The normal (Gaussian) distribution Random Number Generator (RNG) that allows stream numbers to be set deterministically. More...

#include <random-variable-stream.h>

Inheritance diagram for ns3::NormalRandomVariable:

Collaboration diagram for ns3::NormalRandomVariable:

Public Member Functions
	NormalRandomVariable ()
	Creates a normal distribution RNG with the default values for the mean, variance, and bound.
double	GetBound (void) const
	Returns the bound on values that can be returned by this RNG stream.
uint32_t	GetInteger (uint32_t mean, uint32_t variance, uint32_t bound)
	Returns a random unsigned integer from a normal distribution with the specified mean, variance, and bound.
virtual uint32_t	GetInteger (void)
	Returns a random unsigned integer from a normal distribution with the current mean, variance, and bound.
double	GetMean (void) const
	Returns the mean value for the normal distribution returned by this RNG stream.
double	GetValue (double mean, double variance, double bound=NormalRandomVariable::INFINITE_VALUE)
	Returns a random double from a normal distribution with the specified mean, variance, and bound.
virtual double	GetValue (void)
	Returns a random double from a normal distribution with the current mean, variance, and bound.
double	GetVariance (void) const
	Returns the variance value for the normal distribution returned by this RNG stream.
Public Member Functions inherited from ns3::RandomVariableStream
	RandomVariableStream ()
virtual	~RandomVariableStream ()
int64_t	GetStream (void) const
	Returns the stream number for this RNG stream.
bool	IsAntithetic (void) const
	Returns true if antithetic values should be generated.
void	SetAntithetic (bool isAntithetic)
	Specifies whether antithetic values should be generated.
void	SetStream (int64_t stream)
	Specifies the stream number for this RNG stream.
Public Member Functions inherited from ns3::Object
	Object ()
virtual	~Object ()
void	AggregateObject (Ptr< Object > other)
void	Dispose (void)
AggregateIterator	GetAggregateIterator (void) const
virtual TypeId	GetInstanceTypeId (void) const
template<typename T >
Ptr< T >	GetObject (void) const
template<typename T >
Ptr< T >	GetObject (TypeId tid) const
void	Start (void)
Public Member Functions inherited from ns3::SimpleRefCount< Object, ObjectBase, ObjectDeleter >
	SimpleRefCount ()
	SimpleRefCount (const SimpleRefCount &o)
uint32_t	GetReferenceCount (void) const
SimpleRefCount &	operator= (const SimpleRefCount &o)
void	Ref (void) const
void	Unref (void) const
Public Member Functions inherited from ns3::ObjectBase
virtual	~ObjectBase ()
void	GetAttribute (std::string name, AttributeValue &value) const
bool	GetAttributeFailSafe (std::string name, AttributeValue &attribute) const
void	SetAttribute (std::string name, const AttributeValue &value)
bool	SetAttributeFailSafe (std::string name, const AttributeValue &value)
bool	TraceConnect (std::string name, std::string context, const CallbackBase &cb)
bool	TraceConnectWithoutContext (std::string name, const CallbackBase &cb)
bool	TraceDisconnect (std::string name, std::string context, const CallbackBase &cb)
bool	TraceDisconnectWithoutContext (std::string name, const CallbackBase &cb)

Static Public Member Functions
static TypeId	GetTypeId (void)
	This method returns the TypeId associated to ns3::NormalRandomVariable.

Static Public Attributes
static const double	INFINITE_VALUE = 1e307

Private Attributes
double	m_bound
	The bound on values that can be returned by this RNG stream.
double	m_mean
	The mean value for the normal distribution returned by this RNG stream.
double	m_next
	The algorithm produces two values at a time.
bool	m_nextValid
	True if the next value is valid.
double	m_variance
	The variance value for the normal distribution returned by this RNG stream.

Additional Inherited Members
Protected Member Functions inherited from ns3::RandomVariableStream
RngStream *	Peek (void) const
	Returns a pointer to the underlying RNG stream.

Detailed Description

The normal (Gaussian) distribution Random Number Generator (RNG) that allows stream numbers to be set deterministically.

This class supports the creation of objects that return random numbers from a fixed normal distribution. It also supports the generation of single random numbers from various normal distributions.

