[SciPy-Dev] cephes_smirnov never returns on mips/sparc/...

Yaroslav Halchenko lists@onerussian....
Fri Mar 30 11:48:03 CDT 2012


related -- what is the canonical way to trigger build scipy (out of git)
without any optimization flags for gcc?

tried

FFLAGS='-O0 -g' CXXFLAGS='-O0 -g' CFLAGS='-O0 -g' python-dbg setup.py build_ext --inplace --debug

but still getting e.g.

Fortran fix compiler: /usr/bin/gfortran -Wall -ffixed-form -fno-second-underscore -Wall -fno-second-underscore -O0 -g -O3 -funroll-loops

where it gets overriden


On Fri, 30 Mar 2012, josef.pktd@gmail.com wrote:

> On Fri, Mar 30, 2012 at 11:43 AM, Yaroslav Halchenko
> <lists@onerussian.com> wrote:
> > I have reported this issue some time ago on Debian
> > http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=653948
> > and then forgot about it until now that I ran into it again.

> > With recent scipy (including git master 0fbfdbc)

> > scipy.stats.ksone.fit

> > seems to stall (never return) on big-endian boxes and return (1.0, nan,
> > nan) on x86.  It seems that it is  working correctly with scipy
> > 0.7.2 (as it is now in Debian stable).

> > So -- is that anything known?

> No, never seen before.

> I didn't think anyone would ever fit ksone, It doesn't even have a pdf
> defined in the source. It's mainly included for Kolmogorov-Smirnov
> test.


> I don't know how to interpret gdp. Is it clear that it is
> cephes_smirnov? Do you know the values that trigger it?
> If not, you could put a print in the ksone_gen._cdf to see where it
> gets stuck. (it might print a lot)

> I think it's a bug for scipy.stats that ksone doesn't define the
> support boundary .b, it looks like it should be (0,1) (default a=0
> looks ok.)
> There will be lots of nans during fit().  I don't think the generic
> fit is smart enough to figure out non-nan or non-inf starting values
> for your dataset. (There is a ticket to avoid inf in starting values
> but it hasn't been included yet.)

> Josef


> > snippet to replicate:

> > import numpy as np
> > import scipy.stats as ss


> > d = np.array([-0.18879233,  0.15734249,  0.18695107,  0.27908787, -0.248649,
> >              -0.2171497 ,  0.12233512,  0.15126419,  0.03119282,  0.4365294 ,
> >              0.08930393, -0.23509903,  0.28231224, -0.09974875, -0.25196048,
> >              0.11102028,  0.1427649 ,  0.10176452,  0.18754054,  0.25826724,
> >              0.05988819,  0.0531668 ,  0.21906056,  0.32106729,  0.2117662 ,
> >              0.10886442,  0.09375789,  0.24583286, -0.22968366, -0.07842391,
> >              -0.31195432, -0.21271196,  0.1114243 , -0.13293002,  0.01331725,
> >              -0.04330977, -0.09485776, -0.28434547,  0.22245721, -0.18518199,
> >              -0.10943985, -0.35243174,  0.06897665, -0.03553363, -0.0701746 ,
> >              -0.06037974,  0.37670779, -0.21684405])

> > print "Fitting now"
> > print ss.ksone.fit(d)


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> > Yaroslav Halchenko                 www.ohloh.net/accounts/yarikoptic
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