Hi Richard, Ah, I searched the list but didn't find those posts before…
I can easily imagine that correlation is defined differently in different disciplines. Both ways are correct and it's just a convention or definition. In my field (Digital Communications, Digital Signal Processing) the vast majority uses the convention implemented by the code. Here are a few examples of prominent text books: - Papoulis, "Probaility, Random Variables, and Stochastic Processes", McGraw-Hill, 2nd ed. - Benvenuto, Cherubini, "Algorithms for Communications Systems and their Applications", Wiley. - Carlson, "Communication Systems" 4th ed. 2002, McGraw-Hill. Last not least, Matlab's xcorr() function behaves exactly like correlate() does right now, see - http://www.mathworks.de/de/help/signal/ref/xcorr.html But, as you say, the most important aspect might be, that most people will probably prefer changing the docs instead of changing the code. Should I file a bug somewhere? Cheers, Bernhard On 08.10.2013, at 21:10, Richard Hattersley <rhatters...@gmail.com> wrote: > Hi Bernard, > > Looks like you're on to something - two other people have raised this > discrepancy before: https://github.com/numpy/numpy/issues/2588. > Unfortunately, when it comes to resolving the discrepancy one of the previous > comments takes the opposite view. Namely, that the docstring is correct and > the code is wrong. > > Do different domains use different conventions here? Are there some > references to back up one stance or another? > > But all else being equal, I'm guessing there'll be far more appetite for > updating the documentation than the code. > > Regards, > Richard Hattersley > > > On 7 October 2013 22:09, Bernhard Spinnler <bernhard.spinn...@gmx.net> wrote: > The numpy.correlate documentation says: > > correlate(a, v) = z[k] = sum_n a[n] * conj(v[n+k]) > > In [1]: a = [1, 2] > > In [2]: v = [2, 1j] > > In [3]: z = correlate(a, v, 'full') > > In [4]: z > Out[4]: array([ 0.-1.j, 2.-2.j, 4.+0.j]) > > However, according to the documentation, z should be > > z[-1] = a[1] * conj(v[0]) = 4.+0.j > z[0] = a[0] * conj(v[0]) + a[1] * conj(v[1]) = 2.-2.j > z[1] = a[0] * conj(v[1]) = 0.-1.j > > which is the time reversed version of what correlate() calculates. > > IMHO, the correlate() code is correct. The correct formula in the docs (which > is also the correlation formula in standard text books) should be > > z[k] = sum_n a[n+k] * conj(v[n]) > > Cheers, > Bernhard > _______________________________________________ > 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
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