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

#include <random-variable-stream.h>

Inheritance diagram for ns3::LogNormalRandomVariable:

Public Member Functions
	LogNormalRandomVariable ()
	Creates a log-normal distribution RNG with the default values for mu and sigma.

uint32_t	GetInteger (uint32_t mu, uint32_t sigma)
	Returns a random unsigned integer from a log-normal distribution with the specified mu and sigma. More...

virtual uint32_t	GetInteger (void)
	Returns a random unsigned integer from a log-normal distribution with the current mu and sigma. More...

double	GetMu (void) const
	Returns the mu value for the log-normal distribution returned by this RNG stream. More...

double	GetSigma (void) const
	Returns the sigma value for the log-normal distribution returned by this RNG stream. More...

double	GetValue (double mu, double sigma)
	Returns a random double from a log-normal distribution with the specified mu and sigma. More...

virtual double	GetValue (void)
	Returns a random double from a log-normal distribution with the current mu and sigma. 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 Attributes
double	m_mu
	The mu value for the log-normal distribution returned by this RNG stream.

double	m_sigma
	The sigma value for the log-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.

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 log-normal 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 log-normal distribution. It also supports the generation of single random numbers from various log-normal distributions.

LogNormalRandomVariable defines a random variable with a log-normal distribution. If one takes the natural logarithm of random variable following the log-normal distribution, the obtained values follow a normal distribution.

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

The $\mu$ and $\sigma$ parameters can be calculated instead if the mean and variance are known with the following equations: $\mu = ln(mean) - \frac{1}{2}ln\left(1+\frac{variance}{mean^2}\right)$ , and, $\sigma = \sqrt{ln\left(1+\frac{variance}{mean^2}\right)}$

Here is an example of how to use this class:

double mu = 5.0;
double sigma = 2.0;
Ptr<LogNormalRandomVariable> x = CreateObject<LogNormalRandomVariable> ();
x->SetAttribute ("Mu", DoubleValue (mu));
x->SetAttribute ("Sigma", DoubleValue (sigma));
// The expected value for the mean of the values returned by a
// log-normally distributed random variable is equal to 
//
//                             2
//                   mu + sigma  / 2
//     E[value]  =  e                 .
//
double value = x->GetValue ();

Config Paths

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

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

Attributes

Mu: The mu value for the log-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
Sigma: The sigma value for the log-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

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 1266 of file random-variable-stream.h.

Member Function Documentation

uint32_t ns3::LogNormalRandomVariable::GetInteger	(	uint32_t	mu,
		uint32_t	sigma
	)

Returns a random unsigned integer from a log-normal distribution with the specified mu and sigma.

Parameters

mu	Mu value for the log-normal distribution.
sigma	Sigma value for the log-normal distribution.

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 value that would be returned normally, $x$ , is calculated as follows:

$\begin{eqnarray*} v1 & = & -1 + 2 * u1 \\ v2 & = & -1 + 2 * u2 \\ r2 & = & v1 * v1 + v2 * v2 \\ normal & = & v1 * \sqrt{\frac{-2.0 * \log{r2}}{r2}} \\ x & = & \exp{sigma * normal + mu} . \end{eqnarray*}$

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

$\begin{eqnarray*} v1' & = & -1 + 2 * (1 - u1) \\ v2' & = & -1 + 2 * (1 - u2) \\ r2' & = & v1' * v1' + v2' * v2' \\ normal' & = & v1' * \sqrt{\frac{-2.0 * \log{r2'}}{r2'}} \\ x' & = & \exp{sigma * normal' + mu} . \end{eqnarray*}$

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

Definition at line 844 of file random-variable-stream.cc.

References GetValue(), and NS_LOG_FUNCTION.

uint32_t ns3::LogNormalRandomVariable::GetInteger ( void )

virtual

Returns a random unsigned integer from a log-normal distribution with the current mu and sigma.

