Numpy python - calculating sum of columns from irregular dimension-CodePudding

I have a multi-dimensional array for scores, and for which, I need to get sum of each columns at 3rd level in Python. I am using Numpy to achieve this.

import numpy as np

Data is something like:

score_list = [
    [[1,1,3], [1,2,5]],
    [[2,7,5], [4,1,3]]
]

This should return:

[[3 8 8] [5 3 8]]

Which is happening correctly using this:

sum_array = np_array.sum(axis=0)
print(sum_array)

However, if I have irregular shape like this:

score_list = [
    [[1,1], [1,2,5]],
    [[2,7], [4,1,3]]
]

I expect it to return:

[[3 8] [5 3 8]]

However, it comes up with warning and the return value is:

[list([1, 1, 2, 7]) list([1, 2, 5, 4, 1, 3])]

How can I get expected result?

CodePudding user response：

numpy will try to cast it into an nd array which will fail, instead consider passing each sublist individually using zip.

score_list = [
    [[1,1], [1,2,5]],
    [[2,7], [4,1,3]]
]

import numpy as np
res = [np.sum(x,axis=0) for x in zip(*score_list)]
print(res)

[array([3, 8]), array([5, 3, 8])]

CodePudding user response：

Here is one solution for doing this, keep in mind that it doesn't use numpy and will be very inefficient for larger matrices (but for smaller matrices runs just fine).

# Create matrix
score_list = [
[[1,1,3], [1,2,5]],
[[2,7,5], [4,1,3]]
]

# Get each row
for i in range(1, len(score_list)):

  # Get each list within the row
  for j in range(len(score_list[i])):

    # Get each value in each list
    for k in range(len(score_list[i][j])):

        # Add current value to the same index 
        # on the first row 
        score_list[0][j][k]  = score_list[i][j][k]

print(score_list[0])

There is bound to be a better solution but this is a temporary fix for you :)

Edit. Made more efficient

CodePudding user response：

A possible solution:

a = np.vstack([np.array(score_list[x], dtype='object')
              for x in range(len(score_list))])
[np.add(*[x for x in a[:, i]]) for i in range(a.shape[1])]

Another possible solution:

a = sum(score_list, [])
b = [a[x] for x in range(0,len(a),2)]
c = [a[x] for x in range(1,len(a),2)]
[np.add(x[0], x[1]) for x in [b, c]]

Output:

[array([3, 8]), array([5, 3, 8])]