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trick/trick_source/sim_services/MonteCarlo/test/MonteCarlo_test.cpp
Alex Lin d3acfa5fc0 Test code does not work with new directory locations. 
Adjusted all of the source code to point to the header files in their new
locations.  Adjusted the makefiles for the header locations as well.
Added .gitignore files in the test directories to ignore test object code.
2015-06-22 16:11:08 -05:00

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#define protected public
#include <iostream>
#include <sys/types.h>
#include <signal.h>
#include <string>
#include <sstream>
#include <cmath>
#include "gtest/gtest.h"
#include "trick/ExecutiveException.hh"
#include "trick/Executive.hh"
#include "trick/MonteCarlo.hh"
#include "trick/MonteVar.hh"
#include "trick/MonteVarCalculated.hh"
#include "trick/MonteVarFile.hh"
#include "trick/MonteVarFixed.hh"
#include "trick/MonteVarRandom.hh"
#include "trick/montecarlo_c_intf.h"
#include "trick/exec_proto.h"
#include "trick/exec_proto.hh"
#include "trick/SimObject.hh"
#include "trick/MemoryManager.hh"
#include "trick/memorymanager_c_intf.h"
#include "trick/rand_generator.h"
//#include "trick/RequirementScribe.hh"
void sig_hand(int sig) ;
void child_handler(int sig) ;
#if (__APPLE__ | __CYGWIN__ | __INTERIX )
void fpe_sig_handler(int sig) ;
#else
void fpe_sig_handler(int sig, siginfo_t * sip, void *uap) ;
#endif
namespace Trick {
class testSimObject : public Trick::SimObject {
public:
int default_data_1() {
return 0 ;
}
int initialization_1() {
return 0 ;
}
int return_error() {
return -1 ;
}
int throw_exception() {
return exec_terminate("throw_exception", "exec_terminate called") ;
}
testSimObject() {
int ii = 0 ;
add_job(0, ii++, "monte_master_init", NULL, 1, "master_init", "TRK") ;
add_job(0, ii++, "monte_master_pre", NULL, 1, "master_pre", "TRK") ;
add_job(0, ii++, "monte_master_post", NULL, 1, "master_post", "TRK") ;
add_job(0, ii++, "monte_master_shutdown", NULL, 1, "master_shutdown", "TRK") ;
add_job(0, ii++, "monte_slave_init", NULL, 1, "slave_init", "TRK") ;
add_job(0, ii++, "monte_slave_pre", NULL, 1, "slave_pre", "TRK") ;
add_job(0, ii++, "monte_slave_post", NULL, 1, "slave_post", "TRK") ;
add_job(0, ii++, "monte_slave_shutdown", NULL, 1, "slave_shutdown", "TRK") ;
}
virtual int call_function( Trick::JobData * curr_job ) ;
virtual double call_function_double( Trick::JobData * curr_job ) { (void)curr_job ; return 0.0 ; } ;
} ;
int testSimObject::call_function( __attribute__((unused)) Trick::JobData * curr_job ) {
int trick_ret = 0 ;
return trick_ret ;
} ;
class MonteCarloTest : public ::testing::Test {
protected:
Trick::MonteCarlo exec;
Trick::Executive executive;
testSimObject so1 ;
//Trick::RequirementScribe req;
Trick::MemoryManager mm ;
MonteCarloTest() { exec_register_scheduler(&exec) ; }
~MonteCarloTest() { }
