Monitor (Joone API)

java.lang.Object
- org.joone.engine.Monitor

All Implemented Interfaces:

java.io.Serializable
```
public class Monitor
extends java.lang.Object
implements java.io.Serializable
```
The Monitor object is the controller of the behavior of the neural net. It controls the start/stop actions and permits to set the parameters of the net (learning rate, momentum, ecc.). Each component of the neural net (Layers and Synapses) are connected to a monitor object (the monitor can be different or the same for the all components).

See Also:
Serialized Form

Field Summary

Fields
Modifier and Type Field and Description

protected boolean backprop
Ability to switch on and off the error backpropagation method, specifically for use with RTRL

int learningMode

Fields
Modifier and Type	Field and Description
`protected boolean`	`backprop` Ability to switch on and off the error backpropagation method, specifically for use with RTRL
`int`	`learningMode`

Constructor Summary

Constructors
Constructor and Description

Monitor()
This is the default Constructor.

Constructors
Constructor and Description
`Monitor()` This is the default Constructor.

Method Summary

Methods
Modifier and Type	Method and Description
`void`	`addLearner(int i, java.lang.String learner)` Adds a new Learner to the Neural Network Usage: Monitor.addLearner(0, "org.joone.engine.BasicLearner"); Monitor.addLearner(1, "org.joone.engine.BatchLearner"); Monitor.addLearner(2, "org.joone.engine.RpropLearner");
`void`	`addNeuralNetListener(NeuralNetListener l)` adds a neural net event listener the Monitor
`void`	`addNeuralNetListener(NeuralNetListener l, boolean removable)` adds a neural net event listener to the Monitor
`java.util.TreeSet`	`check()`
`void`	`fireCicleTerminated()` Invoked when an epoch finishes
`void`	`fireErrorChanged()` Invoked when the GlobalError changes
`void`	`fireErrorPattern()`
`void`	`fireNetStarted()` Invoked when the net starts
`void`	`fireNetStopped()` Invoked when all the epochs finish
`void`	`fireNetStoppedError(java.lang.String errMsg)` Invoked when an error occurs
`int`	`getBatchSize()` Getter for the property BatchSize
`int`	`getCurrentCicle()` Returns the current epoch
`double`	`getGlobalError()` Returns the actual (R)MSE of the NN
`java.lang.String[]`	`getKeys()` Return all the keys of the parameters contained in this Monitor.
`Learner`	`getLearner()` Gets a learner for a synapse or layer.
`Learner`	`getLearner(int index)` Getter for the Learner declared at position 'index'
`protected java.util.List`	`getLearners()` Getter for property learners.
`int`	`getLearningMode()` Getter for property learningMode.
`double`	`getLearningRate()` Returns the learning rate
`double`	`getMomentum()` Returns the momentum
`int`	`getNumOfPatterns()`
`java.lang.Object`	`getParam(java.lang.String key)` Gets a custom parameter from the Monitor.
`Monitor`	`getParent()` Getter for property parent.
`int`	`getPreLearning()` Returns the initial ignored input patterns (during the training phase)
`int`	`getRun()` Needed for XML saving
`int`	`getStep()` Returns the actual elaborated pattern
`int`	`getTotCicles()` Returns the total number of epochs
`int`	`getTrainingPatterns()` Returns the number of the input training patterns
`int`	`getValidationPatterns()` Returns the number of the input validation patterns
`void`	`Go()` Deprecated.
`boolean`	`isBackprop()` See if the backprop is enabled
`boolean`	`isExporting()` Getter for property exporting.
`boolean`	`isLearning()` Returns TRUE if the net is into a learning phase
`boolean`	`isLearningCicle(int num)` Returns the phase of the net (learning or not) for the current pattern
`boolean`	`isSingleThreadMode()`
`boolean`	`isSupervised()` Getter for property supervised.
`boolean`	`isTrainingDataForValidation()` Getter for the property trainingDataForValidation, i.e.
`boolean`	`isUseRMSE()` Checks if we should use RMSE (true) or MSE false.
`boolean`	`isValidation()` Getter for property validation.
`boolean`	`nextStep()` Returns if the next pattern must be elaborated
`protected java.lang.Object`	`readResolve()`
`void`	`removeAllListeners()` Removes all the NeuralNetListeners.
`void`	`removeNeuralNetListener(NeuralNetListener l)` Removes a listener
`void`	`resetCycle()`
`void`	`runAgain()` Let continue the net.
`void`	`setBackprop(boolean backprop)` Turns backpropagation on or off
`void`	`setBatchSize(int i)` Setter for the property BatchSize
`void`	`setCurrentCicle(int newCurrentCicle)` Not used
`void`	`setExporting(boolean exporting)` Setter for property exporting.
`void`	`setGlobalError(double newGlobalError)` Sets the actual error of the NN
`void`	`setLearnerFactory(LearnerFactory aFactory)` Set learner factory.
`protected void`	`setLearners(java.util.List learners)` Setter for property learners.
`void`	`setLearning(boolean newLearning)` Sets the phase of the neural network: learning (true) or recall (false)
`void`	`setLearningMode(int learningMode)` Setter for property learningMode.
`void`	`setLearningRate(double newLearningRate)` Sets the learning rate
`void`	`setMomentum(double newMomentum)` Sets the momentum
`void`	`setParam(java.lang.String key, java.lang.Object obj)` Sets a custom parameter of the Monitor.
`void`	`setParent(Monitor parent)` Setter for property parent.
`void`	`setPreLearning(int newPreLearning)` Sets the initial ignored input patterns (during the training phase)
`void`	`setSingleThreadMode(boolean singleThreadMode)`
`void`	`setSupervised(boolean supervised)` Setter for property supervised.
`void`	`setTotCicles(int newTotCicles)` Sets the total number of epochs
`void`	`setTrainingDataForValidation(boolean aMode)` Setter for the property trainingDataForValidation.
`void`	`setTrainingPatterns(int newPatterns)` Sets the number of the input training patterns
`void`	`setUseRMSE(boolean aMode)` Uses the RMSE when set to true.
`void`	`setValidation(boolean validation)` Setter for property validation.
`void`	`setValidationPatterns(int newPatterns)` Sets the number of the input validation patterns
`void`	`Stop()` Stops the NN when running in multi-thread mode.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - learningMode
```
public int learningMode
```
  - backprop
```
protected boolean backprop
```
    Ability to switch on and off the error backpropagation method, specifically for use with RTRL
- Constructor Detail
  - Monitor
```
public Monitor()
```
    This is the default Constructor.
- Method Detail
  - addNeuralNetListener
```
public void addNeuralNetListener(NeuralNetListener l)
```
    adds a neural net event listener the Monitor
    
