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Fixed SOFM U-matrix (individual distances) 

Some "diagonal" pixels were overwritten.
This commit is contained in:
Gilles 2015-09-19 14:46:56 +02:00
parent 88cee6d7b3
commit c1c1a84291
1 changed files with 63 additions and 57 deletions
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120
src/main/java/org/apache/commons/math3/ml/neuralnet/twod/util/UnifiedDistanceMatrix.java
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@ -33,12 +33,18 @@ public class UnifiedDistanceMatrix implements MapVisualization {
/** Distance. */
private final DistanceMeasure distance;
/** Simple constructor.
/**
* Simple constructor.
*
* @param individualDistances If {@code true}, the 8 individual
* inter-units distances will be {@link #computeImage(NeuronSquareMesh2D)
* computed}. They will be stored in additional pixels around each of
* the original units of the 2D-map. The value zero will be stored in the
* pixel corresponding to the location of a unit of the 2D-map.
* the original units of the 2D-map. The additional pixels that lie
* along a "diagonal" are shared by <em>two</em> pairs of units: their
* value will be set to the average distance between the units belonging
* to each of the pairs. The value zero will be stored in the pixel
* corresponding to the location of a unit of the 2D-map.
* <br>
* If {@code false}, only the average distance between a unit and all its
* neighbours will be computed (and stored in the pixel corresponding to
* that unit of the 2D-map). In that case, the number of neighbours taken
@ -79,6 +85,10 @@ public class UnifiedDistanceMatrix implements MapVisualization {
final double[][] uMatrix = new double[numRows * 2 + 1][numCols * 2 + 1];
// 1.
// Fill right and bottom slots of each unit's location with the
// distance between the current unit and each of the two neighbours,
// respectively.
for (int i = 0; i < numRows; i++) {
// Current unit's row index in result image.
final int iR = 2 * i + 1;
@ -90,42 +100,6 @@ public class UnifiedDistanceMatrix implements MapVisualization {
final double[] current = map.getNeuron(i, j).getFeatures();
Neuron neighbour;
// Top-left neighbour.
neighbour = map.getNeuron(i, j,
NeuronSquareMesh2D.HorizontalDirection.LEFT,
NeuronSquareMesh2D.VerticalDirection.UP);
if (neighbour != null) {
uMatrix[iR - 1][jR - 1] = distance.compute(current,
neighbour.getFeatures());
}
// Top-center neighbour.
neighbour = map.getNeuron(i, j,
NeuronSquareMesh2D.HorizontalDirection.CENTER,
NeuronSquareMesh2D.VerticalDirection.UP);
if (neighbour != null) {
uMatrix[iR - 1][jR] = distance.compute(current,
neighbour.getFeatures());
}
// Top-right neighbour.
neighbour = map.getNeuron(i, j,
NeuronSquareMesh2D.HorizontalDirection.RIGHT,
NeuronSquareMesh2D.VerticalDirection.UP);
if (neighbour != null) {
uMatrix[iR - 1][jR + 1] = distance.compute(current,
neighbour.getFeatures());
}
// Left neighbour.
neighbour = map.getNeuron(i, j,
NeuronSquareMesh2D.HorizontalDirection.LEFT,
NeuronSquareMesh2D.VerticalDirection.CENTER);
if (neighbour != null) {
uMatrix[iR][jR - 1] = distance.compute(current,
neighbour.getFeatures());
}
// Right neighbour.
neighbour = map.getNeuron(i, j,
NeuronSquareMesh2D.HorizontalDirection.RIGHT,
@ -135,15 +109,6 @@ public class UnifiedDistanceMatrix implements MapVisualization {
neighbour.getFeatures());
}
// Bottom-left neighbour.
neighbour = map.getNeuron(i, j,
NeuronSquareMesh2D.HorizontalDirection.LEFT,
NeuronSquareMesh2D.VerticalDirection.DOWN);
if (neighbour != null) {
uMatrix[iR + 1][jR - 1] = distance.compute(current,
neighbour.getFeatures());
}
// Bottom-center neighbour.
neighbour = map.getNeuron(i, j,
NeuronSquareMesh2D.HorizontalDirection.CENTER,
@ -152,18 +117,59 @@ public class UnifiedDistanceMatrix implements MapVisualization {
uMatrix[iR + 1][jR] = distance.compute(current,
neighbour.getFeatures());
}
// Bottom-right neighbour.
neighbour = map.getNeuron(i, j,
NeuronSquareMesh2D.HorizontalDirection.RIGHT,
NeuronSquareMesh2D.VerticalDirection.DOWN);
if (neighbour != null) {
uMatrix[iR + 1][jR + 1] = distance.compute(current,
neighbour.getFeatures());
}
}
}
// 2.
// Fill the bottom-rigth slot of each unit's location with the average
// of the distances between
// * the current unit and its bottom-right neighbour, and
// * the bottom-center neighbour and the right neighbour.
for (int i = 0; i < numRows; i++) {
// Current unit's row index in result image.
final int iR = 2 * i + 1;
for (int j = 0; j < numCols; j++) {
// Current unit's column index in result image.
final int jR = 2 * j + 1;
final Neuron current = map.getNeuron(i, j);
final Neuron right = map.getNeuron(i, j,
NeuronSquareMesh2D.HorizontalDirection.RIGHT,
NeuronSquareMesh2D.VerticalDirection.CENTER);
final Neuron bottom = map.getNeuron(i, j,
NeuronSquareMesh2D.HorizontalDirection.CENTER,
NeuronSquareMesh2D.VerticalDirection.DOWN);
final Neuron bottomRight = map.getNeuron(i, j,
NeuronSquareMesh2D.HorizontalDirection.RIGHT,
NeuronSquareMesh2D.VerticalDirection.DOWN);
final double current2BottomRight = bottomRight == null ?
0 :
distance.compute(current.getFeatures(),
bottomRight.getFeatures());
final double right2Bottom = (right == null ||
bottom == null) ?
0 :
distance.compute(right.getFeatures(),
bottom.getFeatures());
// Bottom-right slot.
uMatrix[iR + 1][jR + 1] = 0.5 * (current2BottomRight + right2Bottom);
}
}
// 3. Copy last row into first row.
final int lastRow = uMatrix.length - 1;
uMatrix[0] = uMatrix[lastRow];
// 4.
// Copy last column into first column.
final int lastCol = uMatrix[0].length - 1;
for (int r = 0; r < lastRow; r++) {
uMatrix[r][0] = uMatrix[r][lastCol];
}
return uMatrix;
}