:-) Hi there,
Just stick to the original plan. We know you've got some fixed measurement
points, it really doesn't matter how far apart or irregular they are. You
use these points to interpolate all the values in between for the specific
'time unit' you want to represent. Look at
http://www.scipy.org/Cookbook/Interpolation for an example of using
b-splines.
Interpolation will give you a pretty good 'guesstemate' of what the usage
would have been at that point had you gone and actually measured it.
Of course if you don't want to interpolate, you can simply normalize your
measurements to your time unit. Let's assume time unit of 1 day...
Between 2007-09-13 and 2008-01-02, 3000 units were used - 3000/111 days =
27.02 units per day
Between 2008-01-02 and 2008-02-08, 1000 units were used - 1000/37 days =
27.02 units per day
Between 2008-02-08 and 2008-02-12, 100 units were used - 100/4 days = 25
units per day
This obviously has the same disadvantage as linear interpolation in that
gradual changes over unmeasured periods will be shown as constant.
Hope we're getting closer to something you can use...
Have a nice day.
cputter
On 14/03/2008, Chris Withers <[EMAIL PROTECTED]> wrote:
>
> (meant this to go to the list too)
>
>
> Christiaan Putter wrote:
> > I'm having trouble understanding what it is you exactly want.
>
>
> That's likely my fault ;-)
>
>
> > You said you want to indicate that 'the monthly usage between September
> 1st
> > and January 1st
> > was, on average, the same as that between January 1st and February 1st.'
>
>
> Yes, but "monthly" is a red herring here, the time periods are however
> long it's been since myself or the utility company checked the meter ;-)
>
>
> > The measurement your taking is not in fact the utility usage for one
> month,
> > but rather the sum of all usage over all prior months.
>
>
> Not really, and this was definitely me being unclear...
> We're talking about utility meters here, so you go and look at them and
> they show how many units of whatever it is (water, electicity, etc) they
> have delivered.
>
> So, that's how you get the time series (with more variation, to show
> reality, and avoid red herrings like "month"):
>
> 2007/09/13 - 5000
> 2008/01/02 - 8000
> 2008/02/08 - 9000
> 2008/02/12 - 9100
>
> So, the differences tell us:
>
> Between 2007-09-13 and 2008-01-02, 3000 units were used
> Between 2007-01-02 and 2008-02-08, 1000 units were used
> Between 2007-02-08 and 2008-02-12, 100 units were used
>
> So I guess it's this data that I'm looking to visualise in such a way
> that it's apprarent how much of the utility is being per unit time.
>
> NB: The measurements aren't regular, since they often come from when a
> person turns up and reads the meter, which isn't at all regular ;-)
>
> Does that make more sense? Any ideas?
>
>
> cheers,
>
> Chris
>
> --
> Simplistix - Content Management, Zope & Python Consulting
> - http://www.simplistix.co.uk
>
>
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