void ConvertStatetoVect(MexVector<uint32_t> &SeedState){
if (SeedState.size() != 4)
SeedState.resize(4);
SeedState[0] = w;
SeedState[1] = x;
SeedState[2] = y;
SeedState[3] = z;
}
void ConvertVecttoState(const MexVector<uint32_t> &SeedState) {
this->w = (SeedState.size() > 0) ?
SeedState[0] : (uint32_t)chrono::system_clock::now().time_since_epoch().count();
this->x = (SeedState.size() > 1) ?
SeedState[1] : (uint32_t)chrono::system_clock::now().time_since_epoch().count();
this->y = (SeedState.size() > 2) ?
SeedState[2] : (uint32_t)chrono::system_clock::now().time_since_epoch().count();
this->z = (SeedState.size() > 3) ?
SeedState[3] : (uint32_t)chrono::system_clock::now().time_since_epoch().count();
}
void ConvertStatetoVect(const MexVector<uint32_t> &SeedState){
if (SeedState.size() != 4)
throw ExOps::EXCEPTION_CONST_MOD;
SeedState[0] = w;
SeedState[1] = x;
SeedState[2] = y;
SeedState[3] = z;
}
InternalVars(InputArgs &IArgs) :
N (IArgs.a.size()),
M (IArgs.NStart.size()),
i (0),
Time (IArgs.InitialState.Time),
nSteps (onemsbyTstep*NoOfms),
NoOfSpikes (0),
CurrentQIndex (IArgs.InitialState.CurrentQIndex),
OutputControl (IArgs.OutputControl),
OutputControlString (IArgs.OutputControlString),
StorageStepSize (IArgs.StorageStepSize),
StatusDisplayInterval (IArgs.StatusDisplayInterval),
Network (N),
Neurons (M),
InterestingSyns (IArgs.InterestingSyns),
V (IArgs.InitialState.V),
U (IArgs.InitialState.U),
Iin1(N), // Iin is defined separately as an atomic vect.
Iin2(N),
WeightDeriv (IArgs.InitialState.WeightDeriv),
IextInterface (),
SpikeQueue (),
LSTNeuron (IArgs.InitialState.LSTNeuron),
LSTSyn (IArgs.InitialState.LSTSyn),
AuxArray (M),
PreSynNeuronSectionBeg (N, -1),
PreSynNeuronSectionEnd (N, -1),
PostSynNeuronSectionBeg (N, -1),
PostSynNeuronSectionEnd (N, -1),
BinningBuffer (CacheBuffering*onemsbyTstep*DelayRange / 4),
BufferInsertIndex (onemsbyTstep*DelayRange, 0),
AddressOffset (onemsbyTstep*DelayRange, 0),
onemsbyTstep (IArgs.onemsbyTstep),
NoOfms (IArgs.NoOfms),
DelayRange (IArgs.DelayRange),
CacheBuffering (128),
I0 (IArgs.I0),
CurrentDecayFactor1(IArgs.CurrentDecayFactor1),
CurrentDecayFactor2(IArgs.CurrentDecayFactor2){
// Setting up Network and Neurons
Network.resize(M);
MexTransform(IArgs.NStart.begin(), IArgs.NStart.end(), Network.begin(), FFL([ ](Synapse &Syn, int &NStart)->void{Syn.NStart = NStart ; }));
MexTransform(IArgs.NEnd .begin(), IArgs.NEnd .end(), Network.begin(), FFL([ ](Synapse &Syn, int &NEnd )->void{Syn.NEnd = NEnd ; }));
MexTransform(IArgs.Weight.begin(), IArgs.Weight.end(), Network.begin(), FFL([ ](Synapse &Syn, float &Weight)->void{Syn.Weight = Weight ; }));
MexTransform(IArgs.Delay .begin(), IArgs.Delay .end(), Network.begin(), FFL([&](Synapse &Syn, float &Delay )->void{Syn.DelayinTsteps = Delay*IArgs.onemsbyTstep + 0.5f; }));
Neurons.resize(N);
MexTransform(IArgs.a.begin(), IArgs.a.end(), Neurons.begin(), FFL([](Neuron &Neu, float &a)->void{Neu.a = a; }));
