np.transpose doesn't return transpose of matrix

When I write my code in the following manner :

from numpy import *
H = array([1,1])
Ht = transpose(H)
Ht


I get the same matrix as H instead of the transpose of H.

But when I change the matrix H in the following way :

from numpy import *
H = array(([1,1],[2,3]))
Ht = transpose(H)
Ht


I get the transpose of H.

I fail to understand what is happening here. Is it the way transpose function is used or is it the way a matrix is defined?

2 Answers
2

I think this is the behavior you're looking for:

>>> H = np.array([[1,1]])
>>> H.T
array([[1],
[1]])


Equivalently you can write np.transpose(H). Notice this array has shape (1,2), so it has two dimensions. The array H = np.array([1,2]) has shape (2,). It only has one dimension. To swap the dimensions (transpose), you need at least two of them.

np.transpose(H)

(1,2)

H = np.array([1,2])

(2,)

From the documentation:

numpy.matrix.transpose. Returns a view of the array with axes transposed. For a 1-D array, this has no effect. (To change between column and row vectors, first cast the 1-D array into a matrix object.)

matrix

from numpy import *

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