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Fix compiler warnings #140

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30 changes: 15 additions & 15 deletions Optimizer/src/optimizer.h
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Original file line number Diff line number Diff line change
Expand Up @@ -537,14 +537,14 @@ namespace Optimizer {
}

Eigen::VectorXd Newton (std::function<double (Eigen::VectorXd)> obj_func,
Eigen::VectorXd x, int M = 1000, double epsilon1 = 1e-5, double epsilon2 = 1e-5,
Eigen::VectorXd x, int M = 1000, double epsilon1 = 1e-5, double /*epsilon2*/ = 1e-5,
BM b_meth = BM::B_PHASE,
UDM u_search = UDM::N_RAP) {
// This function does the multi-variable optimization using the Newton's algorithm
// Input parameters are :
// obj_func - The std::function variable containing our objective function
// x - The initial point from where we begin, of type Eigen::VectorXd
// M - Number of interations, type int
// M - Number of iterations, type int
// epsilon1 - termination parameter, type double
// epsilon 2 - termination parameter, type double
// b_meth - Selects the Bracketing method to be used, type enum class BM
Expand Down Expand Up @@ -761,7 +761,7 @@ namespace Optimizer {
//next to worst point
Eigen::VectorXd xg(n);
xg.col(0) = points.row(func_vals[func_vals.size()-2].second);
//central point 1 row with n variabvles
//central point 1 row with n variables
Eigen::VectorXd xc(n);
//i < N because we exclude worst point from this sum(the worst point is also the last point in this vectpr)

Expand Down Expand Up @@ -823,9 +823,9 @@ namespace Optimizer {
}

Eigen::VectorXd MVOptimize (std::function<double (Eigen::VectorXd)> obj_func,
Eigen::VectorXd x, int M = 200, MVO m_opt = MVO::V_METRIC, BM b_meth = BM::B_PHASE,
UDM u_search = UDM::G_SEARCH) {
// This function does the Multi-variable optimzation
Eigen::VectorXd x, int M = 200, MVO m_opt = MVO::V_METRIC, BM /*b_meth*/ = BM::B_PHASE,
UDM /*u_search*/ = UDM::G_SEARCH) {
// This function does the Multi-variable optimization
// Input parameters are :
// obj_func - The std::function variable containing our objective function
// x - Our initial point of type Eigen::VectorXd
Expand Down Expand Up @@ -874,11 +874,11 @@ namespace Optimizer {
Eigen::VectorXd x, Eigen::VectorXd tau, Eigen::VectorXd sigma) {

double sub = 0;
for(int i = 0; i<ineq_const.size(); i++){
for(size_t i = 0; i<ineq_const.size(); i++){
sub -= pow(sigma(i), 2);
}

for(int i = 0; i<eq_const.size(); i++){
for(size_t i = 0; i<eq_const.size(); i++){
sub -= pow(tau(i), 2);
}

Expand All @@ -890,7 +890,7 @@ namespace Optimizer {
int M = 100, double Rineq = 0.1, double Req = 0.1, double cineq = 10, double ceq = 10,
PF Pineq = PF::BRACKET, PF Peq = PF::PARABOLIC, double epsilon = 1e-5) {

double f_prev, f;
double f_prev=0.0, f=0.0;

for (int it = 0; it < M; ++it) {
std::function<double (Eigen::VectorXd)> func = [obj_func, ineq, eq, Rineq, Req, Pineq, Peq]
Expand Down Expand Up @@ -918,15 +918,15 @@ namespace Optimizer {
std::vector<std::function<double (Eigen::VectorXd)>> eq_const, int M = 100,
double R = 0.1, double epsilon = 1e-5) {

double f_new, f;
double f_new = 0.0, f = 0.0;
Eigen::VectorXd x_new = x;
Eigen::VectorXd sigma = Eigen::VectorXd::Zero(ineq_const.size());
Eigen::VectorXd tau = Eigen::VectorXd::Zero(eq_const.size());

