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From: Eric Niebler (eric_at_[hidden])
Date: 2007-07-27 01:24:40

Hugo Duncan wrote:
> Eric,
>>>> I'm not 100% sure I understand your use case. But most of the series
>>>> types and algorithms allow non-discrete sequences. That is, the offsets
>>>> can be floating point. Could that help?
>>> Yes I had seen that, but wasn't sure how it worked for sampled data. In
>>> my case I have a multiple time series with a (common) sample time that
>>> varies stochastically between 40-60ms. It wasn't clear to me that the
>>> offsets could be non-constant stride (whether integer or floating
>>> point).
>>> Even the sparse series seems to require a constant discretisation.
>> So, you have a discrete series (i.e., values at offsets), but the
>> offsets map to discretizations according to some piecewise function? Did
>> I get that right? That's interesting.
> That would be interesting indeed, but no. These are logged data that are
> being collected from a bus as they arrive. The arrival time period is not
> a constant.

OK, the time period isn't a constant, but what is it measured in?
Milliseconds? Then you can make milliseconds your discretization, and
then resample the data at a coarser discretization with the
coarse_grain() algorithm. Am I still not understanding your problem?
Perhaps it would help if you were more explicit about what data is being
pulled from the bus, exactly. Values and time? Time measured how?

I'll have to get back to you about the rest. I'm leaving tomorrow for a
long weekend.

Eric Niebler
Boost Consulting
The Astoria Seminar ==>

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