Exemplo n.º 1
0
matrix1d sum(matrix2d myVector) {
    matrix1d mySum(myVector.size(),0.0);

    for (int i=0; i<myVector.size(); i++) {
        for (int j=0; j<myVector[i].size(); j++) {
            mySum[i]+=myVector[i][j];
        }
    }
    return mySum;
}
Exemplo n.º 2
0
matrix1d mean2(matrix2d myVector) {
    matrix1d myMean(myVector[0].size(),0.0);

    for (int i=0; i<myVector.size(); i++) {
        for (int j=0; j<myVector[i].size(); j++) {
            myMean[j]+=myVector[i][j]/double(myVector.size());
        }
    }
    return myMean;
}
Exemplo n.º 3
0
matrix1d mean1(matrix2d myVector) {
    matrix1d myMean(myVector.size(),0.0);

    for (int i=0; i<myVector.size(); i++) {
        for (int j=0; j<myVector[i].size(); j++) {
            myMean[i]+=myVector[i][j];
        }
        myMean[i]/=double(myVector[i].size());
    }
    return myMean;
}
void matrix2dio<T>::m2dToText(std::ostream & os, const matrix2d<T> & m) {

  size_t i = 0, j = 0;

  for (i = 0; i < m.rows(); i++) {

    std::valarray<T> r = m.row(i);
    os << r[0];

    for (j = 1; j < m.cols(); j++)
      std::cout << ' ' << r[j];

    os << '\n';
  }

  os << std::flush;
}
Exemplo n.º 5
0
matrix1d NeuroEvo::getAction(matrix2d state) {
    matrix1d stateSum(state[0].size(), 0.0);

    // state[type][state_element] -- specifies combination for state
    for (size_t i = 0; i < state.size(); i++) {
        for (size_t j = 0; j < state[i].size(); j++) {
            stateSum[j] += state[i][j];
        }
    }

    return getAction(stateSum);
}