" ? scheduleAt(now()+R::rexp(1.0), \"tock\") :
            msg->name == \"tock\" ? scheduleAt(now()+R::rexp(1.0), \"tick\") :
            Sim::stop_process();
        }
        void stop() {
          finish_time = now();
          Rprintf(\"Finished\\n\");
        }
      };
      // Exported function: Run the simulation once and return the finish time
      // [[Rcpp::export]]
      double call_tick_tock() {
        tick_tock sim;
        Sim::create_process(&sim);
        Sim::run_simulation();
        Sim::clear();
        return sim.finish_time;
      }")
    set.seed(12345)
    replicate(2, call_tick_tock())

    Started
    Time: 0.441808; event: tick
    Time: 1.250275; event: tock
    Time: 1.268724; event: tick
    Time: 1.724134; event: tock
    Time: 1.748072; event: tick
    Time: 5.274728; event: stop
    Finished
    Started
    Time: 1.257961; event: tick
    Time: 3.075964; event: tock
    Time: 3.302451; event: tick
    Time: 3.749214; event: tock
    Time: 5.001675; event: tick
    Time: 5.398762; event: tock
    Time: 5.486878; event: tick
    Time: 7.209042; event: tock
    Time: 9.621881; event: stop
    Finished
    [1] 5.274728 9.621881

## 3 Illness-death model with costs and QALYs

### 3.1 R version

    library(microsimulation, quietly=TRUE)
    illness_death =
        setRefClass("illness_death",
                    contains="BaseDiscreteEventSimulation",
                    fields=list(utility="numeric", QALY="numeric",
                                cost="numeric", cumulative_costs="numeric",
                                debug="logical"),
                    methods=list(
                        initialize = \(debug=TRUE) {debug <<- debug},
                        init = \() {
                            if (debug) cat("Individual:\n")
                            cumulative_costs <<- QALY <<- 0.0
                            toHealthy()
                        },
                        toHealthy = \() {
                            utility <<- 0.95
                            cost <<- 1000
                            scheduleAt(now()+rexp(1,1/30.0), "onset")
                            scheduleAt(now()+rexp(1,1/60.0), "death")
                        },
                        toIllness = \() {
                            utility <<- 0.95*0.8
                            cost <<- 10000
                            scheduleAt(now()+rexp(1,1/5.0), "recovered")
                            scheduleAt(now()+rexp(1,1/10.0), "death")
                        },
                        handleMessage = \(msg) {
                            if (debug) cat(sprintf("Time: %f; event: %s\n", now(), msg))
                            QALY <<- QALY + discountedInterval(utility, previous(), now(), 0.03)
                            cumulative_costs <<- cumulative_costs +
                                discountedInterval(cost, previous(), now(), 0.03)
                            clear()
                            if (msg == "onset")
                                toHealthy()
                            else if (msg == "recovered")
                                toIllness()
                            else
                                clear()
                        }))
    set.seed(12345)
    sim = new("illness_death")
    replicate(5, {sim$run(); c(sim$QALY, sim$cumulative_costs)}) |>
        t() |> data.frame() |> "names<-"(c("QALY","cumulative_cost"))

    Individual:
    Time: 13.254234; event: onset
    Time: 14.361154; event: death
    Individual:
    Time: 1.436288; event: death
    Individual:
    Time: 75.477631; event: death
    Individual:
    Time: 28.865643; event: onset
    Time: 35.660268; event: onset
    Time: 59.485505; event: death
    Individual:
    Time: 2.643472; event: onset
    Time: 115.923108; event: death
           QALY cumulative_cost
    1 11.117066       11702.175
    2  1.335915        1406.227
    3 28.686987       30196.829
    4 26.600625       28000.658
    5 31.094833       32731.403