virtual void SetUp() {}
virtual void TearDown() {}
int get_class_map_value(std::string job_class) { return exec.class_map[job_class] ; }
Trick::ScheduledJobQueue * get_master_init_queue() { return &exec.master_init_queue ; }
Trick::ScheduledJobQueue * get_master_pre_queue() { return &exec.master_pre_queue ; }
Trick::ScheduledJobQueue * get_master_post_queue() { return &exec.master_post_queue ; }
Trick::ScheduledJobQueue * get_master_shutdown_queue() { return &exec.master_shutdown_queue ; }
Trick::ScheduledJobQueue * get_slave_init_queue() { return &exec.slave_init_queue ; }
Trick::ScheduledJobQueue * get_slave_pre_queue() { return &exec.slave_pre_queue ; }
Trick::ScheduledJobQueue * get_slave_post_queue() { return &exec.slave_post_queue ; }
Trick::ScheduledJobQueue * get_slave_shutdown_queue() { return &exec.slave_shutdown_queue ; }
} ;
TEST_F(MonteCarloTest , Job_Queue_Master_Init) {
//req.add_requirement("722132127");
Trick::JobData * curr_job ;
EXPECT_EQ(exec_get_time_tic_value() , 1000000) ;
exec_add_sim_object(&so1 , "so1") ;
curr_job = get_master_init_queue()->get_next_job() ;
ASSERT_FALSE( curr_job == NULL ) ;
EXPECT_STREQ( curr_job->name.c_str() , "so1.master_init") ;
EXPECT_TRUE(executive.check_all_jobs_handled() == 0 ) ;
}
TEST_F(MonteCarloTest , Job_Queue_Master_Pre) {
//req.add_requirement("587551115");
Trick::JobData * curr_job ;
EXPECT_EQ(exec_get_time_tic_value() , 1000000) ;
exec_add_sim_object(&so1 , "so1") ;
curr_job = get_master_pre_queue()->get_next_job() ;
ASSERT_FALSE( curr_job == NULL ) ;
EXPECT_STREQ( curr_job->name.c_str() , "so1.master_pre") ;
EXPECT_TRUE(executive.check_all_jobs_handled() == 0 ) ;
}
TEST_F(MonteCarloTest , Job_Queue_Master_Post) {
//req.add_requirement("4165308678");
Trick::JobData * curr_job ;
EXPECT_EQ(exec_get_time_tic_value() , 1000000) ;
exec_add_sim_object(&so1 , "so1") ;
curr_job = get_master_post_queue()->get_next_job() ;
ASSERT_FALSE( curr_job == NULL ) ;
EXPECT_STREQ( curr_job->name.c_str() , "so1.master_post") ;
EXPECT_TRUE(executive.check_all_jobs_handled() == 0 ) ;
}
TEST_F(MonteCarloTest , Job_Queue_Master_Shutdown) {
//req.add_requirement("3461634900");
Trick::JobData * curr_job ;
EXPECT_EQ(exec_get_time_tic_value() , 1000000) ;
exec_add_sim_object(&so1 , "so1") ;
curr_job = get_master_shutdown_queue()->get_next_job() ;
ASSERT_FALSE( curr_job == NULL ) ;
EXPECT_STREQ( curr_job->name.c_str() , "so1.master_shutdown") ;
EXPECT_TRUE(executive.check_all_jobs_handled() == 0 ) ;
}
TEST_F(MonteCarloTest , Job_Queue_Slave_Init) {
//req.add_requirement("1412318284");
Trick::JobData * curr_job ;
EXPECT_EQ(exec_get_time_tic_value() , 1000000) ;
exec_add_sim_object(&so1 , "so1") ;
curr_job = get_slave_init_queue()->get_next_job() ;
ASSERT_FALSE( curr_job == NULL ) ;
EXPECT_STREQ( curr_job->name.c_str() , "so1.slave_init") ;
EXPECT_TRUE(executive.check_all_jobs_handled() == 0 ) ;
