///
/// <summary> * Signify that this batch of input to the filter is finished. If
/// * the filter requires all instances prior to filtering, output()
/// * may now be called to retrieve the filtered instances. Any
/// * subsequent instances filtered should be filtered based on setting
/// * obtained from the first batch (unless the inputFormat has been
/// * re-assigned or new options have been set). This default
/// * implementation assumes all instance processing occurs during
/// * inputFormat() and input().
/// * </summary>
/// * <returns> true if there are instances pending output </returns>
/// * <exception cref="NullPointerException"> if no input structure has been defined, </exception>
/// * <exception cref="Exception"> if there was a problem finishing the batch. </exception>
///
public override bool batchFinished()
{
if (getInputFormat() == null)
{
throw new java.lang.IllegalStateException("No input instance format defined");
}
// throw if all attributes are not numeric
Instances instances = getInputFormat();
if (instances.numInstances() < getNumCoeffs())
{
throw new java.lang.IllegalStateException("Number of coeffs cannot be greater " + "than the total number of instances");
}
m_attsFT = new AttFTHolder [instances.numAttributes()];
int nearestPower2;
for (int attr = 0; attr < instances.numAttributes(); ++attr)
{
m_attsFT[attr] = new AttFTHolder();
double[] array = instances.attributeToDoubleArray(attr);
// get the nearest power of 2 for the FT
for (nearestPower2 = 1; array.Length > nearestPower2; nearestPower2 <<= 1)
{
;
}
// initialize the complex numbers
m_attsFT[attr].re = new double[nearestPower2];
m_attsFT[attr].im = new double[nearestPower2];
int j = 0;
for (int i=0; i<nearestPower2; ++i, ++j)
{
m_attsFT[attr].re[i] = (j < array.Length) ? array[i] : 0;
m_attsFT[attr].im[i] = 0;
}
// inplace FT
if (m_useFFT)
{
computeFFT(m_attsFT[attr].re, m_attsFT[attr].im);
}
else
{
computeDFT(m_attsFT[attr].re, m_attsFT[attr].im);
}
}
// set instances of the new dataset
for (int i=0; i<getNumCoeffs(); ++i)
{
double[] vals = new double[instances.numAttributes() * 2];
for (int j=0; j<instances.numAttributes(); ++j)
{
vals[2*j] = m_attsFT[j].re[i];
vals[2*j+1] = m_attsFT[j].im[i];
}
Instance inst = new weka.core.DenseInstance(instances.instance(i).weight(), vals);
// Modified
//inst.setDataset(instances.instance(i).dataset());
push(inst);
}
flushInput();
m_NewBatch = true;
return (numPendingOutput() != 0);
}
///
/// <summary> * Signify that this batch of input to the filter is finished. If
/// * the filter requires all instances prior to filtering, output()
/// * may now be called to retrieve the filtered instances. Any
/// * subsequent instances filtered should be filtered based on setting
/// * obtained from the first batch (unless the inputFormat has been
/// * re-assigned or new options have been set). This default
/// * implementation assumes all instance processing occurs during
/// * inputFormat() and input().
/// * </summary>
/// * <returns> true if there are instances pending output </returns>
/// * <exception cref="NullPointerException"> if no input structure has been defined, </exception>
/// * <exception cref="Exception"> if there was a problem finishing the batch. </exception>
///
public override bool batchFinished()
{
if (getInputFormat() == null)
{
throw new java.lang.IllegalStateException("No input instance format defined");
}
// throw if all attributes are not numeric
Instances instances = getInputFormat();
if (instances.numInstances() < getNumCoeffs())
{
throw new java.lang.IllegalStateException("Number of coeffs cannot be greater " + "than the total number of instances");
}
m_attsFT = new AttFTHolder [instances.numAttributes()];
int nearestPower2;
for (int attr = 0; attr < instances.numAttributes(); ++attr)
{
m_attsFT[attr] = new AttFTHolder();
double[] array = instances.attributeToDoubleArray(attr);
// get the nearest power of 2 for the FT
for (nearestPower2 = 1; array.Length > nearestPower2; nearestPower2 <<= 1)
{
;
}
// initialize the complex numbers
m_attsFT[attr].re = new double[nearestPower2];
m_attsFT[attr].im = new double[nearestPower2];
int j = 0;
for (int i = 0; i < nearestPower2; ++i, ++j)
{
m_attsFT[attr].re[i] = (j < array.Length) ? array[i] : 0;
m_attsFT[attr].im[i] = 0;
}
// inplace FT
if (m_useFFT)
{
computeFFT(m_attsFT[attr].re, m_attsFT[attr].im);
}
else
{
computeDFT(m_attsFT[attr].re, m_attsFT[attr].im);
}
}
// set instances of the new dataset
for (int i = 0; i < getNumCoeffs(); ++i)
{
double[] vals = new double[instances.numAttributes() * 2];
for (int j = 0; j < instances.numAttributes(); ++j)
{
vals[2 * j] = m_attsFT[j].re[i];
vals[2 * j + 1] = m_attsFT[j].im[i];
}
Instance inst = new weka.core.DenseInstance(instances.instance(i).weight(), vals);
// Modified
//inst.setDataset(instances.instance(i).dataset());
push(inst);
}
flushInput();
m_NewBatch = true;
return(numPendingOutput() != 0);
}