### 3.2 C++ version

    library(microsimulation, quietly=TRUE)
    sourceCpp(code="
      // [[Rcpp::depends(microsimulation)]]
      #include <microsimulation.h>
      using namespace ssim;
      // define a process
      class illness_death : public cProcess
      {
      public:
        double QALY, utility, cumulative_costs, cost;
        bool debug;
        std::map<std::string,std::vector<double>> report;
        // initialise the simulation
        void init() {
          if (debug) Rprintf(\"Individual:\\n\");
          cumulative_costs = QALY = 0.0;
          this->toHealthy();
        }
        void toHealthy() {
          utility = 0.95;
          cost = 1000.0;
          this->scheduleAt(now()+R::rexp(30.0), \"onset\");
          this->scheduleAt(now()+R::rexp(60.0), \"death\");
        }
        void toIllness() {
          utility = 0.95*0.8;
          cost = 10000.0;
          this->scheduleAt(now()+R::rexp(5.0), \"recovered\");
          this->scheduleAt(now()+R::rexp(10.0), \"death\");
        }
        // handle the messages
        void handleMessage(const cMessage* msg) {
          if (debug) Rprintf(\"Time: %f; event: %s\\n\", now(), msg->name.c_str());
          QALY += discountedInterval(utility, previous(), now(), 0.03);
          cumulative_costs += discountedInterval(cost, previous(), now(), 0.03);
          this->cancel_events(); // in this case, we cancel all of the competing events
          if (msg->name == \"onset\")
            toHealthy();
          else if (msg->name == \"recovered\")
            toIllness();
          else
            Sim::stop_process();
        }
        void stop() {
          report[\"QALY\"].push_back(QALY);
          report[\"cumulative_costs\"].push_back(cumulative_costs);
        }
      };
      // Exported function: Run the simulation once
      // [[Rcpp::export]]
      Rcpp::DataFrame call_illness_death(int n = 5, bool debug = true) {
        illness_death sim;
        sim.debug = debug;
        for (int i=0; i<n; i++) {
          Sim::create_process(&sim);
          Sim::run_simulation();
          Sim::clear();
        }
        return wrap(sim.report);
      }")
    set.seed(12345)
    call_illness_death()

    Individual:
    Time: 13.254234; event: onset
    Time: 14.361154; event: death
    Individual:
    Time: 1.436288; event: death
    Individual:
    Time: 75.477631; event: death
    Individual:
    Time: 28.865643; event: onset
    Time: 35.660268; event: onset
    Time: 59.485505; event: death
    Individual:
    Time: 2.643472; event: onset
    Time: 115.923108; event: death
           QALY cumulative_costs
    1 11.117066        11702.175
    2  1.335915         1406.227
    3 28.686987        30196.829
    4 26.600625        28000.658
    5 31.094833        32731.403

### 3.3 Benchmark comparing R and C++

    microbenchmark::microbenchmark({
        set.seed(12345)
        sim = new("illness_death", debug=FALSE)
        for (i in 1:100) sim$run()
    }, {
        set.seed(12345)
        call_illness_death(100, debug=FALSE)
    },
    times=100) |> ascii()

Unit: microseconds

| expr | min | lq | mean | median | uq | max | neval | cld
--- | --- | --- | --- | --- | --- | --- | --- | --- | ---
1 | { set.seed(12345) sim = new("illnessdeath", debug = FALSE) for (i in 1:100) sim$run() } | 81610.48 | 85125.80 | 111311.62 | 117356.17 | 132919.92 | 248876.28 | 100.00 | b
2 | { set.seed(12345) callillnessdeath(100, debug = FALSE) } | 426.57 | 544.48 | 655.30 | 690.66 | 809.72 | 859.15 | 100.00 | a

## 4 Reporting using a data-frame

### 4.1 R version

    library(ascii)
    options(asciiType="org")
    library(microsimulation, quietly=TRUE)
    simple_person =
      setRefClass("simple_person",
                  contains="BaseDiscreteEventSimulation",
                  fields=list(id="numeric", state="character", report="data.frame"),
                  methods=list(
                      initialize = \() {id <<- -1L},
                      init = \() {
                          id <<- id + 1L
                          state <<- "Healthy"
                          scheduleAt(rweibull(1,8,85), "toOtherDeath")
                          scheduleAt(rweibull(1,3,90), "toCancer")
                      },
                      handleMessage = \(msg) {
                          report <<- dplyr::bind_rows(report,
                                               data.frame(id=id, startTime=previous(),
                                                          endTime=now(), state=state, event=msg))
                          if (msg == "toCancer") {
                              state <<- "Cancer"
                              if (runif(1)<0.5)
                                  scheduleAt(now()+rweibull(1,2,10), "toCancerDeath")
                          } else clear()
                      }))
    set.seed(12345)
    sim = new("simple_person")
    for (i in 1:5) sim$run()
    ascii(sim$report)

