Merge pull request #6 from francesco086/continuous_integration

Continuous integration

Author: Ithanil

.gitignore

@@ -68,6 +68,9 @@ src/*.o
 debug/*.o
 debug/*.txt
 
+debug/unittests/ut*/*.o
+debug/unittests/ut*/*.sh
+
 examples/*/a.out
 examples/*/*.o
 

config_template.sh

@@ -12,6 +12,9 @@ FLAGS="-std=c++11 -Wall -Werror"
 # Optimization flags
 OPTFLAGS="-O3"
 
+# Debuggin flags
+DEBUGFLAGS="-g -O0"
+
 #FFNN Library (used in ex3)
 FFNN_FOLDER="/...../FeedForwardNeuralNetwork"
 IFFNN="-I${FFNN_FOLDER}/src/"

debug/unittests/README.md

@@ -0,0 +1,7 @@
+# LEGEND OF THE UNIT TESTS
+
+
+
+## Unit Test 1
+
+`ut1/`: check that calling the integrator again without doing the findMRT2step and initialDecorrelation gives the same results.

debug/unittests/run.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+
+for folder in ut*
+do
+    cp run_single_unittest.sh ${folder}/
+    cd ${folder}
+    echo "-> running unittest ${folder}"
+    echo ""
+    ./run_single_unittest.sh
+    cd ..
+done

debug/unittests/run_single_unittest.sh

@@ -0,0 +1,31 @@
+#!/bin/bash
+
+# After using this script it is necessary to run again the build.sh script
+# for generating again the library with the optimization flags
+
+OS_NAME=$(uname)
+source ../../../config.sh
+
+\rm -f exe
+\rm -f *.o
+
+ROOT_FOLDER=$(dirname $(dirname $(dirname $(pwd))))
+
+
+## Build the debugging main executable
+$CC $FLAGS $DEBUGFLAGS -Wall -I${ROOT_FOLDER}/src/ -c *.cpp
+
+case ${OS_NAME} in
+    "Linux")
+        $CC $FLAGS $DEBUGFLAGS -L${ROOT_FOLDER} -Wl,-rpath=${RPATH} -o exe *.o -l${LIBNAME}
+        ;;
+    "Darwin")
+        $CC $FLAGS $DEBUGFLAGS -L${ROOT_FOLDER} -o exe *.o -l${LIBNAME}
+        ;;
+    *)
+        echo "The detected operating system is not between the known ones (Linux and Darwin)"
+        ;;
+esac
+
+# Run the debugging executable
+./exe

debug/unittests/ut1/main.cpp

@@ -0,0 +1,84 @@
+#include "MCIntegrator.hpp"
+#include "MCISamplingFunctionInterface.hpp"
+
+#include <iostream>
+#include <math.h>
+#include <assert.h>
+
+using namespace std;
+
+
+
+class ThreeDimGaussianPDF: public MCISamplingFunctionInterface{
+public:
+    ThreeDimGaussianPDF(): MCISamplingFunctionInterface(3, 1){}
+    ~ThreeDimGaussianPDF(){}
+
+    void samplingFunction(const double *in, double * protovalues){
+        protovalues[0] = (in[0]*in[0]) + (in[1]*in[1]) + (in[2]*in[2]);
+    }
+
+
+    double getAcceptance(const double * protoold, const double * protonew){
+        return exp(-protonew[0]+protoold[0]);
+    }
+
+};
+
+
+class XSquared: public MCIObservableFunctionInterface{
+public:
+    XSquared(): MCIObservableFunctionInterface(3, 1){}
+    ~XSquared(){}
+
+    void observableFunction(const double * in, double * out){
+        out[0] = in[0] * in[0];
+    }
+};
+
+
+
+int main(){
+    const long NMC = 10000;
+    const double CORRECT_RESULT = 0.5;
+
+    ThreeDimGaussianPDF * pdf = new ThreeDimGaussianPDF();
+    XSquared * obs = new XSquared();
+
+    MCI * mci = new MCI(3);
+    mci->setSeed(5649871);
+    mci->addSamplingFunction(pdf);
+    mci->addObservable(obs);
+    // the integral should provide 0.5 as answer!
+
+    double * x = new double[3];
+    x[0] = 5.; x[1] = -5.; x[2] = 10.;
+
+    double * average = new double;
+    double * error = new double;
+
+    // this integral will give a wrong answer! This is because the starting point is very bad and initialDecorrelation is skipped (as well as the MRT2step automatic setting)
+    mci->setX(x);
+    mci->integrate(NMC, average, error, false, false);
+    assert( abs(average[0]-CORRECT_RESULT) > 2.*error[0] );
+
+    // this integral, instead, will provide the right answer
+    mci->setX(x);
+    mci->integrate(NMC, average, error);
+    assert( abs(average[0]-CORRECT_RESULT) < 2.*error[0] );
+
+    // now, doing an integral without finding again the MRT2step and doing the initialDecorrelation will also result in a correct result
+    mci->integrate(NMC, average, error, false, false);
+    assert( abs(average[0]-CORRECT_RESULT) < 2.*error[0] );
+
+
+
+    delete pdf;
+    delete obs;
+    delete mci;
+    delete x;
+    delete average;
+    delete error;
+
+    return 0;
+}

