#include <iostream>
#include <functional>
#include <math.h>
#include <typeinfo>
#include <random>
#include <ctime> 
#include <algorithm>
#include <vector>

#include "argh.h"
#include "matrix.h"
#include "network.h"
#include "decider.h"
#include "trainer.h"

int main(int argc, char* argv[])
{
    argh::parser args;
    args.add_params({"-m", "--money"});
    args.add_params({"-s", "--stock"});
    args.add_params({"-p", "--population"});
    args.parse(argc, argv);

    double   money;
    unsigned stock, population;

    args({ "m", "money" }, 1000.)   >> money;
    args({ "s", "stock" }, 1000)    >> stock;
    args({ "p", "population" }, 25) >> population;

    std::uniform_real_distribution<double> distribution(-1.0, 1.0);
    std::default_random_engine random_engine;
    random_engine.seed(std::time(0));

    std::function<double(const int&, const int&)> randomizer = [&](const int& i, const int& j) -> double {
        return distribution(random_engine);
    };

    std::function<double(const double&)> normalizer = [](const double& result) -> double { return erf(result); };

    using current_decider = neural_decider<24, 12, 12, 32, 16>;

    std::function<current_decider()> factory = [&]() -> current_decider {
        current_decider decider(normalizer);
        decider.network.fill(randomizer);

        return decider;
    };

    trainer<current_decider> train(money, stock, population, factory);
    train.test(std::cin);
}