Transposing a NumPy array

问题

I use Python and NumPy and have some problems with \"transpose\":

import numpy as np
a = np.array([5,4])
print(a)
print(a.T)

Invoking a.T is not transposing the array. If a is for example [[],[]] then it transposes correctly, but I need the transpose of [...,...,...].

回答1:

It's working exactly as it's supposed to. The transpose of a 1D array is still a 1D array! (If you're used to matlab, it fundamentally doesn't have a concept of a 1D array. Matlab's "1D" arrays are 2D.)

If you want to turn your 1D vector into a 2D array and then transpose it, just slice it with np.newaxis (or None, they're the same, newaxis is just more readable).

import numpy as np
a = np.array([5,4])[np.newaxis]
print(a)
print(a.T)

Generally speaking though, you don't ever need to worry about this. Adding the extra dimension is usually not what you want, if you're just doing it out of habit. Numpy will automatically broadcast a 1D array when doing various calculations. There's usually no need to distinguish between a row vector and a column vector (neither of which are vectors. They're both 2D!) when you just want a vector.

回答2:

Use two bracket pairs instead of one. This creates a 2D array, which can be transposed, unlike the 1D array you create if you use one bracket pair.

import numpy as np    
a = np.array([[5, 4]])
a.T

More thorough example:

>>> a = [3,6,9]
>>> b = np.array(a)
>>> b.T
array([3, 6, 9])         #Here it didn't transpose because 'a' is 1 dimensional
>>> b = np.array([a])
>>> b.T
array([[3],              #Here it did transpose because a is 2 dimensional
       [6],
       [9]])

Use numpy's shape method to see what is going on here:

>>> b = np.array([10,20,30])
>>> b.shape
(3,)
>>> b = np.array([[10,20,30]])
>>> b.shape
(1, 3)

回答3:

For 1D arrays:

a = np.array([1, 2, 3, 4])
a = a.reshape((-1, 1)) # <--- THIS IS IT

print a
array([[1],
       [2],
       [3],
       [4]])

Once you understand that -1 here means "as many rows as needed", I find this to be the most readable way of "transposing" an array. If your array is of higher dimensionality simply use a.T.

回答4:

You can convert an existing vector into a matrix by wrapping it in an extra set of square brackets...

from numpy import *
v=array([5,4]) ## create a numpy vector
array([v]).T ## transpose a vector into a matrix

numpy also has a matrix class (see array vs. matrix)...

matrix(v).T ## transpose a vector into a matrix

回答5:

numpy 1D array --> column/row matrix:

>>> a=np.array([1,2,4])
>>> a[:, None]    # col
array([[1],
       [2],
       [4]])
>>> a[None, :]    # row, or faster `a[None]`
array([[1, 2, 4]])

And as @joe-kington said, you can replace None with np.newaxis for readability.

回答6:

To 'transpose' a 1d array to a 2d column, you can use numpy.vstack:

>>> numpy.vstack(numpy.array([1,2,3]))
array([[1],
       [2],
       [3]])

It also works for vanilla lists:

>>> numpy.vstack([1,2,3])
array([[1],
       [2],
       [3]])

回答7:

You can only transpose a 2D array. You can use numpy.matrix to create a 2D array. This is three years late, but I am just adding to the possible set of solutions:

import numpy as np
m = np.matrix([2, 3])
m.T

回答8:

Another solution.... :-)

import numpy as np

a = [1,2,4]

[1, 2, 4]

b = np.array([a]).T

array([[1], [2], [4]])

回答9:

The transpose of

x = [[0 1],
     [2 3]]

xT = [[0 2],
      [1 3]]

well the code is:

x = array([[0, 1],[2, 3]]);
np.transpose(x)

this a link for more information:

http://docs.scipy.org/doc/numpy/reference/generated/numpy.transpose.html

回答10:

instead use arr[:,None] to create column vector

回答11:

I am just consolidating the above post, hope it will help others to save some time:

The below array has (2, )dimension, it's a 1-D array,

b_new = np.array([2j, 3j])

There are two ways to transpose a 1-D array:

slice it with "np.newaxis" or none.!

print(b_new[np.newaxis].T.shape)
print(b_new[None].T.shape)

other way of writing, the above without T operation.!

print(b_new[:, np.newaxis].shape)
print(b_new[:, None].shape)

Wrapping [ ] or using np.matrix, means adding a new dimension.!

print(np.array([b_new]).T.shape)
print(np.matrix(b_new).T.shape)

回答12:

As some of the comments above mentioned, the transpose of 1D arrays are 1D arrays, so one way to transpose a 1D array would be to convert the array to a matrix like so:

np.transpose(a.reshape(len(a), 1))

回答13:

The name of the function in numpy is column_stack.

>>>a=np.array([5,4])
>>>np.column_stack(a)
array([[5, 4]])

来源：https://stackoverflow.com/questions/5954603/transposing-a-numpy-array

标签

python

numpy

transpose