# numpy array/vector (n,) dimension -> (n,1) dimension conversion
a = np.arange(3) # a.shape = (3,)
b = a.reshape((3,1)) # b.shape = (3,1)
c = b.reshape((3,)) # c.shape = (3,)
c2 = b.reshape((-1,1)) # c2.shape = (3,)'''
This code is contributed by :
Tanishq Vyas (github : https://github.com/tanishqvyas )
'''
actual = actual.reshape((actual.shape[0], 1))""" assuming that v is a numpy array with shape (N, ) """
new_v = v.reshape(-1, 1) # new_v.shape is (N, 1)>>> a = np.array([[1,2,3], [4,5,6]])
>>> np.reshape(a, 6)
array([1, 2, 3, 4, 5, 6])
>>> np.reshape(a, 6, order='F')
array([1, 4, 2, 5, 3, 6])
>>> np.reshape(a, (3,-1)) # the unspecified value is inferred to be 2
array([[1, 2],
[3, 4],
[5, 6]])