[LNT] r239138 - Fix report submission when there are failed tests.

[Kristof Beyls]

I guess that the biggest problem in switching to use numpy and scipy is
making sure all required packages are available at
http://lab.llvm.org/packages/ so the buildbots won't break?
Is it for specific functions that numpy was much slower than the current
implementation?

2015-06-05 17:54 GMT+01:00 Chris Matthews <chris.matthews at apple.com>:

> Thanks for fixing!  With that assertion I was hoping to flush out all the
> places where we pass ints and None to the stats routines.  Given the way
> the routines are written, they produce subtly wrong results in those
> cases.   I sort of want to switch them to numpy and spicy, but in some
> informal benchmarking we were much faster (10x) than numpy.  Simplicity
> seems to win out there.
>
> > On Jun 5, 2015, at 1:43 AM, James Molloy <james.molloy at arm.com> wrote:
> >
> > Author: jamesm
> > Date: Fri Jun  5 03:43:27 2015
> > New Revision: 239138
> >
> > URL: http://llvm.org/viewvc/llvm-project?rev=239138&view=rev
> > Log:
> > Fix report submission when there are failed tests.
> >
> > When tests fail, we get a .exec.status field type. This has integer
> > type, so calling the stats.* functions will now assert and the
> > import will silently fail (because the assert is caught).
> >
> > Ensure we bypass the stats.* functions when we have integer data.
> >
> > Modified:
> >    lnt/trunk/lnt/server/reporting/analysis.py
> >
> > Modified: lnt/trunk/lnt/server/reporting/analysis.py
> > URL:
> http://llvm.org/viewvc/llvm-project/lnt/trunk/lnt/server/reporting/analysis.py?rev=239138&r1=239137&r2=239138&view=diff
> >
> ==============================================================================
> > --- lnt/trunk/lnt/server/reporting/analysis.py (original)
> > +++ lnt/trunk/lnt/server/reporting/analysis.py Fri Jun  5 03:43:27 2015
> > @@ -77,7 +77,11 @@ class ComparisonResult:
> >
> >         # If we have multiple values for this run, use that to estimate
> the
> >         # distribution.
> > -        if samples and len(samples) > 1:
> > +        #
> > +        # We can get integer sample types here - for example if the
> field is
> > +        # .exec.status. Make sure we don't assert by avoiding the stats
> > +        # functions in this case.
> > +        if samples and len(samples) > 1 and isinstance(samples[0],
> float):
> >             self.stddev = stats.standard_deviation(samples)
> >             self.MAD = stats.median_absolute_deviation(samples)
> >         else:
> >
> >
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