HR-loadparams.cpp

/*************************************************************

Copyright (c) 2025, Alicia Garrido Peña <alicia.garrido@uam.es>
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#include<vector>
#include<string>
#include <DifferentialNeuronWrapper.h>
#include <ChemicalSynapse.h>
#include <HindmarshRoseModel.h>
#include <SystemWrapper.h>
#include <RungeKutta4.h>
#include <iostream>
#include <cstring>
#include <map>
#include <yaml-cpp/yaml.h>
#include <fstream>
#include <chrono>
#include <iomanip>
#include <ctime>
#include <filesystem>


using namespace std;

typedef RungeKutta4 Integrator;
typedef DifferentialNeuronWrapper<SystemWrapper<HindmarshRoseModel<double>>, Integrator> HR;


std::map<std::string,double> parse_file(const std::string& file, const std::string& section)
{
    std::map<std::string,double> config_values;

    // Cargar el YAML
    YAML::Node config = YAML::LoadFile(file);

    // Verificar que exista la subsección
    if (!config[section]) {
        std::cerr << "Section '" << section << "' not found in " << file << std::endl;
        return config_values;
    }

    // Iterar por los pares clave/valor de la subsección
    for (auto it = config[section].begin(); it != config[section].end(); ++it) {
        std::string key = it->first.as<std::string>();
        double value = it->second.as<double>();
        config_values[key] = value;
    }

    return config_values;
}


int main(int argc, char **argv) {
  if (argc < 4) {
      std::cerr << "Usage: " << argv[0]
                << " <yaml_file> <output_file> <simulation_time> [step]\n";
      return 1;
  }

  // Required arguments
  std::string yaml_file   = argv[1];
  std::string output_file = argv[2];
  double simulation_time  = std::atof(argv[3]);

  // Optional argument (step)
  double step = 0.0; // default value
  if (argc >= 5) {
      step = std::atof(argv[4]);
  }

  // Echo input back
  std::cout << "YAML file: " << yaml_file << "\n";
  std::cout << "Output file: " << output_file << "\n";
  std::cout << "Simulation time: " << simulation_time << "\n";
  std::cout << "Step: " << step << "\n";

  // Initialize neuron model parameters
  HR::ConstructorArgs args, args2; 

  std::vector<std::string> param_names = HR::ParamNames();

  std::map<std::string,double> v_args = parse_file(yaml_file, "HR1");

  for(int i=0; i < HR::n_parameters; i++)
  {
    // std::cout << v_args[param_names[i]] << " " << param_names[i] << endl;
    args.params[i] = v_args[param_names[i]];
  }

  HR h1(args);
  h1.set(HR::x, -0.712841);
  h1.set(HR::y, -1.93688);
  h1.set(HR::z, 3.16568);

  v_args = parse_file(yaml_file, "HR2");

  for(int i=0; i < HR::n_parameters; i++)
  {
    // std::cout << v_args[param_names[i]] << " " << param_names[i] << endl;
    args2.params[i] = v_args[param_names[i]];
  }

  HR h2(args2);
  
  h2.set(HR::x, -0.712841);
  h2.set(HR::y, -1.93688);
  h2.set(HR::z, 3.16568);

  Synapse::ConstructorArgs syn_args;
  v_args = parse_file(yaml_file, "Chemical-HR1-HR2");
  param_names = Synapse::ParamNames();

  for(int i=0; i < Synapse::n_parameters; i++)
  {
    // std::cout << v_args[param_names[i]] << " " << param_names[i] << endl;
    syn_args.params[i] = v_args[param_names[i]];
  }
  // Initialize a synapse between the neurons
  Synapse s(h1, HR::x, h2, HR::x, syn_args, 1);
  

  // Set the parameter values
  /*args.params[Neuron::e] = 3.281;
  args.params[Neuron::mu] = 0.0029;
  args.params[Neuron::S] = 4;
  args.params[Neuron::a] = 1;
  args.params[Neuron::b] = 3;
  args.params[Neuron::c] = 1;
  args.params[Neuron::d] = 5;
  args.params[Neuron::xr] = -1.6;
  args.params[Neuron::vh] = 1;

