lesshaste

Thanks for the reply! The paper Iinked discusses when Hyrrö's method is faster than Myers' in some detail. See e.g. page 18. But obviously it doesn't have to worry about...

Have you compared the speed of your new code to the code at https://codegolf.stackexchange.com/questions/200921/calculate-the-average-longest-common-substring-exactly I assume it should be roughly the same?

Oops, sorry. I meant https://codegolf.stackexchange.com/questions/197565/can-you-calculate-the-average-levenshtein-distance-exactly

What is happening under the hood? Here is another example sympy.nsimplify(“23591”) gives \frac{55361684267444749690566057670772755459030104740612012801874693754770668178456137071294070140303775283072547827725214059372529764661566971136719387709460315091508388244902662699700782731942327365191482722530805276999897722717401064024162241228376033289769245635612231268185763210043415291409656410067969574643}{2346729018161345205313953500482574601169889206080403067931166513073661751797824552179928225082716326103979844117612605591285913055569961219824996859804010238945997619200000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000} Whereas sympy.nsimplify(“23592”) gives 23592

How could you work out what the k nearest neighbors are?

I am not sure I am competent to code it well in Julia (first I would have to learn Julia :) ). However this series of answers https://codegolf.stackexchange.com/a/197716/9207 seems to...

+1 for complex number support. It's also an opportunity to be faster than C compiled with gcc/clang which does a bad job of vectorizing complex arithmetic. See https://gcc.gnu.org/bugzilla/show_bug.cgi?id=79102 , https://gcc.gnu.org/bugzilla/show_bug.cgi?id=79336,...

I understand https://umap-learn.readthedocs.io/en/latest/ is regarded as much better than tsne these days.

I have the same problem. In my case the large number of arguments seem to be created internally by symfit. Here is my full code: ``` from symfit import Parameter,...

Unfortunately neither NelderMead nor Powell work well if I use them for LogLikelihood maximisation. Using the code above but setting np.random.seed(333), N = 7 and xs = scipy.stats.weibull_min.rvs(loc=0, c=0.5, size=20000),...