Mailman 3 March 2008 - NumPy-Discussion

PCA on set of face images
by devnew＠gmail.com 14 Apr '08

14 Apr '08

hi guys I have a set of face images with which i want to do face recognition using Petland's PCA method.I gathered these steps from their docs 1.represent matrix of face images data 2.find the adjusted matrix by substracting the mean face 3.calculate covariance matrix (cov=A* A_transpose) where A is from step2 4.find eigenvectors and select those with highest eigenvalues 5.calculate facespace=eigenvectors*A when it comes to implementation i have doubts as to how i should represent the matrix of face images? using PIL image.getdata() i can make an array of each greyscale image. Should the matrix be like each row contains an array representing an image? That will make a matrix with rows=numimages and columns=numpixels cavariancematrix =A *A_transpose will create a square matrix of shape(numimages,numimages) Using numpy.linalg.eigh(covariancematrix) will give eigenvectors of same shape as the covariance matrix. I would like to know if this is the correct way to do this..I have no big expertise in linear algebra so i would be grateful if someone can confirm the right way of doing this RoyG

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vander() docstring
by Andreas Klöckner 11 Apr '08

11 Apr '08

Hi all, The docstring for vander() seems to contradict what the function does. In particular, the columns in the vander() output seem reversed wrt its docstring. I feel like one of the two needs to be fixed, or is there something I'm not seeing? This here is fresh from the Numpy examples page: 8< docstring ----------------------------------------------- X = vander(x,N=None) The Vandermonde matrix of vector x. The i-th column of X is the the i-th power of x. N is the maximum power to compute; if N is None it defaults to len(x). 8< Example ------------------------------------------------- >>> from numpy import * >>> x = array([1,2,3,5]) >>> N=3 >>> vander(x,N) # Vandermonde matrix of the vector x array([[ 1, 1, 1], [ 4, 2, 1], [ 9, 3, 1], [25, 5, 1]]) 8< --------------------------------------------------------- Andreas

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numpyx.pyx (recent svn) works?
by Neal Becker 09 Apr '08

09 Apr '08

I tried numpyx.pyx with cython-0.9.6.12. Here's what I got: In [2]: import numpyx In [3]: numpyx.test() -=-=-=-=-=-=-=-=-=-= printing array info for ndarray at 0x0 print number of dimensions: 0 address of strides: 0x0 strides: memory dump: -1e-30 -=-=-=-=-=-=-=-=-=-= -=-=-=-=-=-=-=-=-=-= --------------------------------------------------------------------------- TypeError Traceback (most recent call last) /home/nbecker/cython/<ipython console> in <module>() /home/nbecker/cython/numpyx.pyx in numpyx.test() 94 95 for arr in [arr1,arr2,arr3,arr4,arr5]: ---> 96 print arr 97 print_array_info(arr) 98 /home/nbecker/cython/numpyx.pyx in numpyx.print_array_info() 12 13 print '-='*10 ---> 14 print 'printing array info for ndarray at 0x%0lx'%(<c_python.Py_intptr_t>arr,) 15 print 'print number of dimensions:',arr.nd 16 print 'address of strides: 0x%0lx'%(<c_python.Py_intptr_t>arr.strides,) TypeError: only length-1 arrays can be converted to Python scalars

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documentation for masked arrays?
by Chris Withers 08 Apr '08

08 Apr '08

Hi All, Where can I find docs for masked arrays? The "paid for" book doesn't even contain the phrase "masked_where" :-( cheers, Chris -- Simplistix - Content Management, Zope & Python Consulting - http://www.simplistix.co.uk

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Generically Creating Intermediate Data Compatible with Either ndarray or MasledArray Types
by Alexander Michael 08 Apr '08

08 Apr '08

I have a function that I would like to work with both MaskedArray's and ndarray's. The only blocker for this particular function is the need to create some stand-in data that is appropriately either a MaskedArray or an ndarray. Currently I have: dummy = numpy.ones(data.shape, dtype=bool) where data has a dtype of float. I've already discovered that numpy.ones_like "does the right thing", but how do I do the equivalent in conjunction with declaring a new dtype? Said another way, how can a create arrays of the same class and (possibly) shape as an existing array, but with a different dtype? Thanks, Alex

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Problem with numpy.linalg.eig?
by Peter Creasey 05 Apr '08

05 Apr '08

Hi all, The following code calling numpy v1.0.4 fails to terminate on my machine, which was not the case with v1.0.3.1 from numpy import arange, float64 from numpy.linalg import eig a = arange(13*13, dtype = float64) a.shape = (13,13) a = a%17 eig(a) Regards, Peter

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Numpy installation
by Amit Itagi 02 Apr '08

02 Apr '08

Hi, I am having problems with numpy installation. 1) These is an atlas 3.8.0 library installed somewhere in the search path. However, the installation gives errors with that installation. Is there a way to tell the installer to install the default (possibly slower) blas, instead of using the one in the path ? 2) Also, my main Python directory is called Python-2.5.2. When I try to configure with the install<prefix>, it changes Python-2.5.2 to "python-2.5.2" and creates a new directory. How can I make the installer not convert the upper-case "P" to a lower-case ? Thanks Rgds, Amit

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Project for Cython integration with NumPy
by Dag Sverre Seljebotn 01 Apr '08

01 Apr '08

I am going to apply for a Google Summer of Code project about "Developing Cython towards better NumPy integration" (Cython: http://cython.org). Anyone interested in how this is done can have a look at the links below, any feedback is welcome. Unfortunately I don't have much time to spare before the application deadline, so the focus now is only on high-level stuff, the application and so on; thinks like syntax or sorting out the exact supported NumPy features will (unfortunately) have to wait until at least next week. The application I am going to submit (to Python Foundation): http://wiki.cython.org/DagSverreSeljebotn/soc It links to a details page with more concrete information. The specification for the NumPy support itself is here: http://wiki.cython.org/enhancements/numpy As you might be able to see, my thoughts so far has primarily been on how to engineer Cython and not so much about what would be the most convenient NumPy syntax possible - but have a look if you are interested. -- Dag Sverre Seljebotn

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linalg.eigh() newbie doubt
by gordon 01 Apr '08

01 Apr '08

hello i was trying the linalg.eigh() when i apply eigh() on a covariance matrix (an ndarray of shape 6x6 i get evals,evectors suppose i get it like evals= array([2.2, 5.5, 4.4, 1.7, 7.7, 6.3]) evectors=array([[3.,5. ,1. ,6. ,2. ,4. ], [2.,1.,5.,7.,5.,3.], [8.,9.,6.,5.,4.,3.], [2.,1.,3.,4.,5.,9.], [0.1,3.,2.,4.,5.,1.], [6.,5.,7.,4.,2.,8.] ]) which is the array that corresponds to eigenvalue 2.2 of evals? is it the first column of evectors? or is it the first row? if i were to sort the evectors based on the eigenvalue ,i guess the most significant eigenvector should correspond to the value of 7.7 ,then am i supposed to consider the 5th column of evectors as the most significant eigenvector? please someone help me clear this confusion thanks gordon

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planet.scipy.org
by Jarrod Millman 01 Apr '08

01 Apr '08

Hey, I just wanted to announce that we now have a NumPy/SciPy blog aggregator thanks to Gaël Varoquaux: http://planet.scipy.org/ Feel free to contact me if you have a blog that you would like included. Thanks, -- Jarrod Millman Computational Infrastructure for Research Labs 10 Giannini Hall, UC Berkeley phone: 510.643.4014 http://cirl.berkeley.edu/

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