| id | startTime | endTime | state | event
--- | --- | --- | --- | --- | ---
1 | 0.00 | 0.00 | 45.90 | Healthy | toCancer
2 | 0.00 | 45.90 | 73.92 | Cancer | toOtherDeath
3 | 1.00 | 0.00 | 65.27 | Healthy | toOtherDeath
4 | 2.00 | 0.00 | 91.44 | Healthy | toOtherDeath
5 | 3.00 | 0.00 | 61.42 | Healthy | toCancer
6 | 3.00 | 61.42 | 80.92 | Cancer | toOtherDeath
7 | 4.00 | 0.00 | 98.92 | Healthy | toOtherDeath

### 4.2 C++ version

      sourceCpp(code = "
      // [[Rcpp::depends(microsimulation)]]
      #include <microsimulation.h>
      // utility to make a factor
      Rcpp::IntegerVector make_factor(std::vector<int> v, Rcpp::CharacterVector levels) {
        Rcpp::IntegerVector f(v.size());
        std::transform(v.begin(), v.end(), f.begin(), [](int i) {return 1+i; });
        f.attr(\"class\") = \"factor\";
        f.attr(\"levels\") = levels;
        return f;
      }
      enum state_t {Healthy,Cancer,Death};
      enum event_t {toOtherDeath, toCancer, toCancerDeath};
      class SimplePerson : public ssim::cProcess
      {
      public:
        int id;
        state_t state;
        std::vector<double> startTimes, endTimes;
        std::vector<int> states, events, ids;
        SimplePerson() : id(-1) {};
        void handleMessage(const ssim::cMessage*);
        void init();
      };
      /**
          Initialise a simulation run for an individual
      */
      void SimplePerson::init() {
        id++;
        state = Healthy;
        double tm = R::rweibull(8.0,85.0);
        this->scheduleAt(tm,toOtherDeath);
        this->scheduleAt(R::rweibull(3.0,90.0),toCancer);
      }
      /**
          Handle receiving self-messages
      */
      void SimplePerson::handleMessage(const ssim::cMessage* msg) {
        ids.push_back(id);
        startTimes.push_back(this->previous());
        endTimes.push_back(ssim::now());
        states.push_back(state);
        events.push_back(msg->kind);
        switch(msg->kind) {
        case toOtherDeath:
        case toCancerDeath:
          ssim::Sim::stop_process();
          break;
        case toCancer:
          state = Cancer;
          if (R::runif(0.0,1.0) < 0.5)
            this->scheduleAt(ssim::now() + R::rweibull(2.0,10.0), toCancerDeath);
          break;
        default:
          REprintf(\"No valid kind of event\\n\");
          break;
        } // switch
      } // handleMessage()
      // [[Rcpp::export]]
      Rcpp::DataFrame callSimplePersonB(int n = 5) {
        SimplePerson person;
        for (int i = 0; i < n; i++) {
          ssim::Sim::create_process(&person);
          ssim::Sim::run_simulation();
          ssim::Sim::clear();
        }
        Rcpp::DataFrame df;
        df.push_back(person.ids,\"id\");
        df.push_back(person.startTimes,\"startTime\");
        df.push_back(person.endTimes,\"endTime\");
        df.push_back(make_factor(person.states,{\"Healthy\",\"Ill\",\"Dead\"}), \"state\");
        df.push_back(make_factor(person.events,{\"toOtherDeath\", \"toCancer\", \"toCancerDeath\"}),
                     \"event\");
        return Rcpp::wrap(df);
      }
    ")
      set.seed(12345)
      callSimplePersonB() |> ascii()

