Create a matrix using a certain vector in Python

Question

I have this vector m = [1,0.8,0.6,0.4,0.2,0] and I have to create the following matrix in Python:

I create a matrix of zeros and a double

mm = np.zeros((6, 6))

for j in list(range(0,6,1)):
    for i in list(range(0,6,1)):
        ind = abs(i-j)
        m[j,i] = mm[ind]

But, I got the following output:

array([[1. , 0.8, 0.6, 0.4, 0.2, 0. ],
   [0.8, 1. , 0.8, 0.6, 0.4, 0.2],
   [0.6, 0.8, 1. , 0.8, 0.6, 0.4],
   [0.4, 0.6, 0.8, 1. , 0.8, 0.6],
   [0.2, 0.4, 0.6, 0.8, 1. , 0.8],
   [0. , 0.2, 0.4, 0.6, 0.8, 1. ]])

That is what I wanted! Thanks anyway.

What did you try so far? You could use a for loop and some modulo indexing. — Lescurel
– Lescurel, Commented Nov 22, 2022 at 10:52
your output seems to match what you want. So what's your question? — user20396240
– user20396240, Commented Nov 22, 2022 at 11:12

Riccardo Bucco · Accepted Answer · 2022-11-22 12:14:01Z

1

Here is a way to implement what you want with only numpy functions, without loops (m is your numpy array):

x = np.tile(np.hstack([np.flip(m[1:]), m]), (m.size, 1))
rows, column_indices = np.ogrid[:x.shape[0], :x.shape[1]]
column_indices = column_indices - np.arange(m.size)[:, np.newaxis]
result = x[rows, column_indices][:, -m.size:]

Example:

>>> result
array([[1. , 0.8, 0.6, 0.4, 0.2, 0. ],
       [0.8, 1. , 0.8, 0.6, 0.4, 0.2],
       [0.6, 0.8, 1. , 0.8, 0.6, 0.4],
       [0.4, 0.6, 0.8, 1. , 0.8, 0.6],
       [0.2, 0.4, 0.6, 0.8, 1. , 0.8],
       [0. , 0.2, 0.4, 0.6, 0.8, 1. ]])

This approach is much faster than using a list comprehension when m is large.

answered Nov 22, 2022 at 12:14

Riccardo Bucco

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Comments

amirhm · Accepted Answer · 2022-11-22 11:13:37Z

1

This could be written by comprehension if you do not want to use numpy,

[m[i::-1] + m[1:len(m)-i]  for i in range(len(m))]

answered Nov 22, 2022 at 11:13

amirhm

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1 Comment

amirhm Over a year ago

you are welcome, you could as well vote up if this answers

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