On Sun, Feb 28, 2010 at 03:01:18PM +0100, Friedrich Romstedt wrote: > > Well, I might not have to compare ndarrays, but fairly arbitrary > > structures (dictionnaries, classes and lists) as I am dealing with > > semi-structured data coming from a stack of unorganised experimental > > data. Python has some logic for comparing these structures by comparing > > their members, but if these are ndarrays, I am back to my original > > problem.
> I also do not understand how to build an oder on such a thing at all, > maybe you can give a simple example? Well, you can't really build an order in the mathematical sens of ordering. All I care is that if you give me twice the samed shuffled list of elements, it comes out identical. I am fighting the fact that dictionnaries in Python have no order, and thus shuflle the data from run to run. > Hmm, you could also replace numpy.greater and similar temporarily with > an with statement like: > # Everything as usual, comparing ndarrays results in ndarrays here. > with monkeypatched_operators: > # Comparing ndarrays may result in scalars or what you need. > pass # Perform the sorting > # Everything as usual ... > Though that's maybe not threadsafe too. Yes, it's not threadsafe either. > Then you could use ndarray.flatten().tolist() to compare them using > usual Python semantics? That solves the local problem of comparing 2 arrays (though will be quite slow), but not the general problem of sorting in a reproducible order (may it be arbitary) objects containing arrays. Anyhow, I solved the problem implementing a subclass of dict and using it everywhere in my code. Right now it seems to be working for what I need. Cheers, Gaël _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