| id | startTime | endTime | state | event
--- | --- | --- | --- | --- | ---
1 | 0.00 | 0.00 | 45.90 | Healthy | toCancer
2 | 0.00 | 45.90 | 73.92 | Ill | toOtherDeath
3 | 1.00 | 0.00 | 65.27 | Healthy | toOtherDeath
4 | 2.00 | 0.00 | 91.44 | Healthy | toOtherDeath
5 | 3.00 | 0.00 | 61.42 | Healthy | toCancer
6 | 3.00 | 61.42 | 80.92 | Ill | toOtherDeath
7 | 4.00 | 0.00 | 98.92 | Healthy | toOtherDeath

### 4.3 Benchmark comparing R and C++

    microbenchmark::microbenchmark({
        set.seed(12345)
        sim = new("simple_person")
        for (i in 1:100) sim$run()
    }, {
        set.seed(12345)
        callSimplePersonB(100)
    },
    times=10) |> ascii()

Unit: milliseconds

| expr | min | lq | mean | median | uq | max | neval | cld
--- | --- | --- | --- | --- | --- | --- | --- | --- | ---
1 | { set.seed(12345) sim = new("simpleperson") for (i in 1:100) sim$run() } | 106.92 | 107.73 | 109.16 | 108.31 | 108.66 | 114.07 | 10.00 | b
2 | { set.seed(12345) callSimplePersonB(100) } | 1.03 | 1.09 | 1.20 | 1.13 | 1.26 | 1.66 | 10.00 | a

### 4.4 C++ using an EventReport

    library(microsimulation)
    sourceCpp(code = "
    // [[Rcpp::depends(microsimulation)]]
    #include <microsimulation.h>
    enum state_t {Healthy,Cancer};
    enum event_t {toOtherDeath, toCancer, toCancerDeath};
    using Report = ssim::EventReport<short,short,double>;
    class SimplePerson : public ssim::cProcess
    {
    public:
      state_t state;
      Report report;
      SimplePerson() { }
      void handleMessage(const ssim::cMessage*);
      void init();
    };
    /**
        Initialise a simulation run for an individual
    */
    void SimplePerson::init() {
      state = Healthy;
      double tm = R::rweibull(8.0,85.0);
      this->scheduleAt(tm,toOtherDeath);
      this->scheduleAt(R::rweibull(3.0,90.0),toCancer);
    }
    /**
        Handle receiving self-messages
    */
    void SimplePerson::handleMessage(const ssim::cMessage* msg) {
      report.add(state,msg->kind,previous(),ssim::now());
      switch(msg->kind) {
      case toOtherDeath:
      case toCancerDeath:
        ssim::Sim::stop_process();
        break;
      case toCancer:
        state = Cancer;
        if (R::runif(0.0,1.0) < 0.5)
          this->scheduleAt(ssim::now() + R::rweibull(2.0,10.0), toCancerDeath);
        break;
      default:
        REprintf(\"No valid kind of event\\n\");
        break;
      } // switch
    } // handleMessage()
    // [[Rcpp::export]]
    SEXP callSimplePersonC(int n = 10000) {
      SimplePerson person;
      for (int i = 0; i < n; i++) {
        ssim::Sim::create_process(&person);
        ssim::Sim::run_simulation();
        ssim::Sim::clear();
      }
      return person.report.wrap();
    }
    ")
    make_factor = function(x, labels)
        factor(as.integer(x)+1L,labels=labels)
    set.seed(12345)
    report = callSimplePersonC()
    rates = with(report, merge(pt,events,all.x=TRUE)) |>
        transform(rate=ifelse(is.na(number),0,number)/pt,
                  Key=make_factor(Key,c("Healthy","Cancer")),
                  event=make_factor(event,c("toOtherDeath", "toCancer", "toCancerDeath")))
    lattice::xyplot(rate~age|Key+event, data=rates, type="l")

Author: Mark Clements

Created: 2023-03-08 Wed 10:42