    Parameters:
    l - NeuralNetListener
  - addNeuralNetListener
```
public void addNeuralNetListener(NeuralNetListener l,
                        boolean removable)
```
    adds a neural net event listener to the Monitor
    
    Parameters:
    l - the new NeuralNetListener
    removable - true if the added listener can be removed by the removeAllListeners method call
  - fireCicleTerminated
```
public void fireCicleTerminated()
```
    Invoked when an epoch finishes
  - fireErrorPattern
```
public void fireErrorPattern()
```
  - fireNetStarted
```
public void fireNetStarted()
```
    Invoked when the net starts
  - fireNetStopped
```
public void fireNetStopped()
```
    Invoked when all the epochs finish
  - fireNetStoppedError
```
public void fireNetStoppedError(java.lang.String errMsg)
```
    Invoked when an error occurs
    
    Parameters:
    errMsg - the thrown error message
  - fireErrorChanged
```
public void fireErrorChanged()
```
    Invoked when the GlobalError changes
  - getCurrentCicle
```
public int getCurrentCicle()
```
    Returns the current epoch
    
    Returns:
    int
  - getGlobalError
```
public double getGlobalError()
```
    Returns the actual (R)MSE of the NN
    
    Returns:
    double
  - getLearningRate
```
public double getLearningRate()
```
    Returns the learning rate
    
    Returns:
    double
  - getMomentum
```
public double getMomentum()
```
    Returns the momentum
    
    Returns:
    double
  - getTrainingPatterns
```
public int getTrainingPatterns()
```
    Returns the number of the input training patterns
    
    Returns:
    int
  - setTrainingPatterns
```
public void setTrainingPatterns(int newPatterns)
```
    Sets the number of the input training patterns
    
    Parameters:
    newPatterns - int
  - getPreLearning
```
public int getPreLearning()
```
    Returns the initial ignored input patterns (during the training phase)
    
    Returns:
    int
  - getStep
```
public int getStep()
```
    Returns the actual elaborated pattern
    
    Returns:
    int
  - getTotCicles
```
public int getTotCicles()
```
    Returns the total number of epochs
    
    Returns:
    int
  - Go
```
@Deprecated
public void Go()
```
    Deprecated.
    
