How do I change a row vector created with np.linspace into a column vector?

Question

So far, I have the following:

beta = np.linspace(1, 10, num = 10) / 55

This returns the row vector:

[0.01818182 0.03636364 0.05454545 0.07272727 0.09090909 0.10909091 0.12727273 0.14545455 0.16363636 0.18181818]

I’ve tried using beta.transpose() but to no avail. Any suggestions?

Asked By: Albert Lee

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Answer 1

This may help you reformat the output of linspace to what you want :- Size of a linspace output

The default output of linspace only has a single dimension (10,), I can’t say this as an idiom but I believe row vectors (length, 1) and column vectors (1, length) are specific cases of a generalized 2D matrix in numpy, while (length,) is just a linear structure

a = np.array([1,2,3])
print(a.shape)
(3,)
print(a.transpose().shape)
(3,)

b = np.array([[1,2,3]])
print(b.shape)
(1,3)
print(b.transpose().shape)
(3,1)

Answered By: fibonachoceres

Answer 2

linspace produced a 1d array. It does not have a transpose, or rather its transpose is the same shape – 1d. numpy, in contrast to MATLAB, does not have row or column vectors. It has arrays, which may have a wide variety of shape.

A 1d array with shape (4,):

In [218]: x
Out[218]: array([1, 2, 3, 4])

One reshape – which may be called a ‘row vector’

In [219]: x.reshape(1,4)
Out[219]: array([[1, 2, 3, 4]])

A different reshape – a ‘column vector’, the transpose of the (1,4)

In [220]: x.reshape(4,1)
Out[220]: 
array([[1],
       [2],
       [3],
       [4]])

Another common way of making such an array:

In [221]: x[:,None]
Out[221]: 
array([[1],
       [2],
       [3],
       [4]])

Answered By: hpaulj

Answer 3

Two ways:

# 1
arr_col = arr.reshape(-1, 1).copy()

# 2
arr_col = arr[:, None].copy()

Answered By: amzon-ex

How do I change a row vector created with np.linspace into a column vector?

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