Mailman 3 December 2009 - NumPy-Discussion

git gui
by Charles R Harris Dec. 9, 2009

Dec. 9, 2009

There is a new git gui <http://www.syntevo.com/smartgit/index.html> out. Some windows users might like to give it a try and report back. Chuck

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Release blockers for 1.4.0 ?
by David Cournapeau Dec. 9, 2009

Dec. 9, 2009

Hi, There are a few issues which have been found on numpy 1.4.0, which worry me: # 1317: segfaults for integer division overflow # 1318: all FPU exceptions ignored by default #1318 worries me the most: I think it is a pretty serious regression, since things like this go unnoticed: x = np.array([1, 2, 3, 4]) / 0 # x is an array of 0, no warning printed But fixing it reveals quite a few problems while running the test suite (invalid value warnings appear 518 times), and I think it is a bite late to fix those. What do people think ? cheers, David

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Applying Patch #1085
by Travis Oliphant Dec. 9, 2009

Dec. 9, 2009

What do people think of applying patch #1085. This patch makes a copy of inputs when the input and output views overlap in ways in which one computation will change later computations. i.e. what is the output of? x = ones((10,3)) x += x[1] I think that copying in such instances is a good idea and it looks like the patch has received careful review. The only downsides I can see are: 1) Increased overhead of the check --- this looks very small 2) Subtle change in behavior --- it's hard to imagine that somebody would be relying on the specific behavior of overlapping views writing into the same output (I know it's something we warn against in teaching) -- but switching from it is a change. Anything else? -Travis

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slices of structured arrays?
by Ernest Adrogué Dec. 9, 2009

Dec. 9, 2009

Hello, Here's a structured array with fields 'a','b' and 'c': s=[(i,int) for i in 'abc'] t=np.zeros(1,s) It has the form: array([(0, 0, 0)] I was wondering if such an array can be accessed like an ordinary array (e.g., with a slice) in order to set multiple values at once. t[0] does not access the first element of the array, instead it returns the whole array. In [329]: t[0] Out[329]: (1, 0, 0) But this array is type np.void and does not support slices. t[0][0] returns the first element, but t[0][:2] fails with IndexError: invalid index. Any suggestion? Ernest

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Bytes vs. Unicode in Python3
by Pauli Virtanen Dec. 9, 2009

Dec. 9, 2009

Hi, The Python 3 porting needs some decisions on what is Bytes and what is Unicode. I'm currently taking the following approach. Comments? *** dtype field names Either Bytes or Unicode. But 'a' and b'a' are *different* fields. The issue is that: Python 2: {'a': 2}[u'a'] == 2, {u'a': 2}['a'] == 2 Python 3: {'a': 2}[b'a'], {b'a': 2}['a'] raise exceptions so the current assumptions in the C code of u'a' == b'a' cease to hold. dtype titles If Bytes or Unicode, work similarly as field names. dtype format strings, datetime tuple, and any other "protocol" strings Bytes. User can pass in Unicode, but it's converted using UTF8 codec. This will likely change repr() of various objects. Acceptable? -- Pauli Virtanen

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more recfunctions, structured array help
by John [H2O] Dec. 9, 2009

Dec. 9, 2009

I see record arrays don't have a masked_where method. How can I achieve the following for a record array: cd.masked_where(cd.co == -9999.) Or something like this. Thanks! -- View this message in context: http://old.nabble.com/more-recfunctions%2C-structured-array-help-tp26700380… Sent from the Numpy-discussion mailing list archive at Nabble.com.

