Mailman 3 February 2010 - NumPy-Discussion

Syntax equivalent for np.array()
by Gökhan Sever Feb. 10, 2010

Feb. 10, 2010

Hi, Simple question: I[4]: a = np.arange(10) I[5]: b = np.array(5) I[8]: a*b.cumsum() O[8]: array([ 0, 5, 10, 15, 20, 25, 30, 35, 40, 45]) I[9]: np.array(a*b).cumsum() O[9]: array([ 0, 5, 15, 30, 50, 75, 105, 140, 180, 225]) Is there a syntactic equivalent for the I[9] --for instance instead of using "list" keyword I use [ ] while creating a list. Is there a shortcut for np.array instead of writing np.array(a*b) explicitly? Thanks. -- Gökhan

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wired error message in scipy.sparse.eigen function: Segmentation fault
by Jankins Feb. 10, 2010

Feb. 10, 2010

Dear all, I am using scipy '0.8.0.dev6120'. And the scipy.sparse.eigen function always produces error message. _Description:_ linalg.eigen(A, k=6, M=None, sigma=None, which='LM', v0=None, ncv=None, maxiter=None, tol=0, return_eigenvectors=True)_ Error messages:_ When I use this function in the way : linalg.eigen(A, k=2, return_eigenvectors=False) it produces error : *** glibc detected *** python: double free or corruption (!prev) when I use : linalg.eigen(A, k=4, return_eigenvectors=False) or linalg.eigen(A, k=8, return_eigenvectors=False) it produces error : Segmentation fault _My goal:_ "A" is an _unsymmetrical CSR sparse matrix_. What I am trying to do is : 1. find a node 's' to delete. For edge (u, v) in all the out-edges and in-edges of node 's', I set A[u, v] = 0.0. 2. calculate the largest eigenvalue using linalg.eigen(A, return_eigenvectors=False) 3. repeat 1-2 steps many times. I had used eigen_symmetric function to compute symmetric CSR sparse matrix and it works very well. But for the 'eigen' function, it is not working very well. Could you please help me about it? If it does not work, I have to rewrite my code in MATLAB, which is what I am trying to avoid. Thanks so much. Yours sincerely, Jankins

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numpy.polynomial.chebyshev (not) in the docs
by josef.pktd＠gmail.com Feb. 9, 2010

Feb. 9, 2010

Similar to the recfunctions, I also don't find the new chebychev polynomials in the docs. Are they linked from any rst file? A search in the online sphinx html docs comes up empty, and http://docs.scipy.org/numpy/docs/numpy-docs/reference/routines.poly.rst/#ro… doesn't link to the new functions. The docstrings look nice but maybe nobody sees them. Josef

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Utility function to find array items are in ascending order
by Vishal Rana Feb. 9, 2010

Feb. 9, 2010

Hi, Is there any utility function to find if values in the array are in ascending or descending order. Example: arr = [1, 2, 4, 6] should return true arr2 = [1, 0, 2, -2] should return false Thanks Vishal

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np.expand_dims is addaxis
by josef.pktd＠gmail.com Feb. 8, 2010

Feb. 8, 2010

np.expand_dims has a name that I never remember and it's difficult to search for in the help. usage: it adds an axis e.g. after a reduce operation Please ignore, this is a message for Mr. Google Josef

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Python 2.6 and numpy 1.3.0/1.4.0 from an extension
by Peter Notebaert Feb. 8, 2010

Feb. 8, 2010

I have made an extension that also uses numpy. I developed with Python 2.6 and numpy 1.4.0 This works all fine. The problem is that users that use this extension get crahes from the moment they use the extension and this because of numpy. It crashes when numpy is initialised. This because those users have also Python 2.6, but with numpy 1.3.0!!! This because they installed both via the Pythonxy setup. How can this be handled that users have different versions of numpy for a given version of Python. Python has no problem using numpy 1.3.0 or 1.4.0, so how can I make this possible in my extension? Thanks for your input

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Compact way of performing array math with specified result type?
by Russell E. Owen Feb. 8, 2010

Feb. 8, 2010

I often find myself doing simple math on sequences of numbers (which might or might not be numpy arrays) where I want the result (and thus the inputs) coerced to a particular data type. I'd like to be able to say: numpy.divide(seq1, seq2, dtype=float) but ufuncs don't allow on to specify a result type. So I do this instead: numpy.array(seq1, dtype=float) / numpy.array(seq2, dtype=float) Is there a more compact solution (without having to create the result array first and supply it as an argument)? -- Russell

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scipy-tickets restarted emailing on jan17 - how about numpy-tickets ?
by Sebastian Haase Feb. 8, 2010

Feb. 8, 2010

Hi, long time ago I had subscript to get both scipy-tickets and numpy-tickets emailed. Now scipy-tickets apparently started emailing again on 17th of Januar. Will numpy-tickets also come back "by itself" - or should I resubscribe? Regards, Sebastian Haase

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Unable to install Numpy
by Vicente Soler Fraile Feb. 7, 2010

Feb. 7, 2010

Hello, I try to install Numpy without success. Windows 7 Python 2.6.4 Numpy numpy-1.4.0-win32-superpack-python2.6.exe The problem is that the installer does not find Python in the Windows Registry. However, I've been using python for quite a long time now. Since I really want to try Numpy, do you have any ideas as to what can I do? Thank you for your help _________________________________________________________________ Ibex 35, comparadores de hipotecas, Euribor, foros de bolsa. ¡Nuevo MSN Dinero! http://dinero.es.msn.com/

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swap elements in two arrays
by Alan G Isaac Feb. 7, 2010

Feb. 7, 2010

I have two 1d arrays, say `a` and `b`. I need to swap elements if a 1d boolean criterion `to_swap` is met. Here's one way: a, b = np.choose([to_swap,np.logical_not(to_swap)], [a, b]) Here is a much faster way: a[to_swap], b[to_swap] = b[to_swap], a[to_swap] Other better ways? Thanks, Alan Isaac

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