    Runs the neural net in multi-thread mode. WARNING: AVOID to invoke this method. Use instead NeuralNet.go()
    
    See Also:
    org.joone.net.NeuralNet.go()
  - isLearning
```
public boolean isLearning()
```
    Returns TRUE if the net is into a learning phase
    
    Returns:
    boolean
  - isLearningCicle
```
public boolean isLearningCicle(int num)
```
    Returns the phase of the net (learning or not) for the current pattern
    
    Parameters:
    num - the pattern requested
    
    Returns:
    boolean
  - resetCycle
```
public void resetCycle()
```
  - nextStep
```
public boolean nextStep()
```
    Returns if the next pattern must be elaborated
    
    Returns:
    boolean
  - readResolve
```
protected java.lang.Object readResolve()
```
  - removeNeuralNetListener
```
public void removeNeuralNetListener(NeuralNetListener l)
```
    Removes a listener
    
    Parameters:
    l - the listener to be removed
  - runAgain
```
public void runAgain()
```
    Let continue the net.
  - setCurrentCicle
```
public void setCurrentCicle(int newCurrentCicle)
```
    Not used
    
    Parameters:
    newCurrentCicle - int
  - setGlobalError
```
public void setGlobalError(double newGlobalError)
```
    Sets the actual error of the NN
    
    Parameters:
    newGlobalError - double
  - setLearning
```
public void setLearning(boolean newLearning)
```
    Sets the phase of the neural network: learning (true) or recall (false)
    
    Parameters:
    newLearning - boolean
  - setLearningRate
```
public void setLearningRate(double newLearningRate)
```
    Sets the learning rate
    
    Parameters:
    newLearningRate - double
  - setMomentum
```
public void setMomentum(double newMomentum)
```
    Sets the momentum
    
    Parameters:
    newMomentum - double
  - setPreLearning
```
public void setPreLearning(int newPreLearning)
```
    Sets the initial ignored input patterns (during the training phase)
    
    Parameters:
    newPreLearning - int
  - setTotCicles
```
public void setTotCicles(int newTotCicles)
```
    Sets the total number of epochs
    
    Parameters:
    newTotCicles - int
  - Stop
```
public void Stop()
```
    Stops the NN when running in multi-thread mode. WARNING: DO NOT INVOKE directly, use instead NeuralNet.stop()
    
    See Also:
    org.joone.net.NeuralNet.stop()
  - isExporting
```
public boolean isExporting()
```
    Getter for property exporting.
    
    Returns:
    Value of property exporting.
  - setExporting
```
public void setExporting(boolean exporting)
```
    Setter for property exporting.
    
    Parameters:
    exporting - New value of property exporting.
  - getRun
```
public int getRun()
```
    Needed for XML saving
  - isValidation
```
public boolean isValidation()
```
    Getter for property validation.
    
    Returns:
    Value of property validation.
  - setValidation
```
public void setValidation(boolean validation)
```
    Setter for property validation.
    
    Parameters:
    validation - New value of property validation.
  - isTrainingDataForValidation
```
public boolean isTrainingDataForValidation()
```
    Getter for the property trainingDataForValidation, i.e. should the training data be used for validation.
    
    Returns:
    true if the training data should be used, false otherwise.
  - setTrainingDataForValidation
```
public void setTrainingDataForValidation(boolean aMode)
```
    Setter for the property trainingDataForValidation.
    
    Parameters:
    aMode - true if the training data should be used for validation, false otherwise.
  - removeAllListeners
```
public void removeAllListeners()
```
    Removes all the NeuralNetListeners. Removes only the listeners marked as removable
    
    See Also:
    addNeuralNetListener
  - getParent
```
public Monitor getParent()
```
    Getter for property parent.
    
    Returns:
    Value of property parent.
  - setParent
```
public void setParent(Monitor parent)
```
    Setter for property parent.
    
    Parameters:
    parent - New value of property parent.
  - getValidationPatterns
```
public int getValidationPatterns()
```
    Returns the number of the input validation patterns
    
    Returns:
    int
  - setValidationPatterns
```
public void setValidationPatterns(int newPatterns)
```
    Sets the number of the input validation patterns
    
    Parameters:
    newPatterns - int
  - getNumOfPatterns
```
public int getNumOfPatterns()
```
  - check
```
public java.util.TreeSet check()
```
  - isSupervised
```
public boolean isSupervised()
```
    Getter for property supervised.
    
    Returns:
    Value of property supervised.
  - setSupervised
```
public void setSupervised(boolean supervised)
```
    Setter for property supervised. (default = false)
    
    Parameters:
    supervised - New value of property supervised.
  - getBatchSize
```
public int getBatchSize()
```
    Getter for the property BatchSize
    
    Returns:
    the size (# of cycles) of the batch mode
  - setBatchSize
```
public void setBatchSize(int i)
```
    Setter for the property BatchSize
    
    Parameters:
    the - size (# of cycles) of the batch mode
  - getLearningMode
```
public int getLearningMode()
```
    Getter for property learningMode. The learningMode determines the kind of learning algorithm applied to the neural network.
    
