I have two arrays, for example a = np.array([[0, 2, 0], [0, 2, 0]])
and b = np.array([1, 1, 2])
.
What I want to do is to create a new array with the same size of a, but where each entry (i,j) corresponds to the value of list b with the index given by a[i][j]
. Formally, I want new_list[i][j] = b[a[i][j]]
.
I know that this can be achieved with for loops, as shown in the code below. However, I wanted to ask if this is possible to do without for loops and only with Numpy or Python built-in functions using code vectorization.
a = np.array([[0, 2, 0], [0, 2, 0]])
b = np.array([0, 0, 2])
new_array = np.empty((2,3))
for i in range(len(a)):
for j in range(3):
new_array[i][j] = b[a[i][j]]
expected output:
array([[0, 2, 0],
[0, 2, 0]])
CodePudding user response:
You can use numpy.take
:
np.take(b, a)
output:
array([[0, 2, 0],
[0, 2, 0]])
non ambiguous example
a = [[0, 2, 0], [1, 1, 2]]
b = [6, 7, 8]
np.take(b, a)
# array([[6, 8, 6],
# [7, 7, 8]])