for(int i=0; i<M; ++i){

std::function<double (Eigen::VectorXd)> func = [R, obj_func, x, ineq_const, eq_const, sigma, tau] (Eigen::VectorXd x)->double {
return obj_func(x) + R * GetMultiplierPenalty(ineq_const, eq_const, x, tau, sigma); };
std::function<double (Eigen::VectorXd)> func = [R, obj_func, x, ineq_const, eq_const, sigma, tau] (Eigen::VectorXd value)->double {
return obj_func(value) + R * GetMultiplierPenalty(ineq_const, eq_const, x, tau, sigma); };

if(i > 0) {
f = f_new;
Expand All @@ -939,7 +939,7 @@ namespace Optimizer {
if(i > 0 && std::abs(f_new - f) < epsilon)
break;
else {
for(int i = 0; i<ineq_const.size(); i++){
for(size_t i = 0; i<ineq_const.size(); i++){
double alpha = ineq_const[i](x) + sigma(i);
if(alpha < 0) {
sigma(i) = alpha;
Expand All @@ -949,9 +949,9 @@ namespace Optimizer {
}
}

for(int i = 0; i<eq_const.size(); i++){
for(size_t i = 0; i < eq_const.size(); i++){
tau(i) += eq_const[i](x);
}
}
}

}
Expand Down
20 changes: 10 additions & 10 deletions Optimizer/src/util.h
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Original file line number Diff line number Diff line change
Expand Up @@ -26,9 +26,9 @@ namespace Optimizer {
if(file_stream.is_open() == true)
{
//go through entire matrix
for(int i = 0; i < path.cols(); i++)
for(Eigen::Index i = 0; i < path.cols(); i++)
{
for(int j = 0; j < path.rows(); j++)
for(Eigen::Index j = 0; j < path.rows(); j++)
{
//print out whole row
file_stream << path(i,j) << " ";
Expand All @@ -46,9 +46,9 @@ namespace Optimizer {
if(file_stream.is_open() == true)
{
//go through entire matrix
for(int i = 0; i < path.cols(); i++)
for (Eigen::Index i = 0; i < path.cols(); i++ )
{
for(int j = 0; j < path.rows(); j++)
for(Eigen::Index j = 0; j < path.rows(); j++)
{
file_stream << path(i,j);
//add comma after each coefficient in matrix
Expand All @@ -58,7 +58,7 @@ namespace Optimizer {
file_stream << ',';
}
}
//add carrige return after every row
//add carriage return after every row
file_stream << '\r' << '\n';
}

Expand Down Expand Up @@ -91,7 +91,7 @@ namespace Optimizer {
// Penalty functions
double Parabolic(std::vector<std::function<double (Eigen::VectorXd)>> constraints, Eigen::VectorXd x, Eigen::VectorXd tau){
double ans = 0;
for(int i = 0; i < constraints.size(); i++) {
for(size_t i = 0; i < constraints.size(); i++) {
ans += pow(constraints[i](x) + tau(i), 2);
}
return ans;
Expand All @@ -100,31 +100,31 @@ namespace Optimizer {

double InfiniteBarrier(std::vector<std::function<double (Eigen::VectorXd)>> constraints, Eigen::VectorXd x){
double ans = 0;
for(int i = 0; i < constraints.size(); i++) {
for(size_t i = 0; i < constraints.size(); i++) {
ans += std::abs(constraints[i](x));
}
return ans;
}

double Log(std::vector<std::function<double (Eigen::VectorXd)>> constraints, Eigen::VectorXd x){
double ans = 0;
for(int i = 0; i < constraints.size(); i++){
for(size_t i = 0; i < constraints.size(); i++){
ans -= log(constraints[i](x));
}
return ans;
}

double Inverse(std::vector<std::function<double (Eigen::VectorXd)>> constraints, Eigen::VectorXd x){
double ans = 0;
for(int i = 0; i < constraints.size(); i++){
for(size_t i = 0; i < constraints.size(); i++){
ans += 1.0 / constraints[i](x);
}
return ans;
}

double Bracket(std::vector<std::function<double (Eigen::VectorXd)>> constraints, Eigen::VectorXd x, Eigen::VectorXd sigma){
double ans = 0;
for(int i = 0; i < constraints.size(); i++){
for(size_t i = 0; i < constraints.size(); i++){
double alpha = constraints[i](x) + sigma(i);
if(alpha < 0) {
ans += pow(alpha, 2);
Expand Down