This C++ code defines functions for statistical analysis and logging of simulation data. It includes functions to initialize log vectors for salesmen data, log field visits to a grid, and write output log files. Functions are also defined for histogramming data, smoothing and averaging vectors, and calculating statistics like the midpoint and variance of a data set.

1. statistics.cpp
#include <iostream>
#include <fstream>
#include <cmath>
#include <vector>
#include <algorithm>
#include <string>
#include "statistics.hpp"
#include "tools.hpp"
using std::endl;
Histogram::Histogram(std::vector<double> &v, double t_bin_size)
{
bin_size = t_bin_size;
//Groesstes und kleinstes Element finden
min = *min_element(v.begin(), v.end());
double max = *max_element(v.begin(), v.end());
int num_bins = int((max - min) / bin_size + 1.0);
data.resize(num_bins, 0);
int position;
for (unsigned int i = 0; i < v.size(); i++)
{
position = int((v[i] - min) / bin_size);
data[position] += 1;
}
}
Histogram::~Histogram() {}
/*-----------------------------------------------*/
void Statistics::Init(int* t_grid_size, int* t_bin_size,
int* t_num_iterations, int* t_num_customers, int* t_num_salesman) {
grid_size = t_grid_size;
log_field.resize((*grid_size) * (*grid_size), 0);
bin_size = t_bin_size;
num_iterations = t_num_iterations;
num_customers = t_num_customers;
num_salesman = t_num_salesman;
log_p.clear(); log_p.resize(*num_salesman);
log_earn.clear(); log_earn.resize(*num_salesman); last_earn.clear();
last_earn.resize(*num_salesman, 0);
log_sales.clear(); log_sales.resize(*num_salesman); last_sales.clear();
last_sales.resize(*num_salesman, 0);
log_visits.clear(); log_visits.resize(*num_salesman);
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2. statistics.cpp
last_visits.clear(); last_visits.resize(*num_salesman, 0);
path = "./output/";
prefix = "out";
}
void Statistics::LogField(int x, int y) {
log_field[x + y * (*grid_size)]++;
}
void Statistics::LogSalesman(int salesm_id, double earnings, double p, int
sales, int visits) {
log_p[salesm_id].push_back(p);
log_earn[salesm_id].push_back(earnings - last_earn[salesm_id]);
log_sales[salesm_id].push_back(sales - last_sales[salesm_id]);
log_visits[salesm_id].push_back(visits - last_visits[salesm_id]);
last_earn[salesm_id] = earnings;
last_sales[salesm_id] = sales;
last_visits[salesm_id] = visits;
}
void Statistics::WriteLogSalesman(std::string name) {
if (name == "") name = prefix;
Write2dVector(log_earn, path + name + "_earn.dat");
Write2dVector(log_p, path + name + "_p.dat");
Write2dVector(log_sales, path + name + "_sales.dat");
Write2dVector(log_visits, path + name + "_visits.dat");
}
void Statistics::Write2dVector(std::vector<std::vector<double> > &v, std::string
filename) {
std::ofstream write(filename.c_str());
for (unsigned int i = 0; i < v[0].size(); i++)
{
write << (i + 1) * (*bin_size) - 1;
for (unsigned int j = 0; j < v.size(); j++) {
write << "t" << v[j][i];
}
write << endl;
}
}
void Statistics::DivideData(std::vector<double> &v, double divisor) {
for (unsigned int i = 0; i < v.size(); i++) {
v[i] = v[i] / divisor;
}
}
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3. statistics.cpp
void Statistics::Smoothing(std::vector<double> &v) {
int N = v.size();
std::vector<double> tmp(N, 0);
for (int i = 0; i < N; i++) {
tmp[i] += 0.4 * v[i];
if (i > 0) tmp[i] += 0.3 * v[i-1];
else tmp[i] += 0.3 * v[i];
if (i < N-1) tmp[i] += 0.3 * v[i+1];
else tmp[i] += 0.3 * v[i];
}
v = tmp;
}
void Statistics::MSmoothing(std::vector<double> &v, int n) {
for (int i = 0; i < n; i++) {
Smoothing(v);
}
}
double Statistics::Midpoint(std::vector<double> &v) {
double sum = 0; unsigned int size = v.size();
for (unsigned int i = 0; i < size; i++) {
sum = sum + v[i];
}
return sum/size;
}
double Statistics::Variance(std::vector<double> &v) {
double midpoint = Midpoint(v);
double sum = 0; unsigned int size = v.size();
for (unsigned int i = 0; i < size; i++) {
sum = sum + (v[i] - midpoint) * (v[i] - midpoint);
}
return sum/(size - 1);
}
void Statistics::WriteHistogram(std::vector<double> &v, double bin_size,
std::string filename) {
filename = path + prefix + "_" + filename;
std::ofstream write(filename.c_str());
Histogram histo(v, bin_size);
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4. statistics.cpp
for (unsigned int i = 0; i < histo.data.size(); i++)
{
write << (i*bin_size + histo.min) << "t" << histo.data[i] <<
endl;
}
}
void Statistics::WriteFields(std::string filename) {
filename = path + prefix + "_" + filename;
std::ofstream write(filename.c_str());
int fx, fy;
for (unsigned int i = 0; i < log_field.size(); i++)
{
fx = i % (*grid_size);
fy = (i - fx) / (*grid_size);
write << fx << "t" << fy << "t" << log_field[i] << endl;
}
}
void Statistics::WriteFieldsDistance(std::string filename, int x, int y) {
filename = path + prefix + "_" + filename;
std::ofstream write(filename.c_str());
int fx, fy;
for (unsigned int i = 0; i < log_field.size(); i++)
{
fx = i % (*grid_size);
fy = (i - fx) / (*grid_size);
write << Distance(x, y, fx, fy, *grid_size) << "t" <<
log_field[i] << endl;
}
}
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