给定大小为3 x 3的矩阵垫，请找到其最终累积总和大于或等于tO 150的每一行中的所有偶数

Question

PROBLEM: Given a matrix mat of size 3 x 3. Find all the even numbers situated in each of the row(s) whose end cumulative sum is greater than or equal to 150.

I am able to find sum but not able to extract row wise sum and also I have issues in assigning these row wise even number sum to a variable.

So My code looked but then I don't know how to extract the row wise sum of even numbers.

import numpy as np 
mat = np.array([[51,21,14], 
                [56,85,22], 
                [99,666,230]]).reshape(3,3)
mat2=mat[mat%2==0]
res_mat=np.cumsum(mat2[:1])
print(mat2)
print(res_mat)

Answer 1

this answer won't be any good if using numpy is a requirement for your problem, not using it might be easier though.

mat = [[51, 21, 14], [56, 85, 22], [99, 666, 230]]
even_numbers_in_target_rows = list()
for row in mat:
    if sum(row) >= 150:
        for val in row:
            if val % 2 == 0:
                even_numbers_in_target_rows.append(val)

print(even_numbers_in_target_rows)

Steps:

1. Loop through matrix row by row
2. Sum row.
3. Check if row sum is over or equal to 150
4. If over, then step through each value
5. If even add to list of even numbers in rows over or equal to 150

Answer 2

If I understand the problem correctly (and I feel that it is written in an awkward way), you have to find the rows whose sums are >= 150:

rows = mat[mat.sum(axis=1) >= 150]

And then choose the even numbers from them:

rows[rows % 2 == 0]
#array([ 56,  22, 666, 230])

Answer 3

Note: the question is a bit ambiguous because it is not clear whether "whose" refers to the rows or to the even numbers within. I'm assuming the latter. The former would be easier.

You can use np.bincount together with np.where

# find even numbers 
even = mat&1 == 0
# translate mask into coordinates
y, x = np.where(even)
# use y coordinate to group into rows
np.bincount(y, mat[even], mat.shape[0])

# array([ 14.,  78., 896.])

Answer 4

You can do this by taking the sum along each row and using the resultant boolean array to index into the original. Then, just get the even numbers:

mat = np.array([[51, 21, 14], 
                [56, 85, 22], 
                [99, 666, 230]])

uniques = np.unique(mat[mat.sum(axis=1) > 150])

uniques[uniques % 2 == 0]

Output:

array([ 22,  56, 230, 666])