Class NeuronSquareMesh2D
java.lang.Object
org.apache.commons.math3.ml.neuralnet.twod.NeuronSquareMesh2D
- All Implemented Interfaces:
Serializable
,Iterable<Neuron>
Neural network with the topology of a two-dimensional surface.
Each neuron defines one surface element.
This network is primarily intended to represent a Self Organizing Feature Map.
This network is primarily intended to represent a Self Organizing Feature Map.
- Since:
- 3.3
- See Also:
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Nested Class Summary
Nested ClassesModifier and TypeClassDescriptionstatic enum
Horizontal (along row) direction.private static class
Serialization.static enum
Vertical (along column) direction. -
Field Summary
FieldsModifier and TypeFieldDescriptionprivate final long[][]
Mapping of the 2D coordinates (in the rectangular mesh) to the neuron identifiers (attributed by thenetwork
instance).private final SquareNeighbourhood
Neighbourhood type.private final Network
Underlying network.private final int
Number of columns.private final int
Number of rows.private static final long
Serial version IDprivate final boolean
Wrap.private final boolean
Wrap. -
Constructor Summary
ConstructorsModifierConstructorDescription(package private)
NeuronSquareMesh2D
(boolean wrapRowDim, boolean wrapColDim, SquareNeighbourhood neighbourhoodType, double[][][] featuresList) Constructor with restricted access, solely used for deserialization.private
NeuronSquareMesh2D
(boolean wrapRowDim, boolean wrapColDim, SquareNeighbourhood neighbourhoodType, Network net, long[][] idGrid) Constructor with restricted access, solely used for making adeep copy
.NeuronSquareMesh2D
(int numRows, boolean wrapRowDim, int numCols, boolean wrapColDim, SquareNeighbourhood neighbourhoodType, FeatureInitializer[] featureInit) Creates a two-dimensional network composed of square cells: Each neuron not located on the border of the mesh has four neurons linked to it. -
Method Summary
Modifier and TypeMethodDescriptioncopy()
Performs a deep copy of this instance.private void
Creates the neighbour relationships between neurons.private int[]
getLocation
(int row, int col, NeuronSquareMesh2D.HorizontalDirection alongRowDir, NeuronSquareMesh2D.VerticalDirection alongColDir) Computes the location of a neighbouring neuron.Retrieves the underlying network.getNeuron
(int i, int j) Retrieves the neuron at location(i, j)
in the map.getNeuron
(int row, int col, NeuronSquareMesh2D.HorizontalDirection alongRowDir, NeuronSquareMesh2D.VerticalDirection alongColDir) Retrieves the neuron at(location[0], location[1])
in the map.int
Gets the number of neurons in each column of this map.int
Gets the number of neurons in each row of this map.iterator()
private void
Prevents proxy bypass.private Object
Custom serialization.Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
Methods inherited from interface java.lang.Iterable
forEach, spliterator
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Field Details
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serialVersionUID
private static final long serialVersionUIDSerial version ID- See Also:
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network
Underlying network. -
numberOfRows
private final int numberOfRowsNumber of rows. -
numberOfColumns
private final int numberOfColumnsNumber of columns. -
wrapRows
private final boolean wrapRowsWrap. -
wrapColumns
private final boolean wrapColumnsWrap. -
neighbourhood
Neighbourhood type. -
identifiers
private final long[][] identifiersMapping of the 2D coordinates (in the rectangular mesh) to the neuron identifiers (attributed by thenetwork
instance).
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Constructor Details
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NeuronSquareMesh2D
NeuronSquareMesh2D(boolean wrapRowDim, boolean wrapColDim, SquareNeighbourhood neighbourhoodType, double[][][] featuresList) Constructor with restricted access, solely used for deserialization.- Parameters:
wrapRowDim
- Whether to wrap the first dimension (i.e the first and last neurons will be linked together).wrapColDim
- Whether to wrap the second dimension (i.e the first and last neurons will be linked together).neighbourhoodType
- Neighbourhood type.featuresList
- Arrays that will initialize the features sets of the network's neurons.- Throws:
NumberIsTooSmallException
- ifnumRows < 2
ornumCols < 2
.
