On 1 April 2010 13:38, Charles R Harris <charlesr.har...@gmail.com> wrote: > > > On Thu, Apr 1, 2010 at 8:37 AM, Charles R Harris <charlesr.har...@gmail.com> > wrote: >> >> >> On Thu, Apr 1, 2010 at 12:46 AM, Anne Archibald >> <peridot.face...@gmail.com> wrote: >>> >>> On 1 April 2010 02:24, Charles R Harris <charlesr.har...@gmail.com> >>> wrote: >>> > >>> > >>> > On Thu, Apr 1, 2010 at 12:04 AM, Anne Archibald >>> > <peridot.face...@gmail.com> >>> > wrote: >>> >> >>> >> On 1 April 2010 01:59, Charles R Harris <charlesr.har...@gmail.com> >>> >> wrote: >>> >> > >>> >> > >>> >> > On Wed, Mar 31, 2010 at 11:46 PM, Anne Archibald >>> >> > <peridot.face...@gmail.com> >>> >> > wrote: >>> >> >> >>> >> >> On 1 April 2010 01:40, Charles R Harris <charlesr.har...@gmail.com> >>> >> >> wrote: >>> >> >> > >>> >> >> > >>> >> >> > On Wed, Mar 31, 2010 at 11:25 PM, <josef.p...@gmail.com> wrote: >>> >> >> >> >>> >> >> >> On Thu, Apr 1, 2010 at 1:22 AM, <josef.p...@gmail.com> wrote: >>> >> >> >> > On Thu, Apr 1, 2010 at 1:17 AM, Charles R Harris >>> >> >> >> > <charlesr.har...@gmail.com> wrote: >>> >> >> >> >> >>> >> >> >> >> >>> >> >> >> >> On Wed, Mar 31, 2010 at 6:08 PM, <josef.p...@gmail.com> >>> >> >> >> >> wrote: >>> >> >> >> >>> >>> >> >> >> >>> On Wed, Mar 31, 2010 at 7:37 PM, Warren Weckesser >>> >> >> >> >>> <warren.weckes...@enthought.com> wrote: >>> >> >> >> >>> > T J wrote: >>> >> >> >> >>> >> On Wed, Mar 31, 2010 at 1:21 PM, Charles R Harris >>> >> >> >> >>> >> <charlesr.har...@gmail.com> wrote: >>> >> >> >> >>> >> >>> >> >> >> >>> >>> Looks like roundoff error. >>> >> >> >> >>> >>> >>> >> >> >> >>> >>> >>> >> >> >> >>> >> >>> >> >> >> >>> >> So this is "expected" behavior? >>> >> >> >> >>> >> >>> >> >> >> >>> >> In [1]: np.logaddexp2(-1.5849625007211563, >>> >> >> >> >>> >> -53.584962500721154) >>> >> >> >> >>> >> Out[1]: -1.5849625007211561 >>> >> >> >> >>> >> >>> >> >> >> >>> >> In [2]: np.logaddexp2(-0.5849625007211563, >>> >> >> >> >>> >> -53.584962500721154) >>> >> >> >> >>> >> Out[2]: nan >>> >> >> >> >>> >> >>> >> >> >> >>> > >>> >> >> >> >>> > Is any able to reproduce this? I don't get 'nan' in >>> >> >> >> >>> > either >>> >> >> >> >>> > 1.4.0 >>> >> >> >> >>> > or >>> >> >> >> >>> > 2.0.0.dev8313 (32 bit Mac OSX). In an earlier email T J >>> >> >> >> >>> > reported >>> >> >> >> >>> > using >>> >> >> >> >>> > 1.5.0.dev8106. >>> >> >> >> >>> >>> >> >> >> >>> >>> >> >> >> >>> >>> >> >> >> >>> >>> np.logaddexp2(-0.5849625007211563, -53.584962500721154) >>> >> >> >> >>> nan >>> >> >> >> >>> >>> np.logaddexp2(-1.5849625007211563, -53.584962500721154) >>> >> >> >> >>> -1.5849625007211561 >>> >> >> >> >>> >>> >> >> >> >>> >>> np.version.version >>> >> >> >> >>> '1.4.0' >>> >> >> >> >>> >>> >> >> >> >>> WindowsXP 32 >>> >> >> >> >>> >>> >> >> >> >> >>> >> >> >> >> What compiler? Mingw? >>> >> >> >> > >>> >> >> >> > yes, mingw 3.4.5. , official binaries release 1.4.0 by David >>> >> >> >> >>> >> >> >> sse2 Pentium M >>> >> >> >> >>> >> >> > >>> >> >> > Can you try the exp2/log2 functions with the problem data and see >>> >> >> > if >>> >> >> > something goes wrong? >>> >> >> >>> >> >> Works fine for me. >>> >> >> >>> >> >> If it helps clarify things, the difference between the two problem >>> >> >> input values is exactly 53 (and that's what logaddexp2 does an exp2 >>> >> >> of); so I can provide a simpler example: >>> >> >> >>> >> >> In [23]: np.logaddexp2(0, -53) >>> >> >> Out[23]: nan >>> >> >> >>> >> >> Of course, for me it fails in both orders. >>> >> >> >>> >> > >>> >> > Ah, that's progress then ;) The effective number of bits in a double >>> >> > is >>> >> > 