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Random Tidy #207

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merged 4 commits into from
Nov 7, 2024
Merged

Random Tidy #207

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74f45b0
Logger to the :bee:
KSkwarczynski Nov 6, 2024
9248f0c
:lukenew: haven't done tidy of plotting exe so here I am
KSkwarczynski Nov 6, 2024
c521688
missed this
KSkwarczynski Nov 6, 2024
67c6027
furhter tidy
KSkwarczynski Nov 6, 2024
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101 changes: 58 additions & 43 deletions mcmc/PSO.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -2,8 +2,9 @@

#include <cmath>

// ***************
PSO::PSO(manager *man) : LikelihoodFit(man) {

// ***************
fConstriction = fitMan->raw()["General"]["PSO"]["Constriction"].as<double>();
fInertia = fitMan->raw()["General"]["PSO"]["Inertia"].as<double>()*fConstriction;
fOne = fitMan->raw()["General"]["PSO"]["One"].as<double>()*fConstriction;
Expand All @@ -20,8 +21,9 @@ PSO::PSO(manager *man) : LikelihoodFit(man) {
}
}

// ***************
void PSO::runMCMC(){

// ***************
PrepareFit();

if(fTestLikelihood){
Expand All @@ -41,17 +43,16 @@ void PSO::runMCMC(){
return;
}


// *************************
void PSO::init(){

// *************************
fBestValue = 1234567890.0;

//KS: For none PCA this will be eqaul to normal parameters
//const int NparsPSOFull = NPars;
//const int NparsPSO = NParsPCA;

std::cout << "Preparing PSO" << std::endl;

MACH3LOG_INFO("Preparing PSO");
// Initialise bounds on parameters
if(fTestLikelihood){
for (int i = 0; i < fDim; i++){
Expand Down Expand Up @@ -105,9 +106,9 @@ void PSO::init(){
}
}

std::cout << "Printing Minimums and Maximums of Variables to be minimised" << std::endl;
for (int i =0; i<fDim; i++){
std::cout << "Variable "<< i<<" :" << ranges_min[i] << ", "<< ranges_max[i] << std::endl;
MACH3LOG_INFO("Printing Minimums and Maximums of Variables to be minimized");
for (int i = 0; i < fDim; i++){
MACH3LOG_INFO("Variable {} : {:.2f}, {:.2f}", i, ranges_min[i], ranges_max[i]);
}

// Initialise particle positions
Expand Down Expand Up @@ -143,10 +144,12 @@ void PSO::init(){
}
}

// *************************
std::vector<std::vector<double> > PSO::bisection(std::vector<double>position,double minimum, double range, double precision){
// *************************
std::vector<std::vector<double>> uncertainties_list;
for (unsigned int i = 0; i< position.size(); ++i){
std::cout << i << std::endl;
for (unsigned int i = 0; i< position.size(); ++i) {
MACH3LOG_INFO("{}", i);
//std::vector<double> uncertainties;
std::vector<double> new_position = position; new_position[i] = position[i]-range;
double val_1 = CalcChi(new_position)-minimum-1.0;
Expand Down Expand Up @@ -201,7 +204,8 @@ std::vector<std::vector<double> > PSO::bisection(std::vector<double>position,dou
position_list_p[1] = new_bisect_position_p;
res = std::abs(position[2]-position[0]);
res_p = std::abs(position_list_p[1][i]-position_list_p[0][i]);
//std::cout << "Pos midpoint is " << position_list_p[1][i] << std::endl;
MACH3LOG_TRACE("Pos midpoint is {:.2f}", position_list_p[1][i]);

