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Fixed major memory bug and docs in RandomVariable

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This commit is contained in:
Raj Bhattacharjea
2007-03-22 12:16:10 -04:00
parent d52242c4ae
commit ac13b5523f
4 changed files with 56 additions and 18 deletions
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33
src/core/random-variable.cc
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@@ -103,6 +103,12 @@ RandomVariable::RandomVariable()
m_generator->InitializeStream();
}
RandomVariable::RandomVariable(const RandomVariable& r)
{
m_generator = new RngStream(*r.m_generator);
RandomVariable::Initialize();
}
RandomVariable::~RandomVariable()
{
delete m_generator;
@@ -237,7 +243,7 @@ UniformVariable::UniformVariable(double s, double l)
: m_min(s), m_max(l) { }
UniformVariable::UniformVariable(const UniformVariable& c)
: m_min(c.m_min), m_max(c.m_max) { }
: RandomVariable(c), m_min(c.m_min), m_max(c.m_max) { }
double UniformVariable::GetValue()
{
@@ -258,7 +264,7 @@ ConstantVariable::ConstantVariable(double c)
: m_const(c) { };
ConstantVariable::ConstantVariable(const ConstantVariable& c)
: m_const(c.m_const) { }
: RandomVariable(c), m_const(c.m_const) { }
void ConstantVariable::NewConstant(double c)
{ m_const = c;}
@@ -293,12 +299,17 @@ SequentialVariable::SequentialVariable(double f, double l, const RandomVariable&
}
SequentialVariable::SequentialVariable(const SequentialVariable& c)
: m_min(c.m_min), m_max(c.m_max),
: RandomVariable(c), m_min(c.m_min), m_max(c.m_max),
m_increment(c.m_increment->Copy()), m_consecutive(c.m_consecutive),
m_current(c.m_current), m_currentConsecutive(c.m_currentConsecutive)
{
}
SequentialVariable::~SequentialVariable()
{
delete m_increment;
}
double SequentialVariable::GetValue()
{ // Return a sequential series of values
double r = m_current;
@@ -329,7 +340,7 @@ ExponentialVariable::ExponentialVariable(double m, double b)
: m_mean(m), m_bound(b) { }
ExponentialVariable::ExponentialVariable(const ExponentialVariable& c)
: m_mean(c.m_mean), m_bound(c.m_bound) { }
: RandomVariable(c), m_mean(c.m_mean), m_bound(c.m_bound) { }
double ExponentialVariable::GetValue()
{
@@ -358,7 +369,8 @@ ParetoVariable::ParetoVariable(double m, double s, double b)
: m_mean(m), m_shape(s), m_bound(b) { }
ParetoVariable::ParetoVariable(const ParetoVariable& c)
: m_mean(c.m_mean), m_shape(c.m_shape), m_bound(c.m_bound) { }
: RandomVariable(c), m_mean(c.m_mean), m_shape(c.m_shape),
m_bound(c.m_bound) { }
double ParetoVariable::GetValue()
{
@@ -383,7 +395,8 @@ WeibullVariable::WeibullVariable(double m, double s)
WeibullVariable::WeibullVariable(double m, double s, double b)
: m_mean(m), m_alpha(s), m_bound(b) { };
WeibullVariable::WeibullVariable(const WeibullVariable& c)
: m_mean(c.m_mean), m_alpha(c.m_alpha), m_bound(c.m_bound) { }
: RandomVariable(c), m_mean(c.m_mean), m_alpha(c.m_alpha),
m_bound(c.m_bound) { }
double WeibullVariable::GetValue()
{
@@ -407,7 +420,8 @@ NormalVariable::NormalVariable(double m, double v, double b)
: m_mean(m), m_variance(v), m_bound(b), m_nextValid(false) { }
NormalVariable::NormalVariable(const NormalVariable& c)
: m_mean(c.m_mean), m_variance(c.m_variance), m_bound(c.m_bound) { }
: RandomVariable(c), m_mean(c.m_mean), m_variance(c.m_variance),
m_bound(c.m_bound) { }
double NormalVariable::GetValue()
{
@@ -458,8 +472,8 @@ ValueCDF::ValueCDF(const ValueCDF& c)
EmpiricalVariable::EmpiricalVariable()
: validated(false) { }
EmpiricalVariable::EmpiricalVariable(const EmpiricalVariable& c)
: validated(c.validated), emp(c.emp) { }
EmpiricalVariable::EmpiricalVariable(const EmpiricalVariable& c)
: RandomVariable(c), validated(c.validated), emp(c.emp) { }
EmpiricalVariable::~EmpiricalVariable() { }
@@ -541,7 +555,6 @@ RandomVariable* IntEmpiricalVariable::Copy() const
return new IntEmpiricalVariable(*this);
}
double IntEmpiricalVariable::Interpolate(double c1, double c2,
double v1, double v2, double r)
{ // Interpolate random value in range [v1..v2) based on [c1 .. r .. c2)

