//TODO Could use some templates perhaps...
bool BasicPlugin::inputsExist() const {
//First, check the inputVectors...
QStringList iv = inputVectorList();
QStringList::ConstIterator ivI = iv.begin();
for (; ivI != iv.end(); ++ivI) {
if (!inputVector(*ivI))
return false;
}
//Now, check the inputScalars...
QStringList is = inputScalarList();
QStringList::ConstIterator isI = is.begin();
for (; isI != is.end(); ++isI) {
if (!inputScalar(*isI))
return false;
}
//Finally, check the inputStrings...
QStringList istr = inputStringList();
QStringList::ConstIterator istrI = istr.begin();
for (; istrI != istr.end(); ++istrI) {
if (!inputString(*istrI))
return false;
}
return true;
}
// Remove some elements from the vector starting from vector[0]
bool Trim::algorithm() {
KstVectorPtr input = inputVector(INPUT);
KstScalarPtr remove = inputScalar(REMOVE);
KstVectorPtr cut = outputVector(CUT);
bool rc = false;
if (input->length() > remove->value()) {
int cutSize = (int)input->length() - (int)remove->value();
cut->resize( cutSize, false );
for (int j=0; j<cutSize; j++) {
cut->value()[j] = input->value()[(int)remove->value()+j];
}
rc = true;
}
return rc;
}
bool CumulativeSum::algorithm() {
KstVectorPtr inputvector = inputVector(INPUTVECTOR);
KstScalarPtr scale_factor = inputScalar(SCALE_FACTOR);
KstVectorPtr cumulative_sum = outputVector(CUMULATIVE_SUM);
/* Memory allocation */
if (cumulative_sum->length() != inputvector->length()) {
cumulative_sum->resize(inputvector->length()+1, true);
}
cumulative_sum->value()[0] = 0.0;
for (int i = 0; i < inputvector->length(); i++) {
cumulative_sum->value()[i+1] =
inputvector->value()[i]*scale_factor->value() + cumulative_sum->value()[i];
}
return true;
}
bool Differentiation::algorithm() {
KstVectorPtr inputvector = inputVector(INPUTVECTOR);
KstScalarPtr time_step = inputScalar(TIME_STEP);
KstVectorPtr derivative = outputVector(DERIVATIVE);
/* Memory allocation */
if (derivative->length() != inputvector->length()) {
derivative->resize(inputvector->length(), true);
}
derivative->value()[0] = (inputvector->value()[1] - inputvector->value()[0]) / time_step->value();
int i = 1;
for (; i < inputvector->length()-1; i++) {
derivative->value()[i] = (inputvector->value()[i+1] - inputvector->value()[i-1])/(2*time_step->value());
}
derivative->value()[i] = (inputvector->value()[i] - inputvector->value()[i-1]) / time_step->value();
return true;
}
bool NoiseAddition::algorithm() {
KstVectorPtr array = inputVector(ARRAY);
KstScalarPtr sigma = inputScalar(SIGMA);
KstVectorPtr output = outputVector(OUTPUT);
const gsl_rng_type* pGeneratorType;
gsl_rng* pRandomNumberGenerator;
double* pResult[1];
int iRetVal = false;
int iLength = array->length();
pResult[0] = 0L;
if (iLength > 0) {
if (output->length() != iLength) {
output->resize(iLength, false);
pResult[0] = (double*)realloc( output->value(), iLength * sizeof( double ) );
} else {
pResult[0] = output->value();
}
}
pGeneratorType = gsl_rng_default;
pRandomNumberGenerator = gsl_rng_alloc( pGeneratorType );
if (pRandomNumberGenerator != NULL) {
if (pResult[0] != NULL) {
for (int i=0; i<iLength; i++) {
output->value()[i] = array->value()[i] + gsl_ran_gaussian( pRandomNumberGenerator, sigma->value() );
}
iRetVal = true;
}
gsl_rng_free( pRandomNumberGenerator );
}
return iRetVal;
}
bool Phase::algorithm() {
KstVectorPtr time = inputVector(TIME);
KstVectorPtr data_i = inputVector(DATA_I);
KstScalarPtr period = inputScalar(PERIOD);
KstScalarPtr zero = inputScalar(ZERO);
KstVectorPtr phase = outputVector(PHASE);
KstVectorPtr data_o = outputVector(DATA_O);
double* pResult[2];
double dPhasePeriod = period->value();
double dPhaseZero = zero->value();
int iLength;
bool iRetVal = false;
if (dPhasePeriod > 0.0) {
if (time->length() == data_i->length()) {
iLength = time->length();
if (phase->length() != iLength) {
phase->resize(iLength, true);
pResult[0] = (double*)realloc( phase->value(), iLength * sizeof( double ) );
} else {
pResult[0] = phase->value();
}
if (data_o->length() != iLength) {
data_o->resize(iLength, true);
pResult[1] = (double*)realloc( data_o->value(), iLength * sizeof( double ) );
} else {
pResult[1] = data_o->value();
}
if (pResult[0] != NULL && pResult[1] != NULL) {
for (int i = 0; i < phase->length(); ++i) {
phase->value()[i] = pResult[0][i];
}
for (int i = 0; i < data_o->length(); ++i) {
data_o->value()[i] = pResult[1][i];
}
/*
determine the phase...
*/
for (int i=0; i<iLength; i++) {
phase->value()[i] = fmod( ( time->value()[i] - dPhaseZero ) / dPhasePeriod, 1.0 );
}
/*
sort by phase...
*/
memcpy( data_o->value(), data_i->value(), iLength * sizeof( double ) );
double* sort[2];
sort[0] = phase->value();
sort[1] = data_o->value();
quicksort( sort, 0, iLength-1 );
iRetVal = true;
}
}
}
return iRetVal;
}