53 >>> >> > (52 + implicit bit). That shouldn't cause problems but it sure looks >>> >> > suspicious. >>> >> >>> >> Indeed, that's what led me to the totally wrong suspicion that >>> >> denormals have something to do with the problem. More data points: >>> >> >>> >> In [38]: np.logaddexp2(63.999, 0) >>> >> Out[38]: nan >>> >> >>> >> In [39]: np.logaddexp2(64, 0) >>> >> Out[39]: 64.0 >>> >> >>> >> In [42]: np.logaddexp2(52.999, 0) >>> >> Out[42]: 52.999000000000002 >>> >> >>> >> In [43]: np.logaddexp2(53, 0) >>> >> Out[43]: nan >>> >> >>> >> It looks to me like perhaps the NaNs are appearing when the smaller >>> >> term affects only the "extra" bits provided by the FPU's internal >>> >> larger-than-double representation. Some such issue would explain why >>> >> the problem seems to be hardware- and compiler-dependent. >>> >> >>> > >>> > Hmm, that 63.999 is kinda strange. Here is a bit of code that might >>> > confuse >>> > a compiler working with different size mantissas: >>> > >>> > @type@ npy_log2...@c@(@type@ x) >>> > { >>> > @type@ u = 1 + x; >>> > if (u == 1) { >>> > return LOG2E*x; >>> > } else { >>> > return npy_l...@c@(u) * x / (u - 1); >>> > } >>> > } >>> > >>> > It might be that u != 1 does not imply u-1 != 0. >>> >>> That does indeed look highly suspicious. I'm not entirely sure how to >>> work around it. GSL uses a volatile declaration: >>> >>> http://www.google.ca/codesearch/p?hl=en#p9nGS4eQGUI/gnu/gsl/gsl-1.8.tar.gz%7C8VCQSLJ5jR8/gsl-1.8/sys/log1p.c&q=log1p >>> On the other hand boost declares itself defeated by optimizing >>> compilers and uses a Taylor series: >>> >>> http://www.google.ca/codesearch/p?hl=en#sdP2GRSfgKo/dcplusplus/trunk/boost/boost/math/special_functions/log1p.hpp&q=log1p&sa=N&cd=7&ct=rc >>> While R makes no mention of the corrected formula or optimizing >>> compilers but takes the same approach, only with Chebyshev series: >>> >>> http://www.google.ca/codesearch/p?hl=en#gBBSWbwZmuk/src/base/R-2/R-2.3.1.tar.gz%7CVuh8XhRbUi8/R-2.3.1/src/nmath/log1p.c&q=log1p >>> >>> Since, at least on my machine, ordinary log1p appears to work fine, is >>> there any reason not to have log2_1p call it and scale the result? Or >>> does the compiler make a hash of our log1p too? >>> >> >> Calling log1p and scaling looks like the right thing to do here. And our >> log1p needs improvement. >> > > Tinkering a bit, I think we should implement the auxiliary function f(p) = > log((1+p)/(1 - p)), which is antisymmetric and has the expansion 2p*(1 + > p^2/3 + p^4/5 + ...). The series in the parens is increasing, so it is easy > to terminate. Note that for p = +/- 1 it goes over to the harmonic series, > so convergence is slow near the ends, but they can be handled using normal > logs. Given 1 + x = (1+p)/(1-p) and solving for p gives p = x/(2 + x), so > when x ranges from -1/2 -> 1/2, p ranges from -1/3 -> 1/5, hence achieving > double precision should involve no more than about 17 terms. I think this > is better than the expansion in R.
First I guess we should check which systems don't have log1p; if glibc has it as an intrinsic, that should cover Linux (though I suppose we should check its quality). Do Windows and Mac have log1p? For testing I suppose we should make our own implementation somehow available even on systems where it's unnecessary. Power series are certainly easy, but would some of the other available tricks - Chebyshev series or rational function approximations - be better? I notice R uses Chebyshev series, although maybe that's just because they have a good evaluator handy. Anne > Chuck > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion