Logo ROOT  
Reference Guide
TNeuron Class Reference

This class describes an elementary neuron, which is the basic element for a Neural Network.

A network is built connecting neurons by synapses. There are different types of neurons: linear (a+bx), sigmoid (1/(1+exp(-x)), tanh or gaussian. An external function can also be used, together with its derivative. In a Multi Layer Perceptron, the input layer is made of inactive neurons (returning the normalized input) and output neurons are linear. Hidden neurons may be anything, the default being sigmoids.

This implementation contains several methods to compute the value, the derivative, the DeDw, ... Values are stored in local buffers. The SetNewEvent() method is there to inform buffered values are outdated.

Definition at line 25 of file TNeuron.h.

Public Types

enum  ENeuronType {
  kOff, kLinear, kSigmoid, kTanh,
  kGauss, kSoftmax, kExternal
}
 
- Public Types inherited from TObject
enum  {
  kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kInconsistent = 0x08000000,
  kBitMask = 0x00ffffff
}
 
enum  { kSingleKey = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) }
 
enum  EDeprecatedStatusBits { kObjInCanvas = BIT(3) }
 
enum  EStatusBits {
  kCanDelete = BIT(0), kMustCleanup = BIT(3), kIsReferenced = BIT(4), kHasUUID = BIT(5),
  kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13)
}
 

Public Member Functions

 TNeuron (ENeuronType type=kSigmoid, const char *name="", const char *title="", const char *extF="", const char *extD="")
 Usual constructor. More...
 
virtual ~TNeuron ()
 
void AddInLayer (TNeuron *)
 Tells a neuron which neurons form its layer (including itself). More...
 
void ForceExternalValue (Double_t value)
 Uses the branch type to force an external value. More...
 
Double_t GetBranch () const
 Returns the formula value. More...
 
Double_t GetDeDw () const
 Computes the derivative of the error wrt the neuron weight. More...
 
Double_t GetDEDw () const
 
Double_t GetDerivative () const
 computes the derivative for the appropriate function at the working point More...
 
Double_t GetError () const
 Computes the error for output neurons. More...
 
TNeuronGetInLayer (Int_t n) const
 
Double_t GetInput () const
 Returns neuron input. More...
 
const Double_tGetNormalisation () const
 
TSynapseGetPost (Int_t n) const
 
TSynapseGetPre (Int_t n) const
 
Double_t GetTarget () const
 Computes the normalized target pattern for output neurons. More...
 
ENeuronType GetType () const
 Returns the neuron type. More...
 
Double_t GetValue () const
 Computes the output using the appropriate function and all the weighted inputs, or uses the branch as input. More...
 
Double_t GetWeight () const
 
void SetDEDw (Double_t in)
 Sets the derivative of the total error wrt the neuron weight. More...
 
void SetNewEvent () const
 Inform the neuron that inputs of the network have changed, so that the buffered values have to be recomputed. More...
 
void SetNormalisation (Double_t mean, Double_t RMS)
 Sets the normalization variables. More...
 
void SetWeight (Double_t w)
 Sets the neuron weight to w. More...
 
TTreeFormulaUseBranch (TTree *, const char *)
 Sets a formula that can be used to make the neuron an input. More...
 
- Public Member Functions inherited from TNamed
 TNamed ()
 
 TNamed (const char *name, const char *title)
 
 TNamed (const TNamed &named)
 TNamed copy ctor. More...
 
 TNamed (const TString &name, const TString &title)
 
virtual ~TNamed ()
 TNamed destructor. More...
 
virtual void Clear (Option_t *option="")
 Set name and title to empty strings (""). More...
 
virtual TObjectClone (const char *newname="") const
 Make a clone of an object using the Streamer facility. More...
 
virtual Int_t Compare (const TObject *obj) const
 Compare two TNamed objects. More...
 
virtual void Copy (TObject &named) const
 Copy this to obj. More...
 
virtual void FillBuffer (char *&buffer)
 Encode TNamed into output buffer. More...
 
virtual const char * GetName () const
 Returns name of object. More...
 
virtual const char * GetTitle () const
 Returns title of object. More...
 
virtual ULong_t Hash () const
 Return hash value for this object. More...
 
virtual Bool_t IsSortable () const
 
virtual void ls (Option_t *option="") const
 List TNamed name and title. More...
 
TNamedoperator= (const TNamed &rhs)
 TNamed assignment operator. More...
 
virtual void Print (Option_t *option="") const
 Print TNamed name and title. More...
 
virtual void SetName (const char *name)
 Set the name of the TNamed. More...
 
virtual void SetNameTitle (const char *name, const char *title)
 Set all the TNamed parameters (name and title). More...
 
virtual void SetTitle (const char *title="")
 Set the title of the TNamed. More...
 
virtual Int_t Sizeof () const
 Return size of the TNamed part of the TObject. More...
 