}
TEST_F(MonteCarloTest , Job_Queue_Slave_Pre) {
//req.add_requirement("3301658297");
Trick::JobData * curr_job ;
EXPECT_EQ(exec_get_time_tic_value() , 1000000) ;
exec_add_sim_object(&so1 , "so1") ;
curr_job = get_slave_pre_queue()->get_next_job() ;
ASSERT_FALSE( curr_job == NULL ) ;
EXPECT_STREQ( curr_job->name.c_str() , "so1.slave_pre") ;
EXPECT_TRUE(executive.check_all_jobs_handled() == 0 ) ;
}
TEST_F(MonteCarloTest , Job_Queue_Slave_Post) {
//req.add_requirement("3882184138");
Trick::JobData * curr_job ;
EXPECT_EQ(exec_get_time_tic_value() , 1000000) ;
exec_add_sim_object(&so1 , "so1") ;
curr_job = get_slave_post_queue()->get_next_job() ;
ASSERT_FALSE( curr_job == NULL ) ;
EXPECT_STREQ( curr_job->name.c_str() , "so1.slave_post") ;
EXPECT_TRUE(executive.check_all_jobs_handled() == 0 ) ;
}
TEST_F(MonteCarloTest , Job_Queue_Slave_Shutdown) {
//req.add_requirement("350185460");
Trick::JobData * curr_job ;
EXPECT_EQ(exec_get_time_tic_value() , 1000000) ;
exec_add_sim_object(&so1 , "so1") ;
curr_job = get_slave_shutdown_queue()->get_next_job() ;
ASSERT_FALSE( curr_job == NULL ) ;
EXPECT_STREQ( curr_job->name.c_str() , "so1.slave_shutdown") ;
EXPECT_TRUE(executive.check_all_jobs_handled() == 0 ) ;
}
TEST_F(MonteCarloTest , Good_Initialization) {
//req.add_requirement("1452306647");
exec_add_sim_object(&so1 , "so1") ;
EXPECT_EQ(exec.execute_monte() , 0 ) ;
}
TEST_F(MonteCarloTest , TestDefaultValues) {
EXPECT_EQ(exec.get_enabled(), false) ;
EXPECT_EQ(exec.get_dry_run(), false) ;
EXPECT_EQ(exec.get_localhost_as_remote(), false) ;
EXPECT_EQ(exec.get_custom_slave_dispatch(), false) ;
EXPECT_EQ(exec.get_timeout(), 120) ;
EXPECT_EQ(exec.get_max_tries(), 2) ;
EXPECT_EQ(exec.get_verbosity(), exec.INFORMATIONAL) ;
EXPECT_EQ(exec.get_num_runs(), 0) ;
EXPECT_EQ(exec.get_slave_id(), 0) ;
EXPECT_EQ(exec.actual_num_runs, 0) ;
EXPECT_EQ(exec.num_results, 0) ;
}
TEST_F(MonteCarloTest, TestSettingValues) {
//req.add_requirement("2840823120");
exec.set_enabled(true) ;
EXPECT_EQ(exec.get_enabled(), true) ;
exec.set_dry_run(true) ;
EXPECT_EQ(exec.get_dry_run(), true) ;
exec.set_localhost_as_remote(true) ;
EXPECT_EQ(exec.get_localhost_as_remote(), true) ;
exec.set_custom_slave_dispatch(true) ;
EXPECT_EQ(exec.get_custom_slave_dispatch(), true) ;
exec.set_timeout(60) ;
EXPECT_EQ(exec.get_timeout(), 60) ;
exec.set_max_tries(4) ;
EXPECT_EQ(exec.get_max_tries(), 4) ;
exec.set_verbosity(exec.NONE) ;
EXPECT_EQ(exec.get_verbosity(), exec.NONE) ;
exec.set_verbosity(exec.ERROR) ;
EXPECT_EQ(exec.get_verbosity(), exec.ERROR) ;
exec.set_verbosity(exec.INFORMATIONAL) ;
EXPECT_EQ(exec.get_verbosity(), exec.INFORMATIONAL) ;
exec.set_verbosity(exec.ALL) ;
EXPECT_EQ(exec.get_verbosity(), exec.ALL) ;
}
TEST_F(MonteCarloTest, TestRanges) {
exec.set_num_runs(25) ;
EXPECT_EQ(exec.get_num_runs(), 25) ;
EXPECT_EQ(exec.actual_num_runs, 25) ;
