Reputation: 663
I don't understand array as index in Python Numpy. For example, I have a 2d array A in Numpy
[[1,2,3]
[4,5,6]
[7,8,9]
[10,11,12]]
What does A[[1,3], [0,1]] mean?
Upvotes: 0
Views: 360
Reputation: 22952
Your are creating a new array:
import numpy as np
A = [[1, 2, 3],
[4, 5, 6],
[7, 8, 9],
[10, 11, 12]]
A = np.array(A)
print(A[[1, 3], [0, 1]])
# [ 4 11]
See Indexing, Slicing and Iterating in the tutorial.
Multidimensional arrays can have one index per axis. These indices are given in a tuple separated by commas
Quoting the doc:
def f(x,y):
return 10*x+y
b = np.fromfunction(f, (5, 4), dtype=int)
print(b[2, 3])
# -> 23
You can also use a NumPy array as index of an array. See Index arrays in the doc.
NumPy arrays may be indexed with other arrays (or any other sequence- like object that can be converted to an array, such as lists, with the exception of tuples; see the end of this document for why this is). The use of index arrays ranges from simple, straightforward cases to complex, hard-to-understand cases. For all cases of index arrays, what is returned is a copy of the original data, not a view as one gets for slices.
Upvotes: 1
Reputation: 3857
Just test it for yourself!
A = np.arange(12).reshape(4,3)
print(A)
>>> array([[ 0, 1, 2],
[ 3, 4, 5],
[ 6, 7, 8],
[ 9, 10, 11]])
By slicing the array the way you did (docs to slicing), you'll get the first row, zero-th column element and the third row, first column element.
A[[1,3], [0,1]]
>>> array([ 3, 10])
I'd highly encourage you to play around with that a bit and have a look at the documentation and the examples.
Upvotes: 1