Efficiently generate numpy array from list comprehension output?
- by shootingstars
Is there a more efficient way than using numpy.asarray() to generate an array from output in the form of a list?
This appears to be copying everything in memory, which doesn't seem like it would be that efficient with very large arrays.
(Updated) Example:
import numpy as np
a1 = np.array([1,2,3,4,5,6,7,8,9,10]) # pretend this has thousands of elements
a2 = np.array([3,7,8])
results = np.asarray([np.amax(np.where(a1 > element)) for element in a2])
