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Minor modifications (eoRng function increment_position(), tests file and

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compilation/installation script).

Failed tests:
From SMP: t-smpMW_eoEasyEA (OTHER_FAULT)
From EOMPI (issue #34): t-mpi-parallelApply (OTHER_FAULT)
	                t-mpi-wrapper (NUMERICAL)
	                t-mpi-multipleRoles (OTHER_FAULT)
	                t-mpi-distrib-exp (OTHER_FAULT)
This commit is contained in:
Adèle Harrissart 2014-10-04 19:17:38 +02:00
commit 34be39f0aa
3 changed files with 47 additions and 43 deletions
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2
build_gcc_linux_install
View file

@ -137,7 +137,7 @@ if [ "$res" = "y" ]; then
fi #ENABLE_64_BIT_RNG_NUMBERS
else
FLAG=$FLAG' '" -DENABLE_CXX11_RANDOM=false"
FLAG=$FLAG' '" -DENABLE_CXX11_RANDOM=false -DENABLE_64_BIT_RNG_NUMBERS=false"
fi #ENABLE_CXX11_RANDOM
color 5 "set $FLAG"

54
src/eo/utils/eoRNG.h
View file

@ -55,17 +55,15 @@ Old contact information: todos@geneura.ugr.es, http://geneura.ugr.es
#include "../eoPersistent.h"
#include "../eoObject.h"
#ifdef HAVE_RANDOM
#include <random> // Mersenne Twister available since C++11 ! About random library :
// "this library allows to produce random numbers using combinations of generators and distributions".
// (see www.cplusplus.com/reference/random/)
#endif
#if (UINT_MAX == 0xFFFFFFFFU) // Compile time check (32-bit vs. 64-bit environment)
#define ENV32BIT
#endif
#ifdef HAVE_RANDOM // If set to true (see CMake cache values)
#include <random> // Mersenne Twister available since C++11 ! About random library :
// "this library allows to produce random numbers using combinations of generators and distributions".
// (see www.cplusplus.com/reference/random/)
#ifndef ENV32BIT // Only on 64-bit environment
#ifdef WITH_64_BIT_RNG_NUMBERS // If set to true (see CMake cache values)
typedef uint64_t uint_t; // The C++11 Mersenne Twister pseudo-random generator can generate 64-bits numbers !
@ -150,7 +148,7 @@ public :
*/
eoRng(uint_t s)
#ifdef HAVE_RANDOM
: seed(s), position(0)
: seed(s), position(0), discard (false)
{
generator.seed(s); // initialize the internal state value
}
@ -181,9 +179,10 @@ public :
void reseed(uint_t s)
{
#ifdef HAVE_RANDOM
seed = s;
seed = 2*s;
position = 0;
generator.seed(s); // re-initialize the internal state value
discard = false;
generator.seed(seed); // re-initialize the internal state value
#else
initialize(2*s);
#endif
@ -229,7 +228,7 @@ public :
double uniform(double min, double max)
{ // random number between [min, max]
#ifdef HAVE_RANDOM
increment_position();
discard = true;
std::uniform_real_distribution<double> distribution(min, max);
return distribution(generator);
#else
@ -300,15 +299,9 @@ public :
double normal(double mean, double stdev)
{
#ifdef HAVE_RANDOM
// Don't increment the position here ...
discard = true;
std::normal_distribution<double> distribution(mean, stdev);
double ret = distribution(generator);
// ... but reseed the generator and call discard() to go further into the state sequence.
generator.seed(seed);
generator.discard(position); // According to the C++11 random library documentation
// the function complexity will be linear in the
// number of equivalent advances
return ret;
return distribution(generator);
#else
return mean + normal(stdev);
#endif
@ -322,7 +315,7 @@ public :
double negexp(double mean)
{
#ifdef HAVE_RANDOM
increment_position();
discard = true;
std::exponential_distribution<double> distribution(mean);
return distribution(generator);
#else
@ -404,10 +397,7 @@ public :
#ifdef HAVE_RANDOM
_is >> seed;
_is >> position;
generator.seed(seed);
generator.discard(position); // According to the C++11 random library documentation
// the function complexity will be linear in the
// number of equivalent advances
discard = true;
#else
for (int i = 0; i < N; ++i)
{
@ -448,9 +438,19 @@ public :
void increment_position()
{
if (position >= generator.state_size)
{
generator.seed(seed);
position = 1;
else
++position;
discard = false;
return;
}
if (discard)
{
generator.seed(seed);
generator.discard(position); // linear complexity
discard = false;
}
++position;
}
#else
@ -497,7 +497,9 @@ private:
// (one of the two requested parameters for the serialization)
unsigned position; // Position of the last generated number into the state sequence
// (one of the two requested parameters for the serialization)
// (one of the two requested parameters for the serialization)
bool discard; // Call discard() after using a distribution
#else

