NumPy-Discussion August 2013

numpy-discussion@python.org

73 participants
69 discussions

Setter on array
by Hugo Gagnon 16 Aug '13

16 Aug '13

Hi, What is the best way, if any, to "do something" whenever array elements are changed in-place? For example, if I have a = arange(10), then setting a[3] = 1 would, say, call a function automatically. Thanks, -- Hugo Gagnon

4 3

Do I Still Have to Edit intelcompiler.py For ICC?
by Will Buckner 14 Aug '13

14 Aug '13

Hey guys, I normally build and install packages with pip, as I like to keep my toolchain up to date with new releases, etc. I was happy to find out both numpy and scipy will honor a ~/.numpy-site.cfg, but, since I need to build with the Intel compilers, I have to supply --compiler and --fcompiler. Is there any way to just do this in site config? Thanks! -Will

3 2

About ready to start 1.8 release process.
by Charles R Harris 14 Aug '13

14 Aug '13

Hi All, I think we are about ready to start on the 1.8 release. There are a few things left to do, but there are PR's for most of them. There are a couple of issues that I think need discussion. 1. Should diagonal return a view in this release or the next? 2. Should multiple field selection return a view in this release of the next? 3. Datetime64 will not be modified in this release. I'd also like to do a major whitespace clean up before the release, a lot has crept in. A style clean up, spaces after commas, etc., might also be desirable but I think it can wait and be done piecemeal. If there is anything that you think* has to be done*, please comment. Chuck

4 8

Optimize removing nan-values of dataset
by Thomas Goebel 14 Aug '13

14 Aug '13

Hi, i am trying to remove nan-values from an array of shape(40, 6). These nan-values at point data[x] should be replaced by the mean of data[x-1] and data[x+1] if both values at x-1 and x+1 are not nan. The function nan_to_mean (see below) is working but i wonder if i could optimize the code. I thought about something like 1. Find all nan values in array: nans = np.isnan(dataarray) 2. Check if values before, after nan indice are not nan 3. Calculate mean While using this script for my original dataset of shape(63856, 6) it takes 139.343 seconds to run it. And some datasets are even bigger. I attached the example_dataset.txt and the example.py script. Thanks for any help, Tom def nan_to_mean(arr): for cnt, value in enumerate(arr): # Check if first value is nan, if so continue if cnt == 0 and np.isnan(value): continue # Check if last value is nan: # If x-1 value is nan dont do anything! # If x-1 is float, last value will be value of x-1 elif cnt == (len(arr)-1): if np.isnan(value) and not np.isnan(arr[cnt-1]): arr[cnt] = arr[cnt-1] # If the first values of file are nan ignore them all elif np.isnan(value) and np.isnan(arr[cnt-1]): continue # Found nan value and x-1 value is of type float elif np.isnan(value) and not np.isnan(arr[cnt-1]): # Check if x+1 value is not nan if not np.isnan(arr[cnt+1]): arr[cnt] = '%.1f' % np.mean(( arr[cnt-1],arr[cnt+1])) # If x+1 value is nan, go to next value else: for N in xrange(2, 30): if cnt+N == (len(arr)): break elif not np.isnan(arr[cnt+N]): arr[cnt] = '%.1f' % np.mean( (arr[cnt-1], arr[cnt+N])) return arr

3 4

Do the prebuilt packages work with the python version that I compile myself?
by Peng Yu 13 Aug '13

13 Aug '13

Hi, I compile the latest python myself on Ubuntu. In this case, I think the packages listed on the following webpage does not work with the python version that I compiled. Am I correct? Thanks. http://www.scipy.org/install.html -- Regards, Peng

2 1

How to compile numpy on ubuntu
by Peng Yu 13 Aug '13

13 Aug '13

Hi, The instructions for compiling numpy on ubuntu seems to be very outdated. Could anybody provide an updated instruction on installing numpy? Thanks. http://docs.scipy.org/doc/numpy/user/install.html -- Regards, Peng

2 1

Reading footer lines
by Resmi 13 Aug '13

13 Aug '13

Hi, I've a list of long files of numerical data ending with footer lines (beginning with #). I am using numpy.loadtxt to read the numbers, and loadtxt ignores these footer lines. I want the numpy code to read one of the footer lines and extract words from it. Is there a way to use loadtxt for this? If there weren't many files I could have used the line number (which keep varying between the files) of the footer line along with *linecache.* Nevertheless there should be a generic way to do this in numpy? As a workaround, I've tried using os.system along with grep. And I get the following output : *>>> os.system("grep -e 'tx' 'data.dat' ")* * ## tx = 2023.06 * *0* Why is there a 0 in the output? The file has no blank lines. Since I want the value 2023.06 in the numpy code for later use I tried to pipe the output to a variable:- *test = os.system(command)* But that isn't working as *test* is getting assigned the value 0. Tried *subprocess.call(['grep','-e','tx','data.dat'])* which is also ending up in the same fashion. It'll be great if I can get to know (i) a way to read the footer lines (ii) to sort out the operation of os.system and subprocess.call output processing. Thanks, Resmi

5 4

numpy bug with negative int pow
by Dmitrey 13 Aug '13

13 Aug '13

Python 3.3.1 (default, Apr 17 2013, 22:32:14) [GCC 4.7.3] on linux >>> import numpy >>> numpy.__version__ '1.8.0.dev-d62f11d' >>> numpy.array((1,2,3)) / 2 array([ 0.5, 1. , 1.5]) #ok, but since division of integer arrays has been converted to float, pow is expected as well, but it's not: >>> numpy.array((1,2,3)) ** -1 array([1, 0, 0], dtype=int32) >>> numpy.array((1,2,3)) ** -2 array([1, 0, 0], dtype=int32) >>> 3**-1 0.3333333333333333 D.

1 0

Using as_strided to avoid copy on repeat (with 2-dimensional array)
by Nicolas Rougier 13 Aug '13

13 Aug '13

Hi, I have a (n,2) shaped array representing points and I would like to double each point as in: A = np.arange(10*2).reshape(10,2) B = np.repeat( A, 2, axis=0 ) Is it possible to do the same using 'as_strided' to avoid copy (and still get the same output shape for B) ? I found this reference: http://stackoverflow.com/questions/5564098/repeat-numpy-array-without-repli… but did not manage to adapt it to my case. Bonus question (if previous 'as_strided' trick is possible), would this work or do I need a different construct ? A = np.arange(10*2).reshape(10,2) B = np.repeat( A[::2], 2, axis=0 ) Nicolas

3 2

quickselect
by Charles R Harris 12 Aug '13

12 Aug '13

Hi All, There is a PR <https://github.com/numpy/numpy/pull/3360> adding quickselect to numpy as a function `partition`. Comments on name and exposure in the numpy API are welcome. Chuck

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NumPy-Discussion August 2013