}
else{
std::vector<double> new_bisect_position_p = position_list_p[1];new_bisect_position_p[i] += (position_list_p[2][i]-position_list_p[1][i])/2;
Expand All @@ -211,17 +215,20 @@ std::vector<std::vector<double> > PSO::bisection(std::vector<double>position,dou
value_list_p[1] = new_val_p;
position_list_p[1] = new_bisect_position_p;
res_p = std::abs(position_list_p[2][i]-position_list_p[1][i]);
//std::cout << "Pos midpoint is " << position_list_p[1][i] << std::endl;
MACH3LOG_TRACE("Pos midpoint is {:.2f}", position_list_p[1][i]);
}
}
uncertainties_list.push_back({std::abs(position[i]-position_list[1][i]),std::abs(position[i]-position_list_p[1][i])});
std::cout << "Uncertainty finished for d = "<< i << std::endl;
std::cout << std::setprecision(10)<< "LLR values for ± positive and negative uncertainties are " << CalcChi(position_list[1]) << " and " << CalcChi(position_list_p[1]) << std::endl;
MACH3LOG_INFO("Uncertainty finished for d = {}", i);
MACH3LOG_INFO("LLR values for ± positive and negative uncertainties are {:<10.2f} and {:<10.2f}",
CalcChi(position_list[1]), CalcChi(position_list_p[1]));
}
return uncertainties_list;
}

std::vector<std::vector<double>> PSO::calc_uncertainty(std::vector<double>position,double minimum) {
// *************************
std::vector<std::vector<double>> PSO::calc_uncertainty(std::vector<double>position, double minimum) {
// *************************
std::vector<double> pos_uncertainty(position.size());
std::vector<double> neg_uncertainty(position.size());
int num = 200;
Expand Down Expand Up @@ -255,7 +262,7 @@ std::vector<std::vector<double>> PSO::calc_uncertainty(std::vector<double>positi
}
}
neg_uncertainty[i] = x[closest_index];
std::cout << "Neg" << std::endl;
MACH3LOG_INFO("Neg");
x.assign(num, 0);
y.assign(num, 0);
StepPoint = (pos_stop-start) / (num - 1);
Expand Down Expand Up @@ -283,11 +290,13 @@ std::vector<std::vector<double>> PSO::calc_uncertainty(std::vector<double>positi
return res;
}

// *************************
void PSO::uncertainty_check(std::vector<double> previous_pos){
// *************************
std::vector<std::vector<double >> x_list;
std::vector<std::vector<double >> y_list;
std::vector<double> position = previous_pos;
int num = 5000;
constexpr int num = 5000;
for (unsigned int i = 0;i<previous_pos.size();++i){
double curr_ival = position[i];
double start = previous_pos[i] - 1e-1;
Expand All @@ -296,30 +305,33 @@ void PSO::uncertainty_check(std::vector<double> previous_pos){
std::vector<double> y(num);
double StepPoint = (stop - start) / (num - 1);
double value = start;
// std::cout << "result for fDim " << 1 << std::endl;
for (int j =0;j< num; ++j){
MACH3LOG_TRACE("result for fDim: {}", 1);
for (int j = 0;j < num; ++j) {
position[i] = value;
double LLR = CalcChi(position);
x[j] = value;
y[j] = LLR;
value += StepPoint;
}
position[i] = curr_ival;
std::cout << " " << std::endl;
std::cout << "For fDim" << i+1 << " x list is " ;
for (unsigned int k= 0;k<x.size(); ++k){
std::cout << x[k] << " , " ;
} std::cout << " " << std::endl;
std::cout << " " << std::endl;
std::cout << "For fDim" << i+1 << " y list is " ;
for (unsigned int k= 0;k<x.size(); ++k){
std::cout << y[k] << " , " ;
} std::cout << " " << std::endl;
std::cout << " " <<std::endl;
MACH3LOG_INFO("");
MACH3LOG_INFO("For fDim{} x list is", i+1);
for (unsigned int k = 0;k<x.size(); ++k){
MACH3LOG_INFO(" {}", x[k]);
}
MACH3LOG_INFO("");
MACH3LOG_INFO("For fDim{} y list is", i+1);
for (unsigned int k = 0; k < x.size(); ++k){
MACH3LOG_INFO(" {}", y[k]);
}
MACH3LOG_INFO("");
}
}

