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## org.neuroph.core
Class Layer

    java.lang.Object
      org.neuroph.core.Layer

All Implemented Interfaces:
  java.io.Serializable

Direct Known Subclasses:
  CompetitiveLayer

    public class Layer

extends java.lang.Object
implements java.io.Serializable

     Layer of neurons in a neural network. The Layer is basic neuron container (a collection of neurons),
     and it provides methods for manipulating neurons (add, remove, get, set, calculate, randomize).

See Also:
  `Neuron`, Serialized Form

Field Summary
`protected java.util.Vector<Neuron>` | `neurons` Neurons collection

Constructor Summary
`Layer()` Creates an instance of empty Layer
`Layer(int neuronsCount, NeuronProperties neuronProperties)` Creates an instance of Layer with the specified number of neurons with specified neuron properties

Method Summary
`void` | `addNeuron(int idx, Neuron neuron)` Adds specified neuron to this layer,at specified index position
`void` | `addNeuron(Neuron neuron)` Adds specified neuron to this layer
`void` | `calculate()` Performs calculaton for all neurons in this layer
`Neuron` | `getNeuronAt(int idx)` Returns neuron at specified index position in this layer
`java.util.Vector<Neuron>` | `getNeurons()` Returns collection of neurons in this layer
`int` | `getNeuronsCount()` Returns number of neurons in this layer
`java.util.Iterator<Neuron>` | `getNeuronsIterator()` Returns interface for iterating neurons in this layer
`NeuralNetwork` | `getParentNetwork()` Returns reference to parent network
`int` | `indexOf(Neuron neuron)` Returns the index position in layer for the specified neuron
`void` | `initializeWeights(double value)` Initialize connection weights for the whole layer to to specified value
`void` | `initializeWeights(double min, double max)`
`void` | `initializeWeights(java.util.Random generator)` Initialize connection weights for the whole layer using a random number generator
`void` | `randomizeWeights()` Randomize input connection weights for all neurons in this layer
`void` | `removeNeuron(Neuron neuron)` Removes neuron from layer
`void` | `removeNeuronAt(int idx)` Removes neuron at specified index position in this layer
`void` | `reset()` Resets the activation and input levels for all neurons in this layer
`void` | `setNeuron(int idx, Neuron neuron)` Sets (replace) the neuron at specified position in layer
`void` | `setParentNetwork(NeuralNetwork parent)` Sets reference on parent network

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

Field Detail

### neurons

    protected java.util.Vector<Neuron> neurons

  Neurons collection

Constructor Detail

### Layer

    public Layer()

  Creates an instance of empty Layer

### Layer

    public Layer(int neuronsCount,
                 NeuronProperties neuronProperties)

  Creates an instance of Layer with the specified number of neurons with specified neuron properties

  Parameters:
    `neuronsCount` - number of neurons in layer
    `neuronProperties` - properties of neurons in layer

Method Detail

### setParentNetwork

    public void setParentNetwork(NeuralNetwork parent)

  Sets reference on parent network

  Parameters:
    `parent` - parent network

### getParentNetwork

    public NeuralNetwork getParentNetwork()

  Returns reference to parent network

  Returns:
    reference on parent neural network

### getNeuronsIterator

    public java.util.Iterator<Neuron> getNeuronsIterator()

  Returns interface for iterating neurons in this layer

  Returns:
    interface for iterating neurons in this layer

### getNeurons

    public java.util.Vector<Neuron> getNeurons()

  Returns collection of neurons in this layer

  Returns:
    collection of neurons in this layer

### addNeuron

    public void addNeuron(Neuron neuron)

  Adds specified neuron to this layer

  Parameters:
    `neuron` - neuron to add

### addNeuron

    public void addNeuron(int idx,
                          Neuron neuron)

  Adds specified neuron to this layer,at specified index position

  Parameters:
    `neuron` - neuron to add
    `idx` - index position at which neuron should be added

### setNeuron

    public void setNeuron(int idx,
                          Neuron neuron)

  Sets (replace) the neuron at specified position in layer

  Parameters:
    `idx` - index position to set/replace
    `neuron` - new Neuron object to set

### removeNeuron

    public void removeNeuron(Neuron neuron)

  Removes neuron from layer

  Parameters:
    `neuron` - neuron to remove

### removeNeuronAt

    public void removeNeuronAt(int idx)

  Removes neuron at specified index position in this layer

  Parameters:
    `idx` - index position of neuron to remove

### getNeuronAt

    public Neuron getNeuronAt(int idx)

  Returns neuron at specified index position in this layer

  Parameters:
    `idx` - neuron index position
  Returns:
    neuron at specified index position

### indexOf

    public int indexOf(Neuron neuron)

  Returns the index position in layer for the specified neuron

  Parameters:
    `neuron` - neuron object
  Returns:
    index position of specified neuron

### getNeuronsCount

    public int getNeuronsCount()

  Returns number of neurons in this layer

  Returns:
    number of neurons in this layer

### calculate

    public void calculate()

  Performs calculaton for all neurons in this layer

### reset

    public void reset()

  Resets the activation and input levels for all neurons in this layer

### randomizeWeights

    public void randomizeWeights()

  Randomize input connection weights for all neurons in this layer

### initializeWeights

    public void initializeWeights(double value)

  Initialize connection weights for the whole layer to to specified value

  Parameters:
    `value` - the weight value

### initializeWeights

    public void initializeWeights(java.util.Random generator)

  Initialize connection weights for the whole layer using a random number generator

  Parameters:
    `generator` - the random number generator

### initializeWeights

    public void initializeWeights(double min,
                                  double max)

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