From 18bf35609ce2c6f8b9cdacd5edc93d79d214a54b Mon Sep 17 00:00:00 2001
From: Ruben Martinez-Cantin <rmcantin@gmail.com>
Date: Tue, 7 Oct 2014 18:35:35 +0200
Subject: [PATCH] Fixing minor bugs and typos

---
 README.md              |  9 +++++----
 matplotpp/matplotpp.cc |  8 ++++----
 matplotpp/matplotpp.h  | 14 +++++++++-----
 src/bayesoptbase.cpp   |  1 +
 utils/lhs.hpp          |  6 +-----
 5 files changed, 20 insertions(+), 18 deletions(-)

diff --git a/README.md b/README.md
index 9473a8f..898bbab 100644
--- a/README.md
+++ b/README.md
@@ -29,7 +29,8 @@ The library can be download from any of this sources:
 - Mirror: <http://mloss.org/software/view/453/>
 
 The install guide and documentation for Windows, Linux and MacOS:
-- [Online install guide](http://rmcantin.bitbucket.org/html/install.html) or [Local install guide](@ref install)
+- [Online install guide](http://rmcantin.bitbucket.org/html/install.html) 
+  or [Local install guide](@ref install)
 
 
 Getting involved
@@ -53,9 +54,9 @@ please consider these recomentations when using BayesOpt:
 publication, we would appreciate it if you would kindly cite BayesOpt
 in your manuscript. Cite BayesOpt as:
 
-> Ruben Martinez-Cantin, **BayesOpt: A Bayesian Optimization Library for Nonlinear
-> Optimization, Experimental Design and Bandits**,
-> <http://bitbucket.org/rmcantin/bayesopt>
+> Ruben Martinez-Cantin, **BayesOpt: A Bayesian Optimization
+> Library for Nonlinear Optimization, Experimental Design and
+> Bandits**. Journal of Machine Learning Research, 2014
 
 - In addition, if you use a specific algorithm (REMBO, GP-Hedge,
 etc.), please also cite the corresponding work. The reference for each
diff --git a/matplotpp/matplotpp.cc b/matplotpp/matplotpp.cc
index 48da8e1..bc675fb 100644
--- a/matplotpp/matplotpp.cc
+++ b/matplotpp/matplotpp.cc
@@ -12,10 +12,10 @@ using namespace std;
 #include "matplotpp.h"
 
 #if defined(_WIN32) || defined(_WIN64)
-#define fmax max
-#define fmin min
-#pragma warning (disable:4996)
-#define snprintf sprintf_s
+#  define fmax max
+#  define fmin min
+#  pragma warning (disable:4996)
+#  define snprintf sprintf_s
 #endif
 
 /// Figure
diff --git a/matplotpp/matplotpp.h b/matplotpp/matplotpp.h
index 7785701..4c3cb8d 100644
--- a/matplotpp/matplotpp.h
+++ b/matplotpp/matplotpp.h
@@ -10,12 +10,16 @@ Modified: Ruben Martinez-Cantin (2013)
     - Fixed bugs
 ****************************************************************************/
 
+//FreeGLUT does not need this. But Nate's GLUT for Windows does.
+#if defined(_WIN32) || defined(_WIN64)
+#    include <windows.h>
+#endif
+
+//Using default GLUT in Mac OS
 #ifdef __APPLE__
-//#include <OpenGL/gl.h> //OS x libs
-//#include <OpenGL/glu.h>
-#include <GLUT/glut.h>
+#    include <GLUT/glut.h>
 #else
-#include <GL/glut.h>
+#    include <GL/glut.h>
 #endif
 
 #include <vector>
@@ -24,7 +28,7 @@ Modified: Ruben Martinez-Cantin (2013)
 #include <valarray>
 #include <iostream>
 #include <cmath>
-#include <time.h>
+#include <ctime>
 #include "gl2ps.h"
 
 #define PI 3.14159265358979323846264
diff --git a/src/bayesoptbase.cpp b/src/bayesoptbase.cpp
index 339d892..902a7f8 100644
--- a/src/bayesoptbase.cpp
+++ b/src/bayesoptbase.cpp
@@ -20,6 +20,7 @@
 ------------------------------------------------------------------------
 */
 
+#include <ctime>
 #include "bayesoptbase.hpp"
 
 #include "log.hpp"
diff --git a/utils/lhs.hpp b/utils/lhs.hpp
index d66ccb2..ca1f14e 100644
--- a/utils/lhs.hpp
+++ b/utils/lhs.hpp
@@ -127,15 +127,11 @@ namespace bayesopt
 			randEngine& mtRandom)
     {
       randFloat sample( mtRandom, realUniformDist(0,1) );
-      //      sample.engine().seed(std::time(0));
-      //      std::cout << &mtRandom;
-      //      mtRandom.seed(std::time(0));
-      //      sample.distribution().reset();
       size_t nA = Result.size1();
       size_t nB = Result.size2();
 
-      //      std::generate(Result.begin2(),Result.end2(),sample);
       // TODO: Improve with iterators
+      // std::generate(Result.begin2(),Result.end2(),sample);
       for (size_t i = 0; i < nA; i++)
       	for (size_t j = 0; j < nB; j++)
       	  Result(i,j) = sample();