private void decodeSpectralData(BitStream inStream)
{
Array.Clear(data, 0, data.Length);
int maxSFB = info.getMaxSFB();
int windowGroups = info.getWindowGroupCount();
int[] offsets = info.getSWBOffsets();
int[] buf = new int[4];
int sfb, j, k, w, hcb, off, width, num;
int groupOff = 0, idx = 0;
for (int g = 0; g < windowGroups; g++)
{
int groupLen = info.getWindowGroupLength(g);
for (sfb = 0; sfb < maxSFB; sfb++, idx++)
{
hcb = sfbCB[idx];
off = groupOff + offsets[sfb];
width = offsets[sfb + 1] - offsets[sfb];
if (hcb == ZERO_HCB || hcb == INTENSITY_HCB || hcb == INTENSITY_HCB2)
{
for (w = 0; w < groupLen; w++, off += 128)
{
Array.Clear(data, off, width);
}
}
else if (hcb == NOISE_HCB)
{
//apply PNS: fill with random values
for (w = 0; w < groupLen; w++, off += 128)
{
float energy = 0;
for (k = 0; k < width; k++)
{
randomState *= 1664525 + 1013904223;
data[off + k] = randomState;
energy += data[off + k] * data[off + k];
}
float scale = (float)(scaleFactors[idx] / Math.Sqrt(energy));
for (k = 0; k < width; k++)
{
data[off + k] *= scale;
}
}
}
else
{
for (w = 0; w < groupLen; w++, off += 128)
{
num = (hcb >= FIRST_PAIR_HCB) ? 2 : 4;
for (k = 0; k < width; k += num)
{
Huffman.decodeSpectralData(inStream, hcb, buf, 0);
//inverse quantization & scaling
for (j = 0; j < num; j++)
{
data[off + k + j] = (buf[j] > 0) ? IQ_TABLE[buf[j]] : -IQ_TABLE[-buf[j]];
data[off + k + j] *= scaleFactors[idx];
}
}
}
}
}
groupOff += groupLen << 7;
}
}
