Suppose I have the following numpy array of shape (10, 5) where I want to split it into two subarrays: the first one contains the first 7 rows and the second one takes the remaining 3 rows. If I do this:
x = np.arange(50).reshape(10, 5)
x1, y1 = np.vsplit(x, 2)
It will split exactly half. How can I make it two subarrays (7,5) and (3,5)?
Use np.split():
In [4]: np.split(x, [7])
Out[4]:
[array([[ 0, 1, 2, 3, 4],
[ 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14],
[15, 16, 17, 18, 19],
[20, 21, 22, 23, 24],
[25, 26, 27, 28, 29],
[30, 31, 32, 33, 34]]), array([[35, 36, 37, 38, 39],
[40, 41, 42, 43, 44],
[45, 46, 47, 48, 49]])]
i think you shhould use fancy indexing, unlike slicing, fancy indexing always copies the data into a new array
n = 10; m = 5; i = 7
arr = np.arange(50).reshape(n, m)
arr7 = arr[np.ix_(range(i))]
arr3 = arr[np.ix_(range(i - n, 0, 1))]