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NeuronSquareMesh2D
public NeuronSquareMesh2D(int numRows, boolean wrapRowDim, int numCols, boolean wrapColDim, SquareNeighbourhood neighbourhoodType, FeatureInitializer[] featureInit) Creates a two-dimensional network composed of square cells: Each neuron not located on the border of the mesh has four neurons linked to it.
The links are bi-directional.
The topology of the network can also be a cylinder (if one of the dimensions is wrapped) or a torus (if both dimensions are wrapped).- Parameters:
numRows
- Number of neurons in the first dimension.wrapRowDim
- Whether to wrap the first dimension (i.e the first and last neurons will be linked together).numCols
- Number of neurons in the second dimension.wrapColDim
- Whether to wrap the second dimension (i.e the first and last neurons will be linked together).neighbourhoodType
- Neighbourhood type.featureInit
- Array of functions that will initialize the corresponding element of the features set of each newly created neuron. In particular, the size of this array defines the size of feature set.- Throws:
NumberIsTooSmallException
- ifnumRows < 2
ornumCols < 2
.
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NeuronSquareMesh2D
private NeuronSquareMesh2D(boolean wrapRowDim, boolean wrapColDim, SquareNeighbourhood neighbourhoodType, Network net, long[][] idGrid) Constructor with restricted access, solely used for making adeep copy
.- Parameters:
wrapRowDim
- Whether to wrap the first dimension (i.e the first and last neurons will be linked together).wrapColDim
- Whether to wrap the second dimension (i.e the first and last neurons will be linked together).neighbourhoodType
- Neighbourhood type.net
- Underlying network.idGrid
- Neuron identifiers.
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Method Details
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copy
Performs a deep copy of this instance. Upon return, the copied and original instances will be independent: Updating one will not affect the other.- Returns:
- a new instance with the same state as this instance.
- Since:
- 3.6
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iterator
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getNetwork
Retrieves the underlying network. A reference is returned (enabling, for example, the network to be trained). This also implies that calling methods that modify theNetwork
topology may cause this class to become inconsistent.- Returns:
- the network.
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getNumberOfRows
public int getNumberOfRows()Gets the number of neurons in each row of this map.- Returns:
- the number of rows.
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getNumberOfColumns
public int getNumberOfColumns()Gets the number of neurons in each column of this map.- Returns:
- the number of column.
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getNeuron
Retrieves the neuron at location(i, j)
in the map. The neuron at position(0, 0)
is located at the upper-left corner of the map.- Parameters:
i
- Row index.j
- Column index.- Returns:
- the neuron at
(i, j)
. - Throws:
OutOfRangeException
- ifi
orj
is out of range.- See Also:
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getNeuron
public Neuron getNeuron(int row, int col, NeuronSquareMesh2D.HorizontalDirection alongRowDir, NeuronSquareMesh2D.VerticalDirection alongColDir) Retrieves the neuron at(location[0], location[1])
in the map. The neuron at position(0, 0)
is located at the upper-left corner of the map.- Parameters:
row
- Row index.col
- Column index.alongRowDir
- Direction along the givenrow
(i.e. an offset will be added to the given column index.alongColDir
- Direction along the givencol
(i.e. an offset will be added to the given row index.- Returns:
- the neuron at the requested location, or
null
if the location is not on the map. - See Also:
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getLocation
private int[] getLocation(int row, int col, NeuronSquareMesh2D.HorizontalDirection alongRowDir, NeuronSquareMesh2D.VerticalDirection alongColDir) Computes the location of a neighbouring neuron. It will returnnull
if the resulting location is not part of the map. Position(0, 0)
is at the upper-left corner of the map.- Parameters:
row
- Row index.col
- Column index.alongRowDir
- Direction along the givenrow
(i.e. an offset will be added to the given column index.alongColDir
- Direction along the givencol
(i.e. an offset will be added to the given row index.- Returns:
- an array of length 2 containing the indices of the requested
location, or
null
if that location is not part of the map. - See Also:
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createLinks
private void createLinks()Creates the neighbour relationships between neurons. -
readObject
Prevents proxy bypass.- Parameters:
in
- Input stream.
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writeReplace
Custom serialization.- Returns:
- the proxy instance that will be actually serialized.
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