Suppose I have a function F(), which is defined for 1-dim arguments. If the user passes an n>1 dim array, I want to apply F to each 1-dim view. For example, for a 2-d array, apply F to each row and return a 2-d result. For a 3-d array, select each 2-d subarray and see above. Return 3-d result. Any suggestions on how to code something like this in numpy?
On Sun, Oct 07, 2007 at 06:52:11AM -0400, Neal Becker wrote:
Suppose I have a function F(), which is defined for 1-dim arguments. If the user passes an n>1 dim array, I want to apply F to each 1-dim view.
For example, for a 2-d array, apply F to each row and return a 2-d result.
For a 3-d array, select each 2-d subarray and see above. Return 3-d result.
Any suggestions on how to code something like this in numpy?
Code your function so that it works well for 2D arrays (using axis=-1 and co), then use a decorator on it so that if you pass it an N-d array, it transforms it in a 2D array, passes it to the decorator, then transforms the output back to the right shape. The idea is quite theoretical, and I have never gotten to implement it, because when I was facing similar problems, it didn't come to my mind, but I think it can work in a very general way. Gaël
On Sun, Oct 07, 2007 at 06:52:11AM -0400, Neal Becker wrote:
Suppose I have a function F(), which is defined for 1-dim arguments. If the user passes an n>1 dim array, I want to apply F to each 1-dim view.
For example, for a 2-d array, apply F to each row and return a 2-d result.
For a 3-d array, select each 2-d subarray and see above. Return 3-d result.
Any suggestions on how to code something like this in numpy?
Not the most efficient way, but easy to read and understand: import numpy as N def func(a): return a.shape z = N.zeros((2,2,2,2)) print N.array([func(sub) for sub in z]) Regards Stéfan
participants (3)
-
Gael Varoquaux -
Neal Becker -
Stefan van der Walt