Understand numpy.stack() with Examples: Join Arrays Along a New Axis

In this tutorial, we will introduce numpy.stack() with some examples. You can learn how to join some arrays by it.

numpy.stack()

It is defined as:

numpy.stack(arrays, axis=0, out=None)

This function will join a sequence of arrays along a new axis.

We should notice a new axis will be added.

Parameters:

arrays: a sequence of arrays, each array must have the same shape.

axis: int, the axis in the result array along which the input arrays are stacked.

Here we will use some examples to show you how to use this function.

Exampe 1: axis = 0

import numpy as np
x1 = np.arange(9).reshape((3,3))
x2 = np.arange(10,19,1).reshape((3,3))

y2 = np.stack((x1,x2),axis=0)
print(y2)

Here axis = 0, which means we will will join x1 and x2 on axis = 0 in y2.

Run this code, we will see:

[[[ 0  1  2]
  [ 3  4  5]
  [ 6  7  8]]

 [[10 11 12]
  [13 14 15]
  [16 17 18]]]

x1 and x2 are in axis = 0 of y2.

Example 2: axis = 1

Similar to example 1, we can find x1 and x2 are in axis = 1 of y2.

Here is an example:

import numpy as np
x1 = np.arange(9).reshape((3,3))
x2 = np.arange(10,19,1).reshape((3,3))

y2 = np.stack((x1,x2),axis=1)
print(y2)

Run this code, we will see:

[[[ 0  1  2]
  [10 11 12]]

 [[ 3  4  5]
  [13 14 15]]

 [[ 6  7  8]
  [16 17 18]]]

Example 3:axis = 2

We will get:

[[[ 0 10]
  [ 1 11]
  [ 2 12]]

 [[ 3 13]
  [ 4 14]
  [ 5 15]]

 [[ 6 16]
  [ 7 17]
  [ 8 18]]]

Example 4: when we only use x1

Look at this example:

import numpy as np
x1 = np.arange(9).reshape((3,3))
print("x1=")
print(x1)

y2 = np.stack(x1,axis=1)
print("y2=")
print(y2)

Here parameter arrays is x1 and axis = 1.

Run this code, we will get:

x1=
[[0 1 2]
 [3 4 5]
 [6 7 8]]
y2=
[[0 3 6]
 [1 4 7]
 [2 5 8]]

Example 5:

import numpy as np
x1 = np.arange(9).reshape((3,3))
print("x1=")
print(x1)

y2 = np.stack([x1],axis=0)
print("y2=")
print(y2)

Here parameter arrays is [x1] and axis = 0, we will get:

x1=
[[0 1 2]
 [3 4 5]
 [6 7 8]]
y2=
[[[0 1 2]
  [3 4 5]
  [6 7 8]]]

From example 4 and 5, we can find:

If parameter arrays is an array x1, y2 will not add new axis. However, if arrays is a list [x1], y2 will add a new aixs.