func (s ScalarSensor) Decode(bits data.Bitset) interface{} {
found := bits.Any(func(int) bool {
return true
})
return (0.5+float64(found))*s.BucketSize + s.MinValue
}
func (c *Column) LearnSequence(learnState data.Bitset) {
logEnabled := log.HtmLogger.Enabled()
if learnState.IsZero() {
// Select the learning cell, but don't increment the target.
c.learning = c.learningTarget
if logEnabled {
log.HtmLogger.Printf("\t(%d, %d)=%04d: skip learning empty sequence",
c.Index, c.learning, c.CellId(c.learning))
}
return
}
cell, sIndex, _ := c.FindBestSegment(learnState, 1, true)
if sIndex >= 0 {
if logEnabled {
log.HtmLogger.Printf("\t(%d, %d)=%04d: Will reinforce segment: %v",
c.Index, cell, c.CellId(cell), c.distal[cell].Segment(sIndex))
}
} else {
if logEnabled {
log.HtmLogger.Printf("\t(%d, %d)=%04d: Will learn a new segment.",
c.Index, c.learningTarget, c.CellId(c.learningTarget))
}
cell = c.learningTarget
c.learningTarget = (c.learningTarget + 1) % c.Height()
sIndex = -1
}
c.learning = cell
update := c.distal[cell].CreateUpdate(sIndex, learnState, 1)
if logEnabled {
log.HtmLogger.Printf("\tLearning sequence %v => (%d, %d)=%04d",
update, c.Index, cell, c.CellId(cell))
}
c.distal[cell].Apply(update, true)
}
func (c Column) FindBestSegment(state data.Bitset, minOverlap int, weak bool) (bestCell, bestSegment, bestOverlap int) {
bestCell = -1
bestSegment = -1
bestOverlap = minOverlap - 1
maxOverlap := state.NumSetBits()
for i := 0; i < c.Height(); i++ {
sIndex, sOverlap := c.distal[i].ComputeActive(state, minOverlap, weak)
if sOverlap > bestOverlap {
bestCell = i
bestSegment = sIndex
bestOverlap = sOverlap
if bestOverlap == maxOverlap {
break
}
}
}
if log.HtmLogger.Enabled() {
if bestSegment >= 0 {
s := c.distal[bestCell].Segment(bestSegment)
log.HtmLogger.Printf("\t\tFind best segment for column=%d, state=%v, minOverlap=%d, weak=%t: (%d, %d)=%04d <= %v (overlap=%d)",
c.Index, state, minOverlap, weak, c.Index, bestCell, c.CellId(bestCell),
s.Connected(), bestOverlap)
}
}
return
}
func (pm *PermanenceMap) weaken(input data.Bitset) {
for k, v := range pm.permanence {
if input.IsSet(k) {
v -= pm.config.Decrement
}
pm.Set(k, v)
}
}
func PermanenceMapFromBits(bits data.Bitset) (pm *PermanenceMap) {
pm = NewPermanenceMap(bits.Len())
bits.Foreach(func(k int) {
pm.permanence[k] = pm.config.Initial
})
if pm.config.Initial > pm.config.Threshold {
pm.synapses.Or(bits)
}
return pm
}
func (pm *PermanenceMap) narrow(input data.Bitset) {
for k, v := range pm.permanence {
if input.IsSet(k) {
v += pm.config.Increment
} else {
v -= pm.config.Decrement
}
pm.Set(k, v)
}
}
func (c *Column) ConfirmPrediction(state data.Bitset) bool {
if c.learning >= 0 && state.IsSet(c.CellId(c.learning)) {
if log.HtmLogger.Enabled() {
log.HtmLogger.Printf("\t(%d, %d)=%04d: Confirmed prediction.",
c.Index, c.learning, c.CellId(c.learning))
}
return true
}
return false
}
func (l *Region) FeedBack(output data.Bitset) *data.Bitset {
dest := data.NewBitset(l.InputLength)
output.Foreach(func(cellId int) {
col := l.columns[cellId/l.Height()]
cell := cellId % l.Height()
if !col.Distal(cell).HasActiveSegment(output, l.MinimumInputOverlap) {
// Not a predicted cell, must be active from fast-forward.
dest.Or(col.Connected())
}
})
return dest
}
func (g *DistalSegmentGroup) CreateUpdate(sIndex int, activeState data.Bitset, minSynapses int) *SegmentUpdate {
state := data.NewBitset(activeState.Len())
if sIndex >= 0 {
s := g.segments[sIndex]
state.ResetTo(s.Connected())
}
state.Or(activeState)
for num := state.NumSetBits(); num < minSynapses; num = state.NumSetBits() {
// TODO(tms): optimize.
indices := segmentRand.Perm(state.Len())[num:minSynapses]
state.Set(indices...)
}
return NewSegmentUpdate(sIndex, state)
}
func (ds *DendriteSegment) broaden(input data.Bitset, minOverlap int) (overlapCount int) {
overlapCount = input.Overlap(ds.Connected())
threshold := ds.Config().Threshold
newPermanence := ds.Config().Minimum + ds.Boost
if newPermanence > threshold {
newPermanence = threshold
}
newSynapses := input.Clone()
newSynapses.AndNot(ds.ReceptiveField())
newSynapses.Foreach(func(k int) {
v := ds.Get(k)
if v < newPermanence {
ds.Set(k, newPermanence)
}
})
ds.overlapHistory.Record(overlapCount >= minOverlap)
if avg, ok := ds.overlapHistory.Average(); ok && avg < ds.MinActivityRatio {
for k, v := range ds.permanence {
ds.Set(k, v*1.01)
}
}
return
}
func (s *PeriodicSensor) Decode(bits data.Bitset) interface{} {
found := bits.Any(func(int) bool {
return true
})
if bits.IsSet(found + 2) {
return found + 1 + s.First
} else if bits.IsSet(found + 1) {
// found is the center bit, so first.
return s.First
} else {
// found is center bit + 1, so last.
return s.Last
}
}
func (s *CategorySensor) Decode(bits data.Bitset) interface{} {
found := bits.Any(func(int) bool {
return true
})
return s.reverse[found/s.W]
}