126_windowSize = windowSize;

84if (end < _windowSize) 91ue = _windowSize - 1; 92ve = end - _windowSize + 1; 104public int WindowSize { get { return _windowSize; } } 127_k = _seriesLength - _windowSize + 1; 128_shouldFftUsed = _windowSize * _k > (3 + 3 * Math.Log(_seriesLength)) * _seriesLength; 148_inputRe[_windowSize + i] = _data[i]; 174_inputRe[_windowSize + i] = _data[i]; 192_ectx.Assert(Utils.Size(cov) >= _windowSize * _windowSize); 205for (i = 1; i < _windowSize; ++i) 209cov[i * _windowSize + j] = cov[j * _windowSize + i]; 212for (j = i; j < _windowSize; ++j) 213cov[i * _windowSize + j] = (float)((double)cov[(i - 1) * _windowSize + j - 1] - (double)_data[i - 1] * _data[j - 1] + (double)_data[i + _k - 1] * _data[j + _k - 1]); 225Single[] covariance = new Single[_windowSize * _windowSize]; 228singularValues = new Single[_windowSize]; 229leftSingularvectors = new Single[_windowSize * _windowSize]; 236EigenUtils.MklSymmetricEigenDecomposition(covariance, _windowSize, out sVal, out sVec); 238var ind = new int[_windowSize]; 241for (i = 0; i < _windowSize; ++i) 245for (i = 0; i < _windowSize; ++i) 248Array.Copy(sVec, _windowSize * ind[i], leftSingularvectors, _windowSize * i, _windowSize); 267_ectx.Assert(Utils.Size(result) >= _windowSize + dstIndex); 272for (j = 0; j < _windowSize; ++j) 297_ectx.Assert(Utils.Size(result) >= _windowSize + dstIndex); 332for (i = 0; i < _windowSize; ++i) 337for (i = 0; i < _windowSize; ++i) 370_ectx.Assert(Utils.Size(vector) >= _windowSize + srcIndex); 380for (i = 0; i < _windowSize; ++i) 400_ectx.Assert(Utils.Size(vector) >= _windowSize + srcIndex); 437result[i + dstIndex] += RoundUpToReal(_outputRe[_windowSize - 1 + i], _outputIm[_windowSize - 1 + i]); 442result[i + dstIndex] = RoundUpToReal(_outputRe[_windowSize - 1 + i], _outputIm[_windowSize - 1 + i]); 489_ectx.Assert(0 <= ue && ue < _windowSize); 501_ectx.Assert(Utils.Size(u) >= _windowSize + uIndex); 562_ectx.Assert(0 <= ue && ue < _windowSize); 572_ectx.Assert(Utils.Size(u) >= _windowSize + uIndex);