Syntax in Python (.T)

Question

In the help resource for the multivariate normal sampling function in SciPy, they give the following example:

x,y = np.random.multivariate_normal(mean,cov,5000).T

My question is rather basic: what does the final .T actually do?

Thanks a lot, I know it is fairly simple, but it is hard to look in Google for “.T”.

Asked By: Leon palafox

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Source

Answer 1

The .T accesses the attribute T of the object, which happens to be a NumPy array. The T attribute is the transpose of the array, see the documentation.

Apparently you are creating random coordinates in the plane. The output of multivariate_normal() might look like this:

>>> np.random.multivariate_normal([0, 0], [[1, 0], [0, 1]], 5)  
array([[ 0.59589335,  0.97741328],
       [-0.58597307,  0.56733234],
       [-0.69164572,  0.17840394],
       [-0.24992978, -2.57494471],
       [ 0.38896689,  0.82221377]])

The transpose of this matrix is:

array([[ 0.59589335, -0.58597307, -0.69164572, -0.24992978,  0.38896689],
       [ 0.97741328,  0.56733234,  0.17840394, -2.57494471,  0.82221377]])

which can be conveniently separated in x and y parts by sequence unpacking.

Answered By: Sven Marnach

Answer 2

.T is just np.transpose().
Best of luck

Answered By: Zhassulan Shaikhygali

Answer 3

Example

import numpy as np
a = [[1, 2, 3]]
b = np.array(a).T  # ndarray.T The transposed array. [[1,2,3]] -> [[1][2][3]]
print("a=", a, "nb=", b)
for i in range(3):
    print(" a=", a[0][i])  # prints  1 2 3
for i in range(3):
    print(" b=", b[i][0])  # prints  1 2 3

Answered By: vk3who

Syntax in Python (.T)

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