[TriPython] Time Series Matching

[Kurt Grandis]

I'm not quite sure I follow the criteria for sameness or elimination
between the time series. Are each series independent sensor readings for
the same environment?

"Close" could mean a lot of things depending on how you're looking at the
data--what dimensions or time frames you're considering. Do you have an
idea of what the variance about each reading might be? Something so you can
model "closeness" around each point.

It sounds like you might want to explore transforming these readings into a
continuous representation maybe using the above distribution model about
each event. You can play with things like convolving the signals or using
something like lowpass filters to trim extraneous readings.

If you're looking to align the signals you can look into something like
cross-correlation. It sounds like another approach depending on how many
errant events there are is find the max cross correlation and remove the
timestamps without partners; repeat.

Not sure of the nature of the data you're dealing with, but hope something
above helps.