Mailman 3 November 2007 - SciPy-User

New example
by Anne Archibald Nov. 22, 2007

Nov. 22, 2007

Hi, I just wrote up a calculation using scipy: http://www.scipy.org/Trinity It's a fluid dynamics calculation describing the evolution of a spherical blast wave. There's some theory there, though I skimmed it as much as possible, and a reasonable calculation using scipy; specifically, it uses odeint, simps, and pylab. Is this a useful sort of tutorial/example? Do we want more things like this? Anne

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Web Site's Down
by Rich Shepard Nov. 22, 2007

Nov. 22, 2007

Did the server for the scipy.org web site take off for the Thanksgiving holiday? Firefox keeps reporting that the server cannot be found. Rich -- Richard B. Shepard, Ph.D. | Integrity Credibility Applied Ecosystem Services, Inc. | Innovation <http://www.appl-ecosys.com> Voice: 503-667-4517 Fax: 503-667-8863

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Numpy matrix and blitz Matrix
by Paolo Tenconi Nov. 22, 2007

Nov. 22, 2007

Hi Everyone, *) numpy arrays are automatically converted to blitz arrays. That's fine. *) I need to work with blitz Matrix objects, but I noticed that numpy matrix objects are not converted to them and I get a compilation error too 3) Does someone on the list succeeded doing that? Or is there a workaround to create quickly a blitz matrix object from a numpy 2D array or numpy-matrix without wasting time in casting operations? It would be nice having an automatic translation of numpy.matrix to blitz Matrix as matrices are used frequently in scientific computing. Any suggestion or help would be very glad. Paolo #------------------ EXAMPLE CODE ----------------------------------- import numpy import scipy #Dot product with arrays (it works) x=numpy.array([[1,2,],[3,4]]) y=numpy.zeros((2,2)) scipy.weave.inline("""y=x*x;""",['x','y'],type_converters=scipy.weave.converters.blitz,compiler='gcc',force=1) #Matrix multiplication with matrix (gives compilation error) X=numpy.matlib.mat('1 2; 3 4') Y=numpy.matlib.zeros((2,2)) scipy.weave.inline("""Y=X*X;""",['X','Y'],type_converters=scipy.weave.converters.blitz,compiler='gcc') #--------------------------------------------------------------------

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Re: [SciPy-user] SciPy-user Digest, Vol 51, Issue 45
by Anand Patil Nov. 22, 2007

Nov. 22, 2007

>From: "Boris von Loesch" <boris(a)vonloesch.de> > Subject: Re: [SciPy-user] Sparse matrix advice > > Hi Anand, > > I use the COO-format for the creation of the matrix, because it could > be assembled quite fast. A second advantage is, that you need to > create the sparsity only the first time and then just create a vector > with the non-zero entries. > For calculations I convert it to CSR-Format, which is also quite fast. > With this method I can create a 255^2*255^2 sparse matrix with roughly > 8 non-zero entries per row in about 0.25 sec. Creating the matrix in > LIL-format or DIC-format is a lot slower. > > Best regards, > Boris Hi Boris, Thanks for the advice, I think I can get where I'm trying to go now. A couple of additional questions: Is there a triangular version (DTRMM) of csrmucsr out there somewhere? How about a CSR-CSR triangular solve? Thanks, Anand

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help on array manipulation
by Tim Michelsen Nov. 21, 2007

Nov. 21, 2007

Hello, I have the following array: In [240]: z Out[240]: array([[ 15., 3., 7., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [ 16., 3., 7., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [ 17., 3., 7., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]]) How do I get it be become like: 15 3 15 7 15 0 ... 16 3 16 7 ... 17 3 Is there a special function I can use for this or do I need to build various for loops to achive this? I mean this example has few data. But what if the amount increases? I am stuck here. I'd be very glad if anyone could point be to a good tutorial for array manipulation. Scipy Cookbook is not enough. Well, I also found : http://numpy.scipy.org/numpydoc and http://www.penzilla.net/tutorials/python/numeric Thanks in advance, Timmie ### # Code for the array: ### z = numpy.zeros((3,25)) z = numpy.zeros((3,25)) for i in xrange(z.shape[1]): z[:,0] = 1 z[:,1] = 3 z[:,2] = 7 for i in xrange(z.shape[0]): z[0,0] = 15 z[1,0] = 16 z[2,0] = 17

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a small OpenOpt example howto benchmark solvers
by dmitrey Nov. 21, 2007

Nov. 21, 2007

Hi all, I have got a letter from Nils Wagner about interest of NLP solvers comparison, and maybe some of scipy-user mailist subscribers could be interested as well. So if anyone is interested - here's an example of ALGENCAN, cobyla and lincher comparison: http://openopt.blogspot.com/2007/11/example-of-oo-nlp-solvers-benchmark.html Please let me note that usually ALGENCAN is much more better, and choosing correct stop criteria for your problem (gradtol, ftol, xtol etc) is very essential. Regards, D

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Adding pysamplerate to scikits ?
by David Cournapeau Nov. 21, 2007