The density probability function is defined over the interval ( $-\infty$ , $+\infty$ ) as: $\frac{1}{\sigma\sqrt{2\pi}} e^{-\frac{(x-\mu)^2}{s\sigma^2}}$ where $mean = \mu$ and $variance = \sigma^2$

Since normal distributions can theoretically return unbounded values, it is sometimes useful to specify a fixed bound. The NormalRandomVariable is bounded symmetrically about the mean by this bound, i.e. its values are confined to the interval [ $mean-bound$ , $mean+bound$ ].

Here is an example of how to use this class:

double mean = 5.0;
double variance = 2.0;
Ptr<NormalRandomVariable> x = CreateObject<NormalRandomVariable> ();
x->SetAttribute ("Mean", DoubleValue (mean));
x->SetAttribute ("Variance", DoubleValue (variance));
// The expected value for the mean of the values returned by a
// normally distributed random variable is equal to mean.
double value = x->GetValue ();

Definition at line 1024 of file random-variable-stream.h.

Constructor & Destructor Documentation

ns3::NormalRandomVariable::NormalRandomVariable ( )

Creates a normal distribution RNG with the default values for the mean, variance, and bound.

Definition at line 600 of file random-variable-stream.cc.

Member Function Documentation

double ns3::NormalRandomVariable::GetBound ( void ) const

Returns the bound on values that can be returned by this RNG stream.

Returns: The bound on values that can be returned by this RNG stream.

Definition at line 619 of file random-variable-stream.cc.

References m_bound.

uint32_t ns3::NormalRandomVariable::GetInteger	(	uint32_t	mean,
		uint32_t	variance,
		uint32_t	bound
	)

Returns a random unsigned integer from a normal distribution with the specified mean, variance, and bound.

Parameters

mean	Mean value for the normal distribution.
variance	Variance value for the normal distribution.
bound	Bound on values returned.

Returns: A random unsigned integer value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u1$ and $u2$ are uniform variables over [0,1], then the values that would be returned normally, $x1$ and $x2$ , are calculated as follows:

$\begin{eqnarray*} v1 & = & 2 * u1 - 1 \\ v2 & = & 2 * u2 - 1 \\ w & = & v1 * v1 + v2 * v2 \\ y & = & \sqrt{\frac{-2 * \log(w)}{w}} \\ x1 & = & mean + v1 * y * \sqrt{variance} \\ x2 & = & mean + v2 * y * \sqrt{variance} . \end{eqnarray*}$

For the antithetic case, $(1 - u1$ ) and $(1 - u2$ ) are the distances that $u1$ and $u2$ would be from $1$ . The antithetic values returned, $x1'$ and $x2'$ , are calculated as follows:

$\begin{eqnarray*} v1' & = & 2 * (1 - u1) - 1 \\ v2' & = & 2 * (1 - u2) - 1 \\ w' & = & v1' * v1' + v2' * v2' \\ y' & = & \sqrt{\frac{-2 * \log(w')}{w'}} \\ x1' & = & mean + v1' * y' * \sqrt{variance} \\ x2' & = & mean + v2' * y' * \sqrt{variance} , \end{eqnarray*}$

which now involves the distances $u1$ and $u2$ are from 1.

Definition at line 670 of file random-variable-stream.cc.

References GetValue().

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uint32_t ns3::NormalRandomVariable::GetInteger ( void )

virtual

Returns a random unsigned integer from a normal distribution with the current mean, variance, and bound.

Returns: A random unsigned integer value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u1$ and $u2$ are uniform variables over [0,1], then the values that would be returned normally, $x1$ and $x2$ , are calculated as follows:

$\begin{eqnarray*} v1 & = & 2 * u1 - 1 \\ v2 & = & 2 * u2 - 1 \\ w & = & v1 * v1 + v2 * v2 \\ y & = & \sqrt{\frac{-2 * \log(w)}{w}} \\ x1 & = & mean + v1 * y * \sqrt{variance} \\ x2 & = & mean + v2 * y * \sqrt{variance} . \end{eqnarray*}$

For the antithetic case, $(1 - u1$ ) and $(1 - u2$ ) are the distances that $u1$ and $u2$ would be from $1$ . The antithetic values returned, $x1'$ and $x2'$ , are calculated as follows:

$\begin{eqnarray*} v1' & = & 2 * (1 - u1) - 1 \\ v2' & = & 2 * (1 - u2) - 1 \\ w' & = & v1' * v1' + v2' * v2' \\ y' & = & \sqrt{\frac{-2 * \log(w')}{w'}} \\ x1' & = & mean + v1' * y' * \sqrt{variance} \\ x2' & = & mean + v2' * y' * \sqrt{variance} , \end{eqnarray*}$

which now involves the distances $u1$ and $u2$ are from 1.

