I have actually the following values, every of i beg your pardon is a scalar of form double: a1, a2, a3, a4, a5.

You are watching: Valueerror: zero-dimensional arrays cannot be concatenated

I tried to concatenate them using Numpy, together follows:

f = np.concatenate((a1,a2,a3,a4,a5))I yet get the complying with error:

ValueError: zero-dimensional arrays can not be concatenatedWhat could I be doing wrong?



concatenate transforms each the the items in the list into range (if that isn"t already), and tries to sign up with them:

In <129>: np.concatenate(<1,2,3,4>)...ValueError: zero-dimensional arrays can not be concatenatedhstack takes the added step of: arrs = , making sure they space at the very least 1d:

In <130>: np.hstack(<1,2,3,4>)Out<130>: array(<1, 2, 3, 4>)But the standard means of creating variety from scalars is through np.array, which join the items follow me a new axis:

In <131>: np.array(<1,2,3,4>)Out<131>: array(<1, 2, 3, 4>)Note the np.array of 1 scalar is a 0d array:

In <132>: np.array(1)Out<132>: array(1)In <133>: _.shapeOut<133>: ()If I want to sign up with 4 0d arrays together, how long will certainly that be? 4*0 =0? 4 1d arrays join on their typical axis is 4*1=4; 4 2d arrays (n,m), will certainly be either (4n,m) or (n,4m) relying on the axis.

np.stack likewise works. The does something comparable to:

In <139>: np.concatenate(>)Out<139>: array(<1, 2, 3, 4>)
edited january 27 "18 at 3:51
answered jan 27 "18 in ~ 3:39


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