Is there a multi-dimensional version of arange/linspace in numpy?

Question

I would like a list of 2d NumPy arrays (x,y) , where each x is in {-5, -4.5, -4, -3.5, ..., 3.5, 4, 4.5, 5} and the same for y.

I could do

x = np.ar         


        

Answer 1

This is just what you are looking for:

matr = np.linspace((1,2),(10,20),10)

This means:

For the first column; from 1 of (1,2) to 10 of (10,20), put the increasing 10 numbers.

For the second column; from 2 of (1,2) to 20 of (10,20), put the incresing 10 numbers.

And the result will be:

[[ 1.  2.]
 [ 2.  4.]
 [ 3.  6.]
 [ 4.  8.]
 [ 5. 10.]
 [ 6. 12.]
 [ 7. 14.]
 [ 8. 16.]
 [ 9. 18.]
 [10. 20.]]

You may also keep only one column's values increasing, for example, if you say that:

matr = np.linspace((1,2),(1,20),10)

The first column will be from 1 of (1,2) to 1 of (1,20) for 10 times which means that it will stay as 1 and the result will be:

[[ 1.  2.]
 [ 1.  4.]
 [ 1.  6.]
 [ 1.  8.]
 [ 1. 10.]
 [ 1. 12.]
 [ 1. 14.]
 [ 1. 16.]
 [ 1. 18.]
 [ 1. 20.]]