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ns3::NormalRandomVariable Class Reference

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:

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. More...
 
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. More...
 
virtual uint32_t GetInteger (void)
 Returns a random unsigned integer from a normal distribution with the current mean, variance, and bound. More...
 
double GetMean (void) const
 Returns the mean value for the normal distribution returned by this RNG stream. More...
 
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. More...
 
virtual double GetValue (void)
 Returns a random double from a normal distribution with the current mean, variance, and bound. More...
 
double GetVariance (void) const
 Returns the variance value for the normal distribution returned by this RNG stream. 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
 
SimpleRefCountoperator= (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)
 

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
RngStreamPeek (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 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 ();

Config Paths

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

  • /ChannelList/[i]/$ns3::WifiChannel/$ns3::YansWifiChannel/PropagationDelayModel/$ns3::RandomPropagationDelayModel/Variable/$ns3::NormalRandomVariable
  • /ChannelList/[i]/$ns3::WifiChannel/$ns3::YansWifiChannel/PropagationLossModel/$ns3::RandomPropagationLossModel/Variable/$ns3::NormalRandomVariable
  • /ChannelList/[i]/$ns3::YansWifiChannel/PropagationDelayModel/$ns3::RandomPropagationDelayModel/Variable/$ns3::NormalRandomVariable
  • /ChannelList/[i]/$ns3::YansWifiChannel/PropagationLossModel/$ns3::RandomPropagationLossModel/Variable/$ns3::NormalRandomVariable
  • /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/$ns3::BurstErrorModel/BurstSize/$ns3::NormalRandomVariable
  • /NodeList/[i]/DeviceList/[i]/$ns3::CsmaNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstStart/$ns3::NormalRandomVariable
  • /NodeList/[i]/DeviceList/[i]/$ns3::CsmaNetDevice/ReceiveErrorModel/$ns3::RateErrorModel/RanVar/$ns3::NormalRandomVariable
  • /NodeList/[i]/DeviceList/[i]/$ns3::PointToPointNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstSize/$ns3::NormalRandomVariable
  • /NodeList/[i]/DeviceList/[i]/$ns3::PointToPointNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstStart/$ns3::NormalRandomVariable
  • /NodeList/[i]/DeviceList/[i]/$ns3::PointToPointNetDevice/ReceiveErrorModel/$ns3::RateErrorModel/RanVar/$ns3::NormalRandomVariable
  • /NodeList/[i]/DeviceList/[i]/$ns3::SimpleNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstSize/$ns3::NormalRandomVariable
  • /NodeList/[i]/DeviceList/[i]/$ns3::SimpleNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstStart/$ns3::NormalRandomVariable
  • /NodeList/[i]/DeviceList/[i]/$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

  • 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 are defined for this type.

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

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 672 of file random-variable-stream.cc.

References m_bound, and NS_LOG_FUNCTION.

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
meanMean value for the normal distribution.
varianceVariance value for the normal distribution.
boundBound 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 725 of file random-variable-stream.cc.

References GetValue(), and NS_LOG_FUNCTION.

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 738 of file random-variable-stream.cc.

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

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 660 of file random-variable-stream.cc.

References m_mean, and NS_LOG_FUNCTION.

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
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 679 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 RandomVariableStreamNormalTestCase::DoRun(), and RandomVariableStreamNormalAntitheticTestCase::DoRun().

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 732 of file random-variable-stream.cc.

References m_bound, m_mean, m_variance, and NS_LOG_FUNCTION.

Referenced by GetInteger().

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

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

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

Definition at line 666 of file random-variable-stream.cc.

References m_variance, and NS_LOG_FUNCTION.


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