Evonet is the neural network taken from the EvoRobot. More...

Inheritance diagram for Evonet:

Signals
void	evonetUpdated ()
	emitted everytime the Evonet has been updated

Public Member Functions
float	computeMeanSquaredError (QVector< float > trainingSet, QVector< float > desiredOutput)

void	computeParameters ()

void	configure (ConfigurationParameters &params, QString prefix)
	Configures the object using a ConfigurationParameters object.

void	copyPheParameters (int *pheGene)

void	create_net_block (int inputNeuronType, int hiddenNeuronType, int outputNeuronType, bool recurrentHiddens, bool inputOutputConnections, bool recurrentOutputs, bool biasOnHidden, bool biasOnOutput)
	create the block structure for a standard architecture create x-y coordinate for network architecture display store in local variable the number of neurons

void	endTraining ()

int	exportWeightsToMATLABFile (char *path)

int	extractWeightsFromNet (Eigen::VectorXf &w)

int	freeParameters ()

float	getFreeParameter (int i)

float	getHidden (int h)

float	getInput (int in)

void	getMutations (float *mut)

float	getNeuron (int in)

int	getNoHiddens ()

int	getNoInputs ()

int	getNoNeurons ()

int	getNoOutputs ()

float *	getOldestStoredActivations ()
	Returns the oldest stored activation vector and removes it.

float	getOutput (int out)

int	getParamBias (int nbias)

ParameterSettableUI *	getUIManager ()
	Return a new instance of the EvonetUI.

float	getWeight (int to, int from)

float	getWrange ()

void	hardwire ()

int	importWeightsFromMATLABFile (char *path)

int	importWeightsFromVector (Eigen::VectorXf &w)

void	initWeightsInRange (float min, float max)

void	initWeightsNguyenWidrow (float min, float max)

void	injectHidden (int nh, float val)

bool	inTraining ()

int	load_net_blocks (const char *filename, int mode)
	load the architecture and the free parameters of a controller mode=0, load only the architecture mode=1, load also the parameters

float	logistic (float f)

bool	pheFileLoaded ()

void	prepareForTraining (QVector< float > &err_w)

void	printAct ()

void	printBlocks ()

void	printIO ()

void	printWeights ()

void	readNewPheLine (QStringList, float , float )

void	readOldPheLine (QStringList, float , float )

void	resetNet ()

void	save (ConfigurationParameters &params, QString prefix)
	Saves the actual status of parameters into the ConfigurationParameters object passed.

void	save_net_blocks (const char *filename, int mode)

int	setInput (int inp, float value)

void	setNeckReflex ()

void	setParameters (const int *dt)

void	setRanges (double weight, double bias, double gain)

void	setWeight (int to, int from, float w)

float	tansig (float f)
	— STUFF ADDED BY MANLIO FOR LEARNING

float	trainLevembergMarquardt (QVector< float > trainingSet, QVector< float > desiredOutput, float maxError)

float	trainLevembergMarquardtThroughTime (QVector< float > trainingSet, QVector< float > desiredOutput, int time, float maxError)

int	updateCounts ()
	return the number of updates (step) done

void	updateNet ()

Public Member Functions inherited from ParameterSettableWithConfigureFunction
void	addObserver (RuntimeParameterObserver *obs)

T	getRuntimeParameter (QString paramName)

	ParameterSettable ()

virtual void	postConfigureInitialization ()

void	removeObserver (RuntimeParameterObserver *obs)

void	setRuntimeParameter (QString paramName, T newvalue)

QString	typeName () const

Public Member Functions inherited from ParameterSettable
void	addObserver (RuntimeParameterObserver *obs)

T	getRuntimeParameter (QString paramName)

void	removeObserver (RuntimeParameterObserver *obs)

void	setRuntimeParameter (QString paramName, T newvalue)

QString	typeName () const

Static Public Member Functions
static void	describe (QString type)
	Add to Factory::typeDescriptions() the descriptions of all parameters and subgroups.

