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Split out signatures from our current metrics (i.e., the "metrics" that only take one timeseries, mean, min, max, etc.)
Create a new class of metrics that first calculates the signature for primary and secondary (based on some initial grouping, event, annual, etc), and then calculates a metric on top of that. A two-step process.
The returned "metric" could be just the final metric or a dictionary that contains the signatures (A series of signatures) and the signature metric.
There is still something missing in this concept I think. We can currently do this with chained queries I think.
The text was updated successfully, but these errors were encountered:
Not sure if this is mentioned elsewhere, but we should also consider changing the different metric properties to have more explicit names i.e., input_timeseries for signature metrics and primary_input_timeseries and secondary_input_timeseries for comparative metrics because the current pattern is difficult for convey to users. We don't convey that the first value is the primary and the second the secondary, etc.
Under this issue, we want to:
There is still something missing in this concept I think. We can currently do this with chained queries I think.
The text was updated successfully, but these errors were encountered: