Mailman 3 July 2004 - NumPy-Discussion

I move your "Bugs" reports...
by Todd Miller 16 Jul '04

16 Jul '04

Not infrequently even very experienced numarray contributors file bug reports in the numpy "Bugs" tracker. Because numpy is a shared SF project with both Numeric and numarray, numarray bugs are actually tracked in the "Numarray Bugs" tracker, here: http://sourceforge.net/tracker/?atid=450446&group_id=1369&func=browse "Numarray Bugs" can also be found through the "Tracker" link at the top of any numpy SF web page. So, don't worry, your painstaking reports are not getting deleted, they're getting relocated to a place where *only* numarray bugs live. There's probably a better way to do this, but until I find it or someone tells me about it, I thought I should tell everyone what's going on. Thanks to everybody who takes the time to fill out bug reports to make numarray better... Regards, Todd

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NA.dot transposing in place
by Curzio Basso 15 Jul '04

15 Jul '04

Hi all. I wonder if anyone noticed the following behaviour (new in 1.0) of the dot/matrixmultiply functions: >>> alpha = NA.arange(10, shape = (10,1)) >>> beta = NA.arange(10, shape = (10,1)) >>> NA.dot(alpha, alpha) array([[285]]) >>> alpha.shape # here it looks like it's doing the transpose in place (1, 10) >>> NA.dot(beta, alpha) array([[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [ 0, 2, 4, 6, 8, 10, 12, 14, 16, 18], [ 0, 3, 6, 9, 12, 15, 18, 21, 24, 27], [ 0, 4, 8, 12, 16, 20, 24, 28, 32, 36], [ 0, 5, 10, 15, 20, 25, 30, 35, 40, 45], [ 0, 6, 12, 18, 24, 30, 36, 42, 48, 54], [ 0, 7, 14, 21, 28, 35, 42, 49, 56, 63], [ 0, 8, 16, 24, 32, 40, 48, 56, 64, 72], [ 0, 9, 18, 27, 36, 45, 54, 63, 72, 81]]) >>> alpha.shape, beta.shape # but not the second time ((1, 10), (10, 1)) ------------------------------------------------- Can someone explain me what's going on? thanks, curzio

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Re: [Numpy-discussion] sum() and mean() broken?
by Gary Ruben 15 Jul '04

15 Jul '04

Thanks Todd, It's under Win98 as you suspected and the selftest definitely doesn't pass. Are you planning on supporting Win98? If so, I'll revert to numarray 0.9. Otherwise, I'll just use Numeric for this task and restrict playing with numarray 1.0 to my Win2k laptop. thanks, Gary -- _______________________________________________ Talk More, Pay Less with Net2Phone Direct(R), up to 1500 minutes free! http://www.net2phone.com/cgi-bin/link.cgi?143

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static void** libnumarray_API
by Mathieu Gontier 15 Jul '04

15 Jul '04

Hello, I am developping FEM bendings from a C++ code to Python with Numarray. So, I have the following problem. In the distribution file 'libnumarray.h', the variable 'libnumarray_API' is defined as a static variable (because of the symbol NO_IMPORT is not defined). Then, I understand that all the examples are implemented in a unique file. But, in my project, I must edit header files and source files in order to solve other problems (like cycle includes). So, I have two different source files which use numarray : - the file containing the 'init' function which call the function 'import_libnumarray()' (which initialize 'libnumarray_API') - a file containing implementations, more precisely an implementation calling numarray functionnalities: with is 'static' state, this 'libnumarray_API' is NULL... I tried to compile NumArray with the symbol 'NO_IMPORT' (see libnumarray.h) in order to have an extern variable. But this symbol doesn't allow to import numarray in the python environment. So, does someone have a solution allowing to use NumArray API with header/source files ? Thanks, Mathieu Gontier

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sum() and mean() broken?
by Gary Ruben 15 Jul '04