exec.add_range(3, 5) ;
EXPECT_EQ(exec.actual_num_runs, 3) ;
exec.add_range(20) ;
EXPECT_EQ(exec.actual_num_runs, 4) ;
EXPECT_EQ(exec.in_range(exec.runs[3]) , true) ;
EXPECT_EQ(exec.in_range(exec.runs[10]), false) ;
}
TEST_F(MonteCarloTest, TestSlaves) {
//req.add_requirement("1098748189");
Trick::MonteSlave slave0("localhost") ;
Trick::MonteSlave slave1("WonderWoman") ;
EXPECT_EQ(exec.slaves.empty(), true) ;
EXPECT_EQ(exec.get_slave_index(1), -1) ;
exec.add_slave(&slave0) ;
EXPECT_EQ(exec.slaves.empty(), false) ;
EXPECT_EQ(exec.slaves.size(), 1) ;
exec.add_slave(&slave1) ;
EXPECT_EQ(exec.slaves.size(), 2) ;
EXPECT_EQ(slave0.id, 1) ;
EXPECT_EQ(slave1.id, 2) ;
EXPECT_EQ(exec.get_slave_index(1), 0) ;
EXPECT_EQ(exec.get_slave_index(2), 1) ;
EXPECT_EQ(slave0.state, Trick::MonteSlave::UNINITIALIZED) ;
EXPECT_EQ(slave1.state, Trick::MonteSlave::UNINITIALIZED) ;
exec.disable_slave("WonderWoman", true) ;
EXPECT_EQ(slave1.state, Trick::MonteSlave::STOPPED) ;
EXPECT_EQ(exec.slaves.size(), 2) ;
exec.disable_slave("WonderWoman", false) ;
EXPECT_EQ(slave1.state, Trick::MonteSlave::UNINITIALIZED) ;
EXPECT_EQ(slave0.machine_name, "localhost") ;
EXPECT_EQ(slave1.machine_name, "WonderWoman") ;
}
TEST_F(MonteCarloTest, MonteVarFile) {
std::string buffer;
std::string buffer2;
//req.add_requirement("3932595803");
// Test MonteVarFile
Trick::MonteVarFile var0("time_to_fire_1", "M_jet_firings_inline", 2) ;
EXPECT_EQ(exec.variables.size(), 0) ;
exec.add_variable(&var0) ;
EXPECT_EQ(var0.get_next_value(), "time_to_fire_1 = 1") ;
EXPECT_EQ(exec.variables.size(), 1) ;
}
TEST_F(MonteCarloTest, MonteVarRandom_Gaussian) {
std::string str;
double value;
//req.add_requirement("3932595803");
// Test MonteVarRandom
// Gaussian
Trick::MonteVarRandom var1("time_to_fire_1", Trick::MonteVarRandom::GAUSSIAN) ;
var1.set_mu(4.0) ;
var1.set_min(-4.0) ;
var1.set_max(4.0) ;
var1.set_seed(12345);
var1.set_sigma_range(0) ;
exec.add_variable(&var1) ;
var1.get_next_value();
str = var1.value;
std::stringstream sstream(str);
sstream >> value;
EXPECT_LE(value, 8);
EXPECT_GE(value, 0);
EXPECT_EQ(var1.name, "time_to_fire_1") ;
EXPECT_EQ(var1.distribution, 0) ;
EXPECT_EQ(var1.randist.mu, 4.0) ;
EXPECT_EQ(var1.randist.min, -4.0) ;
EXPECT_EQ(var1.randist.max, 4.0) ;
EXPECT_EQ(var1.unit, "") ;
EXPECT_EQ(exec.variables.size(), 1) ;
}
TEST_F(MonteCarloTest, MonteVarRandom_Poisson) {
std::string str;
double value;
//req.add_requirement("3932595803");
// Test MonteVarRandom
// Poisson
Trick::MonteVarRandom var2("time_to_fire_1", Trick::MonteVarRandom::POISSON, "s") ;
var2.set_mu(4.0) ;
var2.set_min(-4.0) ;
var2.set_max(4.0) ;
var2.set_min_is_relative(0);
var2.set_max_is_relative(0);
var2.set_seed(12345);
var2.set_sigma_range(0) ;
exec.add_variable(&var2) ;
var2.get_next_value();
str = var2.value;
std::stringstream sstream(str);
sstream >> value;
#if _HAVE_GSL
EXPECT_GE(value, 0);
