SICALLBACK aaOcean_BeginEvaluate( ICENodeContext& in_ctxt )
{
// get ocean pointer from user-data
aaOcean *pOcean = (aaOcean *)(CValue::siPtrType)in_ctxt.GetUserData();
// get ICE node input port arrays
CDataArrayLong PointID( in_ctxt, ID_IN_PointID);
CDataArrayLong resolution( in_ctxt, ID_IN_RESOLUTION);
CDataArrayLong seed( in_ctxt, ID_IN_SEED);
CDataArrayFloat waveHeight( in_ctxt, ID_IN_WAVE_HEIGHT);
CDataArrayFloat waveSpeed( in_ctxt, ID_IN_WAVESPEED);
CDataArrayFloat chop( in_ctxt, ID_IN_CHOP);
CDataArrayFloat oceanScale( in_ctxt, ID_IN_OCEAN_SCALE );
CDataArrayFloat oceanDepth( in_ctxt, ID_IN_OCEAN_DEPTH );
CDataArrayFloat windDir( in_ctxt, ID_IN_WINDDIR );
CDataArrayFloat cutoff( in_ctxt, ID_IN_CUTOFF);
CDataArrayFloat velocity( in_ctxt, ID_IN_WINDVELOCITY);
CDataArrayLong windAlign( in_ctxt, ID_IN_WINDALIGN );
CDataArrayFloat damp( in_ctxt, ID_IN_DAMP);
CDataArrayBool enableFoam( in_ctxt, ID_IN_ENABLEFOAM);
CDataArrayFloat time( in_ctxt, ID_IN_TIME);
CDataArrayFloat loopTime( in_ctxt, ID_IN_REPEAT_TIME);
CDataArrayFloat surfaceTension( in_ctxt, ID_IN_SURFACE_TENSION);
CDataArrayFloat randWeight( in_ctxt, ID_IN_RAND_WEIGHT);
pOcean->input(resolution[0],
seed[0],
oceanScale[0],
oceanDepth[0],
surfaceTension[0],
velocity[0],
cutoff[0],
windDir[0],
windAlign[0],
damp[0],
waveSpeed[0],
waveHeight[0],
chop[0],
time[0],
loopTime[0],
enableFoam[0],
randWeight[0]);
return CStatus::OK;
}
//main teaching function
void teachNeuron(int selection, int truthTable[4][4], int statesArray[4][2], int erasAmount, int reportFreq, float bias, float eta, float threshold, int statesAmount) {
/**
* variables in function definition
*/
int i, j, wartoscOczekiwana, x0, x1 = 0, min = -2, max = 2;
float w0, w1, w2, dw0, dw1, dw2, max_err, min_err, adder, blad = 0.0;
//proper selection value
--selection;
//set first random weight
w0 = randWeight(min,max);
w1 = randWeight(min,max);
w2 = randWeight(min,max);
//diagnostic info
printf("Wylosowane wagi poczatkowe to: w0 = %2.2f, w1 = %2.2f, w2 = %2.2f\n", w0, w1, w2);
//learning process loops
//eras count
for (; i < erasAmount; i++) {
//steps count
for(; j < statesAmount; j++) {
adder = 0;
w0 = w0 + dw0;
w1 = w1 + dw1;
w2 = w2 + dw2;
x0 = statesArray[j][0];
x1 = statesArray[j][1];
wartoscOczekiwana = truthTable[selection][j];
adder = w0*bias+w1*x0+w2*x1;
blad = wartoscOczekiwana - adder;
dw0 = eta * blad * bias;
dw1 = eta * blad * x0;
dw2 = eta * blad * x1;
//check max and min error
if(blad > max_err) {
max_err = blad;
}
if(blad < min_err) {
min_err = blad;
}
//print error info
if(i%reportFreq == 0) {
printf("Zarejestrowany blad dla ostatnich %d epok to: %f\n", reportFreq, max_err-min_err);
min_err = 0;
max_err = 0;
}
}
j = 0;
}
//diagnostic info
printf("Dobrane wagi koncowe to: w0 = %2.2f, w1 = %2.2f, w2 = %2.2f\n", w0, w1, w2);
// return returnArray;
}
