python - How to fix error when concatenating two numpy arrays? -

i trying following:

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

which gives me following error:

valueerror: input arrays must have same number of dimensions

but why error? why can't append new row rand matrix rands command?

remark:

i can 'fix' using following command:

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

but looks not pythonic anymore, cumbersome...

maybe there better solution less brackets , reshaping...?

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

in [19]: rands.shape out[19]: (0, 10)  in [20]: rand.shape out[20]: (10,)

if try concatenate along 0-axis, 0-axis of rands (of length 0) concatenated 0-axis of rand (of length 10). pictorially, looks this:

rands:

|   |   |   |   |   |   |   |   |   |   |

rand:

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

the 2 shapes not fit because 1-axis of rands has length 10 , rand lacks 1-axis.

to fix problem, promote rand 2d array of shape (1, 10):

in [21]: rand[none,:].shape out[21]: (1, 10)

so 10 items in rand laid out along 1-axis.

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

returns array of shape (1, 10)

in [26]: np.concatenate((rands,rand[none,:]),axis=0).shape out[26]: (1, 10)

alternatively, use row_stack without promoting rand 2d array:

in [28]: np.row_stack((rands,rand)).shape out[28]: (1, 10)

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