Numpy

numpy_array_manipulation2.py

## 1. moveaxis routine
import numpy as np

x = np.zeros((3, 4, 5))

## In this all the elements shape gets shifted in the direction of source to destonation, so for this example 
## it is just like cyclic rotation in clockwise direction.
print(np.moveaxis(x, 0, -1).shape)

#[Output]:
#(7, 5, 4, 6)

print(np.moveaxis(x, -1, 0).shape)

#[Output];
#(5, 3, 4)


## In this example, last axes remain unchanged.

print(np.moveaxis(x, 0, 1).shape)

#[Output]:
#(7, 6, 5, 4)

x = np.zeros((6, 7, 5, 4))
print(np.moveaxis(x, 0, 2).shape)

#[Output]:
#(7, 5, 6, 4)


## 2. numpy.transpose

x = np.arange(4).reshape((2,2))
print(x)

#[Output]:
#array([[0, 1],
#     [2, 3]])

print(np.transpose(x))

#[Output]:
#array([[0, 2],
#       [1, 3]])


## In this example we doesn't set the axes=none and here we set axes-0 dimensions to axes-1, axes-1 dimensions to axes-0 etc.   
x = np.ones((1, 2, 3))

print(np.transpose(x, (1, 0, 2)).shape)

#[Output]:
#(2, 1, 3)


## 3. numpy.ndarray.T
x = np.array([[1.,2.],[3.,4.]])
print(x)

#[Output]:
#array([[1., 2.],
#       [3., 4.]])

print(x.T)

#[Output]:
#array([[1., 3.],
#       [2., 4.]])