public override void pushAwayFrom(List <double> otherPositions, MersenneTwister rng)
{
// If min and max are the same, nothing to do
if (this.max == this.min)
{
return;
}
// How many potential other positions to evaluate?
int numPositions = otherPositions.Count * 4;
if (numPositions == 0)
{
return;
}
// Assign a weight to each potential position based on how close it is
// to other particles.
stepSize = (double)(this.max - this.min) / numPositions;
double[] positions = ArrayUtils.Arrange(this.min, this.max + stepSize.Value, stepSize.Value);
// Get rid of duplicates.
numPositions = positions.Length;
double[] weights = new double[numPositions];
// Assign a weight to each potential position, based on a gaussian falloff
// from each existing variable. The weight of a variable to each potential
// position is given as:
// e ^ -(dist^2/stepSize^2)
double maxDistanceSq = -1 * Math.Pow(stepSize.Value, 2);
foreach (var pos in otherPositions)
{
var distances = ArrayUtils.Sub(positions, pos);// pos - positions;
var varWeights = distances.Select(d => Math.Exp(Math.Pow(d, 2) / maxDistanceSq)).ToArray();
//var varWeights = Math.Exp(Math.Pow(distances, 2) / maxDistanceSq);
weights = ArrayUtils.Add(weights, varWeights);
}
// Put this particle at the position with smallest weight.
int positionIdx = ArrayUtils.Argmin(weights);
this._position = positions[positionIdx];
// Set its best position to this.
this._bestPosition = this.getPosition();
// Give it a random direction.
this._velocity *= rng.Choice(new[] { 1, -1 });
}
/**
* Return the internal topDownMapping matrix used for handling the
* bucketInfo() and topDownCompute() methods. This is a matrix, one row per
* category (bucket) where each row contains the encoded output for that
* category.
*
* @param c the connections memory
* @return the internal topDownMapping
*/
public SparseObjectMatrix <int[]> GetTopDownMapping()
{
if (base.topDownMapping == null)
{
//The input scalar value corresponding to each possible output encoding
if (IsPeriodic())
{
SetTopDownValues(
ArrayUtils.Arrange(GetMinVal() + GetResolution() / 2.0,
GetMaxVal(), GetResolution()));
}
else
{
//Number of values is (max-min)/resolutions
SetTopDownValues(
ArrayUtils.Arrange(GetMinVal(), GetMaxVal() + GetResolution() / 2.0,
GetResolution()));
}
}
//Each row represents an encoded output pattern
int numCategories = GetTopDownValues().Length;
SparseObjectMatrix <int[]> topDownMapping;
SetTopDownMapping(
topDownMapping = new SparseObjectMatrix <int[]>(
new int[] { numCategories }));
double[] topDownValues = GetTopDownValues();
int[] outputSpace = new int[GetN()];
double minVal = GetMinVal();
double maxVal = GetMaxVal();
for (int i = 0; i < numCategories; i++)
{
double value = topDownValues[i];
value = Math.Max(value, minVal);
value = Math.Min(value, maxVal);
EncodeIntoArray(value, outputSpace);
topDownMapping.Set(i, Arrays.CopyOf(outputSpace, outputSpace.Length));
}
return(topDownMapping);
}