Implements ns3::RandomVariableStream.

Definition at line 681 of file random-variable-stream.cc.

References GetValue(), m_bound, m_mean, and m_variance.

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double ns3::NormalRandomVariable::GetMean ( void ) const

Returns the mean value for the normal distribution returned by this RNG stream.

Returns: The mean value for the normal distribution returned by this RNG stream.

Definition at line 609 of file random-variable-stream.cc.

References m_mean.

TypeId ns3::NormalRandomVariable::GetTypeId ( void )

static

This method returns the TypeId associated to ns3::NormalRandomVariable.

This object is accessible through the following paths with Config::Set and Config::Connect:

/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/MeanDirection/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/MeanPitch/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/MeanVelocity/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/NormalDirection
/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/NormalPitch
/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/NormalVelocity
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomDirection2dMobilityModel/Pause/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomDirection2dMobilityModel/Speed/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWalk2dMobilityModel/Direction/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWalk2dMobilityModel/Speed/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/Pause/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomBoxPositionAllocator/X/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomBoxPositionAllocator/Y/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomBoxPositionAllocator/Z/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomDiscPositionAllocator/Rho/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomDiscPositionAllocator/Theta/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomRectanglePositionAllocator/X/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomRectanglePositionAllocator/Y/$ns3::NormalRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/Speed/$ns3::NormalRandomVariable
/NodeList/[i]/ApplicationList/[i]/$ns3::OnOffApplication/OffTime/$ns3::NormalRandomVariable
/NodeList/[i]/ApplicationList/[i]/$ns3::OnOffApplication/OnTime/$ns3::NormalRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::CsmaNetDevice/ReceiveErrorModel/$ns3::RateErrorModel/RanVar/$ns3::NormalRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::PointToPointNetDevice/ReceiveErrorModel/$ns3::RateErrorModel/RanVar/$ns3::NormalRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::SimpleNetDevice/ReceiveErrorModel/$ns3::RateErrorModel/RanVar/$ns3::NormalRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::WifiNetDevice/Channel/$ns3::YansWifiChannel/PropagationDelayModel/$ns3::RandomPropagationDelayModel/Variable/$ns3::NormalRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::WifiNetDevice/Channel/$ns3::YansWifiChannel/PropagationLossModel/$ns3::RandomPropagationLossModel/Variable/$ns3::NormalRandomVariable

Attributes defined for this type:

Mean: The mean value for the normal distribution returned by this RNG stream.
- Set with class: ns3::DoubleValue
- Underlying type: double -1.79769e+308:1.79769e+308
- Initial value: 0
- Flags: construct write read
Variance: The variance value for the normal distribution returned by this RNG stream.
- Set with class: ns3::DoubleValue
- Underlying type: double -1.79769e+308:1.79769e+308
- Initial value: 1
- Flags: construct write read
Bound: The bound on the values returned by this RNG stream.
- Set with class: ns3::DoubleValue
- Underlying type: double -1.79769e+308:1.79769e+308
- Initial value: 1e+307
- Flags: construct write read

Attributes defined in parent class ns3::RandomVariableStream:

Stream: The stream number for this RNG stream. -1 means "allocate a stream automatically". Note that if -1 is set, Get will return -1 so that it is not possible to know which value was automatically allocated.
- Set with class: ns3::IntegerValue
- Underlying type: int64_t -9223372036854775808:9223372036854775807
- Initial value: -1
- Flags: construct write read
Antithetic: Set this RNG stream to generate antithetic values
- Set with class: BooleanValue
- Underlying type: bool
- Initial value: false
- Flags: construct write read

No TraceSources defined for this type.

Reimplemented from ns3::RandomVariableStream.

Definition at line 580 of file random-variable-stream.cc.

