1

I am performing prioritized sweeping for which I have a matrix which has 1000*1000 cells (gridworld) whose cells I have to access repeatedly in a while true loop for assignment (I am not essentially iterating over the list but all cells are accessed more than once). Right now I'm mapping my positions (i,j) of matrix to store in a 1D array. So my 1000*1000 matrix is one large 1*(1000000) list. I am wondering if this is going to slow down fetch time and I am better off using 1000*1000 matrix. Also which is faster numpy or using lists ? It would be great if you could help me out with this!

Improve this question
3
  • You can use timeit to check. Commented Apr 16, 2018 at 17:58
  • Check this one: stackoverflow.com/questions/35232406/… Commented Apr 16, 2018 at 18:32
  • Turns out numpy was slowing me down. Thanks! Commented Apr 16, 2018 at 21:28
Related questions
1
Efficiency of 2D indexing methods in Numpy
2
Is there a better way of getting elements with x,y coordinates from a numpy array?
0
Python: Fastest Way to Traverse 2-D Array
Load 7 more related questions Show fewer related questions

0

Reset to default

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Start asking to get answers

Find the answer to your question by asking.

Ask question

Explore related questions

See similar questions with these tags.