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ns3::GammaRandomVariable Class Reference

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:
+ Collaboration diagram for ns3::GammaRandomVariable:

Public Member Functions

 GammaRandomVariable ()
 Creates a gamma distribution RNG with the default values for alpha and beta. More...
 
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
 RandomVariableStream ()
 
virtual ~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
 Object ()
 
virtual ~Object ()
 
void AggregateObject (Ptr< Object > other)
 
void Dispose (void)
 Run the DoDispose methods of this object and all the objects aggregated to it. More...
 
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)
 This method calls the virtual DoInitialize method on all the objects aggregated to this object. More...
 
- Public Member Functions inherited from ns3::SimpleRefCount< Object, ObjectBase, ObjectDeleter >
 SimpleRefCount ()
 Constructor. More...
 
 SimpleRefCount (const SimpleRefCount &o)
 Copy constructor. More...
 
uint32_t GetReferenceCount (void) const
 Get the reference count of the object. More...
 
SimpleRefCountoperator= (const SimpleRefCount &o)
 Assignment. More...
 
void Ref (void) const
 Increment the reference count. More...
 
void Unref (void) const
 Decrement the reference count. More...
 
- Public Member Functions inherited from ns3::ObjectBase
virtual ~ObjectBase ()
 Virtual destructor. More...
 
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)
 Register this type. More...
 
- Static Public Member Functions inherited from ns3::SimpleRefCount< Object, ObjectBase, ObjectDeleter >
static void Cleanup (void)
 Noop. More...
 
- Static Public Member Functions inherited from ns3::ObjectBase
static TypeId GetTypeId (void)
 Get the type ID. More...
 

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. More...
 
double m_beta
 The beta value for the gamma distribution returned by this RNG stream. More...
 
double m_next
 The algorithm produces two normal values at a time. More...
 
bool m_nextValid
 True if the next normal value is valid. More...
 

Additional Inherited Members

- Protected Member Functions inherited from ns3::RandomVariableStream
RngStreamPeek (void) const
 Returns a pointer to the underlying RNG stream. More...
 
- Protected Member Functions inherited from ns3::Object
 Object (const Object &o)
 
virtual void DoDispose (void)
 This method is called by Object::Dispose or by the object's destructor, whichever comes first. More...
 
virtual void DoInitialize (void)
 This method is called only once by Object::Initialize. More...
 
virtual void NotifyNewAggregate (void)
 This method is invoked whenever two sets of objects are aggregated together. More...
 
- Protected Member Functions inherited from ns3::ObjectBase
void ConstructSelf (const AttributeConstructionList &attributes)
 
virtual void NotifyConstructionCompleted (void)
 This method is invoked once all member attributes have been initialized. More...
 

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::ArpL3Protocol/RequestJitter/$ns3::GammaRandomVariable
  • /NodeList/[i]/$ns3::Icmpv6L4Protocol/SolicitationJitter/$ns3::GammaRandomVariable
  • /NodeList/[i]/$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 1499 of file random-variable-stream.h.

Constructor & Destructor Documentation

ns3::GammaRandomVariable::GammaRandomVariable ( )

Creates a gamma distribution RNG with the default values for alpha and beta.

Definition at line 882 of file random-variable-stream.cc.

References NS_LOG_FUNCTION.

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
alphaAlpha value for the gamma distribution.
betaBeta 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.

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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.

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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
meanMean value for the normal distribution.
varianceVariance value for the normal distribution.
boundBound 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(), ns3::RngStream::RandU01(), and visualizer.higcontainer::w.

Referenced by GetValue().

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TypeId ns3::GammaRandomVariable::GetTypeId ( void  )
static

Definition at line 866 of file random-variable-stream.cc.

References m_alpha, m_beta, and ns3::TypeId::SetParent().

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

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

Parameters
alphaAlpha value for the gamma distribution.
betaBeta 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::NormalRandomVariable::INFINITE_VALUE, ns3::RandomVariableStream::IsAntithetic(), NS_LOG_FUNCTION, ns3::RandomVariableStream::Peek(), ns3::RngStream::RandU01(), and sample-rng-plot::x.

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

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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().

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Member Data Documentation

double ns3::GammaRandomVariable::m_alpha
private

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

Definition at line 1623 of file random-variable-stream.h.

Referenced by GetAlpha(), GetInteger(), GetTypeId(), and GetValue().

double ns3::GammaRandomVariable::m_beta
private

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

Definition at line 1626 of file random-variable-stream.h.

Referenced by GetBeta(), GetInteger(), GetTypeId(), and GetValue().

double ns3::GammaRandomVariable::m_next
private

The algorithm produces two normal values at a time.

Definition at line 1632 of file random-variable-stream.h.

Referenced by GetNormalValue().

bool ns3::GammaRandomVariable::m_nextValid
private

True if the next normal value is valid.

Definition at line 1629 of file random-variable-stream.h.

Referenced by GetNormalValue().


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