15 Jul '04

I'm getting tracebacks on even the most basic sum() and mean() calls in numarray 1.0 under Windows. Apologies if this has already been reported. Gary >>> from numarray import * >>> arange(10).sum() Traceback (most recent call last): File "<pyshell#4>", line 1, in -toplevel- arange(10).sum() File "C:\APPS\PYTHON23\Lib\site-packages\numarray\numarraycore.py", line 1106, in sum return ufunc.add.reduce(ufunc.add.areduce(self, type=type).flat, type=type) error: Int32asInt64: buffer not aligned on 8 byte boundary. -- _______________________________________________ Talk More, Pay Less with Net2Phone Direct(R), up to 1500 minutes free! http://www.net2phone.com/cgi-bin/link.cgi?143

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Re: [Numpy-discussion] How to median filter a masked array?
by Russell E Owen 14 Jul '04

14 Jul '04

At 9:50 AM -0700 2004-07-14, Paul F. Dubois wrote: >The median filter is prepared to take an argument of a numarray >array but ignorant of and unprepared to deal with masked values. >Using the __array__ trick, both Numeric.MA and numarray.ma would >'know' this and therefore replace the missing values in the filter's >argument with the 'fill value' for that type -- a big number in the >case of real arrays. You could explicitly choose that value (say >using the overall median of the data m) by passing x.filled(m) >rather than x to the filter. > >If there is no such value, you probably do have to do it in C. If >you wrote it in C, how would you treat missing elements? BTW it >wouldn't be that hard; just pass both the array and its mask as >separate elements to a C routine and use SWIG to hook it up. I already have routines that handle masked data in C to create a radial profiles from 2-d integer data (since I could not figure out how to do that in numarray). I chose to pass the mask as a separate array, since I could not find any C interface for numarray.ma and since NaN made no sense for integer data. That code was pretty straightforward. I wish I could have found a simple way to support multiple array types. I thought using C++ with prototypes would be the ticket, but absent any examples and after looking through the numarray code, I gave up and took the easy way out. (I didn't use SWIG, though, I just hand coded everything. Maybe that was a mistake.) I confess that makes me worry about the underpinnings of numarray. It seems an obvious candidate to be written in C++ with prototypes. I hate to think what the developers have to go through, instead. In any case, writing a median filter is a bigger deal than taking a radial profile, and since one already existed I thought I'd ask. >I doubt NaN would help you here; you'd still have to figure out what >to do in those places. Numeric did not have support for NaN because >there were portability problems. Probably still are. And you still >are stuck in a lot of cases anyway. Well, NaN isn't very general in any case, since it's meaningless for integer data. So maybe that's a red herring. (Though if NaN had worked to mask data I would cheerfully have converted my images to floats to take advantage of it!). What's really wanted is a more unified approach to masked data. I suppose it's pie in the sky, but I sure wish most the numarray functions took an optional mask array (or accepted a numarray.ma object -- nice for the user, but probably too painful for words under the hood). I don't think there are major issues with what to do with masked data. Simply ignoring it works in most cases, e.g. mean, std dev, sum, max... In some cases one needs the new mask as output (e.g. matrix multiply). Filtering is a bit subtle: can masked data be treated the same as data off the edge? I hope so, but I'm not sure. Anyway, I am grateful for what we do have. Without Numeric or numarray I would have to write all my image processing code in a different language. -- Russell

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How to median filter a masked array?
by Russell E Owen 14 Jul '04

14 Jul '04

I want to 3x3 median filter a masked array (2-d array of ints -- an astronomical image), where the masked data and points off the edge are excluded from the local median calculation. Any suggestions for how to do this efficiently? I suspect I have to write it in C, which is an unpleasant prospect. I tried using NaN for points to mask out, but the median filter seems to handle those as "infinity", or something equally inappropriate. In a related vein, has Python come along far enough that it would be reasonable to add support for NaN to numarray -- in the sense that statistics calculations, filters, etc. could be convinced to ignore NaNs? Obviously this support would be contingent on compiling python with IEEE floating point support, but I suspect that's the default on most platforms these days. -- Russell

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ANN matplotlib-0.60.2: python graphs and charts
by John Hunter 14 Jul '04