EXPECT_LE(value, 4);
#else
EXPECT_EQ(value, 0);
#endif
EXPECT_EQ(var2.name, "time_to_fire_1") ;
EXPECT_EQ(var2.distribution, 2) ;
EXPECT_EQ(var2.unit, "s") ;
EXPECT_EQ(exec.variables.size(), 1) ;
}
TEST_F(MonteCarloTest, MonteVarRandom_Flat) {
std::string str;
double value;
//req.add_requirement("3932595803");
// Test MonteVarRandom
// Flat
Trick::MonteVarRandom var3("time_to_fire_4", Trick::MonteVarRandom::FLAT) ;
var3.set_mu(4.0) ;
var3.set_min(-4.0) ;
var3.set_max(4.0) ;
var3.set_seed(12345);
var3.set_sigma_range(0) ;
exec.add_variable(&var3) ;
var3.get_next_value();
str = var3.value;
std::stringstream sstream(str);
sstream >> value;
EXPECT_GE(value, 0);
EXPECT_LE(value, 8);
EXPECT_EQ(var3.name, "time_to_fire_4") ;
EXPECT_EQ(var3.distribution, 1) ;
EXPECT_EQ(var3.unit, "") ;
EXPECT_EQ(exec.variables.size(), 1) ;
}
TEST_F(MonteCarloTest, MonteVarRandom_NonGSL) {
//req.add_requirement("3932595803");
Trick::MonteVarRandom var4("time_to_fire_1", Trick::MonteVarRandom::GAUSSIAN) ;
var4.set_mu(4.0) ;
var4.set_min(-4.0) ;
var4.set_max(4.0) ;
var4.set_seed(12345);
// for this test, let sigma_range default to 1 var4.set_sigma_range(0) ;
exec.add_variable(&var4) ;
// Test MonteVarRandom
// non GSL library variables
EXPECT_EQ(var4.randist.uniform, LCG1) ;
var4.set_uniform_generator(TRIPLE) ;
EXPECT_EQ(var4.randist.uniform, 1) ;
var4.set_uniform_generator(LCG1) ;
EXPECT_EQ(var4.randist.uniform, LCG1) ;
EXPECT_EQ(var4.randist.sigma_range, 1) ;
var4.set_sigma_range(8) ;
EXPECT_EQ(var4.randist.sigma_range, 8) ;
}
TEST_F(MonteCarloTest, MonteVarFixed) {
//req.add_requirement("3932595803");
// Test MonteVarFixed
Trick::MonteVarFixed var5("time_to_fire_5", 3.1415) ;
exec.add_variable(&var5) ;
EXPECT_EQ(var5.get_next_value(), "time_to_fire_5 = 3.1415") ;
EXPECT_EQ(var5.name, "time_to_fire_5") ;
EXPECT_EQ(var5.unit, "") ;
EXPECT_EQ(exec.variables.size(), 1) ;
}
///@brief check that the final distribution is correct. (Bug 6950: The non-GSL was wrong for GAUSSIAN and FLAT)
TEST_F(MonteCarloTest, MonteVarRandom_Gaussian_distributionMatchesSpec) {
//req.add_requirement("3932595803");
std::string str ;
double value ;
Trick::MonteVarRandom var6("time_to_fire_1", Trick::MonteVarRandom::GAUSSIAN) ;
exec.add_variable(&var6) ;
double expected_mean = 10.0 ;
double expected_sigma = 2.0 ;
var6.set_seed(12345) ;
var6.set_mu(expected_mean) ;
var6.set_sigma(expected_sigma) ;
var6.set_min(-10.0) ;
var6.set_max(10.0) ;
var6.set_sigma_range(0) ;
// maintain running sums for calculating mean and variance
double mean = 0.0 ;
double sum_variance = 0.0 ;
int n = 0 ;
double delta = 0.0 ;
int numRuns = 100 ;
for (int ii = 0; ii <= numRuns; ++ii) {
{
var6.get_next_value() ;
str = var6.value ;
std::stringstream sstream(str) ;
sstream >> value ;
}
n++ ;
delta = value - mean ;
mean += delta / (double)n ;
sum_variance += delta * (value - mean) ;
