A toy-case for my problem:
I have a numpy array of size, say, 1000:
import numpy as np
a = np.arange(1000)
I also have a "projection array" p which is a mapping from a to another array b:
p = np.random.randint(0,1000,(1000,1000))
It is easy to get b from a using "fancy indexing":
b = a[p]
But b is not a view, as noted by several previous questions/answers and the numpy documentation.
Unfortunately, in my case only the values in a change over the course of a long simulation and using fancy indexing at each iteration to obtain b becomes very costly. I only read from b and do not modify it.
I understand it is not possible (yet) to solve this with fancy indexing.
I was wondering if anyone had a similar problem/bottleneck and came up with some other workaround?
baccessed in every iteration? If yes, there is no cheaper way than extracting all ofb– you might need to improve the algorithm in other ways. If no, you don't need to buildb, and instead of accessingb[i, j], you can usea[p[i, j]].