/**
* Returns a randomly generated permanence value for a synapses that is to be initialized in a
* non-connected state.
*
* @return a randomly generated permanence value
*/
public static double initPermNonConnected(Connections c) {
double p = c.getSynPermConnected() * c.getRandom().nextDouble();
// Note from Python implementation on conditioning below:
// Ensure we don't have too much unnecessary precision. A full 64 bits of
// precision causes numerical stability issues across platforms and across
// implementations
p = ((int) (p * 100000)) / 100000.0d;
return p;
}
/**
* Maps a column to its input bits. This method encapsulates the topology of the region. It takes
* the index of the column as an argument and determines what are the indices of the input vector
* that are located within the column's potential pool. The return value is a list containing the
* indices of the input bits. The current implementation of the base class only supports a 1
* dimensional topology of columns with a 1 dimensional topology of inputs. To extend this class
* to support 2-D topology you will need to override this method. Examples of the expected output
* of this method: * If the potentialRadius is greater than or equal to the entire input space,
* (global visibility), then this method returns an array filled with all the indices * If the
* topology is one dimensional, and the potentialRadius is 5, this method will return an array
* containing 5 consecutive values centered on the index of the column (wrapping around if
* necessary). * If the topology is two dimensional (not implemented), and the potentialRadius is
* 5, the method should return an array containing 25 '1's, where the exact indices are to be
* determined by the mapping from 1-D index to 2-D position.
*
* @param c {@link Connections} the main memory model
* @param columnIndex The index identifying a column in the permanence, potential and connectivity
* matrices.
* @param wrapAround A boolean value indicating that boundaries should be ignored.
* @return
*/
public int[] mapPotential(Connections c, int columnIndex, boolean wrapAround) {
int index = mapColumn(c, columnIndex);
TIntArrayList indices =
getNeighborsND(c, index, c.getInputMatrix(), c.getPotentialRadius(), wrapAround);
indices.add(index);
// TODO: See https://github.com/numenta/nupic.core/issues/128
indices.sort();
int[] retVal = new int[(int) Math.round(indices.size() * c.getPotentialPct())];
return ArrayUtils.sample(indices, retVal, c.getRandom());
}