}
// final statistics
double variance = sum_variance / (double) (n - 1) ;
double sigma = sqrt(variance) ;
EXPECT_NEAR(expected_mean, mean, 0.05 * expected_mean) ;
EXPECT_NEAR(expected_sigma, sigma, 0.10 * expected_sigma) ;
}
#ifndef _HAVE_GSL
///@brief set_sigma_range(int) feature was only implemented for nonGsl with non-C++11 fallbacks
TEST_F(MonteCarloTest, MonteVarRandom_Gaussian_nonGslSigmaRangeDefaulted_maxDeviationFromMeanIs1Sigma) {
//req.add_requirement("3932595803");
std::string str ;
double value ;
Trick::MonteVarRandom var7("time_to_fire_1", Trick::MonteVarRandom::GAUSSIAN) ;
exec.add_variable(&var7) ;
double expected_mean = 10.0 ;
double expected_sigma = 2.0 ;
var7.set_seed(12345) ;
var7.set_mu(expected_mean) ;
var7.set_sigma(expected_sigma) ;
var7.set_min(-10.0) ;
var7.set_max(10.0) ;
// without this call, default sigma_range is 1
// var7.set_sigma_range(0) ;
int num_runs = 100 ;
double sigmas_max_deviation_from_mean = 0.0 ;
double deviation_sigmas = 0.0 ;
for (int ii = 0; ii <= num_runs; ++ii) {
{
var7.get_next_value() ;
str = var7.value ;
std::stringstream sstream(str) ;
sstream >> value ;
}
deviation_sigmas = fabs( (value - expected_mean) / expected_sigma ) ;
if (deviation_sigmas > sigmas_max_deviation_from_mean) {
sigmas_max_deviation_from_mean = deviation_sigmas ;
}
}
// Loose constraint: anything .LE. 1 will pass.
// (Doesn't require the largest deviations to be around 1.
// In other words, even max deviations of zero would pass.)
//EXPECT_LE(sigmas_max_deviation_from_mean, 1.0) ;
// tighter constraint: the max deviation with 100 runs
// should be pretty close to but still <= 1.0.
// This specifies the range 0.9 .. 1.0
EXPECT_NEAR(sigmas_max_deviation_from_mean, 0.95, 0.05) ;
}
///@brief test set_sigma_range feature works for STL random
TEST_F(MonteCarloTest, MonteVarRandom_StlGaussian_nonGslSigmaRangeDefaulted_maxDeviationFromMeanIs1Sigma) {
//req.add_requirement("3932595803");
std::string str ;
double value ;
Trick::MonteVarRandom var9("time_to_fire_1", Trick::MonteVarRandom::GAUSSIAN, "", Trick::MonteVarRandom::TRICK_DEFAULT_ENGINE) ;
exec.add_variable(&var9) ;
double expected_mean = 10.0 ;
double expected_sigma = 2.0 ;
var9.set_seed(12345) ;
var9.set_mu(expected_mean) ;
var9.set_sigma(expected_sigma) ;
var9.set_min(-10.0) ;
var9.set_max(10.0) ;
// without this call, default sigma_range is 1
// var9.set_sigma_range(0) ;
int num_runs = 1000 ;
double sigmas_max_deviation_from_mean = 0.0 ;
double deviation_sigmas = 0.0 ;
for (int ii = 0; ii <= num_runs; ++ii) {
{
var9.get_next_value() ;
str = var9.value ;
std::stringstream sstream(str) ;
sstream >> value ;
}
deviation_sigmas = fabs( (value - expected_mean) / expected_sigma ) ;
if (deviation_sigmas > sigmas_max_deviation_from_mean) {
sigmas_max_deviation_from_mean = deviation_sigmas ;
}
}
// Loose constraint: anything .LE. 1 will pass.