Static Public Member Functions inherited from ParameterSettableWithConfigureFunction
static void	describe (QString type)

static QString	fullParameterDescriptionPath (QString type, QString param)

static QString	fullSubgroupDescriptionPath (QString type, QString sub)

Static Public Member Functions inherited from ParameterSettable
static void	describe (QString type)

static QString	fullParameterDescriptionPath (QString type, QString param)

static QString	fullSubgroupDescriptionPath (QString type, QString sub)

Public Attributes
int	maxIterations

QColor	neurondcolor [MAXN]

int	neurondisplay [MAXN]

char	neuronl [MAXN][10]

bool	neuronlesion [MAXN]

int	neuronlesions

float	neuronlesionVal [MAXN]

double	neuronrange [MAXN][2]

int	nselected

float **	selectedp

Public Attributes inherited from ParameterSettableWithConfigureFunction
	AllowMultiple

	Default

	IsList

	IsMandatory

Public Attributes inherited from ParameterSettable
	AllowMultiple

	Default

	IsList

	IsMandatory

Static Public Attributes
static const float	DEFAULT_VALUE = -99.0f
	DEFAULT_VALUE is used for do not assign values to mut and parameters.

static const int	MAXN = 1000
	Maximum number of neurons for a neural network of this type.

static const int	MAXSTOREDACTIVATIONS = 100
	The maximum number of stored activation vectors.

Static Public Attributes inherited from ParameterSettableWithConfigureFunction
static const double	Infinity

static const int	MaxInteger

static const int	MinInteger

Static Public Attributes inherited from ParameterSettable
static const double	Infinity

static const int	MaxInteger

static const int	MinInteger

Friends
class	NetworkDialog

class	RendNetwork

Additional Inherited Members
Public Types inherited from ParameterSettableWithConfigureFunction
enum	Property

Protected Member Functions inherited from ParameterSettableWithConfigureFunction
void	notifyChangesToParam (QString paramName)

Static Protected Member Functions inherited from ParameterSettableWithConfigureFunction
static Descriptor	addTypeDescription (QString type, QString shortHelp, QString longHelp=QString(""))

static void	setGraphicalEditor (QString type)

Detailed Description

Evonet is the neural network taken from the EvoRobot.

Simple class to load a evorobot.net configuration file

Definition at line 70 of file evonet.h.

Member Function Documentation

void configure	(	ConfigurationParameters &	params,
		QString	prefix
	)

virtual

Configures the object using a ConfigurationParameters object.

Parameters

params	the configuration parameters object with parameters to use
prefix	the prefix to use to access the object configuration parameters. This is guaranteed to end with the separator character when called by the factory, so you don't need to add one

Implements ParameterSettableWithConfigureFunction.

Definition at line 85 of file evonet.cpp.

References Evonet::create_net_block(), Evonet::DEFAULT_VALUE, Logger::error(), ConfigurationHelper::getBool(), ConfigurationHelper::getDouble(), ConfigurationHelper::getInt(), ConfigurationHelper::getString(), Evonet::load_net_blocks(), Evonet::MAXN, and ConfigurationHelper::throwUserConfigError().

void create_net_block	(	int	inputNeuronType,
		int	hiddenNeuronType,
		int	outputNeuronType,
		bool	recurrentHiddens,
		bool	inputOutputConnections,
		bool	recurrentOutputs,
		bool	biasOnHidden,
		bool	biasOnOutput
	)

create the block structure for a standard architecture create x-y coordinate for network architecture display store in local variable the number of neurons

Definition at line 239 of file evonet.cpp.

Referenced by Evonet::configure().

void describe ( QString type )

static

Add to Factory::typeDescriptions() the descriptions of all parameters and subgroups.

Definition at line 216 of file evonet.cpp.

void evonetUpdated ( )

signal

emitted everytime the Evonet has been updated

Note: connect this signal to all necessary slots for updating the graphics stuff

float * getOldestStoredActivations ( )

Returns the oldest stored activation vector and removes it.

This returns the oldest activation vector and deletes it (memory is not freed, simply an internal index is incremented), so that subsequent calls will progressively return newer activation vectors. Returns NULL when no activation vector is stored