Creating a grid type 3D data array from data points

[Arman777]

I have a 3 data column $(X, Y, Z)$ ranges from $(min, max)$. For example,

$X = (0, 5)$, $Y=(0, 3)$, $Z=(0, 2)$. By using them I need to create a numpy array in the form of

$[(0, 0, 0), (0, 0, 1), (0, 0, 2), (0, 1, 0), (0, 1, 1), (0, 1, 2), (0, 2, 0)...]$

So in total there will be $6 \times 4 \times 3 = 72$ data points.

Is there a simple command to do this ?

 

[pbuk]

numpy arrays cannot hold tuples

If you want to create a 2D 72 x 3 numpy array similar to that there is no simple function*; this is a typical exercise for any aspiring coder.

* the np.indices, np.mgrid and np.ogrid functions do something similar, but I don't think there is anything that does exactly this.

Edit: I suppose you could view a list comprehension as a "simple command" (but the word "command" is not appropriate here):

np.array([[x, y, z] for x in range(6) for y in range(4) for z in range(3)])