//
// Created by martin on 7/15/18.
//

#include <vector>

#include "ErrorFunctions.h"



size_t ErrorFunction::get_dimension() {
    return this->dimension;
}

MSE::MSE(NeuralNetwork *net, DataSet *ds) {
    this->net = net;
    this->ds = ds;
    this->dimension = net->get_n_weights() + net->get_n_biases();
}

double MSE::eval(std::vector<double> *weights) {
    unsigned int dim_out = this->ds->get_output_dim();
//    unsigned int dim_in = this->ds->get_input_dim();
    size_t n_elements = this->ds->get_n_elements();
    double error = 0.0, val;

    std::vector<std::pair<std::vector<double>, std::vector<double>>>* data = this->ds->get_data();

//    //TODO instead use something smarter
//    this->net->copy_weights(weights);

    std::vector<double> output( dim_out );

    for(unsigned int i = 0; i < n_elements; ++i){  // Iterate through every element in the test set

        this->net->eval_single(data->at(i).first, output, weights);  // Compute the net output and store it into 'output' variable


//        printf("errors: ");
        for(unsigned int j = 0; j < dim_out; ++j) {  // Compute difference for every element of the output vector

            val = output[j] - data->at(i).second[j];
            error += val * val;

//            printf("%f, ", val * val);
        }
//        printf("\n");

    }

//    printf("n_elements: %d\n", n_elements);
    return error/n_elements;
}

ErrorSum::ErrorSum() {
    this->summand = nullptr;
    this->summand_coefficient = nullptr;
    this->dimension = 0;
}

ErrorSum::~ErrorSum(){
    if( this->summand ){
        delete this->summand;
    }
    if( this->summand_coefficient ){
        delete this->summand_coefficient;
    }
}

double ErrorSum::eval(std::vector<double> *weights) {
    double output = 0.0;

    for( unsigned int i = 0; i < this->summand->size(); ++i ){
        output += this->summand->at( i )->eval( weights ) * this->summand_coefficient->at( i );
    }

    return output;
}

void ErrorSum::add_error_function( ErrorFunction *F, double alpha ) {
    if(!this->summand){
        this->summand = new std::vector<ErrorFunction*>(0);
    }
    this->summand->push_back( F );

    if(!this->summand_coefficient){
        this->summand_coefficient = new std::vector<double>(0);
    }
    this->summand_coefficient->push_back( alpha );

    if(F->get_dimension() > this->dimension){
        this->dimension = F->get_dimension();
    }
}

size_t ErrorSum::get_dimension() {
//    if(!this->dimension) {
//        size_t max = 0;
//        for(auto e : *this->summand) {
//            if(e->get_dimension() > max) {
//                max = e->get_dimension();
//            }
//        };
//
//        this->dimension = max;
//    }
    return this->dimension;
}