- Public Member Functions inherited from TObject
 TObject ()
 TObject constructor. More...
 
 TObject (const TObject &object)
 TObject copy ctor. More...
 
virtual ~TObject ()
 TObject destructor. More...
 
void AbstractMethod (const char *method) const
 Use this method to implement an "abstract" method that you don't want to leave purely abstract. More...
 
virtual void AppendPad (Option_t *option="")
 Append graphics object to current pad. More...
 
virtual void Browse (TBrowser *b)
 Browse object. May be overridden for another default action. More...
 
ULong_t CheckedHash ()
 Check and record whether this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object. More...
 
virtual const char * ClassName () const
 Returns name of class to which the object belongs. More...
 
virtual void Delete (Option_t *option="")
 Delete this object. More...
 
virtual Int_t DistancetoPrimitive (Int_t px, Int_t py)
 Computes distance from point (px,py) to the object. More...
 
virtual void Draw (Option_t *option="")
 Default Draw method for all objects. More...
 
virtual void DrawClass () const
 Draw class inheritance tree of the class to which this object belongs. More...
 
virtual TObjectDrawClone (Option_t *option="") const
 Draw a clone of this object in the current selected pad for instance with: gROOT->SetSelectedPad(gPad). More...
 
virtual void Dump () const
 Dump contents of object on stdout. More...
 
virtual void Error (const char *method, const char *msgfmt,...) const
 Issue error message. More...
 
virtual void Execute (const char *method, const char *params, Int_t *error=0)
 Execute method on this object with the given parameter string, e.g. More...
 
virtual void Execute (TMethod *method, TObjArray *params, Int_t *error=0)
 Execute method on this object with parameters stored in the TObjArray. More...
 
virtual void ExecuteEvent (Int_t event, Int_t px, Int_t py)
 Execute action corresponding to an event at (px,py). More...
 
virtual void Fatal (const char *method, const char *msgfmt,...) const
 Issue fatal error message. More...
 
virtual TObjectFindObject (const char *name) const
 Must be redefined in derived classes. More...
 
virtual TObjectFindObject (const TObject *obj) const
 Must be redefined in derived classes. More...
 
virtual Option_tGetDrawOption () const
 Get option used by the graphics system to draw this object. More...
 
virtual const char * GetIconName () const
 Returns mime type name of object. More...
 
virtual char * GetObjectInfo (Int_t px, Int_t py) const
 Returns string containing info about the object at position (px,py). More...
 
virtual Option_tGetOption () const
 
virtual UInt_t GetUniqueID () const
 Return the unique object id. More...
 
virtual Bool_t HandleTimer (TTimer *timer)
 Execute action in response of a timer timing out. More...
 
Bool_t HasInconsistentHash () const
 Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e. More...
 
virtual void Info (const char *method, const char *msgfmt,...) const
 Issue info message. More...
 
virtual Bool_t InheritsFrom (const char *classname) const
 Returns kTRUE if object inherits from class "classname". More...
 
virtual Bool_t InheritsFrom (const TClass *cl) const
 Returns kTRUE if object inherits from TClass cl. More...
 
virtual void Inspect () const
 Dump contents of this object in a graphics canvas. More...
 
void InvertBit (UInt_t f)
 
virtual Bool_t IsEqual (const TObject *obj) const
 Default equal comparison (objects are equal if they have the same address in memory). More...
 
virtual Bool_t IsFolder () const
 Returns kTRUE in case object contains browsable objects (like containers or lists of other objects). More...
 
R__ALWAYS_INLINE Bool_t IsOnHeap () const
 
R__ALWAYS_INLINE Bool_t IsZombie () const
 
void MayNotUse (const char *method) const
 Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary). More...
 
virtual Bool_t Notify ()
 This method must be overridden to handle object notification. More...
 
void Obsolete (const char *method, const char *asOfVers, const char *removedFromVers) const
 Use this method to declare a method obsolete. More...
 
void operator delete (void *ptr)
 Operator delete. More...
 
void operator delete[] (void *ptr)
 Operator delete []. More...
 
voidoperator new (size_t sz)
 
voidoperator new (size_t sz, void *vp)
 
voidoperator new[] (size_t sz)
 
voidoperator new[] (size_t sz, void *vp)
 
TObjectoperator= (const TObject &rhs)
 TObject assignment operator. More...
 
