Like resizing, removing elements from an NumPy array is a slow operation (especially for large arrays since it requires allocating space and copying all the data from the original array to the new array).
It should be avoided if possible.
Often you can avoid it by working with a masked array instead. For example, consider the array a
:
import numpy as np
a = np.array([0,1,2,3,4,5,5,6,7,8,9])
print(a)
print(a.sum())
# [0 1 2 3 4 5 5 6 7 8 9]
# 50
We can mask its value at index 3 and can perform a summation which ignores masked elements:
a = np.ma.array(a, mask=False)
a.mask[3] = True
print(a)
print(a.sum())
# [0 1 2 -- 4 5 5 6 7 8 9]
# 47
Masked arrays also support many operations besides sum
.
If you really need to, it is also possible to remove masked elements using the compressed
method:
print(a.compressed())
# [0 1 2 4 5 5 6 7 8 9]
But as mentioned above, avoid it if possible.
与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…