/**
* Feeds the {@link Network with the final phrase consisting of the first
* two words of the final question "fox, eats, ...".
*
* @param network the current {@link Network} object
* @param it an {@link Iterator} over the input source file lines
* @return
*/
Term feedQuestion(Network network, String[] phrase) {
for (int i = 0; i < 2; i++) {
int[] sdr = getFingerprintSDR(phrase[i]);
network.compute(sdr);
}
int[] sdr = new int[128 * 128];
Arrays.fill(sdr, 1);
Layer<?> layer = network.lookup("Region 1").lookup("Layer 2/3");
Set<Cell> predictiveCells = layer.getConnections().getPredictiveCells();
System.out.println("predictiveCells " + predictiveCells.toString());
int[] prediction =
SDR.cellsAsColumnIndices(predictiveCells, layer.getConnections().getCellsPerColumn());
network.compute(sdr);
Set<Cell> ffActive = layer.getActiveCells();
System.out.println("activeCells " + ffActive.toString());
int[] paPrediction =
SDR.cellsAsColumnIndices(ffActive, layer.getConnections().getCellsPerColumn());
Term term = getClosestTerm(prediction);
Term paterm = getClosestTerm(paPrediction);
System.out.println(paterm.toString());
cache.put(term.getTerm(), term);
return term;
}
@Ignore
public void testPlayground() {
final int NUM_CYCLES = 600;
final int INPUT_GROUP_COUNT = 7; // Days of Week
///////////////////////////////////////
// Load a Network //
///////////////////////////////////////
Network network = getLoadedDayOfWeekNetwork();
int cellsPerCol = (int) network.getParameters().get(KEY.CELLS_PER_COLUMN);
network
.observe()
.subscribe(
new Observer<Inference>() {
@Override
public void onCompleted() {}
@Override
public void onError(Throwable e) {
e.printStackTrace();
}
@SuppressWarnings("unused")
@Override
public void onNext(Inference inf) {
/** see {@link #createDayOfWeekInferencePrintout()} */
int cycle = dayOfWeekPrintout.apply(inf, cellsPerCol);
}
});
Publisher pub = network.getPublisher();
network.start();
int cycleCount = 0;
for (; cycleCount < NUM_CYCLES; cycleCount++) {
for (double j = 0; j < INPUT_GROUP_COUNT; j++) {
pub.onNext("" + j);
}
network.reset();
}
// Test network output
try {
Region r1 = network.lookup("r1");
r1.lookup("1").getLayerThread().join(2000);
} catch (Exception e) {
e.printStackTrace();
}
}
/**
* Feeds the {@link Network with the final phrase consisting of the first
* two words of the final question "fox, eats, ...".
*
* @param network the current {@link Network} object
* @param it an {@link Iterator} over the input source file lines
* @return
*/
Term feedQuestion(Network network, String[] phrase) {
for (int i = 0; i < 2; i++) {
int[] sdr = getFingerprintSDR(phrase[i]);
network.compute(sdr);
}
Layer<?> layer = network.lookup("Region 1").lookup("Layer 2/3");
Set<Cell> predictiveCells = layer.getPredictiveCells();
int[] prediction =
SDR.cellsAsColumnIndices(predictiveCells, layer.getConnections().getCellsPerColumn());
Term term = getClosestTerm(prediction);
cache.put(term.getTerm(), term);
return term;
}
