Mailman 3 August 2008 - SciPy-User

2D data plot
by Martin Höfling 21 Aug '08

21 Aug '08

Hi folks, I am trying to plot 2D data (x,y->z). Contour nearly does what I want except that I wanna fill a full pixel/square/rectangle for each x,y pair (since x and y are integer values). Contour plot draws lines and bevels between the points. What's the right plot/option for me. Best Martin

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from scipy import *, from scipy import signal
by Ryan Krauss 18 Aug '08

18 Aug '08

I upgraded to svn this morning and am having a rough time. I think I eventually got everything to compile, but I am having problems running the script I am working with. I have two primary problems (I think). 1. I have a lot of legacy code of mine that starts with "from scipy import *". But with the current svn versions, this doens't seem to do what it used to (it doesn't seem to bring in signal and integrate at least). 2. Secondly, adding "from scipy import signal" to fix problem #1, produces this message: In [2]: from scipy import signal --------------------------------------------------------------------------- <type 'exceptions.RuntimeError'> Traceback (most recent call last) <type 'exceptions.RuntimeError'>: module compiled against version 1000009 of C-API but this version of numpy is 100000a _um=None What is the easiest way to resolve these two issues? Thanks, Ryan

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SOM in scipy.cluster
by Corran Webster 18 Aug '08

18 Aug '08

> On Wed, Aug 13, 2008 at 10:31, Eric Bruning <eric(a)deeplycloudy.com> > wrote: > > Greetings, > > > > I'm considering using self-organizing maps for mining some lightning > > data, and info.py in scipy.cluster mentions that implementation of > > self-organizing maps is under development. I've found a few examples > > written in python around the web, but none that are likely to be > > efficient enough for my use. > > > > Is there still interest in including SOM in scipy? I'd be happy to > > coordinate on a contribution if nothing else is under way. > > Sure! My colleague Corran Webster was thinking about doing some SOM > stuff for scipy, too, so you two should talk. Hi, yes, I've been thinking seriously about adding some SOM algorithms to scipy - I used them heavily in my previous job (we used SOMs to classify documents for the Mayo clinic and slot machine players for casinos...). I think that there is a place for a simple and fast batch SOM algorithm in scipy.cluster.vq, since the batch SOM can be viewed as a generalization of K-means. For more general variations of the SOM algorithm, it may make sense to put them elsewhere - possibly in the machine learning scikit where the algorithms can access other. I'd be interested to hear what your needs are as far as data types, distance functions, data set sizes and SOM topologies, as that would likely influence on where I concentrate my energy. Best Regards, Corran

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[ Python(x,y) ] New release : 2.0.2
by Pierre Raybaut 17 Aug '08

17 Aug '08

Hi all, As you may already know, Python(x,y) is a free scientific-oriented Python Distribution based on Qt and Eclipse providing a self-consistent scientific development environment. Release 2.0.2 is now available on http://www.pythonxy.com. (Full release, and update patch for 2.0.0 only because of disk space quota - If you have already installed the 2.0.1 release, please take a look at http://code.google.com/p/pythonxy for an update in a three parts archive which will be soon available) Note: GDCM will be included but only in the next release Changes history 08 -17 -2008 - Version 2.0.2 : * Updated: o Enthought Tool Suite 3.0.0 o ITK 3.8 Regards, Pierre Raybaut

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Possible new multiplication operators for Python
by Fernando Perez 16 Aug '08

16 Aug '08

Hi all, [ please keep all replies to this only on the numpy list. I'm cc'ing the scipy ones to make others aware of the topic, but do NOT reply on those lists so we can have an organized thread for future reference] In the Python-dev mailing lists, there were recently two threads regarding the possibility of adding to the language new multiplication operators (amongst others). This would allow one to define things like an element-wise and a matrix product for numpy arrays, for example: http://mail.python.org/pipermail/python-dev/2008-July/081508.html http://mail.python.org/pipermail/python-dev/2008-July/081551.html It turns out that there's an old pep on this issue: http://www.python.org/dev/peps/pep-0225/ which hasn't been ruled out, simply postponed. At this point it seems that there is room for some discussion, and obviously the input of the numpy/scipy crowd would be very welcome. I volunteered to host a BOF next week at scipy so we could collect feedback from those present, but it's important that those NOT present at the conference can equally voice their ideas/opinions. So I wanted to open this thread here to collect feedback. We'll then try to have the bof next week at the conference, and I'll summarize everything for python-dev. Obviously this doesn't mean that we'll get any changes in, but at least there's interest in discussing a topic that has been dear to everyone here. Cheers, f

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Re: [SciPy-user] [ Python(x,y) ] New release : 2.0.1
by Pierre Raybaut 16 Aug '08

