Most efficient way to reverse a numpy array
numpy, python
Solution
reversed_arr = arr[::-1]
gives a reversed view into the original array `arr`. Any changes made to the original array `arr` will also be immediately visible in `reversed_arr`. The underlying data buffers for `arr` and `reversed_arr` are shared, so creating this view is always instantaneous, and does not require any additional memory allocation or copying for the array contents.
See also, this discussion on NumPy views: How do I create a view onto a NumPy array?
Possible solutions to performance problems regarding views
Are you re-creating the view more often than you need to? You should be able to do something like this:
arr = np.array(some_sequence)
reversed_arr = arr[::-1]
do_something(arr)
look_at(reversed_arr)
do_something_else(arr)
look_at(reversed_arr)
I'm not a numpy expert, but this seems like it would be the fastest way to do things in numpy. If this is what you are already doing, I don't think you can improve on it.
Problem
Believe it or not, after profiling my current code, the repetitive operation of numpy array reversion ate a giant chunk of the running time. What I have right now is the common view-based method: ``` reversed_arr = arr[::-1] ``` Is there any other way to do it more efficiently, or is it just an illusion from my obsession with unrealistic numpy performance?