Examples of how to calculate the sum along an axis with numpy in python:
Create a random matrix with numpy
Let's create a random matrix with numpy of size = (3,3):
import numpy as np
data = np.random.randint(0,5,size=(3,3))
returns for example
array([[4, 1, 2],
[2, 1, 1],
[4, 0, 1]])
Sum along the first axis (axis=0)
To sum along a given axis of a matrix with numpy, a solution is to use numpy.sum with the parameter "axis":
data.sum(axis=0)
gives
array([10, 2, 4])
Sum along the second axis (axis=1)
Another example along the axis=1
data.sum(axis=1)
gives
array([7, 4, 5])
Sum all elements of a matrix with numpy
Note: to sum all elements of a matrix with numpy:
data.sum()
gives here
16
Another example with more than 2 dimensions
Another example with a matrix of size = (3,3,3)
import numpy as np
data = np.random.randint(0,5,size=(3,3,3))
gives gor example
array([[[4, 2, 4],
[3, 3, 1],
[0, 4, 1]],
[[3, 4, 0],
[3, 1, 3],
[4, 4, 2]],
[[2, 0, 2],
[2, 4, 1],
[3, 3, 4]]])
Sum along axis=0
data.sum(axis=0)
gives
array([[ 9, 6, 6],
[ 8, 8, 5],
[ 7, 11, 7]])
Sum along axis=1
data.sum(axis=1)
gives
array([[ 7, 9, 6],
[10, 9, 5],
[ 7, 7, 7]])
Sum along axis=2
data.sum(axis=2)
gives
array([[10, 7, 5],
[ 7, 7, 10],
[ 4, 7, 10]])