Line data    Source code

       1             : /* 
       2             : * Copyright (C) 2020-2025 MEmilio
       3             : *
       4             : * Authors: Martin J Kuehn, Anna Wendler, Lena Ploetzke
       5             : *
       6             : * Contact: Martin J. Kuehn <Martin.Kuehn@DLR.de>
       7             : *
       8             : * Licensed under the Apache License, Version 2.0 (the "License");
       9             : * you may not use this file except in compliance with the License.
      10             : * You may obtain a copy of the License at
      11             : *
      12             : *     http://www.apache.org/licenses/LICENSE-2.0
      13             : *
      14             : * Unless required by applicable law or agreed to in writing, software
      15             : * distributed under the License is distributed on an "AS IS" BASIS,
      16             : * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
      17             : * See the License for the specific language governing permissions and
      18             : * limitations under the License.
      19             : */
      20             : #include "ide_secir/simulation.h"
      21             : #include "ide_secir/model.h"
      22             : #include "memilio/config.h"
      23             : #include "memilio/utils/time_series.h"
      24             : #include <memory>
      25             : 
      26             : namespace mio
      27             : {
      28             : namespace isecir
      29             : {
      30             : 
      31          15 : void Simulation::advance(ScalarType tmax)
      32             : {
      33          15 :     mio::log_info("Simulating IDE-SECIR from t0 = {} until tmax = {} with dt = {} .",
      34          15 :                   m_model->m_transitions.get_last_time(), tmax, m_dt);
      35          15 :     m_model->set_transitiondistributions_support_max(m_dt);
      36          15 :     m_model->set_transitiondistributions_derivative(m_dt);
      37          15 :     m_model->set_transitiondistributions_in_forceofinfection(m_dt);
      38          15 :     m_model->initial_compute_compartments(m_dt);
      39             : 
      40             :     // For every time step:
      41         123 :     while (m_model->m_transitions.get_last_time() < tmax - m_dt / 2) {
      42             : 
      43         108 :         m_model->m_transitions.add_time_point(m_model->m_transitions.get_last_time() + m_dt);
      44         108 :         m_model->m_populations.add_time_point(m_model->m_populations.get_last_time() + m_dt);
      45             : 
      46             :         // compute Susceptibles:
      47         108 :         m_model->compute_susceptibles(m_dt);
      48             : 
      49             :         // Compute flows:
      50         108 :         m_model->flows_current_timestep(m_dt);
      51             : 
      52             :         // Update remaining compartments:
      53         108 :         m_model->update_compartments();
      54             : 
      55             :         // Compute m_forceofinfection (only used for calculation of Susceptibles and flow SusceptibleToExposed in the next timestep!):
      56         108 :         m_model->compute_forceofinfection(m_dt);
      57             :     }
      58          15 : }
      59             : 
      60           2 : TimeSeries<ScalarType> simulate(ScalarType tmax, ScalarType dt, Model const& m_model)
      61             : {
      62           2 :     m_model.check_constraints(dt);
      63           2 :     Simulation sim(m_model, dt);
      64           2 :     sim.advance(tmax);
      65           4 :     return sim.get_result();
      66           2 : }
      67             : 
      68             : } // namespace isecir
      69             : } // namespace mio