virtual void Paint (Option_t *option="")
 This method must be overridden if a class wants to paint itself. More...
 
virtual void Pop ()
 Pop on object drawn in a pad to the top of the display list. More...
 
virtual Int_t Read (const char *name)
 Read contents of object with specified name from the current directory. More...
 
virtual void RecursiveRemove (TObject *obj)
 Recursively remove this object from a list. More...
 
void ResetBit (UInt_t f)
 
virtual void SaveAs (const char *filename="", Option_t *option="") const
 Save this object in the file specified by filename. More...
 
virtual void SavePrimitive (std::ostream &out, Option_t *option="")
 Save a primitive as a C++ statement(s) on output stream "out". More...
 
void SetBit (UInt_t f)
 
void SetBit (UInt_t f, Bool_t set)
 Set or unset the user status bits as specified in f. More...
 
virtual void SetDrawOption (Option_t *option="")
 Set drawing option for object. More...
 
virtual void SetUniqueID (UInt_t uid)
 Set the unique object id. More...
 
virtual void SysError (const char *method, const char *msgfmt,...) const
 Issue system error message. More...
 
R__ALWAYS_INLINE Bool_t TestBit (UInt_t f) const
 
Int_t TestBits (UInt_t f) const
 
virtual void UseCurrentStyle ()
 Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked. More...
 
virtual void Warning (const char *method, const char *msgfmt,...) const
 Issue warning message. More...
 
virtual Int_t Write (const char *name=0, Int_t option=0, Int_t bufsize=0)
 Write this object to the current directory. More...
 
virtual Int_t Write (const char *name=0, Int_t option=0, Int_t bufsize=0) const
 Write this object to the current directory. More...
 

Protected Member Functions

void AddPost (TSynapse *)
 Adds a synapse to the neuron as an output This method is used by the TSynapse while connecting two neurons. More...
 
void AddPre (TSynapse *)
 Adds a synapse to the neuron as an input This method is used by the TSynapse while connecting two neurons. More...
 
Double_t DSigmoid (Double_t x) const
 The Derivative of the Sigmoid. More...
 
Double_t Sigmoid (Double_t x) const
 The Sigmoid. More...
 
- Protected Member Functions inherited from TObject
virtual void DoError (int level, const char *location, const char *fmt, va_list va) const
 Interface to ErrorHandler (protected). More...
 
void MakeZombie ()
 

Private Member Functions

 TNeuron (const TNeuron &)
 
TNeuronoperator= (const TNeuron &)
 

Private Attributes

Double_t fDeDw
 ! buffer containing the last derivative of the error More...
 
Double_t fDEDw
 ! buffer containing the sum over all examples of DeDw More...
 
Double_t fDerivative
 ! buffer containing the last neuron derivative More...
 
TFormulafExtD
 derivative (external mode) More...
 
TFormulafExtF
 function (external mode) More...
 
TTreeFormulafFormula
 ! formula to be used for inputs and outputs More...
 
Int_t fIndex
 ! index in the formula More...
 
Double_t fInput
 ! buffer containing the last neuron input More...
 
TObjArray flayer
 pointers to the current level in a network (neurons, not synapses) More...
 
Bool_t fNewDeDw
 ! do we need to compute fDeDw again ? More...
 
Bool_t fNewDeriv
 ! do we need to compute fDerivative again ? More...
 
Bool_t fNewInput
 ! do we need to compute fInput again ? More...
 
Bool_t fNewValue
 ! do we need to compute fValue again ? More...
 
Double_t fNorm [2]
 normalisation to mean=0, RMS=1. More...
 
TObjArray fpost
 pointers to the next level in a network More...
 
TObjArray fpre
 pointers to the previous level in a network More...
 
ENeuronType fType
 neuron type More...
 
Double_t fValue
 ! buffer containing the last neuron output More...
 
Double_t fWeight
 weight used for computation More...
 

Friends

class TSynapse
 

Additional Inherited Members

- Static Public Member Functions inherited from TObject
static Long_t GetDtorOnly ()
 Return destructor only flag. More...
 
static Bool_t GetObjectStat ()
 Get status of object stat flag. More...
 
static void SetDtorOnly (void *obj)
 Set destructor only flag. More...
 
static void SetObjectStat (Bool_t stat)
 Turn on/off tracking of objects in the TObjectTable. More...
 
- Protected Attributes inherited from TNamed
TString fName
 
TString fTitle
 

#include <TMVA/TNeuron.h>

Inheritance diagram for TNeuron:
[legend]

Member Enumeration Documentation

◆ ENeuronType

Enumerator
kOff 
kLinear 
kSigmoid 
kTanh 
kGauss 
kSoftmax 
kExternal 

Definition at line 29 of file TNeuron.h.

