Reshapes-MATLAB-Like-Python

Reshape arrays row-wisely like python.

MATLAB-Reshapes-Like-Python

Reshape arrays row-wisely like python.

RESHAPE(A, new_size)

Usage:

A is an array

new_size is an array represents the shape of the new n-dimensional matrix. [new_size_1, new_size_2, ..., new_size_n] The shape have to be compatable.

It will return the reshaped array. The computation time is propotional to the number of indices of the tensor, not the number of the elements.

Examples

In MATLAB

>> a = 1:6;
>> 
>> b = RESHAPE(a, [2,3])

b =

     1     2     3
     4     5     6

>> b = RESHAPE(a, [2,1,3])

b(:,:,1) =

     1
     4


b(:,:,2) =

     2
     5


b(:,:,3) =

     3
     6

>> b = RESHAPE(a, [2,3,1])

b =

     1     2     3
     4     5     6

>> a = RESHAPE(b, [1, 6])

a =

     1     2     3     4     5     6

>> 

The array is reshaped in matlab as in python, except the indices of matlab start with 1 while indices of python start with 0.

>>> import numpy as np
>>> a = np.linspace(1, 6, 6)
>>> b = a.reshape(2,3)
>>> b
array([[1., 2., 3.],
       [4., 5., 6.]])
>>> b = a.reshape(2,1,3)
>>> b
array([[[1., 2., 3.]],

       [[4., 5., 6.]]])
>>> b[:,:,1]
array([[2.],
       [5.]])
>>> b[:,:,0]
array([[1.],
       [4.]])
>>> b[:,:,2]
array([[3.],
       [6.]])
>>> b = a.reshape(2,3,1)
>>> b
array([[[1.],
        [2.],
        [3.]],

       [[4.],
        [5.],
        [6.]]])
>>> b[:,:,0]
array([[1., 2., 3.],
       [4., 5., 6.]])
>>> a = b.reshape(1, 6)
>>> a
array([[1., 2., 3., 4., 5., 6.]])