Re: [Numpy-discussion] numpy reference array
Chris Barker - NOAA Federal chris.barker at noaa.gov writes: check out stride tricks for clever things you can do. But numpy does require that the data in your array be a contiguous block, in order, so you can't arbitrarily re-arrange it while keeping a view. HTH, -Chris Hi Chris, Thanks for the reply, you've just saved me a lot of time. I did run across 'views' but it looked like I couldn't have my data arbitrarily arranged. Thank you for confirming that. Unfortunately my desired view does not fit a neat striding pattern. Cheers, Matt ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] numpy reference array
Is it possible to create a numpy array which points to the same data in a different numpy array (but in different order etc)? For example: Code: -- import numpy as np a = np.arange(10) ids = np.array([0,0,5,5,9,9,1,1]) b = a[ids] a[0] = -1 b[0] #should be -1 if b[0] referenced the same data as a[0] 0 -- ctypes almost does it for me, but the access is inconvenient. I would like to access b as a regular numpy array: Code: -- import numpy as np import ctypes a = np.arange(10) ids = np.array([0,0,5,5,9,9,1,1]) b = [a[id:id+1].ctypes.data_as(ctypes.POINTER(ctypes.c_long)) for id in ids] a[0] = -1 b[0][0] #access is inconvenient -1 -- Some more information: I've written a finite-element code, and I'm working on optimizing the python implementation. Profiling shows the slowest operation is the re-creation of an array that extracts edge degrees of freedom from the volume of the element (similar to b above). So, I'm trying to avoid copying the data every time, and just setting up 'b' once. The ctypes solution is sub-optimal since my code is mostly vectorized, that is, later I'd like to something like Code: -- c[ids] = b[ids] + d[ids] -- where c, and d are the same shape as b but contain different data. Any thoughts? If it's not possible that will save me time searching. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] numpy reference array
On Wed, Mar 13, 2013 at 6:56 AM, Matt U mpuec...@mit.edu wrote: Is it possible to create a numpy array which points to the same data in a different numpy array (but in different order etc)? You can do this (easily), but only if the different order can be defined in terms of strides. A simple example is a transpose: In [3]: a = np.arange(12).reshape((3,4)) In [4]: a Out[4]: array([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11]]) In [5]: b = a.T In [6]: b Out[6]: array([[ 0, 4, 8], [ 1, 5, 9], [ 2, 6, 10], [ 3, 7, 11]]) # b is the transpose of a # but a view on the same data block: # change a: In [7]: a[2,1] = 44 In [8]: a Out[8]: array([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 44, 10, 11]]) # b is changed, too. In [9]: b Out[9]: array([[ 0, 4, 8], [ 1, 5, 44], [ 2, 6, 10], [ 3, 7, 11]]) check out stride tricks for clever things you can do. But numpy does require that the data in your array be a contiguous block, in order, so you can't arbitrarily re-arrange it while keeping a view. HTH, -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/ORR(206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
