Example 1: sum axis in python
import numpy as np
array1 = np.array(
[[1, 2],
[3, 4],
[5, 6]])
total_0_axis = np.sum(array1, axis=0)
print(f'Sum of elements at 0-axis is {total_0_axis}')
total_1_axis = np.sum(array1, axis=1)
print(f'Sum of elements at 1-axis is {total_1_axis}')
Output:
Sum of elements at 0-axis is [ 9 12]
Sum of elements at 1-axis is [ 3 7 11]
Example 2: sum along axis python
import numpy as np
matrix=np.ones((10,10))
print(matrix.sum(axis=0))
print(matrix.sum(axis=1))
Example 3: sum of a numpy array
>>> np.sum([0.5, 1.5])
2.0
>>> np.sum([0.5, 0.7, 0.2, 1.5], dtype=np.int32)
1
>>> np.sum([[0, 1], [0, 5]])
6
>>> np.sum([[0, 1], [0, 5]], axis=0)
array([0, 6])
>>> np.sum([[0, 1], [0, 5]], axis=1)
array([1, 5])
>>> np.sum([[0, 1], [np.nan, 5]], where=[False, True], axis=1)
array([1., 5.])
Example 4: python sum of list axes
>>> np.sum([[0, 1], [0, 5]])
6
>>> np.sum([[0, 1], [0, 5]], axis=0)
array([0, 6])
>>> np.sum([[0, 1], [0, 5]], axis=1)
array([1, 5])
Example 5: python np.sum
npsum = np.sum(array)
Example 6: sum every ith element numpy
import numpy as np
c = [1, 0, 0, 0, 0, 2, 0, 0, 0, 0]
np.add.reduceat(c, np.arange(0, len(c), 5))