Emilio G. Cota <[email protected]> writes:
> On Fri, Jul 01, 2016 at 17:16:08 +0100, Alex Bennée wrote:
> (snip)
>> run 1: ret=0 (PASS), time=4.755824 (1/1)
>> run 2: ret=0 (PASS), time=4.756076 (2/2)
>> run 3: ret=0 (PASS), time=4.755916 (3/3)
>> run 4: ret=0 (PASS), time=4.755853 (4/4)
>> run 5: ret=0 (PASS), time=4.755929 (5/5)
>> Results summary:
>> 0: 5 times (100.00%), avg time 4.755920 (0.000000 deviation)
>
> (snip)
>> run 1: ret=0 (PASS), time=9.761559 (1/1)
>> run 2: ret=0 (PASS), time=9.511616 (2/2)
>> run 3: ret=0 (PASS), time=9.761713 (3/3)
>> run 4: ret=0 (PASS), time=10.262504 (4/4)
>> run 5: ret=0 (PASS), time=9.762059 (5/5)
>> Results summary:
>> 0: 5 times (100.00%), avg time 9.811890 (0.060150 deviation)
>
> This is a needless diversion, but I was explaining this stuff today
> to a student so couldn't help but notice.
>
> The computed deviations seem overly small. For instance, the corrected sample
> standard deviation ( https://en.wikipedia.org/wiki/Standard_deviation )
> (which is usually referred to as "standard deviation", or "error")
> for the last test should be 0.2742 instead of 0.06.
Hmm I was doing from memory but it should be the mean of the sum of the
squares of the deviation:
# calculate deviation
deviation = 0
for r in res:
deviation += (r.time - avg_time)**2
deviation = deviation / count
>
> How are they being computed? I tried to find the source of your script
> (in the kvm-unit-tests repo) but couldn't find it.
It's a retry script that got a little out of hand:
https://github.com/stsquad/retry
>
> Thanks,
>
> Emilio
--
Alex Bennée
