Mailman 3 July 2013 - NumPy-Discussion

retrieving original array locations from 2d argsort
by Moroney, Catherine M (398D) 16 Jul '13

16 Jul '13

I know that there's an easy way to solve this problem, but I'm not sufficiently knowledgeable about numpy indexing to figure it out. Here is the problem: Take a 2-d array a, of any size. Sort it in ascending order using, I presume, argsort. Step through the sorted array in order, and for each element in the sorted array, retrieve what the corresponding (line, sample) indices in the original array are. For instance: a = numpy.arange(0, 16).reshape(4,4) a[0,:] = -1*numpy.arange(0,4) a[2,:] = -1*numpy.arange(4,8) asort = numpy.sort(a, axis=None) for idx in xrange(0, asort.size): element = asort[idx] !! Find the line and sample location in a that corresponds to the i-th element in assort Thank-you for your help, Catherine

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read-only or immutable masked array
by Gregorio Bastardo 15 Jul '13

15 Jul '13

Hi, I use masked arrays to mark missing values in data and found it very convenient, although sometimes counterintuitive. I'd like to make a pool of masked arrays (shared between several processing steps) read-only (both data and mask property) to protect the arrays from accidental modification (and the array users from hours of debugging). The regular ndarray trick array.flags.writeable = False is perfectly fine, but it does not work on ma-s. Moreover, mask hardening only protects masked elements, and does not raise error (as I'd expect). Could you recommend an easy way to set an ma read-only? Thanks, Gregorio

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PIL and NumPy
by Brady McCary 15 Jul '13

15 Jul '13

NumPy Folks, I want to load images with PIL and then operate on them with NumPy. According to the PIL and NumPy documentation, I would expect the following to work, but it is not. Python 2.7.4 (default, Apr 19 2013, 18:28:01) [GCC 4.7.3] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import numpy >>> numpy.version.version >>> >>> import Image >>> Image.VERSION '1.1.7' >>> >>> im = Image.open('big-0.png') >>> im.size (2550, 3300) >>> >>> ar = numpy.asarray(im) >>> ar.size 1 >>> ar.shape () >>> ar array(<PIL.PngImagePlugin.PngImageFile image mode=LA size=2550x3300 at 0x1E5BA70>, dtype=object) By "not working" I mean that I would have expected the data to be loaded/available in ar. PIL and NumPy/SciPy seem to be working fine independently of each other. Any guidance? Brady

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nansum, nanmean, nanvar, nanstd
by Charles R Harris 13 Jul '13

13 Jul '13

Hi All, I've been working on Benjamin's PR, which I took down as he didn't have time to finish it. I've made the following changes and thought I'd run them past others before putting up a new pull request. 1. The new functions are consolidated with the old ones inn (new) numpy/lib/nanfunctions.py. 2. There is a new test module numpy/lib/tests/test_nanfunctions.py 3. The functions punt to standard routines if the array is not inexact. 4. If the array is inexact, then so must be the optional out and dtype arguments. 5. Nans are returned for all nan axis, no warnings are raised. 6. If cnt - ddof <= 0 the result is Nan for that axis, no warnings are raised. 7. For scalar returns the type of the array, or the type given by the dtype option, is preserved. Number 7 does not hold for current mean, var, and std. I propose that those functions be fixed. Chuck

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numpy.sign query
by Alan G Isaac 13 Jul '13

13 Jul '13

The docs for numpy.sign at http://docs.scipy.org/doc/numpy/reference/generated/numpy.sign.html do not indicate how complex numbers are handled. Currently, np.sign appears to return the sign of the real part as a complex value. Was this an explicit choice? Was x/abs(x) considered (for non-zero elements)? Thanks, Alan Isaac

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flip array on axis
by Andreas Hilboll 12 Jul '13

12 Jul '13

Hi, there are np.flipud and np.fliplr methods to flip 2d arrays on the first and second dimension, respectively. What can I do to flip an array on an axis which I don't know before runtime? I'd really like to see a np.flip(arr, axis) method which lets me specify which axis to flip on. Any ideas? Cheers, Andreas.