Constructor & Destructor Documentation

◆ TNeuron() [1/2]

TNeuron::TNeuron ( TNeuron::ENeuronType  type = kSigmoid,
const char *  name = "",
const char *  title = "",
const char *  extF = "",
const char *  extD = "" 
)

Usual constructor.

Definition at line 47 of file TNeuron.cxx.

◆ ~TNeuron()

virtual TNeuron::~TNeuron ( )
inlinevirtual

Definition at line 34 of file TNeuron.h.

◆ TNeuron() [2/2]

TNeuron::TNeuron ( const TNeuron )
private

Member Function Documentation

◆ AddInLayer()

void TNeuron::AddInLayer ( TNeuron nearP)

Tells a neuron which neurons form its layer (including itself).

This is needed for self-normalizing functions, like Softmax.

Definition at line 853 of file TNeuron.cxx.

◆ AddPost()

void TNeuron::AddPost ( TSynapse post)
protected

Adds a synapse to the neuron as an output This method is used by the TSynapse while connecting two neurons.

Definition at line 842 of file TNeuron.cxx.

◆ AddPre()

void TNeuron::AddPre ( TSynapse pre)
protected

Adds a synapse to the neuron as an input This method is used by the TSynapse while connecting two neurons.

Definition at line 830 of file TNeuron.cxx.

◆ DSigmoid()

Double_t TNeuron::DSigmoid ( Double_t  x) const
protected

The Derivative of the Sigmoid.

Definition at line 814 of file TNeuron.cxx.

◆ ForceExternalValue()

void TNeuron::ForceExternalValue ( Double_t  value)

Uses the branch type to force an external value.

Definition at line 1121 of file TNeuron.cxx.

◆ GetBranch()

Double_t TNeuron::GetBranch ( ) const

Returns the formula value.

Definition at line 910 of file TNeuron.cxx.

◆ GetDeDw()

Double_t TNeuron::GetDeDw ( ) const

Computes the derivative of the error wrt the neuron weight.

Definition at line 1080 of file TNeuron.cxx.

◆ GetDEDw()

Double_t TNeuron::GetDEDw ( ) const
inline

Definition at line 53 of file TNeuron.h.

◆ GetDerivative()

Double_t TNeuron::GetDerivative ( ) const

computes the derivative for the appropriate function at the working point

Definition at line 1007 of file TNeuron.cxx.

◆ GetError()

Double_t TNeuron::GetError ( ) const

Computes the error for output neurons.

Returns 0 for other neurons.

Definition at line 1059 of file TNeuron.cxx.

◆ GetInLayer()

TNeuron* TNeuron::GetInLayer ( Int_t  n) const
inline

Definition at line 37 of file TNeuron.h.

◆ GetInput()

Double_t TNeuron::GetInput ( ) const

Returns neuron input.

Definition at line 921 of file TNeuron.cxx.

◆ GetNormalisation()

const Double_t* TNeuron::GetNormalisation ( ) const
inline

Definition at line 50 of file TNeuron.h.

◆ GetPost()

TSynapse* TNeuron::GetPost ( Int_t  n) const
inline

Definition at line 36 of file TNeuron.h.

◆ GetPre()

TSynapse* TNeuron::GetPre ( Int_t  n) const
inline

Definition at line 35 of file TNeuron.h.

◆ GetTarget()

Double_t TNeuron::GetTarget ( ) const

Computes the normalized target pattern for output neurons.

Returns 0 for other neurons.

Definition at line 1070 of file TNeuron.cxx.

◆ GetType()

TNeuron::ENeuronType TNeuron::GetType ( ) const

Returns the neuron type.

Definition at line 863 of file TNeuron.cxx.

◆ GetValue()

Double_t TNeuron::GetValue ( ) const

Computes the output using the appropriate function and all the weighted inputs, or uses the branch as input.

In that case, the branch normalisation is also used.

Definition at line 944 of file TNeuron.cxx.

◆ GetWeight()

Double_t TNeuron::GetWeight ( ) const
inline

Definition at line 48 of file TNeuron.h.

◆ operator=()

TNeuron& TNeuron::operator= ( const TNeuron )
private

◆ SetDEDw()

void TNeuron::SetDEDw ( Double_t  in)

Sets the derivative of the total error wrt the neuron weight.

Definition at line 1164 of file TNeuron.cxx.

◆ SetNewEvent()

void TNeuron::SetNewEvent ( ) const

Inform the neuron that inputs of the network have changed, so that the buffered values have to be recomputed.