// (Doesn't require the largest deviations to be around 1.
// In other words, even max deviations of zero would pass.)
//EXPECT_LE(sigmas_max_deviation_from_mean, 1.0) ;
// tighter constraint: the max deviation with 100 runs
// should be pretty close to but still <= 1.0.
// This specifies the range 0.9 .. 1.0
EXPECT_NEAR(sigmas_max_deviation_from_mean, 0.95, 0.05) ;
}
#endif // not _HAVE_GSL
#if (defined(_HAVE_TR1_RANDOM) || defined(_HAVE_STL_RANDOM))
TEST_F(MonteCarloTest, MonteVarRandom_StlGaussian_distributionMatchesSpec) {
//req.add_requirement("3932595803");
std::string str ;
double value ;
Trick::MonteVarRandom var8("time_to_fire_1", Trick::MonteVarRandom::GAUSSIAN, "--",
Trick::MonteVarRandom::TRICK_DEFAULT_ENGINE) ;
exec.add_variable(&var8) ;
double expected_mean = 10.0 ;
double expected_sigma = 2.0 ;
var8.set_seed(12345) ;
var8.set_sigma_range(0) ;
var8.set_mu(expected_mean) ;
var8.set_sigma(expected_sigma) ;
var8.set_min(-10.0) ;
var8.set_max(10.0) ;
// maintain running sums for calculating mean and variance
double mean = 0.0 ;
double sum_variance = 0.0 ;
int n = 0 ;
double delta = 0.0 ;
int numRuns = 100 ;
for (int ii = 0; ii <= numRuns; ++ii) {
{
var8.get_next_value() ;
str = var8.value ;
std::stringstream sstream(str) ;
sstream >> value ;
}
n++ ;
delta = value - mean ;
mean += delta / (double)n ;
sum_variance += delta * (value - mean) ;
}
// final statistics
double variance = sum_variance / (double) (n - 1) ;
double sigma = sqrt(variance) ;
EXPECT_NEAR(expected_mean, mean, 0.05 * expected_mean) ;
EXPECT_NEAR(expected_sigma, sigma, 0.10 * expected_sigma) ;
}
///@breif test relative min/max work as expected for STL
TEST_F(MonteCarloTest, MonteVarRandom_StlGaussian_relativeMinMaxWorks) {
//req.add_requirement("3932595803");
std::string str ;
double value ;
Trick::MonteVarRandom var6("time_to_fire_1", Trick::MonteVarRandom::GAUSSIAN) ;
exec.add_variable(&var6) ;
double expected_mean = 10.0 ;
double expected_sigma = 2.0 ;
var6.set_seed(12345) ;
var6.set_sigma_range(0) ;
var6.set_mu(expected_mean) ;
var6.set_sigma(expected_sigma) ;
var6.set_min(-1.0) ;
var6.set_max(1.0) ;
var6.set_min_is_relative(true) ;
var6.set_max_is_relative(true) ;
// maintain running sums for calculating mean and variance
int numRuns = 100 ;
double saw_min = 1000.0;
double saw_max = -1000.0;
for (int ii = 0; ii <= numRuns; ++ii) {
{
var6.get_next_value() ;
str = var6.value ;
std::stringstream sstream(str) ;
sstream >> value ;
}
if (value < saw_min) {
saw_min = value;
}
if (value > saw_max) {
saw_max = value;
}
}
// these conditions should be true if valid
// relative min/max range of 10 +/- 1 is being imposed
EXPECT_NEAR(9.05, saw_min, 0.05) ;
EXPECT_NEAR(10.95, saw_max, 0.05) ;
}
///@breif test relative min/max works after calling set_mu, as expected for STL
TEST_F(MonteCarloTest, MonteVarRandom_StlGaussian_callSetMu_relativeMinMaxWorks) {
//req.add_requirement("3932595803");
std::string str ;
double value ;
Trick::MonteVarRandom var11("time_to_fire_1", Trick::MonteVarRandom::GAUSSIAN) ;
exec.add_variable(&var11) ;
double expected_mean = 10.0 ;
double expected_sigma = 2.0 ;