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 value that would be returned normally, $x$ , is calculated as follows:

$\begin{eqnarray*} v1 & = & -1 + 2 * u1 \\ v2 & = & -1 + 2 * u2 \\ r2 & = & v1 * v1 + v2 * v2 \\ normal & = & v1 * \sqrt{\frac{-2.0 * \log{r2}}{r2}} \\ x & = & \exp{sigma * normal + mu} . \end{eqnarray*}$

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

$\begin{eqnarray*} v1' & = & -1 + 2 * (1 - u1) \\ v2' & = & -1 + 2 * (1 - u2) \\ r2' & = & v1' * v1' + v2' * v2' \\ normal' & = & v1' * \sqrt{\frac{-2.0 * \log{r2'}}{r2'}} \\ x' & = & \exp{sigma * normal' + mu} . \end{eqnarray*}$

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

Implements ns3::RandomVariableStream.

Definition at line 857 of file random-variable-stream.cc.

References GetValue(), m_mu, m_sigma, and NS_LOG_FUNCTION.

double ns3::LogNormalRandomVariable::GetMu ( void ) const

Returns the mu value for the log-normal distribution returned by this RNG stream.

Returns: The mu value for the log-normal distribution returned by this RNG stream.

Definition at line 771 of file random-variable-stream.cc.

References m_mu, and NS_LOG_FUNCTION.

double ns3::LogNormalRandomVariable::GetSigma ( void ) const

Returns the sigma value for the log-normal distribution returned by this RNG stream.

Returns: The sigma value for the log-normal distribution returned by this RNG stream.

Definition at line 777 of file random-variable-stream.cc.

References m_sigma, and NS_LOG_FUNCTION.

double ns3::LogNormalRandomVariable::GetValue	(	double	mu,
		double	sigma
	)

Returns a random double from a log-normal distribution with the specified mu and sigma.

Parameters

mu	Mu value for the log-normal distribution.
sigma	Sigma value for the log-normal distribution.

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 value that would be returned normally, $x$ , is calculated as follows:

$\begin{eqnarray*} v1 & = & -1 + 2 * u1 \\ v2 & = & -1 + 2 * u2 \\ r2 & = & v1 * v1 + v2 * v2 \\ normal & = & v1 * \sqrt{\frac{-2.0 * \log{r2}}{r2}} \\ x & = & \exp{sigma * normal + mu} . \end{eqnarray*}$

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

$\begin{eqnarray*} v1' & = & -1 + 2 * (1 - u1) \\ v2' & = & -1 + 2 * (1 - u2) \\ r2' & = & v1' * v1' + v2' * v2' \\ normal' & = & v1' * \sqrt{\frac{-2.0 * \log{r2'}}{r2'}} \\ x' & = & \exp{sigma * normal' + mu} . \end{eqnarray*}$

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

Definition at line 810 of file random-variable-stream.cc.

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

Referenced by RandomVariableStreamLogNormalTestCase::DoRun(), and RandomVariableStreamLogNormalAntitheticTestCase::DoRun().

double ns3::LogNormalRandomVariable::GetValue ( void )

virtual

Returns a random double from a log-normal distribution with the current mu and sigma.

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 value that would be returned normally, $x$ , is calculated as follows:

$\begin{eqnarray*} v1 & = & -1 + 2 * u1 \\ v2 & = & -1 + 2 * u2 \\ r2 & = & v1 * v1 + v2 * v2 \\ normal & = & v1 * \sqrt{\frac{-2.0 * \log{r2}}{r2}} \\ x & = & \exp{sigma * normal + mu} . \end{eqnarray*}$

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

$\begin{eqnarray*} v1' & = & -1 + 2 * (1 - u1) \\ v2' & = & -1 + 2 * (1 - u2) \\ r2' & = & v1' * v1' + v2' * v2' \\ normal' & = & v1' * \sqrt{\frac{-2.0 * \log{r2'}}{r2'}} \\ x' & = & \exp{sigma * normal' + mu} . \end{eqnarray*}$

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 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 851 of file random-variable-stream.cc.

References m_mu, m_sigma, and NS_LOG_FUNCTION.

Referenced by GetInteger().

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 Attributes

Additional Inherited Members

Detailed Description

Config Paths

Attributes

Attributes defined in parent class ns3::RandomVariableStream

Member Function Documentation