Calculating anomaly score for multivariate data set.

[Lingaselvan]

I have been using Luminol to calculate anomaly scores for a univariate data sets(Timestamp & Value) and getting good results. Now, I want to move into multivariate data sets(Timestamp & Value 1 & Value 2 & .... & Value N) and detect a single anomaly score based upon all values. I finding hard on how to proceed with this problem statement. Is there a way I can apply Luminol to this problem or could you suggest me a way on how to proceed?

Thank you.

[lionsq]

I don't think Luminol support multivariate. I have checked the data structure of TimeSeries supported by this module.

In the initialization code of the TimeSeries class, it is defined as follows.
def init(self, series):
self.timestamps = []
self.values = []
.....
self.values.append(float(series[ts]))
clearly the values is only an array with uni-variate time series