is it possible to get values from numpy array based on list of indexes like i.e 1 and 3? Then, I want to put another values instead of them.
Here is example:
import numpy as np
array = np.array([0, 1, 2, 8, 4, 9, 1, 2])
idx = [3, 5]
So I want to replace X[3] = 8 and X[5] = 9 with another values but I do not want to this in a loop because I could have large array. Is it a way or maybe a function to do operations like this but not in a loop?
You should use array[idx] = new_values. This approach is much faster than native python loops. But you will have to convert 'idx' and 'new_values' to numpy arrays as well.
import numpy as np
n = 100000
array = np.random.random(n)
idx = np.random.randint(0, n, n//10)
new_values = np.random.random(n//10)
%time array[idx] = new_values
Wall time: 257 µs
def f():
for i, v in zip(idx, new_values):
array[i] = v
%time f()
Wall time: 5.93 ms
Use np.r_:
larr = np.array([0, 1, 2, 8, 4, 9, 1, 2])
larr[np.r_[3, 5]]
Output
array([8, 9])
As @MadPhysicist suggest, using larr[np.array([3, 5])] will work also, and is faster.
np.array?larr[np.array([3, 5])]. Not shorter, but faster