  Synapse::ConstructorArgs syn_args;
  syn_args.params[Synapse::gfast] = 0.015;
  syn_args.params[Synapse::Esyn] = -75;
  syn_args.params[Synapse::sfast] = 0.2;
  syn_args.params[Synapse::Vfast] = -50;
  syn_args.params[Synapse::gslow] = 0.025; //When 0, use only fast
  syn_args.params[Synapse::k1] = 1;
  syn_args.params[Synapse::k2] = 0.03;
  syn_args.params[Synapse::sslow] = 1;*/


  // // Set initial value of V in neuron n1
  // h1.set(HR::v, -75);

  // Open output file
    std::ofstream out(output_file);
    if (!out.is_open()) {
        std::cerr << "Error: could not open " << output_file << " for writing.\n";
        return 1;
    }

    // Write header
    out << "Time Vpre Vpost i ifast islow\n";

    // Check if distances.txt exists already
    std::string dist_file = "distances.csv";
    bool exists = std::filesystem::exists(dist_file);

    // Secondary file (append mode)
    std::ofstream dist_out(dist_file, std::ios::app);
    if (!dist_out.is_open()) {
        std::cerr << "Error: could not open distances.csv\n";
        return 1;
    }

    double h1_min = std::numeric_limits<double>::max();
    double h1_max = std::numeric_limits<double>::lowest();
    double syn_min = std::numeric_limits<double>::max();
    double syn_max = std::numeric_limits<double>::lowest();

    // Option 1: store all values in vectors for second pass
    std::vector<double> h1_vals;
    std::vector<double> syn_vals;
    std::vector<double> times;

    // Simulation loop
    for (double time = 0; time < simulation_time; time += step) {
        s.step(step, h1.get(HR::x), h2.get(HR::x));

        // Provide an external current input to both neurons
        h2.add_synaptic_input(s.get(Synapse::i));

        h1.step(step);
        h2.step(step);

        double h1_val = h1.get(HR::x);
        double syn_val = s.get(Synapse::ifast);

        // store
        times.push_back(time);
        h1_vals.push_back(h1_val);
        syn_vals.push_back(syn_val);

        // update min/max
        if (h1_val < h1_min) h1_min = h1_val;
        if (h1_val > h1_max) h1_max = h1_val;
        if (syn_val < syn_min) syn_min = syn_val;
        if (syn_val > syn_max) syn_max = syn_val;

        out << time << " "
            << h1.get(HR::x) << " "
            << h2.get(HR::x) << " "
            << s.get(Synapse::i) << " "
            << s.get(Synapse::ifast) << " "
            << s.get(Synapse::islow)
            << "\n";
    }

    double accumulated_distance = 0.0;
    for (size_t i = 0; i < h1_vals.size(); ++i) {
        double h1_norm = (h1_vals[i] - h1_min) / (h1_max - h1_min);
        double syn_norm = (syn_vals[i] - syn_min) / (syn_max - syn_min);

        double distance = std::abs(h1_norm - syn_norm);
        accumulated_distance += distance;
    } 

    // Write header if first time
    if (!exists) {
        dist_out << "timestamp,yaml_file,data_file,simulation_time,step,accumulated_distance\n";
    }
    // Get current time
    auto now = std::chrono::system_clock::now();
    std::time_t now_c = std::chrono::system_clock::to_time_t(now);
    // After loop: append just once
    dist_out << std::put_time(std::localtime(&now_c), "%F %T") << "," 
            << yaml_file << ","
            << output_file << ","
            << simulation_time << ","
            << step << ","
            << accumulated_distance << "\n";

    out.close();
    dist_out.close();
    std::cout << "Simulation finished. Results written to " << output_file << "\n";
    std::cout << "Distance append in " << dist_file << "\n";


  return 0;
}