Mailman 3 February 2011 - NumPy-Discussion

int is a subtype of bool?
by Nathaniel Smith 09 Feb '11

09 Feb '11

This can't possibly be right, can it? Or am I missing something? (It certainly doesn't seem to match any documentation that I can find) >>> np.issubdtype(int, bool) True >>> np.__version__ '1.5.1' -- Nathaniel

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Indexing a 2-d array with a 1-d mask
by Alok Singhal 09 Feb '11

09 Feb '11

Hi, I have an NxM array, which I am indexing with a 1-d, length N boolean array. For example, with a 3x5 array: In [1]: import numpy In [2]: data = numpy.arange(15) In [3]: data.shape = 3, 5 Now, I want to select rows 0 and 2, so I can do: In [4]: mask = numpy.array([True, False, True]) In [5]: data[mask] Out[5]: array([[ 0, 1, 2, 3, 4], [10, 11, 12, 13, 14]]) But when the shape of 'data' is a 0xM, this indexing fails: In [6]: data2 = numpy.zeros((0, 5), 'd') In [7]: mask2 = numpy.zeros(0, 'bool') In [8]: data2[mask2] ------------------------------------------------------------ Traceback (most recent call last): File "<ipython console>", line 1, in <module> IndexError: invalid index I would have expected the above to give me a 0x5 array. Of course, I can check on "len(data)" and not use the above indexing when it is zero, but I am hoping that I don't need to special case the boundary condition and have numpy fancy indexing do the "right thing" always. Is this a bug in numpy? Is there any other way to do what I am doing? Here is my numpy setup (numpy installed from the git repository): In [1]: import numpy In [2]: numpy.__version__ Out[2]: '1.6.0.dev-13c83fd' In [3]: numpy.show_config() blas_info: libraries = ['blas'] library_dirs = ['/usr/lib'] language = f77 lapack_info: libraries = ['lapack'] library_dirs = ['/usr/lib'] language = f77 atlas_threads_info: NOT AVAILABLE blas_opt_info: libraries = ['blas'] library_dirs = ['/usr/lib'] language = f77 define_macros = [('NO_ATLAS_INFO', 1)] atlas_blas_threads_info: NOT AVAILABLE lapack_opt_info: libraries = ['lapack', 'blas'] library_dirs = ['/usr/lib'] language = f77 define_macros = [('NO_ATLAS_INFO', 1)] atlas_info: NOT AVAILABLE lapack_mkl_info: NOT AVAILABLE blas_mkl_info: NOT AVAILABLE atlas_blas_info: NOT AVAILABLE mkl_info: NOT AVAILABLE In [4]: import sys In [5]: print sys.version 2.6.5 (r265:79063, Apr 16 2010, 13:09:56) [GCC 4.4.3] Thanks!

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Re: [Numpy-discussion] how to do this efficiently?
by Mark Bakker 09 Feb '11

09 Feb '11

I recently needed a find_first function and searched the list. It has been discussed a few times before. And I haven't seen an elegant solution yet. Maybe we should file a feature request, as it would be awfully nice to have? Mark > > > Still, I wonder if numpy would benefit from a 'find_first' function. > > I certainly could have used one many times. > > -- > Robert Kern > >

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how to do this efficiently?
by Neal Becker 09 Feb '11

09 Feb '11

In a 1-d array, find the first point where all subsequent points have values less than a threshold, T.

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Permission to close ticket for Mark Wiebe
by Charles R Harris 09 Feb '11

09 Feb '11

I don't know who handles these permissions, I didn't see a way to do it myself. Chuck

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question on use of newaxis
by Mark Bakker 09 Feb '11

09 Feb '11

Hello List, I have a simple array a = array([1,2,3]) I want to take the last two terms and make it a column vector: a[[1,2],newaxis] But I get a funny error: TypeError: long() argument must be a string or a number, not 'NoneType' It does work if I do a[[1,2]][:,newaxis] But I don't understand why the first wouldn't work. Is there a reason such syntax is not supported? It would be very useful. Thanks, Mark

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Computing the norm of an array of vectors
by Ben Gamari 08 Feb '11

08 Feb '11

I have an array of (say, row) vectors, v = [ [ a1, a2, a3 ], [ b1, b2, b3 ], [ c1, c2, c3 ], ... ] What is the optimal way to compute the norm of each vector, norm(v)**2 = [ [ a1**2 + a2**2 + a3**2 ], [ b1**2 + b2**2 + b3**2 ], ... ] It seems clear that numpy.norm does not handle the multidimensional case as needed. The best thing I can think of is to do something like, sum(v**2, axis=0) * ones(3) but surely there must be a better way. Any ideas? Cheers, - Ben

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Need a good idea: calculate the mean of many vectors
by EMMEL Thomas 08 Feb '11

08 Feb '11

Hi, here is something I am thinking about for some time and I am wondering whether there is a better solution within numpy. The task is: I have an array (300000+ entries) with arrays each with length == 3, that is initially empty like this: n = 100 # for test otherwise ~300000 a1 = reshape(zeros(3*n).astype(float), (n,3)) (Speaking literally this is a field of displacements in a Finite-Element-Mesh) Now I have a lot of triangles where the corners are the nodes, each with an index between 0 and n-1 and I like to add a unique displacement for all three nodes to a1 like this a2 = zeros(n).astype(int) for indices, data in [...]: #data = array((1.,2.,3.)) #indices = (1,5,60) for index in indices: a1[index] += data a2[index] += 1 Now after filling a1 and a2 over and over (for a lot of triangles) I can finally calculate the averaged displacement on all points by this meand = a1/reshape(a2,(n,1)) I am doing this in the old numeric package (and can do it in numpy). I wonder whether there is a better way to do that in numpy. Numpy is in this actual case 20times slower than Numeric and I know that is due to the fact that I need to change only 3 values of the big array every loop. The basic problem is: How can I add very few values to a big array with a good performance? I thought about this: m = zeros(n) put(m, indices,1.) # only 3 ones in a long list of zeros! a1 += outer(m, data) a2 += m which is in fact very slow due to the function outer. Any help appriciated Thomas

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moving C++ binary data to numpy
by Ilya Shlyakhter 07 Feb '11

07 Feb '11

Is there a portable way to save vector of C++ structs to a binary file, and then load it as a numpy recarray? thanks, ilya

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f2py on mac
by McEnerney, James F. 07 Feb '11

07 Feb '11

On my mac (10.6.5) I'm running python2.6 with numpy 1.5.0. While using f2py with f2py -c --fcompiler=gnu95 --f77flags='-m32 -O1 -fno-second-underscore -fbounds-check' src/mars.pyf src/mars.f It compiles but has link warnings. -m32 is not being passed to gcc. ld: warning: in /var/folders/k-/k-SUt4dLGyWuiaA0fiYLOU++4GM/-Tmp-/tmp8xkKpp/var/folders/k-/k-SUt4dLGyWuiaA0fiYLOU++4GM/-Tmp-/tmp8xkKpp/src.macosx-10.6-i386-2.6/src/marsmodule.o, file was built for unsupported file format which is not the architecture being linked (i386) ld: warning: in /var/folders/k-/k-SUt4dLGyWuiaA0fiYLOU++4GM/-Tmp-/tmp8xkKpp/var/folders/k-/k-SUt4dLGyWuiaA0fiYLOU++4GM/-Tmp-/tmp8xkKpp/src.macosx-10.6-i386-2.6/fortranobject.o, file was built for unsupported file format which is not the architecture being linked (i386) Any help would be appreciated!!! Jim

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