I have
x=np.array([[1,2,3],[3,4,5],[5,7,8]])
y=np.array([[5,2,5],[1,1,1],[2,2,2]])
I'd like to get
xy=[(1,5),(2,2),(3,5),(3,1),(4,1),(5,1),(5,2),(7,2),(8,2)]
What's the best (quick and clean) way to do so? Also, once I have xy, how do I relate the indexes of xy to the original numpy matrixes x,y ?
You can use this approach to get xy:
zip(x.flatten(),y.flatten())
#[(1, 5), (2, 2), (3, 5), (3, 1), (4, 1), (5, 1), (5, 2), (7, 2), (8, 2)]
You can try:
>>> x = [[1,2,3],[3,4,5],[5,7,8]]
>>> y = [[5,2,5],[1,1,1],[2,2,2]]
>>> x1 = [val for x_data in x for val in x_data]
>>> y1 = [val for y_data in y for val in y_data]
>>> final = [(a,b) for a, b in zip(x1, y1)]
>>> print final
[(1, 5), (2, 2), (3, 5), (3, 1), (4, 1), (5, 1), (5, 2), (7, 2), (8, 2)]
Transpose or use nop.dstack():
>>> np.dstack((x.ravel(), y.ravel()))[0]
array([[1, 5],
[2, 2],
[3, 5],
[3, 1],
[4, 1],
[5, 1],
[5, 2],
[7, 2],
[8, 2]])
>>>
>>>
>>> np.array((x.ravel(), y.ravel())).T
array([[1, 5],
[2, 2],
[3, 5],
[3, 1],
[4, 1],
[5, 1],
[5, 2],
[7, 2],
[8, 2]])
dstack: np.dstack((x,y)).reshape(-1,2).