From f3d69ba680517be33ca5e68ccf922916ec1a1d03 Mon Sep 17 00:00:00 2001
From: Michal Kravcenko <michal.kravcenko@vsb.cz>
Date: Wed, 27 Feb 2019 13:54:06 +0100
Subject: [PATCH] MOD: placed the random generator to the body of the class for
more robust rng
---
src/DataSet/DataSet.cpp | 16 ++++++++++------
src/DataSet/DataSet.h | 5 +++++
2 files changed, 15 insertions(+), 6 deletions(-)
diff --git a/src/DataSet/DataSet.cpp b/src/DataSet/DataSet.cpp
index 1501e1ac..820c1e61 100644
--- a/src/DataSet/DataSet.cpp
+++ b/src/DataSet/DataSet.cpp
@@ -17,10 +17,13 @@ namespace lib4neuro {
this->n_elements = 0;
this->input_dim = 0;
this->output_dim = 0;
+ this->gen = boost::random::mt19937(std::time(0));
}
DataSet::DataSet(std::string file_path) {
std::ifstream ifs(file_path);
+ this->gen = boost::random::mt19937(std::time(0));
+
if(ifs.is_open()) {
try {
boost::archive::text_iarchive ia(ifs);
@@ -42,6 +45,7 @@ namespace lib4neuro {
this->data = *data_ptr;
this->input_dim = this->data[0].first.size();
this->output_dim = this->data[0].second.size();
+ this->gen = boost::random::mt19937(std::time(0));
if(ns) {
this->normalization_strategy = ns;
@@ -62,6 +66,7 @@ namespace lib4neuro {
this->n_elements = 0;
this->input_dim = 1;
this->output_dim = 1;
+ this->gen = boost::random::mt19937(std::time(0));
if(ns) {
this->normalization_strategy = ns;
@@ -82,6 +87,7 @@ namespace lib4neuro {
this->input_dim = bounds.size() / 2;
this->output_dim = output_dim;
this->n_elements = 0;
+ this->gen = boost::random::mt19937(std::time(0));
if(ns) {
this->normalization_strategy = ns;
@@ -400,19 +406,17 @@ namespace lib4neuro {
* Method returning random amount of data pairs between 1-max
*/
std::vector<std::pair<std::vector<double>, std::vector<double>>> DataSet::get_random_data_batch(size_t max) {
- if (max <= 0) {
+ if (max <= 0 || max >= this->data.size()) {
return this->data;
} else {
std::vector<std::pair<std::vector<double>, std::vector<double>>> newData;
- srand(time(NULL)); //TODO use Mersen twister from Boost
+ boost::random::uniform_int_distribution<> dist(0, this->data.size() - 1);
- size_t n_chosen = rand() % std::min(max, this->data.size())+1;
- n_chosen = max;
std::vector<size_t> chosens;
size_t chosen;
- for (int i = 0; i < n_chosen; i++) {
- chosen = rand() % this->data.size();
+ for (int i = 0; i < max; i++) {
+ chosen = dist(gen);
auto it = std::find(chosens.begin(), chosens.end(), chosen);
if (it != chosens.end()) {
diff --git a/src/DataSet/DataSet.h b/src/DataSet/DataSet.h
index 7793b748..fd20913a 100644
--- a/src/DataSet/DataSet.h
+++ b/src/DataSet/DataSet.h
@@ -12,6 +12,9 @@
#include <string>
#include <functional>
#include <limits>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_int_distribution.hpp>
+#include <ctime>
#include "../settings.h"
#include "../NormalizationStrategy/NormalizationStrategy.h"
@@ -26,6 +29,8 @@ namespace lib4neuro {
private:
+ boost::random::mt19937 gen;
+
/**
* Number of elements in the data set
*/
--
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