bool TRf24Radio::Set(const uint16& NodeId, const TIntPrV& ValIdValPrV) {
Notify->OnNotifyFmt(TNotifyType::ntInfo, "Calling multiple SET for node %d ...", NodeId);
bool Success = true;
const int NMsgs = ceil(double(ValIdValPrV.Len()) / double(VALS_PER_PAYLOAD));
int RemainN = ValIdValPrV.Len();
for (int MsgN = 0; MsgN < NMsgs; MsgN++) {
const int PayloadSize = TMath::Mn(RemainN, VALS_PER_PAYLOAD);
TVec<TRadioValue> ValV(PayloadSize);
for (int ValN = 0; ValN < PayloadSize; ValN++) {
const TIntPr& ValIdValPr = ValIdValPrV[MsgN*VALS_PER_PAYLOAD + ValN];
TRadioValue& RadioVal = ValV[ValN];
RadioVal.SetValId((char) ValIdValPr.Val1);
RadioVal.SetVal(ValIdValPr.Val2);
}
TMem Payload; TRadioProtocol::GenSetPayload(ValV, Payload);
Success &= Send(NodeId, REQUEST_SET, Payload);
RemainN -= VALS_PER_PAYLOAD;
}
return Success;
}
bool TRf24Radio::Set(const uint16& NodeId, const int& ValId, const int& Val) {
Notify->OnNotifyFmt(TNotifyType::ntInfo, "Calling SET for node %d, valId: %d, value %d ...", NodeId, ValId, Val);
TVec<TRadioValue> ValV(1,1);
ValV[0].SetValId((char) ValId);
ValV[0].SetVal(Val);
TMem Payload; TRadioProtocol::GenSetPayload(ValV, Payload);
return Send(NodeId, REQUEST_SET, Payload);
}
/////////////////////////////////////////////////
// Epidemiological modeling and model fitting
void TEpidemModel::RunModel(const TFltV& StartValV, const double& StartT, const double& StopT, const int& NSteps, TVec<TFltV>& OutValV) {
TFltV ValV(StartValV), dydx(StartValV.Len()), ValV2(StartValV.Len());
OutValV.Clr(false);
for (int v = 0; v < StartValV.Len(); v++) {
OutValV.Add();
OutValV[v].Clr(false);
OutValV[v].Add(StartValV[v]);
}
const double h = (StopT-StartT) / NSteps;
double x = StartT;
for (int k = 0; k < NSteps; k++) {
GetDerivs(x, ValV, dydx);
RungeKutta(ValV, dydx, x, h, ValV2);
for (int v = 0; v < ValV2.Len(); v++) {
double X = ValV2[v];
if (X < 0 || _isnan(X) || !_finite(X)) { X = 0; }
OutValV[v].Add(X);
}
ValV = ValV2;
x += h;
}
}
void TEpidemModel::RunEuler(const TFltV& StartValV, const double& StartT, const double& StopT, const int& NSteps, TVec<TFltV>& OutValV) {
const double h = (StopT-StartT) / NSteps;
TFltV ValV(StartValV), dydx(StartValV.Len()), ValV2(StartValV.Len());
for (int v = 0; v < StartValV.Len(); v++) {
OutValV.Add();
OutValV[v].Clr(false);
OutValV[v].Add(StartValV[v]);
}
OutValV.Add(); // x values
OutValV.Last().Add(StartT);
for (double x = StartT; x <= StopT; x += h) {
GetDerivs(x, ValV, dydx);
for (int v = 0; v < ValV.Len(); v++) {
ValV[v] += h*dydx[v];
OutValV[v].Add(ValV[v]);
}
OutValV.Last().Add(x+h);
}
for (int v = 1; v < OutValV.Len(); v++) {
IAssert(OutValV[v].Len()==OutValV[v-1].Len());
}
}
// run the model internally with 10 times greater resolution
void TEpidemModel::RunModel10(const TFltV& StartValV, const double& StartT, const double& StopT, const int& NSteps, TVec<TFltV>& OutValV) {
TFltV ValV(StartValV), dydx(StartValV.Len()), ValV2(StartValV.Len());
OutValV.Clr(false);
for (int v = 0; v < StartValV.Len(); v++) {
OutValV.Add();
OutValV[v].Clr(false);
OutValV[v].Add(StartValV[v]);
}
const double h = (StopT-StartT) / (10*NSteps);
double x = StartT;
for (int k = 0; k < 10*NSteps; k++) {
GetDerivs(x, ValV, dydx);
RungeKutta(ValV, dydx, x, h, ValV2);
// take values at only every 10th step
if (k % 10 == 0) {
for (int v = 0; v < ValV2.Len(); v++) {
OutValV[v].Add(ValV2[v]); }
}
ValV = ValV2;
x += h;
}
}
