/// <summary>
/// This is a function for analyze one layer for root cause, we select one dimension with values who contributes the most to the anomaly.
/// </summary>
private RootCause AnalyzeOneLayer(RootCauseLocalizationInput src)
{
RootCause dst = new RootCause();
dst.Items = new List <RootCauseItem>();
DimensionInfo dimensionInfo = SeparateDimension(src.AnomalyDimension, src.AggregateSymbol);
Tuple <PointTree, PointTree, Dictionary <Dictionary <string, object>, TimeSeriesPoint> > pointInfo = GetPointsInfo(src, dimensionInfo);
PointTree pointTree = pointInfo.Item1;
PointTree anomalyTree = pointInfo.Item2;
Dictionary <Dictionary <string, Object>, TimeSeriesPoint> dimPointMapping = pointInfo.Item3;
//which means there is no anomaly point with the anomaly dimension or no point under anomaly dimension
if (anomalyTree.ParentNode == null || dimPointMapping.Count == 0)
{
return(dst);
}
dst.Items.AddRange(LocalizeRootCauseByDimension(anomalyTree, pointTree, src.AnomalyDimension, dimensionInfo.AggDims));
GetRootCauseDirectionAndScore(dimPointMapping, src.AnomalyDimension, dst, _beta, pointTree, src.AggregateType, src.AggregateSymbol);
return(dst);
}
private void GetRootCauseDirectionAndScore(Dictionary <Dictionary <string, Object>, TimeSeriesPoint> dimPointMapping, Dictionary <string, Object> anomalyRoot, RootCause dst, double beta, PointTree pointTree, AggregateType aggType, Object aggSymbol)
{
TimeSeriesPoint anomalyPoint = GetPointByDimension(dimPointMapping, anomalyRoot, pointTree, aggType, aggSymbol);
if (dst.Items.Count > 1)
{
//get surprise value and explanatory power value
List <RootCauseScore> scoreList = new List <RootCauseScore>();
foreach (RootCauseItem item in dst.Items)
{
TimeSeriesPoint rootCausePoint = GetPointByDimension(dimPointMapping, item.Dimension, pointTree, aggType, aggSymbol);
if (anomalyPoint != null && rootCausePoint != null)
{
Tuple <double, double> scores = GetSurpriseAndExplanatoryScore(rootCausePoint, anomalyPoint);
scoreList.Add(new RootCauseScore(scores.Item1, scores.Item2));
item.Direction = GetRootCauseDirection(rootCausePoint);
}
}
//get final score
for (int i = 0; i < scoreList.Count; i++)
{
if (aggType.Equals(AggregateType.Max) || aggType.Equals(AggregateType.Min))
{
dst.Items[i].Score = 1;
}
else
{
dst.Items[i].Score = GetFinalScore(scoreList[i].Surprise, Math.Abs(scoreList[i].ExplanatoryScore), beta);
}
}
}
else if (dst.Items.Count == 1)
{
TimeSeriesPoint rootCausePoint = GetPointByDimension(dimPointMapping, dst.Items[0].Dimension, pointTree, aggType, aggSymbol);
if (anomalyPoint != null && rootCausePoint != null)
{
Tuple <double, double> scores = GetSurpriseAndExplanatoryScore(rootCausePoint, anomalyPoint);
if (aggType.Equals(AggregateType.Max) || aggType.Equals(AggregateType.Min))
{
dst.Items[0].Score = 1;
}
else
{
dst.Items[0].Score = GetFinalScore(scores.Item1, scores.Item2, beta);
}
dst.Items[0].Direction = GetRootCauseDirection(rootCausePoint);
}
}
}
private void LocalizeRootCausesByDimension(PointTree anomalyTree, PointTree pointTree, Dictionary <string, Object> anomalyDimension, List <string> aggDims)
{
IEnumerable <BestDimension> best;
if (anomalyTree.ChildrenNodes.Count == 0)
{
//has no children node information, should use the leaves node (whose point has no aggregated dimensions) information
best = SelectOrderedDimension(pointTree.Leaves, anomalyTree.Leaves, aggDims);
}
else
{
//has no leaves information, should calculate the entropy information according to the children nodes
best = SelectOrderedDimensions(pointTree.ChildrenNodes, anomalyTree.ChildrenNodes, aggDims);
}
if (best == null)
{
_preparedCauses.Add(new RootCause {
Items = new List <RootCauseItem>()
{
new RootCauseItem(anomalyDimension)
}
});
}
bool rootAsAnomaly = false;
foreach (var dimension in best)
{
RootCause rootCause = new RootCause {
Items = new List <RootCauseItem>()
};
rootCause.GainRatio = dimension.GainRatio;
List <TimeSeriesPoint> children = null;
if (anomalyTree.ChildrenNodes.ContainsKey(dimension.DimensionKey))
{
//Use children node information to get top anomalies
children = GetTopAnomaly(anomalyTree.ChildrenNodes[dimension.DimensionKey], anomalyTree.ParentNode, pointTree.ChildrenNodes[dimension.DimensionKey].Count > 0 ? pointTree.ChildrenNodes[dimension.DimensionKey] : pointTree.Leaves, dimension.DimensionKey, !(pointTree.ChildrenNodes[dimension.DimensionKey].Count > 0));
}
else
{
//Use leaves node informatin to get top anomalies
children = GetTopAnomaly(anomalyTree.Leaves, anomalyTree.ParentNode, pointTree.Leaves, dimension.DimensionKey, true);
}
if (children == null)
{
//As the cause couldn't be found, the root cause should be itself
if (!rootAsAnomaly)
{
rootAsAnomaly = true;
rootCause.Items.Add(new RootCauseItem(anomalyDimension));
}
}
else
{
rootCause.Items.AddRange(children.Select(anomaly =>
new RootCauseItem(UpdateDimensionValue(anomalyDimension, dimension.DimensionKey, anomaly.Dimension[dimension.DimensionKey]), new List <string>()
{
dimension.DimensionKey
})));
}
_preparedCauses.Add(rootCause);
}
}
