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

#include <random-variable-stream.h>

Inheritance diagram for ns3::GammaRandomVariable:

Public Member Functions
	GammaRandomVariable ()
	Creates a gamma distribution RNG with the default values for alpha and beta.

double	GetAlpha (void) const
	Returns the alpha value for the gamma distribution returned by this RNG stream. More...

double	GetBeta (void) const
	Returns the beta value for the gamma distribution returned by this RNG stream. More...

uint32_t	GetInteger (uint32_t alpha, uint32_t beta)
	Returns a random unsigned integer from a gamma distribution with the specified alpha and beta. More...

virtual uint32_t	GetInteger (void)
	Returns a random unsigned integer from a gamma distribution with the current alpha and beta. More...

double	GetValue (double alpha, double beta)
	Returns a random double from a gamma distribution with the specified alpha and beta. More...

virtual double	GetValue (void)
	Returns a random double from a gamma distribution with the current alpha and beta. More...

Public Member Functions inherited from ns3::RandomVariableStream
int64_t	GetStream (void) const
	Returns the stream number for this RNG stream. More...

bool	IsAntithetic (void) const
	Returns true if antithetic values should be generated. More...

void	SetAntithetic (bool isAntithetic)
	Specifies whether antithetic values should be generated. More...

void	SetStream (int64_t stream)
	Specifies the stream number for this RNG stream. More...

Public Member Functions inherited from ns3::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	Initialize (void)

Public Member Functions inherited from ns3::SimpleRefCount< Object, ObjectBase, ObjectDeleter >
	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
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)

Static Public Member Functions inherited from ns3::RandomVariableStream
static TypeId	GetTypeId (void)

Static Public Member Functions inherited from ns3::Object
static TypeId	GetTypeId (void)

Static Public Member Functions inherited from ns3::SimpleRefCount< Object, ObjectBase, ObjectDeleter >
static void	Cleanup (void)

Static Public Member Functions inherited from ns3::ObjectBase
static TypeId	GetTypeId (void)

Private Member Functions
double	GetNormalValue (double mean, double variance, double bound)
	Returns a random double from a normal distribution with the specified mean, variance, and bound. More...

Private Attributes
double	m_alpha
	The alpha value for the gamma distribution returned by this RNG stream.

double	m_beta
	The beta value for the gamma distribution returned by this RNG stream.

double	m_next
	The algorithm produces two normal values at a time.

bool	m_nextValid
	True if the next normal value is valid.

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

Protected Member Functions inherited from ns3::Object
	Object (const Object &o)

virtual void	DoDispose (void)

virtual void	DoInitialize (void)

virtual void	NotifyNewAggregate (void)

Protected Member Functions inherited from ns3::ObjectBase
void	ConstructSelf (const AttributeConstructionList &attributes)

virtual void	NotifyConstructionCompleted (void)

Detailed Description

The gamma 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 gamma distribution. It also supports the generation of single random numbers from various gamma distributions.

The probability density function is defined over the interval [0, $+\infty$ ) as: $x^{\alpha-1} \frac{e^{-\frac{x}{\beta}}}{\beta^\alpha \Gamma(\alpha)}$ where $mean = \alpha\beta$ and $variance = \alpha \beta^2$

Here is an example of how to use this class:

double alpha = 5.0;
double beta = 2.0;
Ptr<GammaRandomVariable> x = CreateObject<GammaRandomVariable> ();
x->SetAttribute ("Alpha", DoubleValue (alpha));
x->SetAttribute ("Beta", DoubleValue (beta));
// The expected value for the mean of the values returned by a
// gammaly distributed random variable is equal to 
//
//     E[value]  =  alpha * beta  .
//
double value = x->GetValue ();

Config Paths

ns3::GammaRandomVariable is accessible through the following paths with Config::Set and Config::Connect:

/ChannelList/[i]/$ns3::WifiChannel/$ns3::YansWifiChannel/PropagationDelayModel/$ns3::RandomPropagationDelayModel/Variable/$ns3::GammaRandomVariable
/ChannelList/[i]/$ns3::WifiChannel/$ns3::YansWifiChannel/PropagationLossModel/$ns3::NakagamiPropagationLossModel/GammaRv
/ChannelList/[i]/$ns3::WifiChannel/$ns3::YansWifiChannel/PropagationLossModel/$ns3::RandomPropagationLossModel/Variable/$ns3::GammaRandomVariable
/ChannelList/[i]/$ns3::YansWifiChannel/PropagationDelayModel/$ns3::RandomPropagationDelayModel/Variable/$ns3::GammaRandomVariable
/ChannelList/[i]/$ns3::YansWifiChannel/PropagationLossModel/$ns3::NakagamiPropagationLossModel/GammaRv
/ChannelList/[i]/$ns3::YansWifiChannel/PropagationLossModel/$ns3::RandomPropagationLossModel/Variable/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/MeanDirection/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/MeanPitch/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/MeanVelocity/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomDirection2dMobilityModel/Pause/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomDirection2dMobilityModel/Speed/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWalk2dMobilityModel/Direction/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWalk2dMobilityModel/Speed/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/Pause/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomBoxPositionAllocator/X/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomBoxPositionAllocator/Y/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomBoxPositionAllocator/Z/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomDiscPositionAllocator/Rho/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomDiscPositionAllocator/Theta/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomRectanglePositionAllocator/X/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomRectanglePositionAllocator/Y/$ns3::GammaRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/Speed/$ns3::GammaRandomVariable
/NodeList/[i]/ApplicationList/[i]/$ns3::OnOffApplication/OffTime/$ns3::GammaRandomVariable
/NodeList/[i]/ApplicationList/[i]/$ns3::OnOffApplication/OnTime/$ns3::GammaRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::CsmaNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstSize/$ns3::GammaRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::CsmaNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstStart/$ns3::GammaRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::CsmaNetDevice/ReceiveErrorModel/$ns3::RateErrorModel/RanVar/$ns3::GammaRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::PointToPointNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstSize/$ns3::GammaRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::PointToPointNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstStart/$ns3::GammaRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::PointToPointNetDevice/ReceiveErrorModel/$ns3::RateErrorModel/RanVar/$ns3::GammaRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::SimpleNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstSize/$ns3::GammaRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::SimpleNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstStart/$ns3::GammaRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::SimpleNetDevice/ReceiveErrorModel/$ns3::RateErrorModel/RanVar/$ns3::GammaRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::WifiNetDevice/Channel/$ns3::YansWifiChannel/PropagationDelayModel/$ns3::RandomPropagationDelayModel/Variable/$ns3::GammaRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::WifiNetDevice/Channel/$ns3::YansWifiChannel/PropagationLossModel/$ns3::NakagamiPropagationLossModel/GammaRv
/NodeList/[i]/DeviceList/[i]/$ns3::WifiNetDevice/Channel/$ns3::YansWifiChannel/PropagationLossModel/$ns3::RandomPropagationLossModel/Variable/$ns3::GammaRandomVariable