24
src/core/random-variable.h
View File

@@ -87,6 +87,11 @@ public:
*/
RandomVariable();
/**
* \brief Copy constructor
*/
RandomVariable(const RandomVariable&);
/**
* \brief Destructor for a random number generator with a random seed.
*/
@@ -145,6 +150,7 @@ public:
/**
* \brief Use the global seed to force precisely reproducible results.
*
* It is often desirable to create a simulation that uses random
* numbers, while at the same time is completely reproducible.
* Specifying this set of six random seeds initializes the
@@ -210,6 +216,7 @@ private:
/**
* \brief A random variable that returns a constant
*
* Class ConstantVariable defines a random number generator that
* returns the same value every sample.
*/
@@ -217,7 +224,7 @@ class ConstantVariable : public RandomVariable {
public:
/**
* \brief Construct a ConstantVariable RNG that returns zero every sample
* Construct a ConstantVariable RNG that returns zero every sample
*/
ConstantVariable();
@@ -249,6 +256,7 @@ private:
/**
* \brief Return a sequential list of values
*
* Class SequentialVariable defines a random number generator that
* returns a sequential sequence. The sequence monotonically
* increases for a period, then wraps around to the low value
@@ -259,6 +267,7 @@ class SequentialVariable : public RandomVariable {
public:
/**
* \brief Constructor for the SequentialVariable RNG.
*
* The four parameters define the sequence. For example
* SequentialVariable(0,5,1,2) creates a RNG that has the sequence
* 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 0, 0 ...
@@ -271,16 +280,19 @@ public:
/**
* \brief Constructor for the SequentialVariable RNG.
*
* Differs from the first only in that the increment parameter is a
* random variable
* \param f First value of the sequence.
* \param l One more than the last value of the sequence.
* \param i Reference to a Random variable for the sequence increment
* \param i Reference to a RandomVariable for the sequence increment
* \param c Number of times each member of the sequence is repeated
*/
SequentialVariable(double f, double l, const RandomVariable& i, uint32_t c = 1);
SequentialVariable(const SequentialVariable& c);
~SequentialVariable();
/**
* \return The next value in the Sequence
*/
@@ -297,6 +309,7 @@ private:
/**
* \brief Exponentially Distributed random var
*
* ExponentialVariable defines a random variable with an exponential distribution
*/
class ExponentialVariable : public RandomVariable {
@@ -316,6 +329,7 @@ public:
/**
* \brief Constructs an exponential random variable with spefified
* \brief mean and upper limit.
*
* Since exponential distributions can theoretically return unbounded values,
* it is sometimes useful to specify a fixed upper limit. Note however when
* the upper limit is specified, the true mean of the distribution is
@@ -492,6 +506,7 @@ public:
/**
* \brief EmpiricalVariable distribution random var
*
* Defines a random variable that has a specified, empirical
* distribution. The distribution is specified by a
* series of calls the the CDF member function, specifying a
@@ -531,14 +546,14 @@ private:
/**
* Defines an empirical distribution where all values are integers.
* Indentical to {\tt EmpiricalVariable}, but with slightly different
* Indentical to EmpiricalVariable, but with slightly different
* interpolation between points.
*/
class IntEmpiricalVariable : public EmpiricalVariable {
public:
IntEmpiricalVariable();
virtual RandomVariable* Copy() const;
/**
* \return An integer value from this empirical distribution
@@ -558,6 +573,7 @@ class DeterministicVariable : public RandomVariable {
public:
/**
* \brief Constructor
*
* Creates a generator that returns successive elements of the d array
* on successive calls to ::Value(). Note that the d pointer is copied
* for use by the generator (shallow-copy), not its contents, so the

12
src/core/rng-stream.cc
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@@ -316,6 +316,18 @@ RngStream::RngStream ()
// Stream initialization moved to separate method.
}
RngStream::RngStream(const RngStream& r)
{
anti = r.anti;
incPrec = r.incPrec;
for (int i = 0; i < 6; ++i) {
Cg[i] = r.Cg[i];
Bg[i] = r.Bg[i];
Ig[i] = r.Ig[i];
}
}
void RngStream::InitializeStream()
{ // Moved from the RngStream constructor above to allow seeding
// AFTER the global package seed has been set in the Random

5
src/core/rng-stream.h
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@@ -23,13 +23,10 @@
namespace ns3{
/**
* \brief RngStream by Pierre L'Ecuyer, University of Montreal
* Adapted to NS3 by Rajib Bhattacharjea, Georgia Tech.
*/
class RngStream {
public: //public api
RngStream ();
RngStream (const RngStream&);
void InitializeStream(); // Separate initialization
void ResetStartStream ();
void ResetStartSubstream ();