MexTransform(IArgs.b.begin(), IArgs.b.end(), Neurons.begin(), FFL([](Neuron &Neu, float &b)->void{Neu.b = b; }));
MexTransform(IArgs.c.begin(), IArgs.c.end(), Neurons.begin(), FFL([](Neuron &Neu, float &c)->void{Neu.c = c; }));
MexTransform(IArgs.d.begin(), IArgs.d.end(), Neurons.begin(), FFL([](Neuron &Neu, float &d)->void{Neu.d = d; }));
// Setting Initial Conditions of V and U
if (U.istrulyempty()){
U.resize(N);
for (int j = 0; j<N; ++j)
U[j] = Neurons[j].b*(Neurons[j].b - 5.0f - sqrt((5.0f - Neurons[j].b)*(5.0f - Neurons[j].b) - 22.4f)) / 0.08f;
}
else if (U.size() != N){
// GIVE ERROR MESSAGE HERE
return;
}
if (V.istrulyempty()){
V.resize(N);
for (int j = 0; j<N; ++j){
V[j] = (Neurons[j].b - 5.0f - sqrt((5.0f - Neurons[j].b)*(5.0f - Neurons[j].b) - 22.4f)) / 0.08f;
}
}
else if (V.size() != N){
// GIVE ERROR MESSAGE HEREx
return;
}
// Setting Initial Conditions for INTERNAL CURRENT 1
if (IArgs.InitialState.Iin1.size() == N){
for (int j = 0; j < N; ++j){
Iin1[j] = (long long int)(IArgs.InitialState.Iin1[j] * (1i64 << 32));
}
}
else if (IArgs.InitialState.Iin1.size()){
// GIVE ERROR MESSAGE HERE
return;
}
//else{
// Iin1 is already initialized to zero by tbb::zero_allocator<long long>
//}
// Setting Initial Conditions for INTERNAL CURRENT 2
if (IArgs.InitialState.Iin2.size() == N){
for (int j = 0; j < N; ++j){
Iin2[j] = (long long int)(IArgs.InitialState.Iin2[j] * (1i64 << 32));
}
}
else if (IArgs.InitialState.Iin2.size()){
// GIVE ERROR MESSAGE HERE
return;
}
//else{
// Iin2 is already initialized to zero by tbb::zero_allocator<long long>
//}
// Setting Initial Conditions for Weight Derivative
if (WeightDeriv.istrulyempty()){
WeightDeriv.resize(M, 0.0f);
}
else if (WeightDeriv.size() != M){
// Return Exception
return;
}
// Initializing InternalVars for IextInternal giving it
// 1. The IExtInterface::InternalVarsStruct in InternalVars
// 2. The IExtInterface::InputVarsStruct in InputVars
// 3. The IExtInterface::SingleStateStruct (Initial State) in InputVars
// 4. InputVars itself to take parameters such as N, onemsbyTstep,
// Noofms etc.
IExtInterface::initInternalVariables(
IextInterface,
IArgs.IextInterface,
IArgs.InitialState.IextInterface,
IArgs
);
// Setting Initial Conditions of SpikeQueue
if (IArgs.InitialState.SpikeQueue.istrulyempty()){
SpikeQueue = MexVector<MexVector<int> >(onemsbyTstep * DelayRange, MexVector<int>());
}
else if (IArgs.InitialState.SpikeQueue.depth() == 1 && IArgs.InitialState.SpikeQueue.LevelSize(0) == onemsbyTstep*DelayRange) {
IArgs.InitialState.SpikeQueue.getVectTree(SpikeQueue);
}
else {
//GIVE ERROR MESSAGE HERE
return;
}
// Setting Initial Conditions for LSTs
if (LSTNeuron.istrulyempty()){
LSTNeuron = MexVector<int>(N, -1);
}
else if (LSTNeuron.size() != N){
//GIVE ERROR MESSAGE HERE
return;
}
if (LSTSyn.istrulyempty()){
LSTSyn = MexVector<int>(M, -1);
}
else if (LSTSyn.size() != M){
//GIVE ERROR MESSAGE HERE
return;
}
}