16 Aug '08

> > Message: 2 > Date: Thu, 14 Aug 2008 13:59:34 -0400 > From: "william ratcliff" <william.ratcliff(a)gmail.com> > Subject: Re: [SciPy-user] [ Python(x,y) ] New release : 2.0.1 > To: "SciPy Users List" <scipy-user(a)scipy.org> > Message-ID: > <827183970808141059u1069a322xe4af0b421a24c7f6(a)mail.gmail.com> > Content-Type: text/plain; charset="iso-8859-1" > > Thanks for all of your work on this! A quick question about your VTK > distribution--there is an option to compile VTK to use GL2PS to allow the > export of scene's to eps, ps, pdf, etc. see: > http://davis.lbl.gov/Manuals/VTK-4.5/classvtkGL2PSExporter.html > > Is your version compiled with this option. I believe it is not the default > due to licensing issues. > > > Thanks, > William Hi William, Actually yes, the VTK version included in Python(x,y) was compiled with this option. Thank for your message. Regards, Pierre

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bezier splines from given control points (2D)
by Sebastian Haase 15 Aug '08

15 Aug '08

Hi, I am looking for a way to calculate x,y-coordinates for a polygon interpolating a cubic or (better) a quadratic bezier spline. The bezier spline would be defined by known x,y coordinates of n control points. I found spline references both in scipy.interpolate and in scipy.signal. Which of the spline "stuff" in scipy in best suited for me ? Thanks for any help, Sebastian Haase

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Finding local minima of greater than a given depth
by Zane Selvans 14 Aug '08

14 Aug '08

Is there a function within scipy somewhere which will, given an array representing values of a function, find all the local minima having a depth greater than some specified minimum? The following works great for smooth functions, but when the data has noise in it, it also returns all of the (very) local minima, which I don't want. The functions I'm working with are periodic (hence the modulo in the indices for endpoint cases). Or, if there isn't such a built in functionality, what's the right way to measure the depth of a local minimum? def local_minima(fitlist): minima = [] for i in range(len(fitlist)): if fitlist[i] < fitlist[mod(i+1,len(fitlist))] and fitlist[i] < fitlist[mod(i-1,len(fitlist))]: minima.append(fitlist[i]) minima.sort() good_indices = [ fitlist.index(fit) for fit in minima ] good_fits = [ fit for fit in minima ] return(good_indices, good_fits) -- Zane Selvans Amateur Earthling http://zaneselvans.org zane(a)ideotrope.org 303/815-6866 PGP Key: 55E0815F

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SOM in scipy.cluster
by Eric Bruning 14 Aug '08

14 Aug '08

Greetings, I'm considering using self-organizing maps for mining some lightning data, and info.py in scipy.cluster mentions that implementation of self-organizing maps is under development. I've found a few examples written in python around the web, but none that are likely to be efficient enough for my use. Is there still interest in including SOM in scipy? I'd be happy to coordinate on a contribution if nothing else is under way. Thanks, Eric

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ANN: HDF5 for Python (h5py) 0.3.0
by Andrew Collette 14 Aug '08

14 Aug '08

======================================= Announcing HDF5 for Python (h5py) 0.3.0 ======================================= HDF5 for Python (h5py) is a general-purpose Python interface to the Hierarchical Data Format library, version 5. HDF5 is a versatile, mature scientific software library designed for the fast, flexible storage of enormous amounts of data. The h5py project has been under informal development for a few months now, and has reached the point where it might be generally useful to others. Unlike the fantastic PyTables project, h5py aims to provide access to the full HDF5 C library, although in a more Pythonic fashion. Almost all of the HDF5 1.6.X API is covered, with improvements like: - object-oriented identifiers with reference counting - automatic raising of Python exceptions for HDF5 errors - conversion between NumPy and HDF5 datatypes It also includes a set of high-level, pure-Python classes which represent basic HDF5 abstractions like files, groups, and datasets, using native Python and NumPy infrastructure. For example, datasets carry a shape tuple and dtype, and support partial I/O via the standard extended slicing syntax. The primary focus of the project is read/write interoperability with existing HDF5 data; using Python and the NumPy package, you can access data in HDF5 format, process it, and write files that any HDF5-aware program can understand. Automatic conversion is provided between NumPy and HDF5 datatypes; almost all NumPy types can be transparently converted to their HDF5 equivalents. This includes constructs like complex numbers in addition to arbitrarily nested compound ("recarray") data types. Resources ========= Python 2.5 and Numpy >= 1.0.3 are required. For UNIX, a C compiler is also required which can build Python extensions. HDF5 versions 1.6.5, 1.6.7, 1.8.0 and 1.8.1 are supported. The Windows installer includes HDF5 1.8.1. Source installers for UNIX and an integrated installer for Windows are available from the Google Code development page: http://h5py.googlecode.com Comprehensive documentation, including installation instructions and a quick-start guide, is available at: http://h5py.alfven.org You can read more about the HDF5 library at the HDF Group web site: http://www.hdfgroup.com/HDF5 *** This project is NOT affiliated with the HDF Group. *** All code for this project is released under the BSD license. Thanks ====== Thanks to D. Dale, D. Brooks, E. Lawrence for their comments and suggestions in development, and the PyTables project for general inspiration, along with "definitions.pxd". :) ---- Andrew Collette http://www.alfven.org Mail: "h5py" at the domain "alfven.org"

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