static void adaptSegment(
Connections& connections,
Segment segment,
const vector<CellIdx>& prevActiveCells,
Permanence permanenceIncrement,
Permanence permanenceDecrement)
{
const vector<Synapse>& synapses = connections.synapsesForSegment(segment);
for (SynapseIdx i = 0; i < synapses.size();)
{
const SynapseData& synapseData = connections.dataForSynapse(synapses[i]);
const bool isActive =
std::binary_search(prevActiveCells.begin(), prevActiveCells.end(),
synapseData.presynapticCell);
Permanence permanence = synapseData.permanence;
if (isActive)
{
permanence += permanenceIncrement;
}
else
{
permanence -= permanenceDecrement;
}
permanence = min(permanence, (Permanence)1.0);
permanence = max(permanence, (Permanence)0.0);
if (permanence < EPSILON)
{
connections.destroySynapse(synapses[i]);
// Synapses vector is modified in-place, so don't update `i`.
}
else
{
connections.updateSynapsePermanence(synapses[i], permanence);
i++;
}
}
if (synapses.size() == 0)
{
connections.destroySegment(segment);
}
}
static void growSynapses(
Connections& connections,
Random& rng,
Segment segment,
UInt32 nDesiredNewSynapses,
const vector<CellIdx>& prevWinnerCells,
Permanence initialPermanence)
{
// It's possible to optimize this, swapping candidates to the end as
// they're used. But this is awkward to mimic in other
// implementations, especially because it requires iterating over
// the existing synapses in a particular order.
vector<CellIdx> candidates(prevWinnerCells.begin(), prevWinnerCells.end());
NTA_ASSERT(std::is_sorted(candidates.begin(), candidates.end()));
// Remove cells that are already synapsed on by this segment
for (Synapse synapse : connections.synapsesForSegment(segment))
{
CellIdx presynapticCell =
connections.dataForSynapse(synapse).presynapticCell;
auto ineligible = std::lower_bound(candidates.begin(), candidates.end(),
presynapticCell);
if (ineligible != candidates.end() && *ineligible == presynapticCell)
{
candidates.erase(ineligible);
}
}
const UInt32 nActual = std::min(nDesiredNewSynapses,
(UInt32)candidates.size());
// Pick nActual cells randomly.
for (UInt32 c = 0; c < nActual; c++)
{
size_t i = rng.getUInt32(candidates.size());
connections.createSynapse(segment, candidates[i], initialPermanence);
candidates.erase(candidates.begin() + i);
}
}