References INFINITE_VALUE, m_bound, m_mean, m_variance, and ns3::TypeId::SetParent().

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double ns3::NormalRandomVariable::GetValue	(	double	mean,
		double	variance,
		double	bound = `NormalRandomVariable::INFINITE_VALUE`
	)

Returns a random double from a normal distribution with the specified mean, variance, and bound.

Parameters

mean	Mean value for the normal distribution.
variance	Variance value for the normal distribution.
bound	Bound on values returned.

Returns: A floating point random value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u1$ and $u2$ are uniform variables over [0,1], then the values that would be returned normally, $x1$ and $x2$ , are calculated as follows:

$\begin{eqnarray*} v1 & = & 2 * u1 - 1 \\ v2 & = & 2 * u2 - 1 \\ w & = & v1 * v1 + v2 * v2 \\ y & = & \sqrt{\frac{-2 * \log(w)}{w}} \\ x1 & = & mean + v1 * y * \sqrt{variance} \\ x2 & = & mean + v2 * y * \sqrt{variance} . \end{eqnarray*}$

For the antithetic case, $(1 - u1$ ) and $(1 - u2$ ) are the distances that $u1$ and $u2$ would be from $1$ . The antithetic values returned, $x1'$ and $x2'$ , are calculated as follows:

$\begin{eqnarray*} v1' & = & 2 * (1 - u1) - 1 \\ v2' & = & 2 * (1 - u2) - 1 \\ w' & = & v1' * v1' + v2' * v2' \\ y' & = & \sqrt{\frac{-2 * \log(w')}{w'}} \\ x1' & = & mean + v1' * y' * \sqrt{variance} \\ x2' & = & mean + v2' * y' * \sqrt{variance} , \end{eqnarray*}$

which now involves the distances $u1$ and $u2$ are from 1.

Definition at line 625 of file random-variable-stream.cc.

References ns3::RandomVariableStream::IsAntithetic(), m_next, m_nextValid, ns3::RandomVariableStream::Peek(), ns3::RngStream::RandU01(), and visualizer.higcontainer::w.

Referenced by RandomVariableStreamNormalTestCase::ChiSquaredTest(), RandomVariableStreamNormalAntitheticTestCase::ChiSquaredTest(), RandomVariableStreamNormalTestCase::DoRun(), RandomVariableStreamNormalAntitheticTestCase::DoRun(), ns3::BuildingsPropagationLossModel::GetShadowing(), and ns3::GaussMarkovMobilityModel::Start().

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double ns3::NormalRandomVariable::GetValue ( void )

virtual

Returns a random double from a normal distribution with the current mean, variance, and bound.

Returns: A floating point random value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u1$ and $u2$ are uniform variables over [0,1], then the values that would be returned normally, $x1$ and $x2$ , are calculated as follows:

$\begin{eqnarray*} v1 & = & 2 * u1 - 1 \\ v2 & = & 2 * u2 - 1 \\ w & = & v1 * v1 + v2 * v2 \\ y & = & \sqrt{\frac{-2 * \log(w)}{w}} \\ x1 & = & mean + v1 * y * \sqrt{variance} \\ x2 & = & mean + v2 * y * \sqrt{variance} . \end{eqnarray*}$

For the antithetic case, $(1 - u1$ ) and $(1 - u2$ ) are the distances that $u1$ and $u2$ would be from $1$ . The antithetic values returned, $x1'$ and $x2'$ , are calculated as follows:

$\begin{eqnarray*} v1' & = & 2 * (1 - u1) - 1 \\ v2' & = & 2 * (1 - u2) - 1 \\ w' & = & v1' * v1' + v2' * v2' \\ y' & = & \sqrt{\frac{-2 * \log(w')}{w'}} \\ x1' & = & mean + v1' * y' * \sqrt{variance} \\ x2' & = & mean + v2' * y' * \sqrt{variance} , \end{eqnarray*}$

which now involves the distances $u1$ and $u2$ are from 1.

Note that we have to re-implement this method here because the method is overloaded above for the three-argument variant and the c++ name resolution rules don't work well with overloads split between parent and child classes.

Implements ns3::RandomVariableStream.

Definition at line 676 of file random-variable-stream.cc.

References m_bound, m_mean, and m_variance.

Referenced by GetInteger().

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