How to copy numpy array in matlab style

Question

in matlab/ GNU Octave( which i am actually using ), I use this method to copy particular elements of a 2D array to another 2D array:

B(2:6, 2:6) = A

where

size(A) = (5, 5)

My question is, "How can this be achieved in python using numpy?" currently, for example, I am using the following nested loop in python:

>>> import numpy as np
>>> a = np.int32(np.random.rand(5,5)*10)
>>> b = np.zeros((6,6), dtype = np.int32)

>>> print a
[[6 7 5 1 3]
 [3 9 7 2 0]
 [9 3 7 6 7]
 [9 8 2 0 8]
 [8 7 7 9 9]]
>>> print b
[[0, 0, 0, 0, 0, 0],
 [0, 0, 0, 0, 0, 0],
 [0, 0, 0, 0, 0, 0],
 [0, 0, 0, 0, 0, 0],
 [0, 0, 0, 0, 0, 0],
 [0, 0, 0, 0, 0, 0]]

>>> for i in range(1,6):
        for j in range(1,6):
            b[i][j] = a[i-1][j-1]
>>> print b
[[0, 0, 0, 0, 0, 0],
 [0, 6, 7, 5, 1, 3],
 [0, 3, 9, 7, 2, 0],
 [0, 9, 3, 7, 6, 7],
 [0, 9, 8, 2, 0, 8],
 [0, 8, 7, 7, 9, 9]]

Is there a better way to do this?

BrenBarn · Accepted Answer · 2012-11-12 08:44:47Z

5

It's almost the same as the MATLAB:

b[1:6, 1:6] = a

The only thing is that Python uses 0-based indexing so the second element is 1 instead of 2.

answered Nov 12, 2012 at 8:44

BrenBarn

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2 Comments

Yash Over a year ago

Oh, thanks. That's it! I was trying it as b[1:6][1:6]. Now i feel so silly asking this question.........

John Greenall Over a year ago

google 'numpy for matlab users' theres a great reference guide in the numpy docs

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