How to fix error when concatenating two numpy arrays?

Question

I am trying the following:

rands = np.empty((0, 10))
rand = np.random.normal(1, 0.1, 10)
rands = np.concatenate((rands,rand),axis=0)

which gives me the following error:

ValueError: all the input arrays must have same number of dimensions

But why is this error? Why can't I append a new row rand into the matrix rands with this command?

Remark:

I can 'fix' this by using the following command:

rands = np.concatenate((rands,rand.reshape(1, 10)),axis=0)

but it looks not pythonic anymore, but cumbersome...

Maybe there is a better solution with less brackets and reshaping...?

Well although rands has initially an empty row it is still 2 dimensional the shape is (0,10) which is why it borks — EdChum
– EdChum, Commented Nov 10, 2016 at 9:15
Yes, and a row is one-dimensional with 10 elements. I don't understand what the problem is here... — Alex
– Alex, Commented Nov 10, 2016 at 9:16
Not in numpy's eyes it isn't you'd still get the same error with rands = np.empty((1, 10)) — EdChum
– EdChum, Commented Nov 10, 2016 at 9:17
what about: rands = np.empty((1,10)) rands = np.concatenate((rands[0],rand),axis=0) — Maximilian Peters
– Maximilian Peters, Commented Nov 10, 2016 at 9:19
no does not work. I will add more rows later, I have to repeat this concatenate line multiple times, in a loop — Alex
– Alex, Commented Nov 10, 2016 at 9:20

unutbu · Accepted Answer · 2016-11-10 09:21:32Z

3

rands has shape (0, 10) and rand has shape (10,).

In [19]: rands.shape
Out[19]: (0, 10)

In [20]: rand.shape
Out[20]: (10,)

If you try to concatenate along the 0-axis, then the 0-axis of rands (of length 0) is concatenated with the 0-axis of rand (of length 10). Pictorially, it looks like this:

rands:

|   |   |   |   |   |   |   |   |   |   |

rand:

|   |
|   |
|   |
|   |
|   |
|   |
|   |
|   |
|   |
|   |

The two shapes do not fit together well because the 1-axis of rands has length 10 and rand lacks a 1-axis.

To fix the problem, you could promote rand to a 2D array of shape (1, 10):

In [21]: rand[None,:].shape
Out[21]: (1, 10)

So that the 10 items in rand are now laid out along the 1-axis. Then

rands = np.concatenate((rands,rand[None,:]), axis=0)

returns an array of shape (1, 10)

In [26]: np.concatenate((rands,rand[None,:]),axis=0).shape
Out[26]: (1, 10)

Alternatively, you could use row_stack without promoting rand to a 2D array:

In [28]: np.row_stack((rands,rand)).shape
Out[28]: (1, 10)

answered Nov 10, 2016 at 9:21

unutbu

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1 Comment

Alex Over a year ago

I like row_stack. And now it looks more pythonic.Thanks!

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