public void run() { for (int i = firstRow; i < lastRow; i++) { fftColumns.realForward(a, i * columns); } } });
public void run() { for (long i = firstRow; i < lastRow; i++) { fftColumns.realForward(a, i * columnsl); } } });
public void run() { for (int i = firstRow; i < lastRow; i++) { fftColumns.realForward(a[i]); } } });
public void run() { for (long i = firstRow; i < lastRow; i++) { fftColumns.realForward(a, i * columnsl); } } });
public void run() { for (int i = firstRow; i < lastRow; i++) { fftColumns.realForward(a[i]); } } });
public void run() { for (int i = firstRow; i < lastRow; i++) { fftColumns.realForward(a, i * columns); } } });
public double[] calculateNoiseIndicator() { double[] output = new double[6]; lock.lock(); int startingIndex = (circularBufferIndex + 1 ) % numSamples; for (int s=0; s<numSamples; s++ ) { System.arraycopy( data[s] , 0, tempData[s], 0, 6); } lock.unlock(); for (int i=0; i<6; i++ ) { for (int s=0; s< numSamples; s++) { orderedSamples[s] = (float)tempData[ (s + startingIndex ) % numSamples ][i]; } fftCalculator.realForward( orderedSamples ); output[i] = 0; // note: this number has no physical meaning, it is just a rough amount of "noise". for (int s = 1; s < numSamples* 0.75/ 2.0; s++ ) { output[i] += Math.abs( orderedSamples[s*2] ); // + Math.abs( orderedSamples[s*2+1] ); } } return output; }
public void run() { if (icr == 0) { if (isgn == -1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexForward(a[r]); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexInverse(a[r], scale); } } } else if (isgn == 1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.realForward(a[r]); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.realInverse(a[r], scale); } } } });
public void run() { if (icr == 0) { if (isgn == -1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexForward(a, r * columns); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexInverse(a, r * columns, scale); } } } else if (isgn == 1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.realForward(a, r * columns); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.realInverse(a, r * columns, scale); } } } });
public void run() { if (icr == 0) { if (isgn == -1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexForward(a, r * columns); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexInverse(a, r * columns, scale); } } } else if (isgn == 1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.realForward(a, r * columns); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.realInverse(a, r * columns, scale); } } } });
public void run() { if (icr == 0) { if (isgn == -1) { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.complexForward(a, r * columnsl); } } else { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.complexInverse(a, r * columnsl, scale); } } } else if (isgn == 1) { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.realForward(a, r * columnsl); } } else { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.realInverse(a, r * columnsl, scale); } } } });
public void run() { if (icr == 0) { if (isgn == -1) { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.complexForward(a, r * columnsl); } } else { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.complexInverse(a, r * columnsl, scale); } } } else if (isgn == 1) { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.realForward(a, r * columnsl); } } else { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.realInverse2(a, r * columnsl, scale); } } } });
public void run() { if (icr == 0) { if (isgn == -1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexForward(a, r * columns); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexInverse(a, r * columns, scale); } } } else if (isgn == 1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.realForward(a, r * columns); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.realInverse2(a, r * columns, scale); } } } });
public void run() { if (icr == 0) { if (isgn == -1) { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.complexForward(a, r * columnsl); } } else { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.complexInverse(a, r * columnsl, scale); } } } else if (isgn == 1) { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.realForward(a, r * columnsl); } } else { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.realInverse2(a, r * columnsl, scale); } } } });
public void run() { if (icr == 0) { if (isgn == -1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexForward(a[r]); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexInverse(a[r], scale); } } } else if (isgn == 1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.realForward(a[r]); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.realInverse(a[r], scale); } } } });
public void run() { if (icr == 0) { if (isgn == -1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexForward(a, r * columns); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexInverse(a, r * columns, scale); } } } else if (isgn == 1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.realForward(a, r * columns); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.realInverse2(a, r * columns, scale); } } } });
public void run() { if (icr == 0) { if (isgn == -1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexForward(a[r]); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexInverse(a[r], scale); } } } else if (isgn == 1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.realForward(a[r]); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.realInverse2(a[r], 0, scale); } } } });
public void run() { if (icr == 0) { if (isgn == -1) { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.complexForward(a, r * columnsl); } } else { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.complexInverse(a, r * columnsl, scale); } } } else if (isgn == 1) { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.realForward(a, r * columnsl); } } else { for (long r = n0; r < rowsl; r += nthreads) { fftColumns.realInverse(a, r * columnsl, scale); } } } });
public void run() { if (icr == 0) { if (isgn == -1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexForward(a[r]); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.complexInverse(a[r], scale); } } } else if (isgn == 1) { for (int r = n0; r < rows; r += nthreads) { fftColumns.realForward(a[r]); } } else { for (int r = n0; r < rows; r += nthreads) { fftColumns.realInverse2(a[r], 0, scale); } } } });
} else { for (int r = 0; r < rows; r++) { fftColumns.realForward(a[r]);