Nov. 21, 2007

Hi, Just wanted to know if it would be ok to add pysamplerate to scikits ? pysamplerate is a (really rough for now) wrapper around SRC for high quality audio resampling (using sinc interpolation). It would be LGPL, as SRC itself: http://www.ar.media.kyoto-u.ac.jp/members/david/softwares/pysamplerate/inde… cheers, David

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Re: [SciPy-user] organizing data
by Gael Varoquaux Nov. 21, 2007

Nov. 21, 2007

Let's keep this on the mailing list, or else, we can switch to French (not that I mind English). On Wed, Nov 21, 2007 at 03:59:39PM +0100, Xavier Barthelemy wrote: > So I think you did not understand my problem. It's a problem of > organizing and cutting by slice of rows in my data. OK, you're telling me you already have interpolated your data, and you have all the values you need (ie regular grids in the different directions you are interested in), but you just need to sort them out. > My data comports 18 values witch depends of 12 parameters. > so I have my data like that: > by rows: > first the 12 parameters, then the 18 values. > each rows represent a numeric experiment. I am doing parameters > exploration, so each varies independently. But the discretization of the > space parameters is not "regular": i have refined some for some values > of the others parameters. If you want to do image plot, it will be more easier to have regular data, that's where interpolation comes in. It looks to me like you want to have an interpolation function f({P}) -> {V} where {P} is your set of parameters and {V} your set of values. When you want to plot the cut along a hyperplane HP, you simply choose a regular grid of this hyper plane, and apply your interpolation function f on it. That's how I would do it, if I understand your problem correctly. > so my problem is really what I have (badly i guess) explained: I would > like to plot 2D (and 3D) graphs. > Let's suppose that I have X ,Y and Z datas corresponding. knowing that, > how do you plot Y(X) with Z constant when you have a bunch of three > columns data? In 1D that's really easy: if D is your [X, Y, Z] array, I would do X = D[:, 0] Y = D[:, 1] Z = D[:, 2] # Select all the data for Z = z0 x = X[Z==z0] y = Y[Z==z0] # Sort, just to make things prettier y = y[argsort(x)] x.sort() plot(x, y) > you 'll have to first sort by Z, and then by X. so when you'll plot > that, for each "X", sequentially sorted, you'll have the different "Y" > for each "Z" values. consequently you will have the number of different > Z values plots. OK, you want to do this for all values of Z. > And my problem now is the generalization with 12 parameters, let's name > them from A to J. How I'll do if I want to plot F(H)? the same, I will > sort by each of the 10 parameters and finally by H and I will have a > family of plots. Yes, you can do this in a nice way using an array with fields and the "order" argument to sort. > but now I want to cut (slice) them to have each plot independently, and > i can plot them by the interfaced gnuplot. You can always generalize the cutting method used in my example. If U, V, W are parameters (similar to Z in the example above), you can define a mask array: mask = (U == u0) & (V == v0) & (W == w0) # You dont really need x and y arrays, you could directly go to xy x = X[mask] y = Y[mask] xy = empty(x.shape, dtype=dtype([('x','float'), ('y','float')])) xy['x'] = x xy['y'] = y xy.sort(order=('x', 'y')) then you have in xy['x'] and xy['y'] what you are interested in, if I understand things right. But I still think you need a regular grid, so either your data already has that structure, and I don't understand why it has been "shuffled", or it hasn't, and you'll need interpolating, so why bother sorting? (selecting might be useful to reduce the amount of points). HTH, Gaël

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Is scipy.io.numpyio.fread working?
by Jose Luis Gomez Dans Nov. 21, 2007

Nov. 21, 2007

Hi, I am trying to read binary data from a binary file. The file has a header, and several chunks of data in it. I want to seek some position, and read from there X data into an array. So, I have done the following: fp = open( file ) fp.seek (header_position ) #My header position a = scipy.io.numpyio.fread(fp, 2400*2400,'f',byteswap=1) This bombs with a <type 'exceptions.TypeError'>: fread() takes no keyword arguments I don't think this has to do with the fact that I seeked the file. I am running scipy.__version__="0.6.0" from Andrew Straw's Ubuntu repository on Ubuntu i386. Is there something wrong here? Cheers! Jose -- GMX FreeMail: 1 GB Postfach, 5 E-Mail-Adressen, 10 Free SMS. Alle Infos und kostenlose Anmeldung: http://www.gmx.net/de/go/freemail

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Place data on grid to minimise cost function
by John Reid Nov. 21, 2007

Nov. 21, 2007

I have a problem for which I do not know any algorithm to solve it. I'm wondering if there is something in scipy that will help me. Apologies if there isn't and this is off-topic. I have a set of N data points, which I want to place on a k x m grid. I have a cost function D(x1,x2) that measures how different 2 data points are. I want to minimise the sum of D over all neighbouring pairs of points on the grid (i.e. I want similar points to be neighbours on the grid). A) Is there some established technique to do this? B) Is it in scipy? BTW, N = k.m Thanks, John.

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