The base abstract class for iterating over neurons of a neural network. More...

Inheritance diagram for NeuronsIterator:

Public Member Functions

virtual ~NeuronsIterator ()
 Destructor. More...
 
virtual double getInput ()=0
 Get the input of the current neuron. More...
 
virtual double getOutput ()=0
 Get the output of the current neuron. More...
 
virtual bool nextNeuron ()=0
 Go to the next neuron of the current block. More...
 
virtual bool setCurrentBlock (QString blockName)=0
 Set the current blocks of neurons to iterate. More...
 
virtual void setGraphicProperties (QString label, double minValue, double maxValue, QColor color)=0
 Set the graphic properties for the current neuron (in case it will be visualized on a GUI) More...
 
virtual void setInput (double value)=0
 Set the input of the current neuron. More...
 

Additional Inherited Members

- Public Types inherited from Resource
enum  ResourceChangeType
 

Detailed Description

The base abstract class for iterating over neurons of a neural network.

The neuron iterator helps on iterating the neurons of the neural network for setting/getting the input/output values of sensor/motor neurons

The NeuronsIterator allow to divide in functional blocks the neural network and give a name to such blocks.

Definition at line 56 of file neuroninterfaces.h.

Constructor & Destructor Documentation

virtual ~NeuronsIterator ( )
inlinevirtual

Destructor.

Definition at line 59 of file neuroninterfaces.h.

Member Function Documentation

virtual double getInput ( )
pure virtual

Get the input of the current neuron.

Implemented in EvonetIterator, and NeuralNetIterator.

virtual bool setCurrentBlock ( QString  blockName)
pure virtual

Set the current blocks of neurons to iterate.

You need to first call this method for iterate over neurons. This method will initialize the internal counters for iterate over neurons, and set the first current neuron. To move forward call the method nextNeuron.

Parameters
blockNameis the name given to the block
Returns
true if the current block is now the block defined with name blockName; false otherwise

Implemented in EvonetIterator, and NeuralNetIterator.

Referenced by FakeMotor::resourceChanged(), FakeSensor::resourceChanged(), ObjectPositionSensor::resourceChanged(), FakeMotor::update(), FakeSensor::update(), KheperaWheelVelocityMotor::update(), MarXbotWheelVelocityMotor::update(), EpuckWheelVelocityMotor::update(), EpuckProximityIRSensor::update(), KheperaProximityIRSensor::update(), ObjectPositionSensor::update(), MarXbotProximityIRSensor::update(), MarXbotWheelVelOrient::update(), EpuckGroundIRSensor::update(), KheperaSampledProximityIRSensor::update(), MarXbotGroundBottomIRSensor::update(), MarXbotColorMotor::update(), EpuckLinearCameraSensor::update(), MarXbotGroundAroundIRSensor::update(), KheperaSampledLightSensor::update(), MarXbotAttachmentDeviceMotor::update(), MarXbotLinearCameraSensor::update(), KheperaGroundSensor::update(), EpuckSampledProximityIRSensor::update(), KheperaWheelSpeedsSensor::update(), MarXbotLinearCameraSensorNew::update(), MarXbotTractionSensor::update(), MarXbotSampledProximityIRSensor::update(), MarXbotAttachmentDeviceSensor::update(), MarXbotWheelSpeedsSensor::update(), MarXbotLaserFrontDistanceSensor::update(), and MarXbotLaserOmniDistanceSensor::update().

virtual void setGraphicProperties ( QString  label,
double  minValue,
double  maxValue,
QColor  color 
)
pure virtual

Set the graphic properties for the current neuron (in case it will be visualized on a GUI)

Parameters
labelis the name to show on the GUI corresponding to current neuron
minValueis the min value for the current neuron (for the GUI visualizing the activation value)
maxValueis the max value for the current neuron (for the GUI visualizing the activation value)
coloris the color on which the above data will be displayed on the GUIs

Implemented in EvonetIterator, and NeuralNetIterator.

Referenced by FakeMotor::resourceChanged(), FakeSensor::resourceChanged(), and ObjectPositionSensor::resourceChanged().


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