// *************************
double PSO::swarmIterate(){
// *************************

std::vector<double> total_pos(fDim,0.0);

for (int i = 0; i < fParticles; ++i) {
Expand Down Expand Up @@ -377,8 +389,9 @@ double PSO::swarmIterate(){
return mean_dist_sq;
}

// *************************
void PSO::run() {

// *************************
double mean_dist_sq = 0;

int iter = 0;
Expand All @@ -398,11 +411,11 @@ void PSO::run() {
accCount++;

if (i%100 == 0){
std::cout << "Mean Dist Sq = " << mean_dist_sq <<std::endl;
std::cout << "Current LLR = " << fBestValue << std::endl;
std::cout << "Position = " <<std::endl;
for (int j = 0; j< fDim; ++j){
std::cout << " Dim " << j << " = " << std::setprecision(10) << get_best_particle()->get_personal_best_position()[j] << std::endl;
MACH3LOG_INFO("Mean Dist Sq = {:.2f}", mean_dist_sq);
MACH3LOG_INFO("Current LLR = {:.2f}", fBestValue);
MACH3LOG_INFO("Position:");
for (int j = 0; j < fDim; ++j){
MACH3LOG_INFO(" Dim {} = {:<10.2f}", j, get_best_particle()->get_personal_best_position()[j]);
}
}
if(fConvergence > 0.0){
Expand All @@ -411,18 +424,20 @@ void PSO::run() {
}
}
}
std::cout << "Finished after " << iter <<" runs out of "<< fIterations << std::endl;
std::cout << "Mean Dist " << mean_dist_sq <<std::endl;
std::cout << "Best LLR " << get_best_particle()->get_personal_best_value() << std::endl;

MACH3LOG_INFO("Finished after {} runs out of {}", iter, fIterations);
MACH3LOG_INFO("Mean Dist: {:.2f}", mean_dist_sq);
MACH3LOG_INFO("Best LLR: {:.2f}", get_best_particle()->get_personal_best_value());
uncertainties = bisection(get_best_particle()->get_personal_best_position(),get_best_particle()->get_personal_best_value(),0.5,0.005);
std::cout << "Position for Global Minimum = "<<std::endl;
MACH3LOG_INFO("Position for Global Minimum = ");
for (int i = 0; i< fDim; ++i){
std::cout << " Dim " << i << " = " << std::setprecision(10) << get_best_particle()->get_personal_best_position()[i] << " +" << uncertainties[i][1] << ", -" << uncertainties[i][0] << std::endl;
MACH3LOG_INFO(" Dim {} = {:<10.2f} +{:.2f}, -{:.2f}", i, get_best_particle()->get_personal_best_position()[i], uncertainties[i][1], uncertainties[i][0]);
}
}

// *************************
void PSO::WriteOutput(){
// *************************

outputFile->cd();

TVectorD* PSOParValue = new TVectorD(fDim);
Expand Down
8 changes: 3 additions & 5 deletions mcmc/PSO.h
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Open in desktop
Original file line number Diff line number Diff line change
@@ -1,9 +1,5 @@
#pragma once
//
// Created by Emily Ip on 24/2/2023.
//
// Created by Emily Ip on 26/1/2023.
//

// C++ includes
#include <algorithm>
#include <functional>
Expand All @@ -15,6 +11,7 @@

/// @brief Class particle - stores the position, velocity and personal best
/// With functions which move particle and update velocity
/// @note Created by Emily Ip on 24/2/2023.
class particle{
public:
particle(){};
Expand Down Expand Up @@ -72,6 +69,7 @@ class particle{
/// @brief Class PSO, consist of a vector of object Class Particle and global best
/// Takes in the size (number of particle) and number of iteration
/// functions includes: finding global best, updating velocity, actual minimisation function
/// @note Created by Emily Ip on 24/2/2023.
class PSO : public LikelihoodFit {
public:
/// @brief constructor
Expand Down
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