doc/user_manual.pdf

@@ -79,6 +79,22 @@ \section{Settings}
 It is not strictly necessary to set all the following settings because there are already default values, however the user should be aware of their existence.
 
 
+
+\subsection{Random generator's seed} % (fold)
+\label{sub:random_generator_seed}
+
+\begin{verbatim}
+>  void setSeed(const long seed)
+\end{verbatim}
+
+One can set the random generator's seed \verb+seed+ simply by invoking:
+\begin{verbatim}
+   mci.setSeed(seed);
+\end{verbatim}
+% subsection random_generator_seed (end)
+
+
+
 \subsection{Integral domain} % (fold)
 \label{sub:integral_domain}
 
@@ -474,7 +490,7 @@ \section{Integration} % (fold)
 \label{sec:integration}
 
 \begin{verbatim}
->  void integrate(const long &Nmc, double * average, double * error);
+>  void integrate(const long &Nmc, double * average, double * error, bool findMRT2step=true, bool initialdecorrelation=true);
 \end{verbatim}
 
 Once that all the settings are done, one can obtain the result of the integral by invoking
@@ -485,6 +501,8 @@ \section{Integration} % (fold)
 \verb+Nmc+ is the number of sampled points: The larger this value, the more accurate will be the result, according to the well known $1/\sqrt{\verb+NMC+}$ rule.
 \verb+average+ will contain the resulting numeric estimation of the integral with an estimated standard deviation stored in \verb+error+.
 
+The two optional parameters \verb+findMRT2step+ and \verb+initialdecorrelation+ can be set to false in case one wants to skip the automatic setting of the MRT2 step and the initial random MC steps used to "warm up" the walker (i.e. perform initial decorrelation from the starting walker position).
+
 The Monte Carlo integral is composed by several substep, completely hidden to the user.
 We report them for general knowledge.
 \begin{enumerate}

doc/user_manual.tex

@@ -10,17 +10,17 @@
 
 //   --- Integrate
 
-void MCI::integrate(const long &Nmc, double * average, double * error)
+void MCI::integrate(const long &Nmc, double * average, double * error, bool findMRT2step, bool initialdecorrelation)
 {
     long i;
 
     if ( _flagpdf )
-        {
-            //find the optimal mrt2 step
-            this->findMRT2Step();
-            // take care to do the initial decorrelation of the walker
-            this->initialDecorrelation();
-        }
+    {
+        //find the optimal mrt2 step
+        if (findMRT2step) this->findMRT2Step();
+        // take care to do the initial decorrelation of the walker
+        if (initialdecorrelation) this->initialDecorrelation();
+    }
 
     //allocation of the array where the data will be stored
     _datax = new double*[Nmc];
@@ -526,6 +526,12 @@ void MCI::setIRange(const double * const * irange)
 }
 
 
+void MCI::setSeed(const long seed)
+{
+    _rgen.seed(seed);
+}
+
+
 //   --- Constructor and Destructor
 
 MCI::MCI(const int & ndim)

src/MCIntegrator.cpp

@@ -88,6 +88,8 @@ class MCI
     ~MCI();  //Destructor
 
     // --- Setters
+    void setSeed(const long seed);
+
     void setIRange(const double * const * irange);
 
     void setX(const double * x);
@@ -127,7 +129,7 @@ class MCI
     double getAcceptanceRate(){return (double(_acc)/(double(_acc+_rej)));}
 
     // --- Integrate
-    void integrate(const long &Nmc, double * average, double * error);
+    void integrate(const long &Nmc, double * average, double * error, bool findMRT2step=true, bool initialdecorrelation=true);
 
 
 };