Compute timeseries standard deviation with synthetic timeseries Hello,I’m looking to compute the standard deviation of a timeseries on the fly with synthetic timeseries.I expected to use this pseudocode formula : sqrt(avg(pow(TS{externalid}-avg(TS{externalid}),2))) with endpoint :client.time_series.data.synthetic.query( expressions=expression, start="2w-ago", end="now")Unfortunately, avg expect at least 2 inputs, I try to switch to aggregate feature but I found it available only for timeseries, not synthetic timeseries.expression = '''sqrt( avg( pow( ts{ID} - ts{ID, aggregate="average", granularity="14d"}, 2 ) ))'''Do you have any tips or workaround to compute this value when “start” value changes ? Dont hesitate to explain I'm open to any opportunity to calculate this metric usi