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Can't set an element of a subset of an array, , ,
by alan＠ajackson.org Dec. 9, 2009

Dec. 9, 2009

Okay, I'm stuck. Why doesn't this work? In [226]: mask Out[226]: array([False, False, False, ..., False, False, False], dtype=bool) In [227]: mask[data['horizon']==i] Out[227]: array([ True, True, False, False, True, False, False, False, False, True, False, False, False, True, False, False, False, False, False, True, False, False, False, False, False, False, True, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, True, False, True, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, True, True, False, False, False, True, False, True, False, False, True, True, False, False, False, False, False, False, False, False, False, True, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, True, False, False, False, False, False, True, False, False, False, True, False, True, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, True, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, True, False, False, True, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False], dtype=bool) In [228]: mask[data['horizon']==i][2] Out[228]: False In [229]: mask[data['horizon']==i][2] = True In [230]: mask[data['horizon']==i][2] Out[230]: False -- ----------------------------------------------------------------------- | Alan K. Jackson | To see a World in a Grain of Sand | | alan(a)ajackson.org | And a Heaven in a Wild Flower, | | www.ajackson.org | Hold Infinity in the palm of your hand | | Houston, Texas | And Eternity in an hour. - Blake | -----------------------------------------------------------------------

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What protocol to use now?
by Christopher Barker Dec. 9, 2009

Dec. 9, 2009

Hi folks, There was just a question on the wxPython list about how to optimize some drawing of data in numpy arrays. Currently, wxPython uses PySequenceGetItem to iterate through an array, so you can imagine there is a fair bit of overhead in that. But what to use? We don't want to require numpy, so using the numpy API directly is out. Using the buffer interface makes it too hard to catch user errors. The array interface was made for this sort of thing, but is deprecated: http://docs.scipy.org/doc/numpy/reference/arrays.interface.html Is the new PEP 3118 protocol now (as of version 1.4) supported by numpy, at least for export? At the moment, a one-way street is OK for this application. thanks, -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker(a)noaa.gov

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Some incompatibilities in numpy trunk
by Gael Varoquaux Dec. 8, 2009

Dec. 8, 2009

I have a lot of code that has stopped working with my latest SVN pull to numpy. * Some compiled code yields an error looking like (from memory): "incorrect type 'numpy.ndarray'" Rebuilding it is sufficient. * I had some code doing: hashlib.md5(x).hexdigest() where x is a numpy array. I had to replace it by: hashlib.md5(np.getbuffer(x)).hexdigest() * Finally, I had to following failure: /home/varoquau/dev/enthought/ets/Mayavi_3.1.0/enthought/tvtk/array_handler.pyc in array2vtk(num_array, vtk_array) --> 298 result_array.SetVoidArray(z_flat, len(z_flat), 1) TypeError: argument 1 must be string or read-only buffer, not numpy.ndarray I can solve the problem using: result_array.SetVoidArray(numpy.getbuffer(z_flat), len(z_flat), 1) However, I am wondering: is this some incompatibility that has been introduced by mistake? I find it a bit strange that a '.x' release induces so much breakage, and I am afraid that it won't be popular amongst our users. Cheers, Gaël

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Complex zerodivision/negative powers not handled correctly
by Jörgen Stenarson Dec. 8, 2009

Dec. 8, 2009

Hi, I have observed a problem with complex zerodivision and negative powers. With a complex zero the result is either zero or NaN NaNj, the first one is clearly wrong and the other one I don't know what is most reasonable some kind of inf or a Nan. This problem has been reported in the tracker as #1271. In [1]: import numpy In [2]: numpy.__version__ Out[2]: '1.4.0rc1' In [3]: from numpy import * In [4]: array([-0., 0])**-1 Out[4]: array([-Inf, Inf]) In [5]: array([-0., 0])**-2 Out[5]: array([ Inf, Inf]) In [6]: array([-0.-0j, -0.+0j, 0-0j, 0+0j])**-2 Out[6]: array([ 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]) In [7]: array([-0.-0j, -0.+0j, 0-0j, 0+0j])**-1 Out[7]: array([ NaN NaNj, NaN NaNj, NaN NaNj, NaN NaNj]) In [8]: 1/array([-0.-0j, -0.+0j, 0-0j, 0+0j]) Out[8]: array([ NaN NaNj, NaN NaNj, NaN NaNj, NaN NaNj])

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