Definition at line 1153 of file TNeuron.cxx.

◆ SetNormalisation()

void TNeuron::SetNormalisation ( Double_t  mean,
Double_t  RMS 
)

Sets the normalization variables.

Any input neuron will return (branch-mean)/RMS. When UseBranch is called, mean and RMS are automatically set to the actual branch mean and RMS.

Definition at line 1133 of file TNeuron.cxx.

◆ SetWeight()

void TNeuron::SetWeight ( Double_t  w)

Sets the neuron weight to w.

The neuron weight corresponds to the bias in the linear combination of the inputs.

Definition at line 1144 of file TNeuron.cxx.

◆ Sigmoid()

Double_t TNeuron::Sigmoid ( Double_t  x) const
protected

The Sigmoid.

Fast computation of the values of the sigmoid function. Uses values of the function up to the seventh order tabulated at 700 points. Values were computed in long double precision (16 bytes, precision to about 37 digits) on a hp computer. Some values were checked with Mathematica. Result should be correct to ~ 15 digits (about double precision)

From the mlpfit package (J.Schwindling 20-Jul-1999)

Definition at line 91 of file TNeuron.cxx.

◆ UseBranch()

TTreeFormula * TNeuron::UseBranch ( TTree input,
const char *  formula 
)

Sets a formula that can be used to make the neuron an input.

The formula is automatically normalized to mean=0, RMS=1. This normalisation is used by GetValue() (input neurons) and GetError() (output neurons)

Definition at line 874 of file TNeuron.cxx.

Friends And Related Function Documentation

◆ TSynapse

friend class TSynapse
friend

Definition at line 26 of file TNeuron.h.

Member Data Documentation

◆ fDeDw

Double_t TNeuron::fDeDw
private

! buffer containing the last derivative of the error

Definition at line 84 of file TNeuron.h.

◆ fDEDw

Double_t TNeuron::fDEDw
private

! buffer containing the sum over all examples of DeDw

Definition at line 85 of file TNeuron.h.

◆ fDerivative

Double_t TNeuron::fDerivative
private

! buffer containing the last neuron derivative

Definition at line 82 of file TNeuron.h.

◆ fExtD

TFormula* TNeuron::fExtD
private

derivative (external mode)

Definition at line 74 of file TNeuron.h.

◆ fExtF

TFormula* TNeuron::fExtF
private

function (external mode)

Definition at line 73 of file TNeuron.h.

◆ fFormula

TTreeFormula* TNeuron::fFormula
private

! formula to be used for inputs and outputs

Definition at line 75 of file TNeuron.h.

◆ fIndex

Int_t TNeuron::fIndex
private

! index in the formula

Definition at line 76 of file TNeuron.h.

◆ fInput

Double_t TNeuron::fInput
private

! buffer containing the last neuron input

Definition at line 78 of file TNeuron.h.

◆ flayer

TObjArray TNeuron::flayer
private

pointers to the current level in a network (neurons, not synapses)

Definition at line 69 of file TNeuron.h.

◆ fNewDeDw

Bool_t TNeuron::fNewDeDw
private

! do we need to compute fDeDw again ?

Definition at line 83 of file TNeuron.h.

◆ fNewDeriv

Bool_t TNeuron::fNewDeriv
private

! do we need to compute fDerivative again ?

Definition at line 81 of file TNeuron.h.

◆ fNewInput

Bool_t TNeuron::fNewInput
private

! do we need to compute fInput again ?

Definition at line 77 of file TNeuron.h.

◆ fNewValue

Bool_t TNeuron::fNewValue
private

! do we need to compute fValue again ?

Definition at line 79 of file TNeuron.h.

◆ fNorm

Double_t TNeuron::fNorm[2]
private

normalisation to mean=0, RMS=1.

Definition at line 71 of file TNeuron.h.

◆ fpost

TObjArray TNeuron::fpost
private

pointers to the next level in a network

Definition at line 68 of file TNeuron.h.

◆ fpre

TObjArray TNeuron::fpre
private

pointers to the previous level in a network

Definition at line 67 of file TNeuron.h.

◆ fType

ENeuronType TNeuron::fType
private

neuron type

Definition at line 72 of file TNeuron.h.

◆ fValue

Double_t TNeuron::fValue
private

! buffer containing the last neuron output

Definition at line 80 of file TNeuron.h.

◆ fWeight

Double_t TNeuron::fWeight
private

weight used for computation

Definition at line 70 of file TNeuron.h.

Libraries for TNeuron:
[legend]

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