14 Jul '04

matplotlib is a 2D plotting library for python. You can use matplotlib interactively from a python shell or IDE, or embed it in GUI applications (WX, GTK, and Tkinter). matplotlib supports many plot types: line plots, bar charts, log plots, images, pseudocolor plots, legends, date plots, finance charts and more. What's new since matplotlib 0.50 This is the first wide release in 5 months and there has been a tremendous amount of development since then, with new backends, many optimizations, new plotting types, new backends and enhanced text support. See http://matplotlib.sourceforge.net/whats_new.html for details. * Todd Miller's tkinter backend (tkagg) with good support for interactive plotting using the standard python shell, ipython or others. matplotlib now runs on windows out of the box with python + numeric/numarry * Full Numeric / numarray integration with Todd Miller's numerix module. Prebuilt installers for numeric and numarray on win32. Others, please set your numerix settings before building matplotlib, as described on http://matplotlib.sourceforge.net/faq.html#NUMARRAY * Mathtext: you can write TeX style math expressions anywhere in your figure. http://matplotlib.sourceforge.net/screenshots.html#mathtext_demo. * Images - figure and axes images with optional interpolated resampling, alpha blending of multiple images, and more with the imshow and figimage commands. Interactive control of colormaps, intensity scaling and colorbars - http://matplotlib.sourceforge.net/screenshots.html#layer_images * Text: freetype2 support, newline separated strings with arbitrary rotations, Paul Barrett's cross platform font manager. http://matplotlib.sourceforge.net/screenshots.html#align_text * Jared Wahlstrand's SVG backend (alpha) * Support for popular financial plot types - http://matplotlib.sourceforge.net/screenshots.html#finance_work2 * Many optimizations and extension code to remove performance bottlenecks. pcolors and scatters are an order of magnitude faster. * GTKAgg, WXAgg, TkAgg backends for http://antigrain.com (agg) rendering in the GUI canvas. Now all the major GUIs (WX, GTK, Tk) can be used with a common (agg) renderer. * Many new examples and demos - see http://matplotlib.sf.net/examples or download the src distribution and look in the examples dir. Documentation and downloads available at http://matplotlib.sourceforge.net. John Hunter

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RE: [Numpy-discussion] a 'for' loop within another 'for' loop?
by Sebastien.deMentendeHorne＠electrabel.com 14 Jul '04

14 Jul '04

I could not resist to propose an other solution: r = array([0,2,5,6,8]) l = (r[:,NewAxis] + r[NewAxis,:]).flat -----Original Message----- From: Hee-Seng Kye [mailto:kyeser@earthlink.net] Sent: mercredi 14 juillet 2004 4:22 To: numpy-discussion(a)lists.sourceforge.net Subject: [Numpy-discussion] a 'for' loop within another 'for' loop? Hi. I wrote a program to calculate sums of every possible combinations of two indices of a list. The main body of the program looks something like this: r = [0,2,5,6,8] l = [] for x in range(0, len(r)): for y in range(0, len(r)): k = r[x]+r[y] l.append(k) print l 1. I've heard that it's not a good idea to have a 'for' loop within another 'for' loop, and I was wondering if there is a more efficient way to do this. 2. Does anyone know if there is a built-in function or module that would do the above task in NumPy or Numarray (or even in Python)? I would really appreciate it if anyone could let me know. Thanks for your help!

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a 'for' loop within another 'for' loop?
by Hee-Seng Kye 14 Jul '04

14 Jul '04

Hi. I wrote a program to calculate sums of every possible combinations of two indices of a list. The main body of the program looks something like this: r = [0,2,5,6,8] l = [] for x in range(0, len(r)): for y in range(0, len(r)): k = r[x]+r[y] l.append(k) print l 1. I've heard that it's not a good idea to have a 'for' loop within another 'for' loop, and I was wondering if there is a more efficient way to do this. 2. Does anyone know if there is a built-in function or module that would do the above task in NumPy or Numarray (or even in Python)? I would really appreciate it if anyone could let me know. Thanks for your help!

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