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new free software for knapsack problem
by Dmitrey 12 Jul '13

12 Jul '13

Hi all, FYI new free software for knapsack problem ( http://en.wikipedia.org/wiki/Knapsack_problem ) has been made (written in Python language); it can solve possibly constrained, possibly (with interalg ) nonlinear and multiobjective problems with specifiable accuracy. Along with interalg lots of MILP solvers can be used. See http://openopt.org/KSP for details. Regards, Dmitrey.

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f2py and setup.py how can I specify where the .so file goes?
by Jose Gomez-Dans 12 Jul '13

12 Jul '13

Hi, I am building a package that exposes some Fortran libraries through f2py. The packages directory looks like this: setup.py my_pack/ | |---------->__init__.py |----------> some.pyf |-----------> code.f90 I thoughat that once installed, I'd get the .so and __init__.py in the same directory (namely ~/.local/lib/python2.7/site-packages/my_pack/). However, I get ~/.local/lib/python2.7/site-packages/mypack_fortran.so ~/.local/lib/python2.7/site-packages/my_pack__fortran-1.0.2-py2.7.egg-info ~/.local/lib/python2.7/site-packages/my_pack/__init__.py Thet setup file is this at the end, I am clearly missing some option here to move the *.so into the my_pack directory.... Anybody know which one? Cheers Jose [setup.py] #!/usr/bin/env python def configuration(parent_package='',top_path=None): from numpy.distutils.misc_util import Configuration config = Configuration(parent_package,top_path) config.add_extension('mypack_fortran', ['the_pack/code.f90'] ) return config if __name__ == "__main__": from numpy.distutils.core import setup # Global variables for this extension: name = "mypack_fortran" # name of the generated python extension (.so) description = "blah" author = "" author_email = "" setup( name=name,\ description=description, \ author=author, \ author_email = author_email, \ configuration = configuration, version="1.0.2",\ packages=["my_pack"])

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Unique() function and avoiding Loop
by Bakhtiyor Zokhidov 10 Jul '13

10 Jul '13

Hi everybody, I have a problem with sorting out the following function. What I expect is that I showed as an example below. Two problems are encountered to achieve the result: 1) The function sometimes can't not sort as expected: I showed an example for that below. 2) I could not do vectorization to avoid loop. OR, Is there another way to solve that problem?? Thanks in advance Example: data = ['', 12, 12, 423, '1', 423, -32, 12, 721, 345]. Expected result: [0, 12, 12, 423, 0, 423, -32, 12, 721, 345], here, '' and '1' are string type I need to replace them by zero The result I got: ['', 12, 12, 423, '1', 423, -32, 12, 721, 345] import numpy as np def func(data): x, i = np.unique(data, return_inverse = True) f = [ np.where( i == ind )[0] for ind in range(len(x)) ] new_data = [] # Obtain 'data' arguments and give these data to New_data for i in range(len(x)): if np.size(f[i]) > 1: for j in f[i]: if str(data[j]) <> '': new_data.append(data[j]) else: data[j] = 0 return data -- Bakhtiyor Zokhidov

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np.ma.argmax not respecting the mask?
by Chao YUE 09 Jul '13

09 Jul '13

Dear all, I am using 1.7.1 version of numpy and np.ma.argmax is not repecting the mask? I expect for all data that are masked, it should also return a mask, but this is not the case. In [96]: d3 Out[96]: masked_array(data = [[-- -- -- -- 4] [5 -- 7 8 9]], mask = [[ True True True True False] [False True False False False]], fill_value = 6) In [97]: np.ma.argmax(d3,axis=0) Out[97]: array([1, 0, 1, 1, 1]) In [98]: np.__version__ Out[98]: '1.7.1' Can I file a bug report on this? thanks, Chao -- *********************************************************************************** Chao YUE Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) UMR 1572 CEA-CNRS-UVSQ Batiment 712 - Pe 119 91191 GIF Sur YVETTE Cedex Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 ************************************************************************************

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