    Returns:
    Value of property learningMode.
    See Also:
    getLearners()
  - setLearningMode
```
public void setLearningMode(int learningMode)
```
    Setter for property learningMode.
    
    Parameters:
    learningMode - New value of property learningMode.
  - getLearner
```
public Learner getLearner(int index)
```
    Getter for the Learner declared at position 'index'
    
    Parameters:
    the - index of the Learner to get
    
    Returns:
    the Learner at 'index' position
    See Also:
    getLearners()
  - getLearner
```
public Learner getLearner()
```
    Gets a learner for a synapse or layer.
    
    Returns:
    a learner for a synapse or layer.
  - getLearners
```
protected java.util.List getLearners()
```
    Getter for property learners.
    
    Returns:
    Value of property learners.
  - setLearners
```
protected void setLearners(java.util.List learners)
```
    Setter for property learners. Used to set all the Learner objects used by this NN.
    
    Parameters:
    learners - New value of property learners.
  - addLearner
```
public void addLearner(int i,
              java.lang.String learner)
```
    Adds a new Learner to the Neural Network Usage: Monitor.addLearner(0, "org.joone.engine.BasicLearner"); Monitor.addLearner(1, "org.joone.engine.BatchLearner"); Monitor.addLearner(2, "org.joone.engine.RpropLearner");
    
    Parameters:
    i - the index of the new Learner
    learner - a String containing the class name of the Learner to add
  - getParam
```
public java.lang.Object getParam(java.lang.String key)
```
    Gets a custom parameter from the Monitor. The user is free to use the custom parameters as s/he wants. They are useful to store a whatever value that could be used by the nnet's components. It has been introduced to set the parameters of new added Learners.
    
    Parameters:
    key - The searched key
    
    Returns:
    The value of the parameter if found, otherwise null
  - setParam
```
public void setParam(java.lang.String key,
            java.lang.Object obj)
```
    Sets a custom parameter of the Monitor. The user is free to use the custom parameters as s/he wants. They are useful to store a whatever value that could be used by the nnet's components. It has been introduced to set the parameters of new added Learners.
    
    Parameters:
    key - The key of the param
    obj - The value of the param
  - getKeys
```
public java.lang.String[] getKeys()
```
    Return all the keys of the parameters contained in this Monitor.
    
    Returns:
    An array of Strings containing all the keys if found, otherwise null
  - setUseRMSE
```
public void setUseRMSE(boolean aMode)
```
    Uses the RMSE when set to true. Uses MSE when set to false.
    
    Parameters:
    aMode - the mode to set true for RMSE, false for MSE.
  - isUseRMSE
```
public boolean isUseRMSE()
```
    Checks if we should use RMSE (true) or MSE false.
    
    Returns:
    true if we should use RMSE, false if we should use MSE.
  - setLearnerFactory
```
public void setLearnerFactory(LearnerFactory aFactory)
```
    Set learner factory.
    
    Parameters:
    aFactory - the learner factory to set.
  - isSingleThreadMode
```
public boolean isSingleThreadMode()
```
  - setSingleThreadMode
```
public void setSingleThreadMode(boolean singleThreadMode)
```
  - isBackprop
```
public boolean isBackprop()
```
    See if the backprop is enabled
  - setBackprop
```
public void setBackprop(boolean backprop)
```
    Turns backpropagation on or off

Class Monitor

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

learningMode

backprop

Constructor Detail

Monitor

Method Detail

addNeuralNetListener

addNeuralNetListener

fireCicleTerminated

fireErrorPattern

fireNetStarted

fireNetStopped

fireNetStoppedError

fireErrorChanged

getCurrentCicle

getGlobalError

getLearningRate

getMomentum

getTrainingPatterns

setTrainingPatterns

getPreLearning

getStep

getTotCicles

Go

isLearning

isLearningCicle

resetCycle

nextStep

readResolve

removeNeuralNetListener

runAgain

setCurrentCicle

setGlobalError

setLearning

setLearningRate

setMomentum

setPreLearning

setTotCicles

Stop

isExporting

setExporting

getRun

isValidation

setValidation

isTrainingDataForValidation

setTrainingDataForValidation

removeAllListeners

getParent

setParent

getValidationPatterns

setValidationPatterns

getNumOfPatterns

check

isSupervised

setSupervised

getBatchSize

setBatchSize

getLearningMode

setLearningMode

getLearner

getLearner

getLearners

setLearners

addLearner

getParam

setParam

getKeys

setUseRMSE

isUseRMSE

setLearnerFactory

isSingleThreadMode

setSingleThreadMode

isBackprop

setBackprop