Attributes

Alpha: The alpha value for the gamma 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
Beta: The beta value for the gamma 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

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 are defined for this type.

Definition at line 1469 of file random-variable-stream.h.

Member Function Documentation

double ns3::GammaRandomVariable::GetAlpha ( void ) const

Returns the alpha value for the gamma distribution returned by this RNG stream.

Returns: The alpha value for the gamma distribution returned by this RNG stream.

Definition at line 892 of file random-variable-stream.cc.

References m_alpha, and NS_LOG_FUNCTION.

double ns3::GammaRandomVariable::GetBeta ( void ) const

Returns the beta value for the gamma distribution returned by this RNG stream.

Returns: The beta value for the gamma distribution returned by this RNG stream.

Definition at line 898 of file random-variable-stream.cc.

References m_beta, and NS_LOG_FUNCTION.

uint32_t ns3::GammaRandomVariable::GetInteger	(	uint32_t	alpha,
		uint32_t	beta
	)

Returns a random unsigned integer from a gamma distribution with the specified alpha and beta.

Parameters

alpha	Alpha value for the gamma distribution.
beta	Beta value for the gamma distribution.

Returns: A random unsigned integer value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u$ is a uniform variable over [0,1] and $x$ is a value that would be returned normally, then $(1 - u$ ) is the distance that $u$ would be from $1$ . The value returned in the antithetic case, $x'$ , uses (1-u), which is the distance $u$ is from the 1.

Definition at line 973 of file random-variable-stream.cc.

References GetValue(), and NS_LOG_FUNCTION.

uint32_t ns3::GammaRandomVariable::GetInteger ( void )

virtual

Returns a random unsigned integer from a gamma distribution with the current alpha and beta.

Returns: A random unsigned integer value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u$ is a uniform variable over [0,1] and $x$ is a value that would be returned normally, then $(1 - u$ ) is the distance that $u$ would be from $1$ . The value returned in the antithetic case, $x'$ , uses (1-u), which is the distance $u$ is from the 1.

Implements ns3::RandomVariableStream.

Definition at line 986 of file random-variable-stream.cc.

References GetValue(), m_alpha, m_beta, and NS_LOG_FUNCTION.

double ns3::GammaRandomVariable::GetNormalValue	(	double	mean,
		double	variance,
		double	bound
	)

private

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 993 of file random-variable-stream.cc.

References ns3::RandomVariableStream::IsAntithetic(), m_next, m_nextValid, NS_LOG_FUNCTION, ns3::RandomVariableStream::Peek(), and ns3::RngStream::RandU01().

Referenced by GetValue().

double ns3::GammaRandomVariable::GetValue	(	double	alpha,
		double	beta
	)

Returns a random double from a gamma distribution with the specified alpha and beta.

Parameters

alpha	Alpha value for the gamma distribution.
beta	Beta value for the gamma distribution.

Returns: A floating point random value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u$ is a uniform variable over [0,1] and $x$ is a value that would be returned normally, then $(1 - u$ ) is the distance that $u$ would be from $1$ . The value returned in the antithetic case, $x'$ , uses (1-u), which is the distance $u$ is from the 1.

Definition at line 921 of file random-variable-stream.cc.

References GetNormalValue(), GetValue(), ns3::RandomVariableStream::IsAntithetic(), NS_LOG_FUNCTION, ns3::RandomVariableStream::Peek(), and ns3::RngStream::RandU01().

Referenced by RandomVariableStreamGammaTestCase::DoRun(), and RandomVariableStreamGammaAntitheticTestCase::DoRun().

double ns3::GammaRandomVariable::GetValue ( void )

virtual

Returns a random double from a gamma distribution with the current alpha and beta.

Returns: A floating point random value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u$ is a uniform variable over [0,1] and $x$ is a value that would be returned normally, then $(1 - u$ ) is the distance that $u$ would be from $1$ . The value returned in the antithetic case, $x'$ , uses (1-u), which is the distance $u$ is from the 1.

Note that we have to re-implement this method here because the method is overloaded above for the two-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 980 of file random-variable-stream.cc.

References m_alpha, m_beta, and NS_LOG_FUNCTION.

Referenced by GetInteger(), and GetValue().

The documentation for this class was generated from the following files:

src/core/model/random-variable-stream.h
src/core/model/random-variable-stream.cc

Public Member Functions

Static Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Config Paths

Attributes

Attributes defined in parent class ns3::RandomVariableStream

Member Function Documentation