27 references to

Microsoft.ML.Core (1)

Utilities\FixedSizeQueue.cs (1)

145q.AddLast(this[index]);

Microsoft.ML.TimeSeries (24)

AdaptiveSingularSpectrumSequenceModeler.cs (8)

192public Single LastValue { get { return _buffer.Count > 0 ? _buffer[_buffer.Count - 1] : Single.NaN; } } 709temp += alpha[n] * window[n]; 804temp += alpha[n] * window[n]; 1135_x[i - len + _windowSize - 1] = _buffer[i]; 1176if (!Single.IsNaN(data[i])) 1177dataArray[count++] = data[i]; 1384_x[i - len + _windowSize] = _buffer[i]; 1464temp += _alpha[j] * lastCol[j];

MovingAverageTransform.cs (5)

135if (Single.IsNaN(others[i])) 138sumValues += others[i]; 164if (!Single.IsNaN(others[i])) 167sumValues += weights[i] * others[i]; 206var newValue = lag == 0 ? input : others[others.Count - lag];

PercentileThresholdTransform.cs (3)

116if (!Single.IsNaN(others[i])) 118greaterVals += (others[i] > theValue) ? 1 : 0; 119equalVals += (others[i] == theValue) ? 1 : 0;

SequentialAnomalyDetectionTransformBase.cs (2)

490diff = rawScore - RawScoreBuffer[i]; 500diff = RawScoreBuffer[0] - RawScoreBuffer[i];

SlidingWindowTransformBase.cs (2)

162result.Values[i] = windowedBuffer[i]; 168result.Values[i] = windowedBuffer[i];

SrCnnAnomalyDetectionBase.cs (2)

247predictArray.Add(data[i]); 253backAddArray.Add(data[i]);

TimeSeriesUtils.cs (2)

23writer.Write(queue[index]); 52writer.Write(queue[index]);

Microsoft.ML.Transforms (2)

Text\NgramUtils.cs (2)

161_ngram[i] = _queue[i]; 190_ngram[i] = _queue[k + i];