How to reshape an array in Python using Numpy?

As mentioned by Chris in his comment you simply want to reshape the array by fixing the number of rows to one and let Python figure out the other dimension:

u=u.reshape(1, -1)

I think @Chris has mentioned well in the comment, you can try out

I have tried out the scenario

>>> import numpy as np
>>> u = np.zeros((10))

>>> u.shape
(10,)
>>> u.T
array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
>>> u = u.reshape(1, -1)
>>> u.shape
(1, 10)
>>> u.T
array([[0.],
   [0.],
   [0.],
   [0.],
   [0.],
   [0.],
   [0.],
   [0.],
   [0.],
   [0.]])

I think for your case u.reshape(1, -1) would do your work.

You can try to use expand_dims() method.

import numpy as np

a = np.zeros(10) # a.shape = (10,)
a = np.expand_dims(a, axis=0)
print(a.shape)

Output

(1, 10)

What you want is :

u = u.reshape((-1, 1)).T

Another trick in the book that works is with np.newaxis

 u = u[np.newaxis,:]

Should give you an array with shape (1,10)