Thanks Anthony, but unless Im missing something I don't think that method
will work since this will only be comparing the ith element with ith+1
element. I still need 2 for loops right?
Using itertools might speed things up though, I've never used them so I
will give it a shot and let you know how it goes. Looks like I need to
download the latest release before I do that too. Thanks for the help.
-Dave
On Thu, Jan 3, 2013 at 12:12 PM, <
pytables-users-requ...@lists.sourceforge.net> wrote:
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> 1. Re: Nested Iteration of HDF5 using PyTables (Anthony Scopatz)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Thu, 3 Jan 2013 11:11:47 -0600
> From: Anthony Scopatz <scop...@gmail.com>
> Subject: Re: [Pytables-users] Nested Iteration of HDF5 using PyTables
> To: Discussion list for PyTables
> <pytables-users@lists.sourceforge.net>
> Message-ID:
> <CAPk-6T5b=
> 1egagp4+jhjcd3_4fnvbxrob2jbhay45rwdqzy...@mail.gmail.com>
> Content-Type: text/plain; charset="iso-8859-1"
>
> HI David,
>
> Tables and table column iteration have been overhauled fairly recently [1].
> So you might try creating two iterators, offset by one, and then doing the
> comparison. I am hacking this out super quick so please forgive me:
>
> from itertools import izip
>
> with tb.openFile(...) as f:
> data = f.root.data
> data_i = iter(data)
> data_j = iter(data)
> data_i.next() # throw the first value away
> for i, j in izip(data_i, data_j):
> compare(i, j)
>
> You get the idea ;)
>
> Be Well
> Anthony
>
> 1. https://github.com/PyTables/PyTables/issues/27
>
>
> On Thu, Jan 3, 2013 at 9:25 AM, David Reed <david.ree...@gmail.com> wrote:
>
> > I was hoping someone could help me out here.
> >
> > This is from a post I put up on StackOverflow,
> >
> > I am have a fairly large dataset that I store in HDF5 and access using
> > PyTables. One operation I need to do on this dataset are pairwise
> > comparisons between each of the elements. This requires 2 loops, one to
> > iterate over each element, and an inner loop to iterate over every other
> > element. This operation thus looks at N(N-1)/2 comparisons.
> >
> > For fairly small sets I found it to be faster to dump the contents into a
> > multdimensional numpy array and then do my iteration. I run into problems
> > with large sets because of memory issues and need to access each element
> of
> > the dataset at run time.
> >
> > Putting the elements into an array gives me about 600 comparisons per
> > second, while operating on hdf5 data itself gives me about 300
> comparisons
> > per second.
> >
> > Is there a way to speed this process up?
> >
> > Example follows (this is not my real code, just an example):
> >
> > *Small Set*:
> >
> >
> > with tb.openFile(h5_file, 'r') as f:
> > data = f.root.data
> >
> > N_elements = len(data)
> > elements = np.empty((N_irises, 1e5))
> >
> > for ii, d in enumerate(data):
> > elements[ii] = data['element']
> >
> > D = np.empty((N_irises, N_irises)) for ii in xrange(N_elements):
> > for jj in xrange(ii+1, N_elements):
> > D[ii, jj] = compare(elements[ii], elements[jj])
> >
> > *Large Set*:
> >
> >
> > with tb.openFile(h5_file, 'r') as f:
> > data = f.root.data
> >
> > N_elements = len(data)
> >
> > D = np.empty((N_irises, N_irises))
> > for ii in xrange(N_elements):
> > for jj in xrange(ii+1, N_elements):
> > D[ii, jj] = compare(data['element'][ii],
> data['element'][jj])
> >
> >
> >
> >
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