34
test/eo/t-eoRNGcxx11.cpp
View file

@ -41,12 +41,13 @@ void basic_tests()
void test_function(const unsigned N, uint_t(eoRng::*ptr)())
{
std::stringstream ss;
ss << rng; // Print eoRNG on stream
uint_t r1 = (rng.*ptr)();
rng.rand();
for (unsigned i = 0; i < N; i++)
(rng.*ptr)();
ss << rng; // Print eoRNG on stream
uint_t r1 = rng.rand();
ss >> rng; // Read eoRNG from stream
uint_t r2 = (rng.*ptr)();
uint_t r2 = rng.rand();
assert(r1 == r2);
}
@ -54,12 +55,13 @@ void test_function(const unsigned N, uint_t(eoRng::*ptr)())
void test_function(const unsigned N, double(eoRng::*ptr)(double), const double m)
{
std::stringstream ss;
ss << rng; // Print eoRNG on stream
uint_t r1 = (rng.*ptr)(m);
rng.rand();
for (unsigned i = 0; i < N; i++)
(rng.*ptr)(m);
ss << rng; // Print eoRNG on stream
uint_t r1 = rng.rand();
ss >> rng; // Read eoRNG from stream
uint_t r2 = (rng.*ptr)(m);
uint_t r2 = rng.rand();
assert(r1 == r2);
}
@ -81,16 +83,16 @@ void serialization_tests(const unsigned N, const double d)
uint_t s = static_cast<uint_t>(time(0));
rng.reseed(s);
test_function(N, ptr_rand);
test_function(N, ptr_rand);
rng.reseed(s);
test_function(N, ptr_uniform, double(1.0));
test_function(N, ptr_uniform, double(1.0));
rng.reseed(s);
test_function(N, ptr_normal, d);
test_function(N, ptr_normal, d);
rng.reseed(s);
test_function(N, ptr_negexp, d);
test_function(N, ptr_negexp, d);
std::cout << "ok" << std::endl;
}
@ -145,7 +147,7 @@ void stat_tests(const unsigned N)
{
// Important : don't forget to reseed the generator
s = static_cast<uint_t>(time(0) + i-1); // Chosen method to reseed generator (contestable):
// Add i-1 seconds to the current time based on the current system
// Add i-1 seconds to the current time based on the current system
rng.reseed(s);
x[i] = rng.normal();
@ -176,7 +178,7 @@ void stat_tests(const unsigned N)
double p_value = PyFloat_AsDouble(PyTuple_GetItem(pResult, 1));
std::cout << "Shapiro-Wilk test statistic:" << W << std::endl;
std::cout << "p-value of the Shapiro-Wilk test (strong if < 0.05):" << p_value << std::endl;
//Py_DECREF(pResult);
Py_DECREF(pResult);
}
// Free allocated memory
@ -206,10 +208,10 @@ void stat_tests(const unsigned N)
for (unsigned i = 0; i < N; i++)
{
// Important : don't forget to reseed the generator
s = static_cast<uint_t>(time(0) + i-1); // Chosen method to reseed generator (contestable):
// Add i-1 seconds to the current time based on the current system
rng.reseed(s);
// // Important : don't forget to reseed the generator
// s = static_cast<uint_t>(time(0) + i-1); // Chosen method to reseed generator (contestable):
// // Add i-1 seconds to the current time based on the current system
// rng.reseed(s);
// Observed frequencies
obs_freq[i] = rng.uniform();