var11.set_seed(12345) ;
var11.set_sigma_range(0) ;
var11.set_mu(expected_mean + 100.0) ;
var11.set_sigma(expected_sigma) ;
var11.set_min(-1.0) ;
var11.set_max(1.0) ;
var11.set_min_is_relative(true) ;
var11.set_max_is_relative(true) ;
var11.set_mu(expected_mean) ;
// maintain running sums for calculating mean and variance
int numRuns = 100 ;
double saw_min = 1000.0;
double saw_max = -1000.0;
for (int ii = 0; ii <= numRuns; ++ii) {
{
var11.get_next_value() ;
str = var11.value ;
std::stringstream sstream(str) ;
sstream >> value ;
}
if (value < saw_min) {
saw_min = value;
}
if (value > saw_max) {
saw_max = value;
}
}
// these conditions should be true if valid
// relative min/max range of 10 +/- 1 is being imposed
EXPECT_NEAR(9.05, saw_min, 0.05) ;
EXPECT_NEAR(10.95, saw_max, 0.05) ;
}
///@breif test absolute min/max works after changing from relative, as expected for STL
TEST_F(MonteCarloTest, MonteVarRandom_StlGaussian_changeToAbsolute_MinMaxWorks) {
//req.add_requirement("3932595803");
std::string str ;
double value ;
Trick::MonteVarRandom var11("time_to_fire_1", Trick::MonteVarRandom::GAUSSIAN) ;
exec.add_variable(&var11) ;
double expected_mean = 10.0 ;
double expected_sigma = 2.0 ;
var11.set_seed(12345) ;
var11.set_sigma_range(0) ;
var11.set_mu(expected_mean) ;
var11.set_sigma(expected_sigma) ;
var11.set_min(9.0) ;
var11.set_max(11.0) ;
var11.set_min_is_relative(false) ;
var11.set_max_is_relative(false) ;
// maintain running sums for calculating mean and variance
int numRuns = 100 ;
double saw_min = 1000.0;
double saw_max = -1000.0;
for (int ii = 0; ii <= numRuns; ++ii) {
{
var11.get_next_value() ;
str = var11.value ;
std::stringstream sstream(str) ;
sstream >> value ;
}
if (value < saw_min) {
saw_min = value;
}
if (value > saw_max) {
saw_max = value;
}
}
// these conditions should be true if valid
// relative min/max range of 10 +/- 1 is being imposed
EXPECT_NEAR(9.05, saw_min, 0.05) ;
EXPECT_NEAR(10.95, saw_max, 0.05) ;
}
///@brief test that the sequence repeats after calling set_seed
TEST_F(MonteCarloTest, MonteVarRandom_StlGaussian_setSeed_TakesEffect) {
//req.add_requirement("3932595803");
std::string str ;
double value ;
Trick::MonteVarRandom var10("time_to_fire_1", Trick::MonteVarRandom::GAUSSIAN) ;
exec.add_variable(&var10) ;
double expected_mean = 10.0 ;
double expected_sigma = 2.0 ;
var10.set_seed(12345) ;
var10.set_sigma_range(0) ;
var10.set_mu(expected_mean) ;
var10.set_sigma(expected_sigma) ;
var10.set_min(-10.0) ;
var10.set_max(10.0) ;
var10.set_min_is_relative(true) ;
var10.set_max_is_relative(true) ;
int numRuns = 10;
for (int ii = 0; ii < numRuns; ++ii) {
{
var10.get_next_value() ;
str = var10.value ;
std::stringstream sstream(str) ;
sstream >> value ;
}
}
double first_value = value;
var10.set_seed(12345) ;
for (int ii = 0; ii < numRuns; ++ii) {
{
var10.get_next_value() ;
str = var10.value ;
std::stringstream sstream(str) ;
sstream >> value ;
}
}
double second_value = value;
EXPECT_NEAR(first_value, second_value, 0.000001) ;
}
#endif // _HAVE_TR1_RANDOM or _HAVE_STL_RANDOM
}
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