SteadyStateRunner.cpp

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#include "SteadyStateRunner.hpp"
#include "ZeroStimulus.hpp"
 
void SteadyStateRunner::RunToSteadyStateImplementation()
{
    // Get necessary things from stimulus current
    boost::shared_ptr<RegularStimulus> p_reg_stim = boost::static_pointer_cast<RegularStimulus>(mpModel->GetStimulusFunction());
    boost::shared_ptr<ZeroStimulus> p_zero_stim(new ZeroStimulus);
    const double pacing_cycle_length = p_reg_stim->GetPeriod(); // ms
    double stimulus_duration = p_reg_stim->GetDuration(); // ms
    double stimulus_start_time = p_reg_stim->GetStartTime(); // ms
    double stimulus_end_time = stimulus_start_time + stimulus_duration;
    double maximum_time_step = pacing_cycle_length; // ms
 
    bool force_reset_setting = mpModel->GetForceReset();
    bool minimal_reset_setting = mpModel->GetMinimalReset();
 
    mpModel->SetMaxSteps(1e5); // Per pace (or part of pace with stimulus start/stop).
    mpModel->SetForceReset(true); // Best way to deal with discontinuities in the RHS according to CVODE
 
    // Set up vectors to monitor progress
    std::vector<double> old_state_vars;
    std::vector<double> new_state_vars;
    CopyToStdVector(mpModel->rGetStateVariables(), old_state_vars);
 
    const unsigned num_paces_to_analyse = (mTwoPaceScan) ? 2u : 1u;
    for (unsigned i = 0; i < mMaxNumPaces; i = i + num_paces_to_analyse)
    {
        // Look at two paces in the hope of detecting alternans and still saying we're steady-ish.
        for (unsigned j = 0; j < num_paces_to_analyse; j++)
        {
            // Pre-stimulus (can skip if stimulus is applied at t=0)
            if (stimulus_start_time > 0)
            {
                mpModel->SetMinimalReset(true); // We are just carrying on from last stop (not on stimulus) so don't need a solver reset.
                mpModel->SetStimulusFunction(p_zero_stim);
                mpModel->Solve((pacing_cycle_length) * (double)(i + j), (pacing_cycle_length) * (double)(i + j) + stimulus_start_time, maximum_time_step);
                mpModel->SetForceReset(true); // Reset every solve call after this (next two) to deal with discontinuities in stimulus.
            }
 
            mpModel->SetStimulusFunction(p_reg_stim); // RegularStimulus applies at stimulus_start_time<=t<=stimulus_end_time (includes bounds).
            mpModel->Solve((pacing_cycle_length) * (double)(i + j) + stimulus_start_time, (pacing_cycle_length) * (double)(i + j) + stimulus_end_time, maximum_time_step);
 
            // Post-stimulus
            mpModel->SetStimulusFunction(p_zero_stim); // added this because the RegularStimulus behaviour is to apply the stimulus at t=stimulus_end_time, which might confuse matters.
            mpModel->Solve((pacing_cycle_length) * (double)(i + j) + stimulus_end_time, (pacing_cycle_length) * (double)(i + j + 1), maximum_time_step);
        }
 
        this->mNumEvaluations += num_paces_to_analyse;
        CopyToStdVector(mpModel->rGetStateVariables(), new_state_vars);
 
        // Calculate the change in the norm of the state variables
        double temp = 0;
        for (unsigned j = 0; j < old_state_vars.size(); j++)
        {
            temp += fabs(new_state_vars[j] - old_state_vars[j]);
        }
 
        if (temp < 1e-6)
        {
            break; // say we are converged enough to steady state to stop here.
        }
 
        old_state_vars = new_state_vars;
    }
 
    // Reset stimulus to normal
    mpModel->SetStimulusFunction(p_reg_stim);
    mpModel->SetForceReset(force_reset_setting);
    mpModel->SetMinimalReset(minimal_reset_setting);
}